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All rotating electrical machines are susceptible to vibrations arising from electromagnetic (EM) forces, electrical faults, mechanical defects, imbalance, and structural resonance. In Doubly Fed Induction Generators (DFIGs), such electromechanical vibrations are especially important because they can degrade reliability, increase noise, and lead to severe damage if resonance-prone operating conditions are not identified in time. Although fault diagnosis in DFIGs has been widely investigated using current, voltage, and flux signatures, comparatively fewer studies have examined fault-specific vibration behaviour under stator and rotor interturn faults (ITTFs), particularly through a coupled EM structural framework. In addition, prior vibration-based studies have not examined the influence of end winding ITTFs, its location, severity, and modal interaction investigating resonance risk. This paper considers vibration characteristics of a variable-speed 2.8 MW DFIG used in a grid-connected Type-3 wind turbine unit (WTU) at no-load operating condition. The DFIG is modelled in ANSYS Academic Research v 2022 R2 Maxwell for EM behaviour assessment for ITTFs in both stator and rotor windings along with modal analysis (MA) in ANSYS Workbench to examine the undamped stator and rotor modes over a range of frequencies. This coupled approach enables identification of vibration signatures associated with different ITTF types. The results show the magnetic flux density near faulty end-winding region increases with fault severity and ranges from 4.19 T to 4.39 T in proximity to faulty windings. A dominant modal frequency band of 60–65 Hz is identified, where stator and rotor modes coincide, creating probable resonance conditions. A severe vibration response is observed for single-phase stator ITTF, showing an amplitude of 2116 mm/s at 480 Hz for a larger number of shorted turns, indicating that asymmetric faults can produce stronger EM excitation than multi-phase faults. The main contribution of this paper is demonstration of a fault-specific, MA and vibration-based Condition monitoring system (CMS) implementation workflow for a DFIG. Unlike prior vibration-based studies that primarily focus on general machine vibration, mechanical faults, bearings, etc., this paper links stator and rotor ITTF induced EM excitation to modal characteristics, resonance behaviour, and measurable vibration signatures, establishing vibration analysis (VA) as a practical complementary technique for CMS of ITTFs in DFIGs. Full article

In Optical Camera Communication (OCC), precise localization of LED arrays under complex tilt conditions is a core challenge for reliable decoding. This paper proposes an OCC reception scheme for RGB-LED arrays that integrates YOLO-OBB rotated object detection with two-stage geometric correction. The system first employs a YOLOv8n-OBB model to extract a quadrilateral region of interest that tightly encloses the LED array boundary. This effectively suppresses background interference caused by superimposed perspective tilt and in-plane rotation. A coarse-to-fine two-stage correction framework is then applied. The first stage rapidly eliminates the dominant perspective distortion based on the detected bounding-box corners. The second stage performs a refined correction using the actual LED center positions. Two homography matrices are cascaded into a combined transformation, achieving two-stage correction accuracy through a single coordinate mapping. In the corrected image, K-Means clustering constructs a 16 × 16 LED topological grid. A locking strategy is adopted so that subsequent frames skip repeated LED detection and clustering. The steady-state per-frame processing time is reduced to approximately 78.9 ms. Experiments covered 16 cross-combinations of vertical tilt from 0° to 45° (0°, 15°, 30°, 45°) and in-plane rotation from 0° to 40° (0°, 15°, 30°, 40°). The uncorrected scheme and the horizontal-box scheme experienced severe bit errors or complete failure under complicated distortion. The proposed scheme maintained error-free transmission under all 16 tested conditions. The ratios of opposite sides of the corrected LED grid remained stable between 0.997 and 1.004. The system simultaneously achieves high reliability and low-latency real-time processing under complex geometric distortions. Full article

Background/Objectives: Given the limited evidence on multi-distance visual function assessment in presbyopia, this study aimed to compare dynamic binocular visual function between presbyopic and non-presbyopic (NP) participants at different distances, and to further evaluate the effects of additional power (ADD) on dynamic sharpness discrimination, binocular integration, and dynamic stereopsis in presbyopic participants. Methods: A total of 54 presbyopic and 77 NP participants were tested at 0.4 m, 0.7 m, 1 m, and 3 m using a dichoptic rotating ring system with red-blue anaglyph glasses. Presbyopia was classified as low (LP, ADD < 1.5D) or high (HP, ADD ≥ 1.5D). Tests included dynamic sharpness discrimination, binocular integration, and stereopsis. To account for potential confounders, generalized linear models (GLM) were applied with sex, eye laterality, age, ADD, spherical equivalent (SE), and group as covariates, allowing comparison of visual function outcomes across different viewing distances between NP and ADD-stratified presbyopic groups. Results: There was no statistically significant difference in the passing rates of dynamic sharpness discrimination test between the presbyopic and NP groups (all p > 0.05). At 0.4 m, 0.7 m, and 1 m, the presbyopic group showed significantly lower passing rates in the binocular integration test compared with the NP group (all p < 0.05), while no significant difference was observed at 3 m (p = 0.051). Furthermore, the passing rates for binocular integration test at all distances were significantly lower in the HP group than those in both the NP and LP groups (all p < 0.05). GLM analysis indicated that both SE and age were potential confounders in the comparison of binocular integration between presbyopic and NP groups (both p < 0.05). There were no significant differences in the passing rates of binocular dynamic stereopsis test at any distance between the NP and presbyopic groups, or between the LP and HP groups (all p > 0.05). Conclusions: This novel dynamic testing method revealed ADD-dependent impairment of binocular integration at near-to-intermediate distances in patients with presbyopia. Full article

Background and Objectives: To compare the buccal bone thickness of adjacent maxillary incisors between the impacted and contralateral control sides in patients with unilateral palatally impacted canines (PICs) using a split-mouth cone-beam computed tomography (CBCT) design. Materials and Methods: CBCT records of 26 patients with a unilateral PIC (18 females, 8 males; mean age, 17.35 ± 4.58 years) were retrospectively analyzed. Buccal bone thickness was measured at five equally spaced levels from the root apex (Level A) to the buccal alveolar crest (Level E) for the central and lateral incisors. Alveolar crest height, incisor torque and rotation, follicular width, canine localization, canine-to-root proximity, and root resorption were also assessed. Results: The impacted side showed significantly reduced buccal bone thickness at the two most apical levels of the lateral incisor: Level A (−0.81 mm; p < 0.001) and Level B (−0.35 mm; p = 0.004). No side differences were observed at the remaining lateral incisor levels or at any central incisor level. In the orientation-adjusted sensitivity model accounting for incisor torque and rotation, Level A remained significant (−0.75 mm; p < 0.001), whereas Level B was attenuated (p > 0.005). Lateral incisors on the impacted side also showed reduced labial torque (−4.97°; p = 0.001) and greater mesiobuccal rotation (−12.23°; p < 0.001). Conclusions: PICs were associated with localized apical reduction in buccal bone thickness of the adjacent lateral incisor, accompanied by reduced labial torque and greater mesiobuccal rotation. Buccal bone thickness may represent a relevant consideration during CBCT-based treatment planning for PICs. Full article

Soil quality assessment, which considers numerous physical, chemical, and biological indicators, has long been a challenge for monitoring soil functions and ensuring sustainable resource use in agriculture. In this study, different indicator selection and weighting methods were compared to derive a reliable Soil Quality Index (SQI) in semi-arid agroecosystems. A total of 117 topsoil samples were taken from the Ap horizon within a 14,200 ha area of the Honam sub-catchment, southwestern Iran. Twenty-one soil indicators were measured and analyzed to assess the overall SQI. Soil indicator selection was performed using Principal Component Analysis (PCA), considering standard and norm value strategies, as well as component rotation. Four weighting approaches, including PCA, Coefficient of Variation (CV), correlation score (r), and Expert Opinion (EO), were applied to the Minimum Dataset (MDS) and Total Dataset (TDS) to compute the Integrated Quality Index (IQI), Nemoro (NQI), simple additive (IQIa), and Fuzzy Fertility Index (FFI). The performance of the SQI models was evaluated using the Sensitivity Index (SI) and their relationships with crop yield. The results showed that the combination of the norm value approach without component rotation was more effective in selecting the influential indicators for SQI determination. The Soil Stability Index (SSI), which integrates soil organic carbon and textural properties, was the key indicator with the highest contribution, ranging between 6.3% and 37.5% in most of the models. Among the evaluated approaches, the IQI-CV-MDS showed the highest sensitivity (SI = 6.8) and the strongest correlation (r = 0.53) with rainfed barley yield. The majority of the samples exhibited moderate SQI values, indicating a general risk of soil quality decline in the study area. The findings of this study highlight that appropriate indicator selection and weighting strategies are essential for improving the reliability of SQI assessments in semi-arid environments with diverse mountainous topography. Full article

Hip joint position sense (JPS), a key component of neuromuscular function arising from muscle spindle and periarticular mechanoreceptor input, remains underexplored, with no standardized and reliable clinical protocol available to assess hip proprioception. This study evaluated the intra- and inter-rater reliability of a laser- and inclinometer-based active hip JPS protocol and established preliminary references in healthy adults. A two-phase reliability study was conducted in accordance with GRRAS and COSMIN guidelines: 17 participants for reliability analyses and 57 for preliminary references. Six movement directions were assessed (flexion, extension, abduction, adduction, medial and lateral rotations). Reliability was quantified using intraclass correlation coefficients with their 95% confidence intervals, using two-way random-effects models with absolute agreement (ICC(3,1) for intra-rater and ICC(2,1) for inter-rater analyses), interpreted as poor (<0.50), moderate (0.50–0.70), or good (≥0.70). Absolute measurement error was reported as standard error of measurement (SEM%) and 95% minimal detectable change (MDC95%), normalized to target amplitudes to allow direct cross-direction comparison. Intra-rater reliability ranged from poor to moderate, with experienced raters reaching ICC = 0.64 (95% CI [0.39; 0.80]) for medial rotation. Inter-rater reliability improved across sessions, peaking for medial rotation (ICC = 0.78; 95% CI [0.50; 0.91]). Rotational movements yielded the lowest SEM% (3–6%), indicating high measurement precision despite trial-to-trial variability (MDC% 9–31%). Normative errors were largest in flexion (21.4 cm) and smallest in rotations (≈2.2–2.3°). Despite overall low-to-moderate reliability, the protocol achieved clinically acceptable measurement precision (SEM% < 10%) for rotational tasks, whereas the laser-based sagittal and frontal-plane components remained exploratory. The protocol provides preliminary reference values for hip JPS in healthy adults and requires further validation before clinical use. Full article

Modeling crop development under different agrotechnologies is important not only for assessing the factors that affect their yields but also because of the role of vegetation in regulation of the hydrology regime. For this reason, interest in the plant module in the semi-distributed hydrological model SWAT is increasing. The model has to be supplied with a lot of information for running and testing, which can be achieved with ground-based, statistical and satellite data. The aim of the study is to determine the accuracy of the SWAT model to predict crop development by using ground-based and satellite data for LAI in the case of a 5-year field experiment. Two staple crops in rotation were monitored—winter wheat and maize—under different erosion control technologies (up-and-down conventional tillage, conventional contour tillage, and minimum contour tillage with inclusion of cover crop before maize) on sloping terrain on moderately eroded Epicalcic Chernozem in the region of Ruse, north Bulgaria. The remote sensing data from the Copernicus Sentinel-2 mission were used for estimation of LAI of both crops and verified against ground-based data in two ways—via a custom LAI script available through the Sentinel Hub cloud platform and as input to a machine learning quantile regression forests (QRF) model. The calibrated satellite-derived LAI, ground-based soil moisture and yields data were used to calibrate several SWAT model parameters (EPCO, ESCO, CN2, LAImax, HU, HI) and assess the model performance regarding these variables. Although a good temporal fit of the SWAT-modeled LAI data with the satellite data was achieved, the accuracy of predicted LAI is moderately high only in the last two years of the rotation (R² = 60.4%). The accuracy of calibrated yields (R² = 55.5%) is acceptable in four of the years. On average for the period, the applied erosion control agrotechnologies did not cause significantly different yields, but they are 14% higher compared to the up-and-down conventional tillage. The most sensitive SWAT parameters accounting for this effect are EPCO and ESCO. Full article

This paper proposes a superelliptic dual quaternion framework that extends classical dual quaternion kinematics by replacing the Euclidean metric structure with a Gielis-formula-induced superelliptic inner product and its associated vector product. Within the resulting space ${\mathbb{R}}_{{\mathbb{S}}_{\mathcal{E}}}^3$, superelliptic dual numbers, dual vectors, and an E-Study-type correspondence between unit dual vectors and directed superelliptic lines are established, yielding an algebraic model adapted to non-Euclidean geometric profiles. In contrast to the standard Euclidean dual quaternion formalism, where rotations, translations, and screw motions are governed by the ordinary inner product of ${\mathbb{R}}^3$, the present formulation encodes these motions relative to a parameter-dependent superelliptic geometry determined by Gielis’ superformula. This distinction enables the kinematic description of motions associated with superelliptic axes and trajectories that cannot be represented naturally within the classical Euclidean setting. A superelliptic screw motion theorem is obtained, showing that a unit superelliptic dual quaternion generates simultaneous rotation about and translation along a common superelliptic axis. The framework offers a compact mathematical basis for advanced rigid-body modeling in robotics and geometric design. The proposed framework represents rotation, translation, and screw displacement by a single unit superelliptic dual quaternion, providing a compact basis for shape-dependent rigid-body modeling in robotics and geometric design. Full article

To enhance the fidelity of the DEM representation of sugar beet roots, the root geometry was reconstructed from three-dimensional scanning data and represented in EDEM2024 as a multi-sphere clump. The Hertz–Mindlin (no slip) model was used to describe particle contact behavior. The root–Q235 steel contact parameters were determined by drop-rebound, inclined-plane sliding, and inclined-plane rolling experiments. For root–root interactions, the parameters were further refined through cylinder-lifting repose-angle simulations combined with the steepest-ascent method and a three-factor quadratic orthogonal rotatable regression scheme. The optimized inter-root restitution coefficient, static friction coefficient, and rolling friction coefficient were 0.534, 0.728, and 0.080, respectively. With this parameter set, the deviation between the simulated and measured angles of repose was 0.86%, and the error obtained in the independent validation test was 1.5%. These results demonstrate that the proposed DEM model and calibrated parameter set can accurately represent the motion and contact behavior of sugar beet roots. Full article

In underground engineering, the dynamic failure mechanisms of rock masses containing openings under impact loading are of vital importance. This study systematically investigates the effects of opening shape, size, and orientation on the dynamic behavior of red sandstone. Dynamic impact tests are first performed using a split Hopkinson pressure bar together with high-speed photography and digital image correlation for full-field strain and crack monitoring. A two-dimensional combined finite–discrete element (FDEM) model is then developed to reproduce the dynamic failure process. It is found that the opening size significantly affects the dynamic compressive strength, while the opening shape dictates crack initiation and propagation. Circular openings induce symmetric cracking, square openings cause corner-dominated cracks, and horseshoe-shaped openings produce asymmetric failure whose dominant side depends on the rotation angle. The FDEM model established in this study successfully reproduces the main crack paths and failure modes observed in experiments, which provides a powerful tool for the analysis of rock dynamic failure. Moreover, the results in this study also provide practical engineering guidance for the reinforcement and support measures for different opening shapes. Full article

The volumetric mass transfer coefficient ($k_{L}a$) governs the design, operation, and scale-up of aerobic bioprocesses, yet its dependence on reactor geometry, impeller design, operating conditions, and fluid properties limits prediction by empirical correlations. Machine learning (ML) improves accuracy but faces two barriers in bioprocess practice: selecting the best model among many candidates requires expertise, and small, highly multicollinear data make models chosen based on test error alone prone to overfitting. Using a browser-based, no-code platform, we trained 14 regression algorithms under an identical pipeline on a published $k_{L}a$ dataset, and introduced a composite objective, the generalization-penalized error (GPE), which is the test RMSE plus the absolute train–test RMSE gap. Minimizing GPE rather than test RMSE expanded the top statistically equivalent group to include not only boosting ensembles but also simpler, interpretable models, indicating that black-box models hold no clear advantage once train–test consistency is assessed. Sensitivity analysis showed that tree models produce discontinuous responses, whereas algebraic learning via elastic net (ALVEN) yields smooth surfaces. Shapley additive explanations (SHAP) and an ontology graph, interpreted by a retrieval-augmented language-model agent, identified rotational speed and gas flow rate as dominant, reproducing the established mass transfer mechanism. The framework offers a reproducible, interpretable, expertise-light route to bioprocess model selection. Full article

Variable-amplitude vibrating screens are widely adopted for screening frozen sea buckthorn berry particles. Investigating their motion characteristics and particle behaviors on the screen surface is essential for optimizing the screening process and improving equipment performance and screening efficiency. In this work, a variable-amplitude vibrating screen is taken as the research subject. Its structural composition and working principle are elaborated, and kinematic simulations are conducted via RecurDyn. The results reveal that the vertical amplitude and velocity of the screen surface increase gradually from the feed end to the discharge end, which facilitates rapid particle penetration. Meanwhile, the horizontal velocity remains stable across all sections of the screen. Specifically, crank length governs the screen amplitude, while crank rotational speed determines the vibration frequency. A dynamic model of particles and the screen surface is established by combining EDEM 2024 and RecurDyn V9R4, and two-way coupling of the discrete element model is realized. Coupled simulation results indicate that the dynamic screening efficiency rises with increasing crank length and rotational speed, reaching the maximum at a crank length of 20 mm and a rotational speed of 208 r/min. Crank parameters exert remarkable effects on the thickness of the particle layer and the quantity of penetrated particles: a thicker particle layer leads to a longer residence time of materials on the screen. Field tests are carried out to verify the model accuracy. It turns out that the simulation results are basically consistent with experimental data. In conclusion, crank length and rotational speed are critical influencing factors for variable-amplitude vibrating screens. Research on the screen’s motion characteristics and particle behaviors can provide a theoretical reference for its efficient operation and optimal design. Full article

The industrial Internet of Things (IoT) allows traditional electromechanical systems to be connected to digital monitoring and control platforms, especially when field devices use industrial protocols that must be integrated into web services without modifying their main operation. This work implements an IoT architecture based on the Open Systems Interconnection (OSI) model to interconnect two Variable Frequency Drives (VFDs) through a LOGO! Programmable Logic Controller (LOGO! PLC), a Human–Machine Interface (HMI), a ZLAN5143D gateway, Node-RED, Message Queuing Telemetry Transport (MQTT), and Adafruit IO. The communication integrates RS485/Modbus RTU at the field level and Modbus TCP/IP over Ethernet at the upper network level using the gateway as the protocol conversion element. The validation was performed through Modbus Poll, variable acquisition, MQTT publication, and web visualization. The results show local communication response, acquisition of frequency, voltage, current, and revolutions per minute (RPM), together with remote control of start, stop, frequency setpoint, and rotation direction. The architecture is presented as a modular solution for electromechanical applications with IoT projection. Full article

Individual tree modeling (ITM) is an effective system for thinned stands, especially in teak (Tectona grandis Linn F.) plantations, allowing the estimation of individual-tree-specific variables. Heartwood diameter and volume have high added value and can be estimated in living trees. Therefore, we developed an ITM system for clonal teak stands capable of projecting technical intervention ages and quantifying heartwood production throughout the rotation in the Eastern Brazilian Amazon. The system included equations for total tree height, site index, and taper of both stem and heartwood, with volumes obtained by integrating the respective taper equations. Future diameters and heights were projected using models based on the algebraic difference approach (ADA) and the generalized algebraic difference approach (GADA). Ages of technical intervention were defined by the maximum mean annual increment in volume with bark. The Lundqvist-Korf-ADA base model was the most accurate in estimating future trees’ diameters and heights. The inclusion of the number of trees as a covariate to represent thinning had a significant and positive impact on variable projections. Optimal technical rotations ranged from 17.1 to 21.3 years, considering volume with bark. An increase in the proportion of heartwood was observed, reaching 78% of the diameter and 53% of the volume at rotation ages. The modeling system developed in the present study enables the estimation of technical rotation ages and the quantification of heartwood production throughout the rotation, which provides reliable information for silvicultural planning and decision-making in the management of clonal teak stands. Full article

To address the challenges of complex multi-channel signal coupling and insufficient long-term temporal dependency characterization in remaining useful life (RUL) prediction of rotating machinery, this paper proposes a multivariate time series forecasting framework integrating multi-channel information fusion and a self-attention gated augmentation unit (SGAU). First, a multilayer perceptron (MLP) explicitly models nonlinear coupling among channels; SGAU replaces the conventional feed-forward network in the Transformer encoder, using multi-head self-attention outputs as gating signals to adaptively regulate feature transformation. Second, multi-channel signals are predicted via this framework; high-dimensional feature vectors are extracted to construct multi-channel Gaussian mixture models (GMMs). Third, Jensen–Shannon divergence (JSD) quantifies deviations between the target and initial data clusters; centroid distance evolutionary trajectory is fused with JSD to construct the health indicator (HI). Continuous HI predictions yield the RUL prediction curve. Experiments on a self-designed wind turbine gearbox platform and the XJTU-SY bearing dataset demonstrate that the proposed framework outperforms baseline methods on Mean Square (MS), Root Mean Square (RMS), and Energy metrics, with average error reductions of 6.6% and 12.1% in the horizontal and vertical directions on the gearbox dataset and 20.9% and 32.3% on the bearing dataset, confirming its effectiveness and generalization capability. Full article