Search Results (214)

Determining a high-precision national geoid is a fundamental step in modernizing Kazakhstan’s vertical reference system. However, the country’s vast territory, complex topography, and limited coverage of modern terrestrial and airborne gravimetric surveys present significant challenges. In this context, Soviet-era gravimetric maps at a 1:200,000 scale remain the only consistent nationwide data source, yet their reliability has not previously been rigorously assessed within modern gravity standards. This study presents the first comprehensive validation of Soviet-era gravimetric surveys using two independent approaches. The first approach is about the comparison of gravity anomalies with the global geopotential models EGM2008, EIGEN-6C4 and XGM2019e_2159. The second approach is about the direct evaluation against absolute gravity measurements from the newly established Qazaqstan Gravity Reference Frame (QazGRF). The analysis demonstrates that, after applying systematic corrections, the Soviet-era gravimetric survey retains high information content. The mean discrepancy with QazGRF measurements is 0.7 mGal with a standard deviation of 2.5 mGal, and more than 90% of the evaluated points deviate by less than ±5 mGal. Larger inconsistencies, up to 20 mGal, are confined to mountainous and geophysically complex regions. In addition, several artifacts inherent to the global models were identified, suggesting that the integration of validated regional gravimetric data can also support future improvements of global gravity models. A key finding was the detection of an artifact in the global models on sheet M43. Its presence was confirmed by comparison with terrestrial gravimetric data and inter-model differences. It was established that the anomaly is caused by inaccuracies in the terrestrial “fill-in” component of the EGM2008 model, which subsequently inherited by later global solutions. The results confirm that Soviet gravimetric maps, once critically re-evaluated and tied to absolute observations, can be effectively integrated with global models. This integration delivers reliable, high-resolution inputs for regional gravity-field modeling. It establishes a robust scientific and practical foundation for constructing the first national geoid of Kazakhstan and for implementing a unified state coordinate and height system. It also helps enhance the accuracy of global geopotential models. Full article

Tall-pier, long-span continuous rigid-frame bridges are prone to wind-induced vibration due to their large spans and pier heights; during cantilever erection, the maximum double-cantilever stage has reduced stiffness and buffeting becomes more evident. Accordingly, a time-domain framework driven by three-component aerodynamic coefficients and their angle-of-attack derivatives is adopted. Code-based target spectra are used to synthesize multi-point fluctuating wind time histories via harmonic superposition, followed by statistical and spectral consistency checks. Buffeting forces are then computed under the quasi-steady assumption, mapped to finite-element nodes, and integrated in time to obtain global responses (displacement and acceleration). In parallel, static six-component wind tunnel tests provide mean force and moment coefficients and their derivatives for comparison. The results indicate that the three-component time-domain approach captures the buffeting features dominated by vertical and torsional responses. When pronounced along-span sectional variation and high angle-of-attack sensitivity are present, errors associated with the strip assumption increase, whereas the force–moment coupling revealed by the six-component data helps explain discrepancies between simulation and tests. These response patterns and error characteristics delineate the applicability and limits of the three-component time-domain evaluation for variable-depth continuous rigid-frame bridges, offering a reference for wind resistance assessment and construction-stage checking of similar bridges. Full article

Background: Repeated vertical jump tests are widely used to assess neuromuscular function and lower limb performance. However, inconsistent formulas for average power output produce large discrepancies, limiting comparability across studies and limiting practical applications. This study aimed to compare three different models for the calculation of average power output, Bosco, Miron Georgescu (MG), and Modified Miron Georgescu-15s (MGM-15), applied to identical jump test data, in order to evaluate their computational behavior and practical relevance in athlete performance profiling. Methods: A single-group quasi-experimental study was conducted with 25 physically active male university students (mean age: 21.4 ± 2.7 years), who performed a 15 s repeated vertical jump test on the OptoJump Next system. Raw parameters including flight time, contact time, and jump height were recorded and exported. Average power output (W/kg) was subsequently calculated using three distinct computational models, each applied to the same dataset of flight and contact times. A repeated-measures ANOVA was used to compare outputs across models, with Bonferroni-adjusted pairwise comparisons for post hoc analysis (α = 0.05). Results: Significant differences were observed (p < 0.001). The Bosco model produced the highest values of average power (40.13 ± 8.56 W/kg), followed by MG (21.07 ± 5.92 W/kg), while MGM-15 yielded the lowest and most consistent outputs (4.08 ± 0.61 W/kg). Effect sizes were very large (η²_p = 0.952), confirming that calculation models strongly influenced the outcomes. Conclusions: The findings demonstrate that average power output differed markedly across formulas, despite identical performance data. Bosco and MG models tended to overestimate values due to simplified assumptions, whereas the MGM-15 method produced lower and more consistent outputs that may better capture repeated jump demands. The standardization of computational models is fundamental to ensure comparability and to improve athlete performance profiling in research and practice. Full article

Floating vertical−axis wind turbines present unique advantages for deep−water offshore deployments, but their basin model testing encounters significant challenges in aerodynamic load simulation due to Reynolds scaling effects. While Froude−scaled experiments accurately replicate hydrodynamic behaviors, the drastic reduction in Reynolds numbers at the model scale leads to substantial discrepancies in aerodynamic forces compared to full−scale conditions. This study proposed two methodologies to address these challenges. Fully physical model tests adopt a “physical wind field + rotor model + floating foundation” approach, realistically simulating aerodynamic loads during rotor rotation. Semi−physical model tests employ a “numerical wind field + rotor model + physical floating foundation” configuration, where theoretical aerodynamic loads are obtained through numerical calculations and then reproduced using controllable actuator structures. For fully physical model tests, a blade reconstruction framework integrated airfoil optimization, chord length adjustments, and twist angle modifications through Taylor expansion−based sensitivity analysis. The method achieved thrust coefficient similarity across the operational tip−speed ratio range. For semi−physical tests, a cruciform−arranged rotor system with eight dynamically controlled rotors and constrained thrust allocation algorithms enabled the simultaneous reproduction of periodic streamwise/crosswind thrusts and vertical−axis torque. Numerical case studies demonstrated that the system effectively simulates six−degree−of−freedom aerodynamic loads under turbulent conditions while maintaining thrust variation rates below 9.3% between adjacent time steps. These solutions addressed VAWTs’ distinct aerodynamic complexities, including azimuth−dependent Reynolds number fluctuations and multidirectional force coupling, which conventional methods fail to accommodate. The developed techniques enhanced the fidelity of floating VAWT basin tests, providing critical experimental validation tools for emerging offshore wind technologies. Full article

The precision of ERA5 reanalysis datasets and their applicability in the mountainous regions of central China are essential for weather forecasting and climate change research in the transitional zone between northern and southern China. This study employs three months of continuous measurements collected from a high-precision remote sensing platform located in a representative mountainous valley (Xinyang city) in central China, spanning December 2024 to February 2025. Our findings indicate that both horizontal and vertical wind speeds from the ERA5 dataset exhibit diminishing deviations as altitude increases. Significant biases are observed below 500 m, with horizontal mean wind speed deviations ranging from −4 to −3 m/s and vertical mean wind speed deviations falling between 0.1 and 0.2 m/s. Conversely, minimal biases are noted near the top of the boundary layer. Both ERA5 and observations reveal a dominance of northeasterly and southwesterly winds at near-surface levels, which aligns with the valley orientation. This underscores the substantial impact of heterogeneous mountainous terrain on the low-level dynamic field. At an altitude of 1000 m, both datasets present similar frequency patterns, with peak frequencies of approximately 15%; however, notable discrepancies in peak wind directions are evident (north–northeast for observations and north–northwest for ERA5). In contrast to dynamic variables, ERA5 temperature deviations are centered around 0 K within the lower layers (0–500 m) but show a slight increase, varying from around 0 K to 6.8 K, indicating an upward trend in deviation with altitude. Similarly, relative humidity (RH) demonstrates an increasing bias with altitude, although its representation of moisture variability remains insufficient. During a typical cold event, substantial deviations in multiple ERA5 variables highlight the needs for further improvements. The integration of machine learning techniques and mathematical correction algorithms is strongly recommended as a means to enhance the accuracy of ERA5 data under such extreme conditions. These findings contribute to a deeper understanding of the use of ERA5 datasets in the mountainous areas of central China and offer reliable scientific references for weather forecasting and climate modelings in these areas. Full article

Background/objective: Class III malocclusion is a relatively common clinical problem among Asian patients, which is caused by skeletal discrepancies and involves complex factors. In growing patients, early intervention with myofunctional appliances can help correct jaw relationships more effectively. This case report presents the use of prefabricated myofunctional appliances (EF and MRC) to address Class III malocclusion through growth modification. Case description: A 9-year-old girl was diagnosed with skeletal Class III and a complete anterior crossbite. She underwent treatment with the prefabricated myofunctional appliances, worn during sleep and an additional two hours during the day for 51 months. The outcomes resulted from a combination of skeletal and dental changes, including a decrease in skeletal discrepancy (ANB: −5° to −2°), upper incisor proclination (U1 to SN: 112.5° to 123°), uprighting of the lower incisor (L1 to MP: 93.5° to 90°), and an increase in cranial flexure angle (123° to 125°) with a vertical mandibular growth pattern. The treatment improved facial profile, reduced skeletal discrepancy, corrected the anterior crossbite, and enhanced interdigitation. Conclusions: Prefabricated myofunctional appliances are effective options for managing skeletal Class III malocclusion in pediatric patients with vertical mandibular growth patterns, producing favorable skeletal and dentoalveolar changes. Full article

In lateral-joint-widening projects of multi-span continuous concrete box girder bridges, significant discrepancies in longitudinal shrinkage, creep deformation, and vertical displacement between the existing and newly added bridge sections can lead to stress concentration and subsequent concrete cracking. Notably, such incompatibility often results in pronounced overall lateral bending deformation, which compromises the structural safety and service reliability of the widened bridge. To address these challenges, this study proposes a novel sliding-type transverse connection structure. This innovative connection enables the independent development of longitudinal shrinkage and creep deformation in the new bridge superstructure relative to the old one through a sliding mechanism, thereby effectively mitigating stress concentration and minimizing overall bending deformation caused by differential deformations. To validate the feasibility and elucidate the load transfer mechanism of the proposed structure, both scaled model tests and finite element simulations were conducted. The results indicate that the connection not only effectively coordinates longitudinal deformation differences and accommodates vertical deformation between the flange plates of the new and old bridges, but also ensures efficient transverse load transfer through shear force transmission. The structural behavior is primarily governed by shear stress distribution. These findings demonstrate that the sliding-type transverse connection significantly improves deformation compatibility in bridge widening applications, thereby enhancing the mechanical performance and safety reliability of the overall structure. Full article

Background/Objectives: Vertical growth pattern significantly influences facial aesthetics and treatment choices. Lateral cephalograms are routinely used for the evaluation of vertical jaw relationships in orthodontic diagnosis. The aim of this study was to evaluate the performance of deep learning algorithms in classifying cephalometric radiographs according to vertical skeletal growth patterns without the need for anatomical landmark identification. Methods: This study was carried out on lateral cephalometric radiographs of 1050 patients. Cephalometric radiographs were divided into 3 subgroups based on FMA, SN-GoGn, and Cant of Occlusal Plane angles. Six deep learning models (ResNet101, DenseNet 201, EfficientNet B0, EfficientNet V2 B0, ConvNetBase, and a hybrid model) were employed for the classification of the dataset. The performances of the well-known deep learning models and the hybrid model were compared for accuracy, precision, F1-Score, mean absolute error, Cohen’s Kappa, and Grad-CAM metrics. Results: The highest accuracy rates were achieved by the Hybrid Model with 86.67% for FMA groups, 87.29% for SN-GoGn groups, and 82.71% for Cant of Occlusal Plane groups. The lowest accuracy rates were achieved by ConvNet with 79.58% for FMA groups, 65% for SN-GoGn, and 70.21% for Cant of Occlusal Plane groups. Conclusions: The six deep learning algorithms employed demonstrated classification success rates ranging from 65% to 87.29%. The highest classification accuracy was observed in the FMA angle, while the lowest accuracy was recorded for the Cant of the Occlusal Plane angle. The proposed DL algorithms showed potential for direct skeletal orthodontic diagnosis without the need for cephalometric landmark detection steps. Full article

Deep learning-based object detection has achieved remarkable maturity after years of intensive research. However, as multi-platform data acquisition becomes increasingly prevalent, spanning satellite, UAV, and ground-based platforms, a critical challenge emerges involving significant vertical perspective variations in captured images. The current object detection literature largely neglects this perspective dimension, particularly the robustness evaluation of single models across diverse viewing angles. To bridge this gap, we first conduct a systematic review categorizing existing approaches into standard and rotated object detection paradigms. Second, we build the Multi-Vertical-Perspective Object Detection (MVPOD) dataset; this dataset is the first comprehensive benchmark integrating spaceborne (nadir), airborne (oblique) and ground-level (horizontal) imagery with dual annotation schemes. Third, rigorous cross-perspective evaluation protocols reveal that vertical viewpoint discrepancies cause measurable performance degradation. Finally, representative methods are benchmarked on the MVPOD dataset, establishing baselines for future research. Full article

With the expansion of offshore and subsea infrastructure in Arctic and sub-Arctic regions, concerns are rising, driven by climate change and global warming, over the risk of drifting icebergs colliding with these structures in cold waters. Traditional methods for estimating iceberg underwater height and assessing subgouge soil properties, such as costly and time-consuming underwater surveys or centrifuge tests, are still used, but the industry continues to seek faster and more cost-efficient solutions. In this study, the extra tree regression (ETR) algorithm was employed for the first time to simultaneously model iceberg drafts and subgouge soil properties in both sandy and clay seabeds. The ETR approach first predicted the iceberg draft, then simulated subgouge soil reaction forces and deformations. A total of 22 ETR models were developed, incorporating parameters relevant to both iceberg draft estimation and subgouge soil characterization. The best-performing ETR models, along with the most influential input variables, were identified through a combination of sensitivity, error, discrepancy, and uncertainty analyses. The ETR model predicted iceberg draft with a high level of accuracy (R = 0.920, RMSE = 1.081), while the superior model for vertical reaction force in sand achieved an RMSE of 43.95 with 70% of predictions within 16% error. The methodology demonstrated improved prediction capacity over traditional techniques and can serve early-stage iceberg risk management. Full article

Aerosol radiative forcing is known to significantly disturb the thermodynamic and dynamic structure of the Planetary Boundary Layer (PBL), particularly in heavily polluted urban regions. In this study, the effects of aerosol–PBL interactions were examined over a megacity in China’s Central Plains by comparing ERA5 reanalysis data with multi-source ground-based observations. Key meteorological variables—including wind speed, wind direction, temperature, and relative humidity—were analyzed across pressure levels from 1000 to 800 hPa. Good agreement in wind direction was observed between ERA5 and observations (R² > 0.84), while wind speed showed a moderate correlation (R² = 0.54–0.73) with an RMSE of 1.85 m/s near 975 hPa. Temperature discrepancies were found to decrease with altitude, with RMSE values reducing from 3.02 K to 1.84 K, indicating a modulation of thermal stratification by aerosol radiative effects. A stable structure was revealed by humidity analysis near the surface but increased variability aloft, with absolute differences reaching ±30% at 850–800 hPa. Diurnal variations were characterized by night-time warming of up to +5 °C in the lower PBL and concurrent cooling above 800 hPa. The Heating and surface Dimming (HD) Index was found to correlate positively with PM_2.5 concentration (R = 0.60), reflecting increased thermal stability and vertical inhomogeneity under aerosol loading. These findings underscore the need for an improved understanding and mitigation of aerosol–PBL interactions to support sustainable urban air quality management strategies. Full article

This study evaluates the applicability and accuracy of coarse-grain modeling (CGM) in discrete-element method (DEM)–based simulations, focusing on particle-mixing efficiency in five representative industrial mixers: the tumbling V mixer, ribbon-blade mixer, paddle-blade mixer, vertical-blade mixer, and conical-screw mixer. Although the DEM is widely employed for particulate system simulations, the high computational cost associated with fine particles significantly hinders large-scale applications. CGM addresses these issues by scaling up particle sizes, thereby reducing particle counts and allowing longer simulation timesteps. We utilized the Lacey mixing index (LMI) as a statistical measure to quantitatively assess mixing uniformity across various CGM scaling factors. Based on the results, CGM significantly reduced computational time (by over 90% in certain cases) while preserving acceptable accuracy levels in terms of LMI values. The mixing behaviors remained consistent under various CGM conditions, based on both visually inspected particle distributions and the temporal LMI trends. Although minor deviations occurred in early-stage mixing, these discrepancies diminished with time, with the final LMI errors remaining below 5% in most scenarios. These findings indicate that CGM effectively enhances computational efficiency in DEM simulations without significantly compromising physical accuracy. This research provides practical guidelines for optimizing industrial-scale particle-mixing processes and conducting computationally feasible, scalable, and reliable DEM simulations. Full article

The current focus of urban environmental governance is on the traffic noise pollution caused by road transportation. Elevated complex roads, defined as transportation systems comprising elevated roads and underlying ground-level roads, exhibit unique traffic noise distribution characteristics due to the presence of double-decked roads and viaducts. This study conducted noise measurements at two sections of elevated complex roads in Guangzhou, including assessing noise levels at the road boundaries and examining noise distribution at different distances from roads and building heights. The results show that the horizontal distance attenuation of noise in adjacent areas exhibits no significant difference from that of ground-level roads, but substantial discrepancies exist in vertical height distribution. The under-viaduct space experiences more severe noise pollution than areas above the viaduct height, and the installation of sound barriers alters the spatial distribution trend of traffic noise. Given that installing sound barriers solely on elevated roads is insufficient to improve the acoustic environment, systematic noise mitigation strategies should be developed for elevated composite road systems. Additionally, the study reveals that nighttime noise fluctuations are significantly greater than those during the day, further exacerbating residents’ noise annoyance. Full article

Objectives: This study aimed to evaluate the effects of AMCOP^® elastodontic appliances on cephalometric parameters of skeletal divergence and upper airway dimensions in growing patients, comparing treated individuals with an untreated control group. Methods: A total of 60 subjects (30 treated with AMCOP^® devices and 30 controls) were selected, with mean ages of 8.67 ± 1.3 and 9.19 ± 0.8 years, respectively. The AMCOP^® appliances, designed for mixed dentition, were worn for 1 h during the day and throughout the night for 6–8 months. Cephalometric analyses were conducted at the beginning (T0) and end (T1) of treatment. Statistical analyses were performed using multivariable linear regression models to assess changes in skeletal and airway parameters, with significance set at p < 0.05. Results: Significant reductions were observed in Ans-Snp^Go-Gn (p = 0.0351), SN^Go-Gn (p = 0.0091), and FMA (p < 0.001) in the treated group compared to controls, indicating improved mandibular rotation. Upper airway spaces (SPAS, MAS, IAS) increased significantly, suggesting enhanced airway patency. Regression models confirmed the positive impact of AMCOP^® therapy on skeletal and airway outcomes, particularly in subjects with pronounced vertical discrepancies. Conclusions: AMCOP^® elastodontic devices effectively promote anterior mandibular rotation and reduce mandibular plane inclination in hyperdivergent patients, contributing to balanced craniofacial growth. The expansion of pharyngeal spaces indicates potential respiratory benefits. Future research is needed to confirm long-term stability and address variability in treatment response. Full article

Aging railroad bridges present complex challenges due to advancing deterioration and outdated design assumptions. This study develops a comprehensive analytical approach for assessing an aging steel truss railroad bridge through finite element (FE) modeling, sensitivity analysis, and model updating, supported by field testing. An initial FE model of the bridge was created based on original drawings and field observations. Field testing using a laser Doppler vibrometer captured the bridge’s dynamic response (vibrations and deflections) under regular train traffic. Key structural parameters (material properties, section properties, support conditions) were identified and varied in a sensitivity analysis to determine their influence on model outputs. A hybrid sensitivity analysis combining log-normal sampling and a genetic algorithm (GA) was employed to explore the parameter space and calibrate the model. The GA optimization tuned the FE model parameters to minimize discrepancies between simulated results and field measurements, focusing on vertical deflections and natural frequencies. The updated FE model showed significantly improved agreement with observed behavior; for example, vertical deflections under a representative train were matched within a few percent, and natural frequencies were accurately reproduced. This validated model provides a more reliable tool for predicting structural performance and fatigue life under various loading scenarios. The results demonstrate that integrating field data, sensitivity analysis, and model updating can greatly enhance the accuracy of structural assessments for aging railroad bridges, supporting more informed maintenance and management decisions. Full article