Search Results (7,486)

Background: Repeat induced abortion (defined as ≥two lifetime procedures) is becoming more common worldwide, yet its independent influence on women’s psychological health remains contested, particularly in settings where access to modern contraception is restricted. Objectives: This review sought to quantify the burden of depression, anxiety, stress, and generic quality of life (QoL) among women with repeat abortions and to determine how barriers to contraceptive access alter those outcomes. Methods: Following the preregistered PRISMA-2020 protocol, PubMed, Embase and Scopus were searched from inception to 31 June 2025. Results: Eight eligible studies comprising approximately 262,000 participants (individual sample sizes up to 79,609) revealed wide variation in psychological morbidity. Prevalence of clinically significant symptoms ranged from 5.5% to 24.8% for depression, 8.3% to 31.2% for anxiety, and 18.8% to 27% for perceived stress; frequent mental distress affected 12.3% of women in neutral policy environments but rose to 21.9% under highly restrictive abortion legislation. Having three or more abortions, compared with none or one, increased the odds of depressive symptoms by roughly one-third (pooled OR ≈ 1.37, 95% CI 1.13–1.67). Contextual factors exerted comparable or stronger effects: abortions sought for socioeconomic reasons elevated depression odds by 34%, unwanted disclosure of the abortion episode increased depressive scores by 0.62 standard deviations, and low partner support raised them by 0.67 SD. At the structural level, every standard deviation improvement in a state’s reproductive rights index reduced frequent mental distress odds by 5%, whereas enactment of a near-total legal ban produced an absolute increase of 6.8 percentage points. QoL outcomes were less frequently reported; where measured, denied or heavily delayed abortions were associated with a 0.41-unit decrement on a seven-point life satisfaction scale. Conclusions: Psychological morbidity after abortion clusters where legal hostility, financial hardship, or interpersonal coercion constrain contraceptive autonomy while, in comparison, the mere number of procedures is a weaker predictor. Interventions that integrate stigma-free mental health support with confidential, affordable, and rights-based contraception are essential to protect well-being in women who experience repeat abortions. Full article

Conventional grain monitoring systems often rely on isolated data points (e.g., point-based temperature measurements), limiting holistic condition assessment. This study proposes a novel Mechanism and Data Driven (MDD) framework that integrates physical mechanisms with real-time sensor data. The framework quantitatively analyzes solar radiation and external air temperature effects on silo boundaries and introduces a novel interpolation-optimized model parameter initialization technique to enable comprehensive grain condition perception. Rigorous multidimensional validation confirms the method’s accuracy: The novel initialization technique achieved high precision, demonstrating only 1.89% error in Day-2 low-temperature zone predictions (27.02 m² measured vs. 26.52 m² simulated). Temperature fields were accurately reconstructed (≤0.5 °C deviation in YOZ planes), capturing spatiotemporal dynamics with ≤0.45 m² maximum low-temperature zone deviation. Cloud map comparisons showed superior simulation fidelity (SSIM > 0.97). Further analysis revealed a 22.97% reduction in total low-temperature zone area (XOZ plane), with Zone 1 (near south exterior wall) declining 27.64%, Zone 2 (center) 25.30%, and Zone 3 20.35%. For dynamic evolution patterns, high-temperature zones exhibit low moisture (<14%), while low-temperature zones retain elevated moisture (>14%). A strong positive correlation between temperature and relative humidity fields; temperature homogenization drives humidity uniformity. The framework enables holistic monitoring, providing actionable insights for smart ventilation control, condensation risk warnings, and mold prevention. It establishes a robust foundation for intelligent grain storage management, ultimately reducing post-harvest losses. Full article

Photogrammetry offers a non-contact and efficient alternative for monitoring structural deformation and is particularly suited to large or complex surfaces such as masonry walls. This study proposes a spatio-temporal photogrammetric refinement framework that enhances the accuracy of three-dimensional (3D) deformation and strain analysis by integrating advanced filtering techniques into markerless image-based measurement workflows. A hybrid methodology was developed using natural image features extracted using the Speeded-Up Robust Features algorithm and refined through a three-stage filtering process: median absolute deviation filtering, Gaussian smoothing, and representative point selection. These techniques significantly mitigated the influence of noise and outliers on deformation and strain analysis. Comparative experiments using both manually placed targets and automatically extracted feature points on a full-scale masonry wall under destructive loading demonstrated that the proposed spatio-temporal filtering effectively improves the consistency of displacement and strain fields, achieving results comparable to traditional marker-based methods. Validation against laser rangefinder measurements confirmed sub-millimeter accuracy in displacement estimates. Additionally, strain analysis based on filtered data captured crack evolution patterns and spatial deformation behavior. Therefore, integrating photogrammetric 3D point tracking with spatio-temporal refinement provides a practical, accurate, and scalable approach to monitor structural deformation in civil engineering applications. Full article

We investigated the repeatability of the MS-39 in determining power vector components—the spherical equivalent (SEQ) and astigmatic powers (C0 and C45) and asphericity (Q)—of corneal epithelium, stroma, and endothelium in a large patient cohort. In this retrospective cross-sectional single-centre study, we evaluated a dataset containing 600 MS-39 anterior segment tomography measurements from 200 eyes (three repeat measurements each) taken prior to cataract surgery. The exported measurements included height map data for the epithelium, stroma, and endothelium surface. Model surfaces (spherocylinder (SphCyl), cylindrical conoid (CylConoid), and biconic (Biconic), all in the 3/6 mm zone) were fitted using nonlinear iterative optimisation, minimising the height difference between the measurement and model. The mean (MEAN) and standard deviation (SD) for each sequence of measurements were derived and analysed. In the 3 mm and 6 mm zone, the MEAN SEQ was 53.47/53.56/53.57 and 53.21/53.54/53.54 D for SphCyl/CylConoid/Biconic for the epithelium, −4.47/−4.51/−4.51 and −4.45/−4.50/−4.50 D for the stroma, and −6.23/−6.26/−6.26 and −6.18/−6.29/−6.30 D for the endothelium. With the three surface models and the 3/6 mm zone, the SD for SEQ/C0/C45 was in the range of 0.04 to 0.11/0.05 to 0.13/0.04 to 0.11 D for epithelium; 0.01 to 0.02/0.01 to 0.05/0.01 to 0.06 D for stroma; and 0.01 to 0.02/0.02 to 0.07/0.03 to 0.07 D for endothelium. Fitting floating model surfaces with astigmatism to map data of the corneal epithelium, stroma, and endothelium seems to be a robust and reliable method for extracting equivalent power and astigmatism using all the datapoints within a region of interest. Full article

Accurate mapping of small water structures and streambeds is essential for hydrological modeling, erosion control, and landscape management. While traditional geodetic methods such as GNSS and total stations provide high precision, they are time-consuming and require specialized equipment. Recent advances in mobile technology, particularly smartphones equipped with LiDAR sensors, offer a potential alternative for rapid and cost-effective field data collection. This study assesses the accuracy of the iPhone 14 Pro’s built-in LiDAR sensor for mapping streambeds and retention structures in challenging terrain. The test site was the Dílský stream in the Oslavany cadastral area, characterized by steep slopes, rocky surfaces, and dense vegetation. The stream channel and water structures were first surveyed using GNSS and a total station and subsequently re-measured with the iPhone. Several scanning workflows were tested to evaluate field applicability. Results show that the iPhone LiDAR sensor can capture landscape features with useful accuracy when supported by reference points spaced every 20 m, achieving a vertical RMSE of 0.16 m. Retention structures were mapped with an average positional error of 7%, with deviations of up to 0.20 m in complex or vegetated areas. The findings highlight the potential of smartphone LiDAR for rapid, small-scale mapping, while acknowledging its limitations in rugged environments. Full article

Background: Rowing is a highly demanding endurance sport, requiring simultaneous work of approximately 70% of the body’s muscle mass and the combined contribution of aerobic and anaerobic energy systems. Objective: This study aimed to analyze the cardiorespiratory responses and performance characteristics of elite junior male and female rowers during maximal effort over 2000 m on a rowing ergometer. Methods: Fifteen junior rowers (six males aged 15–17 and nine females aged 15–18) participated in the study. Anthropometric data (body height, weight, and body surface area) were recorded. All participants performed a maximal 2000 m test on a Concept2 D-model ergometer. Throughout the test, oxygen uptake (VO₂), carbon dioxide production (VCO₂), heart rate, and ventilation parameters were continuously measured. Performance and physiological data were analyzed in three intensity zones, defined by ventilatory thresholds (VT1–VT3), as well as at peak exercise. Results: Significant anthropometric differences were observed between genders. In terms of performance, males completed the 2000 m test significantly faster than females (208.83 ± 87.66 s vs. 333.78 ± 97.51 s, p = 0.0253). Relative VO₂ at peak exercise was higher in males (58.73 ± 5.25 mL·kg⁻¹·min⁻¹) than females (48.32 ± 6.09 mL·kg⁻¹·min⁻¹, p = 0.0046). In most cardiorespiratory parameters, males outperformed females significantly, except for heart rate and ventilatory equivalents. Ranking analysis revealed that higher VO₂max values were generally associated with a better placement in both genders, though this relationship was not perfectly linear. Performance time was negatively correlated with VO₂Peak (r = −0.8286; p < 0.001), rVO₂Peak (r = −0.6781; p < 0.01), and O₂P_Peak (r = −0.7729; p < 0.01). Conclusions: The findings confirm significant gender differences in anthropometric and cardiorespiratory characteristics of elite junior rowers and reinforce VO₂max as a key determinant of performance. Yet, deviations from a direct VO₂max–rank correlation highlight the influence of tactical, psychological, and biomechanical factors. Future research should provide practical recommendations for monitoring performance and tailoring training to optimize adaptation and long-term athlete development. Full article

This paper introduces Exponentiated Inverse Exponential Distribution (EIED), a novel probability model developed within the power inverse exponential distribution framework. A distinctive feature of EIED is its highly flexible hazard rate function, which can exhibit increasing, decreasing, and reverse bathtub (upside-down bathtub) shapes, making it suitable for modeling diverse lifetime phenomena in reliability engineering, survival analysis, and risk assessment. We derived comprehensive statistical properties of the distribution, including the reliability and hazard functions, moments, characteristic and quantile functions, moment generating function, mean deviations, Lorenz and Bonferroni curves, and various entropy measures. The identifiability of the model parameters was rigorously established, and maximum likelihood estimation was employed for parameter inference. Through extensive simulation studies, we demonstrate the robustness of the estimation procedure across different parameter configurations. The practical utility of EIED was validated through applications to real-world datasets, where it showed superior performance compared to existing distributions. The proposed model offers enhanced flexibility for modeling complex lifetime data with varying hazard patterns, particularly in scenarios involving early failure periods, wear-in phases, and wear-out behaviors. Full article

Introduction: Clear aligner therapy has become a mainstream alternative to fixed orthodontics due to its versatility. However, the variability in thermoforming and the limited validation of digital workflows remain major barriers to reproducibility and predictability. Methods: This study addresses that gap by presenting a proof-of-concept digital workflow for clear aligner manufacturing by integrating additive manufacturing (AM), thermoforming simulation, and finite element analysis (FEA). Dental models were 3D-printed and thermoformed under clinically relevant pressures (400 kPa positive and −90 kPa negative). Results and Discussion: Geometric accuracy was quantified using CloudCompare v2.13.0, showing that positive-pressure thermoforming reduced maximum deviations from 1.06 mm to 0.4 mm, with all deviations exceeding the expanded measurement uncertainty. Thickness simulations of PETG sheets (0.5 and 0.75 mm) showed good agreement with experimental values across seven validation points, with errors <10% and overlapping 95% confidence intervals. Stress analysis indicated that force transmission was localized at the aligner–attachment interface, consistent with expected orthodontic mechanics. Conclusion: By quantifying accuracy and mechanical behavior through numerical and experimental validation, this framework demonstrates how controlled thermoforming and simulation-guided design can enhance aligner consistency, reduce adjustments, and improve treatment predictability. Full article

In this study, the modeling of rough surfaces by eddy-viscosity-based roughness models is investigated, specifically focusing on surfaces representative of deterioration in aero-engines. In order to test these models, experimental measurements from a rough T106C blade section at a Reynolds number of 400 K are adopted. The modeling framework is based on the k–ω–SST with Dassler’s roughness transition model. The roughness model is recalibrated for the k–ω–SST model. As a complement to the available experimental data, a high-fidelity test rig designed for scale-resolving simulations is built. This allows us to examine the local flow phenomenon in detail, enabling the identification and rectification of shortcomings in the current RANS models. The scale-resolving simulations feature a high-order flux-reconstruction scheme, which enables the use of curved element faces to match the roughness geometry. The wake-loss predictions, as well as blade pressure profiles, show good agreement, especially between LES and the model-based RANS. The slight deviation from the experimental measurements can be attributed to the inherent uncertainties in the experiment, such as the end-wall effects. The outcomes of this study lend credibility to the roughness models proposed. In fact, these models have the potential to quantify the influence of roughness on the aerodynamics and the aero-acoustics of aero-engines, an area that remains an open question in the maintenance, repair, and overhaul (MRO) of aero-engines. Full article

The quality of digital 3D models of fossils is important from the perspective of their further usage, either for scientific or didactical purposes. However, fidelity evaluation has rarely been attempted for digitized fossil objects. In the present research, a 3D triangulated model of the unique skull of Madygenerpeton pustulatum was built using an YXLON µCT device. The comparative analysis was performed using models obtained from seven optical surface-scanning systems. Methodology for accuracy assessment involved the determination of distances between the points in pairs of models, interchanging the reference and tested ones. Statistical significance testing using paired t-tests was performed. In particular, it was found that the YXLON µCT model was closest to the one obtained from AICON SmartScan, exhibiting an average distance of $\overline{{∆}_d}$ = −0.0183 mm with a standard deviation of σ{∆_d} = 0.0778 mm, which is close to the permissible error of 20 µm given in technical specifications for AICON scanners. It was demonstrated that the analysis maintained measurement validity even though the YXLON model consisted of 23.8 M polygons and the AICON model consisted of 13.9 M polygons. Comparison with other digital models demonstrated that the fidelity of the triangulated µCT model made it feasible for further research and dissemination purposes. Full article

This paper presents the design and evaluation of a Linear Time-Varying Linear Quadratic Gaussian (LTV-LQG) controller for an energy efficient electric vehicle, using a predetermined driving strategy as the reference trajectory. The proposed approach begins with the development of a structured nonlinear vehicle model based on relevant subsystems, enabling accurate energy consumption estimation with a deviation of less than 2% from experimental measurements. This model serves as the basis for computing a near-optimal driving trajectory. The nonlinear model is linearized along the predefined trajectory to support control design. A time-varying control structure is then developed, integrating a Kalman filter that estimates unmeasured external disturbances, such as wind, and enhances feedback performance. The proposed control strategy is evaluated through simulations and compared to a rule-based switching controller that replicates human-like driving behavior. The simulation results demonstrate that the LTV-LQG controller consistently satisfies the time constraints in both headwind- and tailwind-dominant scenarios, where the switching controller tends to exceed the time limit. Moreover, in tailwind-dominant cases, the LTV-LQG controller achieves lower energy consumption (up to 15.4%). The proposed framework represents a computationally efficient and practically feasible control solution for electric vehicles operating under realistic disturbance conditions. Full article

Open-pit mining often induces geological hazards such as slope instability, surface subsidence, and ground fissures. To support sustainable mine operations and safety, high-resolution monitoring and mechanism-based interpretation are essential tools for early warning, risk management, and compliant reclamation. This study focuses on the Baorixile open-pit coal mine in Inner Mongolia, China, where 48 Sentinel-1 images acquired between 3 March 2017 and 23 April 2021 were processed using the Small-Baseline Subset and Distributed-Scatterer Interferometric Synthetic Aperture Radar (SBAS-DS-InSAR) technique to obtain dense and reliable time-series deformation. Furthermore, a Trend–Periodic–Residual Subspace-Constrained Regression (TPRSCR) method was developed to decompose the deformation signals into long-term trends, seasonal and annual components, and residual anomalies. By introducing Distributed-Scatterer (DS) phase optimization, the monitoring density in low-coherence regions increased from 1055 to 338,555 points (approximately 321-fold increase). Deformation measurements at common points showed high consistency ($R^2$ = 0.97, regression slope = 0.88; mean rate difference = −0.093 mm/yr, standard deviation = 3.28 mm/yr), confirming the reliability of the results. Two major deformation zones were identified: one linked to ground compaction caused by transportation activities, and the other associated with minor subsidence from pre-mining site preparation. In addition, the deformation field exhibits a superimposed pattern of persistent subsidence and pronounced seasonality. TPRSCR results indicate that long-term trend rates range from −14.03 to 14.22 mm/yr, with a maximum periodic amplitude of 40 mm. Compared with the Seasonal-Trend decomposition using LOESS (STL), TPRSCR effectively suppressed “periodic leakage into trend” and reduced RMSEs of total, trend, and periodic components by 48.96%, 93.33%, and 89.71%, respectively. Correlation analysis with meteorological data revealed that periodic deformation is strongly controlled by precipitation and temperature, with an approximately 34-day lag relative to the temperature cycle. The proposed “monitoring–decomposition–interpretation” framework turns InSAR-derived deformation into sustainability indicators that enhance deformation characterization and guide early warning, targeted upkeep, climate-aware drainage, and reclamation. These metrics reduce downtime and resource-intensive repairs and inform integrated risk management in open-pit mining. Full article

Advances in sensor technology have significantly improved the efficiency and precision of agricultural spraying. Unmanned aerial vehicles (UAVs) are widely utilized for applying plant protection products (PPPs) and fertilizers, offering enhanced spatial control and operational flexibility. This study evaluated the performance of an autonomous UAV-based precision spraying system that applies variable rates based on zone levels defined in a prescription map. The system integrates real-time kinematic global navigation satellite system positioning with a proximity-triggered spray algorithm. Field experiments on a rice field were conducted to assess spray accuracy and fertilization efficacy with liquid fertilizer. Spray deposition patterns on water-sensitive paper showed that the graded strategy distinguished among zone levels, with the highest deposition in high-spray zones, moderate in medium zones, and minimal in no-spray zones. However, entry and exit deviations—used to measure system response delays—averaged 0.878 m and 0.955 m, respectively, indicating slight lags in spray activation and deactivation. Fertilization results showed that higher application levels significantly increased the grain-filling rate and thousand-grain weight (both p < 0.001), but had no significant effect on panicle number or grain count per panicle (p > 0.05). This suggests that increased fertilization primarily enhances grain development rather than overall plant structure. Overall, the system shows strong potential to optimize inputs and yields, though UAV path tracking errors and system response delays require further refinement to enhance spray uniformity and accuracy under real-world applications. Full article

The bioavailability of a drug is closely linked to its solubility, making its early determination essential in drug development. The saturation shake-flask (SSF) method is the gold standard protocol for this, which includes a phase separation step—either by sedimentation, filtration, or centrifugation. This step is critical, as it can directly influence the accuracy of the results. This study investigated the impact of centrifugation parameters—time and rotation speed—on solubility measurements. Additionally, we compared two sample preparation protocols: continuous stirring for 24 h versus 6 h of stirring followed by 18 h of sedimentation before centrifugation. Four model compounds were tested at three pH values using Britton–Robinson buffers. Centrifugation was conducted for 5, 10, or 20 min at either 5000 or 10,000 rpm. Results showed that pre-sedimented samples yielded solubility values closer to sedimentation-only references, while continuous stirring often led to overestimated values, particularly at higher speeds and longer durations. One such example was papaverine hydrochloride, that showed solubility values 60–70% higher than the reference after centrifugation at 10,000 rpm for 20 min without prior sedimentation. Lower standard deviations were observed with shorter, slower centrifugation, with 5 min and 5000 rpm yielding results closest to the reference values. Full article

This work presents an extensive experimental and numerical analysis, aimed at investigating the impact of shelf-like fences applied on the suction side of a turbine nozzle guide vane. The cascade is constituted of vanes characterized by long chord and low aspect ratio, which are typical features of some LPT first stages directly downstream of an HPT, hence presenting high channel diffusion, especially near the tip. In particular, the present study complements existing literature by highlighting how blade fences positioned on the suction side can reduce the penetration of the large passage vortex. This is particularly effective in applications where flow turning is limited, the blades are lightly loaded at the front, and the horseshoe vortex is weak. The benefits of the present fence design in terms of losses and flow uniformity at the cascade exit plane have been demonstrated by means of a detailed experimental campaign carried out on a large-scale linear cascade in the low-speed wind tunnel installed in the Aerodynamics and Turbomachinery Laboratory of the University of Genova. Measurements mainly focused on the characterization of the flow field upstream and downstream of straight and fenced vane cascades using a five-hole pressure probe, to evaluate the impact of the device in reducing secondary flows. Furthermore, experiments were also adopted to validate both low-fidelity (RANS) and high-fidelity (LES) simulations and revealed the capability of both simulation approaches to accurately predict losses and flow deviation. Moreover, the accuracy in high-fidelity simulations has enabled an in-depth investigation of how fences act mitigating the effects of the passage vortex along the blade channel. By comparing the flow fields of the configurations with and without fences, it is possible to highlight the mitigation of secondary flows within the channel. Full article