Search Results (113)

Background/Objectives: Improper landing mechanics in Taekwondo can lead to non-contact injuries such as ankle sprains and knee ligament tears, highlighting the necessity for objective methods to evaluate landing stability and injury risk. Electromyography (EMG) enables the examination of muscle activation patterns; however, conventional analyses based on simple averages have limited predictive value. Methods: This study analyzed EMG signals recorded during single-leg landings (45 cm height) in 30 elite male Taekwondo athletes. Participants were divided into regular exercise groups (REG, n = 15) and non-exercise groups (NEG, n = 15). Signals were segmented into two phases. Eight features were extracted per muscle per phase. Classification models (Random Forest, XGBoost, Logistic Regression, Voting Classifier) were used to classify between groups, while regression models (Ridge, Random Forest, XGBoost) predicted continuous muscle activation changes as injury risk indicators. Results: The Random Forest Classifier achieved an accuracy of 0.8365 and an F1-score of 0.8547. For regression, Ridge Regression indicated high performance (R² = 0.9974, MAE = 0.2620, RMSE = 0.4284, 5-fold CV MAE: 0.2459 ± 0.0270), demonstrating strong linear correlations between EMG features and outcomes. Conclusions: The AI-enabled EMG analysis can be used as an objective measure of the study of the individual landing stability and risk of injury in Taekwondo athletes, but its clinical application has to be validated in the future by biomechanical injury indicators and prospective cohort studies. Full article

Coastal zones in arid regions are particularly vulnerable to climate change because of their limited sediment supply and high sensitivity to marine and aeolian forces. This study provides probabilistic projections of coastal evolution for a 130 km segment of the Duba shoreline, Saudi Arabia, a rapidly developing region that includes the NEOM mega-project. An integrated modeling framework was developed by combining a four-decade (1985–2024) diachronic analysis of shoreline evolution from Landsat imagery with a cascade of numerical models. Specifically, climate projections from CMIP6 (under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios) were dynamically downscaled using the regional climate models COSMO-CLM and RegCM, which provided boundary conditions for the SWAN hydrodynamic model to simulate the wave dynamics. The SWAN outputs were then used to force the Delft3D morphodynamic model to project future shoreline evolution. A Bayesian framework was applied to systematically quantify and integrate the uncertainties across all modeling steps, enabling robust probabilistic forecasts. Results indicate an accelerated trend of shoreline retreat, with mean Net Shoreline Movement (NSM) by 2100 ranging from −8.1 m under the low-emission SSP1-2.6 scenario to a critical −25.6 m under the high-emission SSP5-8.5 scenario, with 95% confidence intervals reaching −47.9 m. This erosion is mainly driven by a projected relative sea-level rise of up to 48.3 cm (±15.8 cm) and an increase in significant wave height of up to 40% (mean of 1.95 m). By delivering probabilistic rather than deterministic results, this study provides a solid scientific basis to guide sustainable coastal management, inform the design of risk-sensitive infrastructure, and support the development of climate-resilient adaptation strategies in one of the world’s most rapidly transforming coastal regions. Full article

Aircraft emissions are a growing environmental concern due to their contribution to local air pollution and potential health risks, particularly around rapidly expanding airports. In Egypt, rapid urban growth and tourism have driven the construction of new airports, underscoring the need to assess their environmental impacts, particularly those related to aircraft emissions in the surrounding areas. Few studies have assessed aircraft emissions across multiple Egyptian airports, particularly under future capacity and climate scenarios, using dispersion models. This study evaluates the environmental impact of aircraft emissions at four Egyptian airports using the Graz Lagrangian Dispersion Model (GRAL). The analysis accounts for projected increases in airport capacity through 2030 and 2035 and examines how climate change may influence pollutant dispersion. Emissions from 2021 served as a baseline, while future meteorological conditions were simulated with the RegCM4 regional climate model under the RCP4.5 scenario. Results show that maximum daily average carbon monoxide concentrations at Administrative Capital Airport increased from ~24.5 µg/m³ in 2021 to ~100.3 µg/m³ in 2035, while nitrogen dioxide concentrations at El-Meliz Airport rose from ~20.3 to ~47.6 µg/m³. Similar upward trends were observed for sulfur dioxide and particulate matter (PM₁₀), although all simulated values remained below the thresholds established by Egyptian Environmental Law. These findings highlight that continued growth in aviation activity, even without breaching national standards, may contribute to long-term health risks for nearby communities. Full article

The Upper Blue Nile Basin (UBNB), which contributes about 60% to the annual Nile flow, plays a critical role in the Nile water management. However, its complex terrain and climate create significant challenges for accurate regional climate simulations, which are essential for climate impact assessments. This study aims to address the challenges of climate simulation over the UBNB by enhancing the Regional Climate Model system (RegCM5) with its new non-hydrostatic dynamical core (MOLOCH) to simulate precipitation and temperature. The model is driven by ERA5 reanalysis for the period (2000–2009), and two scenarios are simulated using two different schemes of the Planetary Boundary Layer (PBL): Holtslag (Hol) and University of Washington (UW). The two scenarios, noted as (MOLOCH-Hol and MOLOCH-UW), are compared to the previously best-performing hydrostatic configuration. The MOLOCH-UW scenario showed the best precipitation performance relative to observations, with an accepted dry Bias% up to 22%, and a high annual cycle correlation >0.85. However, MOLOCH-Hol showed a very good performance only in the wet season with a wet bias of 4% and moderate correlation of ≈0.6. For temperature, MOLOCH-UW also outperformed, achieving the lowest cold/warm bias range of −2% to +3%, and high correlations of ≈0.9 through the year and the wet season. This study concluded that the MOLOCH-UW is the most reliable configuration for reproducing the climate variability over the UBNB. This developed configuration is a promising tool for the basin’s hydroclimate applications, such as dynamical downscaling of the seasonal forecasts and future climate change scenarios produced by global circulation models. Future improvements could be achieved through convective-permitting simulation at ≤4 km resolution, especially in the application of assessing the land use change impact. Full article

Osseodensification (OD) has emerged as a favorable osteotomy preparation technique that preserves and compacts autogenous bone along the osteotomy walls during site preparation, enhancing primary stability and implant osseointegration. While OD has demonstrated promising results in low-density trabecular bone, especially when used in conjunction with acid-etched (AE) implant surfaces, its efficacy in high-density cortical bone remains unclear—particularly in the context of varying implant surface characteristics. In this study, Grade V titanium alloy implants (Ti-6Al-4V, 4 mm × 10 mm) with deep threads, designated bone chambers and either as-machined (Mach) or AE surfaces were placed in 3.8 mm diameter osteotomies in the submandibular region of 16 adult sheep using either OD or conventional (Reg) drilling protocols. Insertion torque values (N·cm) were measured at the time of implant placement to evaluate primary stability. Mandibles were harvested at 3-, 6-, 12-, or 24-weeks post-implantation (n = 4 sheep/time point), and histologic sections were analyzed to quantify bone-to-implant contact (BIC) and bone area fractional occupancy (BAFO). Qualitative histological analysis confirmed successful osseointegration among all groups at each of the healing time points. No statistically significant differences were observed between OD and conventional drilling techniques in insertion torque (p > 0.628), BIC (p > 0.135), or BAFO (p > 0.060) values, regardless of implant surface type or healing interval. The findings indicate that neither drilling technique nor implant surface treatment significantly influences osseointegration in high density cortical bone. Furthermore, as the osteotomy was not considerably undersized, the use of OD instrumentation showed no signs of necrosis, inflammation, microfractures, or impaired osseointegration in dense cortical bone. Both OD and Reg techniques appear to be suitable for implant placement in dense bone, allowing flexibility based on surgeon preference and clinical circumstances. Full article

The main goal of this study is to present future changes in various precipitation indices at a kilometer-scale resolution for Bulgaria on an annual and seasonal basis. Numerical simulations were conducted using the Non-Hydrostatic Regional Climate Model version 4 (RegCM4-NH) following the Coordinated Regional Climate Downscaling Experiment Flagship Pilot Study protocol for three 10-year periods (1995–2004, 2041–2050, and 2090–2099), with horizontal grid resolutions of 15 km and 3 km, on the petascale supercomputer HPC Discoverer at Sofia Tech Park. Data from the Hadley Centre Global Environment Model version 2 (HadGEM2-ES), based on the Representative Concentration Pathway 8.5 (RCP8.5) scenario, were used as boundary conditions for the regional climate model (RCM) simulations, which were subsequently downscaled to the kilometer-scale (3 km) simulations using a one-way nesting approach. High-resolution model data were compared with high-resolution observational datasets as well as lower-resolution (15 km) data. Future changes in precipitation indices were analyzed on both annual and seasonal scales, including mean daily and hourly precipitation, the frequency and intensity of wet days (>1 mm/day) and wet hours (>0.1 mm/hour), extreme daily precipitation (99th percentile, p99), and extreme hourly precipitation (99.9th percentile, p99.9) for both future periods. Additionally, changes in near-surface (2 m) temperature and surface snow amount were also presented. There is no substantial difference in projected temperature change between the resolutions. A positive trend in annual mean precipitation is expected in the near future. Extreme precipitation (p99 and p99.9) is projected to increase in spring and winter, accompanied by a rise in daily and hourly precipitation intensity across both future periods. An increase in surface snow amount is observed in the central Danubian Plain, Thracian Lowland, and parts of the Rila and Pirin mountains for the near-future period. However, surface snow amount is expected to decrease by the end of the century. Full article

Anthropogenic debris in urban floodplains poses significant environmental and ecological risks, with an estimated 4 to 12 million metric tons entering oceans annually via riverine transport. While remote sensing and artificial intelligence (AI) offer promising tools for automated debris detection, most existing datasets focus on marine environments with homogeneous backgrounds, leaving a critical gap for complex terrestrial floodplains. This study introduces the San Diego River Debris Dataset, a multi-resolution UAV imagery collection with ground reference designed to support automated detection of anthropogenic debris in urban floodplains. The dataset includes manually annotated debris objects captured under diverse environmental conditions using two UAV platforms (DJI Matrice 300 and DJI Mini 2) across spatial resolutions ranging from 0.4 to 4.4 cm. We benchmarked five deep learning architectures (RetinaNet, SSD, Faster R-CNN, DetReg, Cascade R-CNN) to assess detection accuracy across varying image resolutions and environmental settings. Cascade R-CNN achieved the highest accuracy (0.93) at 0.4 cm resolution, with accuracy declining rapidly at resolutions above 1 cm and 3.3 cm. Spatial analysis revealed that 51% of debris was concentrated within unsheltered encampments, which occupied only 2.6% of the study area. Validation confirmed a strong correlation between predicted debris extent and field measurements, supporting the dataset’s operational reliability. This openly available dataset fills a gap in environmental monitoring resources and provides guides for future research and deployment of UAV-based debris detection systems in urban floodplain areas. Full article

Understanding the potential impact of the Three Gorges Reservoir (TGR) on regional extreme precipitation and its mechanisms is critical for the safe operation of the reservoir and the efficient management of regional water resources. This study uses the regional climate model RegCM4 to conduct a double-nested simulation experiment (50 km to 10 km) from 1989 to 2012, evaluated against the CN5.1 observation dataset. Sensitivity experiments with three different lake area ratios (0%, 20% and 100%) were performed using the sub-grid partitioning method in the Community Land Model Version 4.5 to analyze the spatiotemporal distribution, intensity, and frequency of precipitation under varying TGR water areas. The results show that with a 20% lake area ratio, precipitation slightly decreases, but the impact on extreme precipitation indices is not statistically significant. However, with a 100% lake area ratio, significant decreases in both total and extreme precipitation indices occur. The reduction is primarily driven by the formation of anomalous mountain-valley circulation between the TGR and surrounding mountains, which leads to atmospheric subsidence and reduced convective activity. These findings indicate that while the TGR has a negligible impact on extreme precipitation under its current configuration, the exaggerated sensitivity experiments reveal potential mechanisms and localized effects. This research enhances the understanding of the TGR’s influence on regional extreme precipitation and provides valuable insights for water resource management and reservoir operation. Full article

Land suitability analyses are crucial for identifying sustainable areas for agricultural crops and developing appropriate land use strategies. Thus, the present study aims to analyze the current and future land suitability for wheat (Triticum aestivum L.) cultivation in Ethiopia. Twelve variables including soil properties, climate variables, and topographic characteristics were used in the evaluation of land suitability. Statistical methods such as Rotated Empirical Orthogonal Functions (REOF), Coefficient of Variation (CV), correlation, and parametric and non-parametric trend analyses were used to analyze the spatiotemporal variability in current and future climate data and identified significant patterns of variability. For future projections of land suitability and climate, this study employed climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) framework, downscaled using regional climate model version 4.7 (RegCM4.7) under two different Shared Socioeconomic Pathway (SSP) climate scenarios: SSP1 (a lower emission scenario) and SSP5 (a higher emission scenario). Under the current condition, during March, April, and May (MAM), 53.4% of the country was suitable for wheat cultivation while 44.4% was not suitable. In 2050, non-suitable areas for wheat cultivation are expected to increase by 1% and 6.9% during MAM under SSP1 and SSP5 climate scenarios, respectively. Our findings highlight that areas currently suitable for wheat may face challenges in the future due to altered temperature and precipitation patterns, potentially leading to shifts in suitable areas or reduced productivity. This study also found that the suitability of land for wheat cultivation was determined by rainfall amount, temperature, soil type, soil pH, soil organic carbon content, soil nitrogen content, and elevation. This research underscores the critical importance of integrating spatiotemporal climate variability with future projections to comprehensively assess wheat suitability. By elucidating the implications of climate change on wheat cultivation, this study lays the groundwork for developing effective adaptation strategies and actionable recommendations to enhance management practices. The findings support the county’s commitment to refining agricultural land use strategies, increasing wheat production through suitability predictions, and advancing self-sufficiency in wheat production. Additionally, these insights can empower Ethiopia’s agricultural extension services to guide farmers in cultivating wheat in areas identified as highly and moderately suitable, thereby bolstering production in a changing climate. Full article

The aim of this study is to determine the effect of climate change on reference evapotranspiration (ETo) and sunflower and wheat evapotranspiration (ETs and ETw, respectively) in the Trakya Region of Türkiye. ETo Calculator (version 3.2) and CROPWAT 8.0 were used to compute ETo and ET in the reference period (1970–1990), short- (2016–2025), mid- (2046–2055), and long- (2076–2085) terms. Additionally, ETo was tested in 2012 and ETo was simulated for every 1 °C temperature increase up to 5 °C in the reference period. Calculated ETo and ET values for the future were compared with the reference period. For the future, climate data estimated by RegCM3 Regional Climate Model, A2 scenario were used. While the average ETo value of the reference period was 3.3 mm day⁻¹, it was 3.0 mm day⁻¹ in 2012. Compared to the reference period, ETo values change by −3% (3.2 mm day⁻¹), 9% (3.6 mm day⁻¹), and 21% (4.0 mm day⁻¹) in the short-, mid-, and long-term, respectively. The 575 mm ET deficit calculated during the vegetation period of sunflower in the model reference period was forecasted to change by −11% (514 mm), +15% (660 mm), and +25% (721 mm) in the short-, mid-, and long-term, respectively. For wheat, while 59 mm of excess water was calculated in the reference period, it became 193 mm (+227%) in the short-term and a water deficit of 8 mm (−113%) and 6 mm (−110%) in the mid- and long-term, respectively. In addition, it is estimated that there will be an increase of 0.1 mm day⁻¹ (4%) in ETo values for each 1 °C temperature increase compared to the reference period (1970–1990). It was concluded that climate change in the Trakya Region will not significantly affect wheat farming; however, it will cause a serious water deficit in sunflower production. Full article

The link between the escalation of global warming and the increase in extreme precipitation events necessitates a deeper understanding of future trends. This study focused on the dynamics of extreme rainfall in Hubei Province throughout the 21st century, a region already sensitive to climatic shifts and extreme weather occurrences. Using the high-resolution global climate model RegCM4 driven by another high-resolution model, HadGEM2-ES, and based on the representative concentration pathway (RCP8.5) emissions scenario, this research predicted the changes in rainfall patterns in Hubei Province during the summer of the 21st century. The accuracy of the adjusted model was confirmed through the use of five extreme rainfall indices (EPIs), namely maximum 5-day amount of precipitation (RX5day), number of heavy rain days (R10), the simple daily intensity index (SDII), consecutive dry days (CDD), and consecutive wet days (CWD), that measured the intensity and frequency of such events. In particular, excluding the index for continuous dry days (CDD), there was an anticipated increase in extreme rainfall during the summer in the mid-21st century. The number of heavy rain days (R10mm) increased significantly (p < 0.05) in the southeastern parts, especially for Wuhan, Xiantao, Qianjiang, Jinzhou, and Ezhou. The EPI values were higher in southeastern Hubei. Consequently, areas such as Wuhan, Xiantao, and Qianjiang in Hubei Province are projected to face more frequent and severe extreme rainfall episodes as the century progresses. Full article

Assessing the daily water requirements of crops and understanding the severity of drought necessitates precise estimation of potential evapotranspiration (PET), particularly in regions with arid climates such as Egypt. In the present study, the RegCM4 regional climate model was used to investigate the sensitivity of the PET of Egypt to two land surface schemes and boundary layer parameterizations. The land surface schemes are the Biosphere Atmosphere Transfer System (BATS) and the Community Land Model version 4.5 (CLM45). The boundary layer schemes considered are the HOLTSLAG (HOLT) and University of Washington (UW). To accomplish this task, four 32-year simulations were conducted spanning from 1979 to 2010, with the first two years considered as spin up. The ERA-Interim reanalysis was used to downscale the RegCM4 model. The simulated PET was evaluated with respect to the high-resolution ERA5-land PET-based product (hPET). The results showed that the BATS showed a bias of −0.8 to −1.8 mm day⁻¹, while the CLM45 showed a bias of −0.8 to −3 mm day⁻¹. Also, fine-tuning the coefficient of the daily mean air temperature succeeded in reducing the PET bias. Additionally, the UW had a lower PET bias than that noted in HOLT. To further reduce the PET bias, the linear-scaling (LS) bias-correction method was used. The LS showed its potential skills in reducing the mean bias of the PET from −2.2 to +0.4 mm day⁻¹ in the evaluation period and to ±0.2 mm day⁻¹ in the validation period. Furthermore, the added value of the LS was confirmed concerning the climatological annual cycle in different locations representing different climate zones of Egypt. In conclusion, accurate estimation of the PET can be ensured using the BATS, the UW schemes, and the LS technique in the present climate or under different warming scenarios. Full article

We assessed and quantified future projected changes in terrestrial evaporative demand by calculating Potential Evapotranspiration (PET) for the North American Monsoon region in the Southwestern U.S. and Mexico. The PET projections were calculated using the daily Penman–Monteith equation. The terrestrial meteorological variables needed for the equation (i.e., minimum and maximum daily temperature, specific humidity, wind speed, incoming shortwave radiation, and pressure) were obtained from the North American–CORDEX initiative. We used dynamically downscaled projections of three CMIP5 GCMs for RCP8.5 emission scenarios (i.e., HadGEM2-ES, MPI-ESM-LR, and GFDL-ESM2M), and each was dynamically downscaled to ~25 km by two RCMs (i.e., WRF and regCM4). All terrestrial annual PET projections showed a statistically significant increase when comparing the historical period (1986–2005) to future projections (2020–2039 and 2040–2059). The regional spatial average of the six GCM-RCM combinations projected an increase in the annual PET of about +4% and +8% for 2020–2039 and 2040–2059, respectively. The projected average 20-year annual changes over the study area range for the two projection periods were +1.4%–+8.7% and +3%–+14.2%, respectively. The projected annual PET increase trends are consistent across the entire region and for the six GCM-RCM combinations. Higher annual changes are projected in the northeast part of the region, while smaller changes are projected along the pacific coast. The main drivers for the increase are the projected warming and increase in the vapor pressure deficit. The projected changes in PET, which represent the changes in the atmospheric evaporative demand, are substantial and likely to impact vegetation and the hydrometeorological regime in the area. Quantitative assessments of the projected PET changes provided by this study should be considered in upcoming studies to develop resilience plans and adaptation strategies for mitigating the projected future changes. Full article

This study aims to assess potential changes in radiation values at the solar power plant facility in Istanbul using the RegCM. This analysis seeks to estimate the extent of the solar radiation changes and evaluate the production capacity of solar power in Istanbul in the future. The research involved installing an off-grid rooftop solar energy system. Meteorological parameters (temperature, etc.) and the system’s outputs were monitored to evaluate the energy production and its relationship with these parameters. The performance of the Regional Climate Model version 5.0 (RegCMv5) in accurately representing surface solar radiation and temperature patterns was assessed by comparing it with measured monocrystalline solar panel output data. The impact of different cumulus convection schemes was examined on the sensitivity of the RegCM by analyzing surface solar radiation data over the initial three months. Long-term simulations were conducted with the representational concentration path (RCP) scenarios of 2.6, 4.5, and 8.5 spanning from 2023 to 2050 with convection schemes yielding the best results. All scenarios project a slight decrease in incoming surface radiation. Full article

Climate change (CC) impacts on hydrology pose significant global concerns due to their effects on water availability, thereby impacting various human activities reliant on this essential resource. This study assesses the influence of CC on the water supply in the Angostura-Bolivia basin. We employed the RegCM4 system, which develops its own regional climate models (RCMs) tailored to the Angostura basin using specific convective schemes, diverging from reliance on pre-existing RCMs, like those provided by CORDEX. Methodologically, the study involves hydrometeorological data collection and analysis, utilizing dynamic and statistical downscaling methods to refine the RCMs derived from ERA-Interim reanalysis data. Subsequently, precipitation and temperature projections are generated under CC scenarios (RCP 4.5 and RCP 8.5) for both near (2045–2055) and far (2065–2075) future periods, compared to the historical period (1981–2010). The final stage employs the HydroBID system to project future runoff, considering both perturbed and unperturbed hydrometeorological data under CC effects. The analysis of flow duration curves for 50%, 75%, and 90% exceedance probabilities reveals a significant reduction in flows across all scenarios, indicating a noteworthy impact on water availability. These findings underscore the urgency of comprehending and adapting to CC on hydrology, emphasizing the critical importance of sustainable water resource management amidst evolving climatic conditions. Full article