Search Results (26,471)

Background: Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by both motor and non-motor symptoms, including autonomic dysfunction. Structural alterations in the vagus nerve (VN) may contribute to PD pathophysiology, though existing data remain inconsistent. Objective: This study aimed to evaluate morphological changes in the VN using high-resolution ultrasound (USVN) and to investigate associations with autonomic symptoms, heart rate variability (HRV), and clinical characteristics in PD patients. Methods: A cross-sectional study was conducted involving 60 PD patients and 60 age- and sex-matched healthy controls. USVN was performed to assess VN cross-sectional area (CSA), echogenicity, and homogeneity bilaterally. Autonomic symptoms were measured using the Composite Autonomic Symptom Scale 31 (COMPASS-31). HRV parameters—SDNN, RMSSD, and pNN50—were obtained via 24 h Holter monitoring. Additional clinical data included Unified Parkinson’s Disease Rating Scale (UPDRS) scores, transcranial sonography findings, and third ventricle width. Results: PD patients showed significantly reduced VN CSA compared to controls (right: 1.90 ± 0.19 mm² vs. 2.07 ± 0.18 mm²; left: 1.74 ± 0.21 mm² vs. 1.87 ± 0.22 mm²; p < 0.001 and p < 0.02). Altered echogenicity and decreased homogeneity were also observed. Right VN CSA correlated with body weight, third ventricle size, and COMPASS-31 scores. Left VN CSA was associated with body size parameters and negatively correlated with RMSSD (p = 0.025, r = −0.21), indicating reduced vagal tone. Conclusions: USVN detects structural VN changes in PD, correlating with autonomic dysfunction. These findings support its potential as a non-invasive biomarker for early autonomic involvement in PD. Full article

Background: Despite clinical and pathological risk tools, predicting outcomes in non-muscle-invasive bladder cancer (NMIBC), particularly high-grade (HG) cases, remains challenging due to its unpredictable recurrence and progression. There is an urgent need for molecular biomarkers to enhance risk stratification and guide treatment. Methods: We assessed the prognostic potential of eight miRNAs (miR-9, miR-143, miR-182, miR-205, miR-27a, miR-369, let-7c, and let-7g) in a cohort of ninety patients with primary bladder cancer. Expression data were retrieved from our previously published studies. Kaplan–Meier’s and Cox’s regression analyses were used to evaluate the associations with overall survival (OS), metastasis-free survival (MFS), and clinical outcomes. Principal component analysis (PCA) was performed to identify informative miRNA combinations. Target gene prediction, pathway enrichment (DAVID), and drug–gene interaction mapping (DGIdb) were conducted in silico. Results: A high expression of let-7g and miR-9 was significantly associated with better OS in HG NMIBC and MIBC, respectively (p = 0.013 and p = 0.000). MiR-9 downregulation correlated with metastasis in MIBC (p = 0.018). Among all combinations, miR-205 and miR-27a best predicted intermediate-risk NMIBC progression and recurrence (r² = 0.982, p = 0.000). A functional analysis revealed that these miRNAs regulate key cancer-related pathways (MAPK, mTOR, and p53) through genes such as TP53, PTEN, and CDKN1A. Drug interaction mapping identified nine target genes (e.g., DAPK1, ATR, and MTR) associated with eight FDA-approved bladder cancer therapies, including cisplatin and gemcitabine. Conclusion: Let-7g, miR-9, miR-143, miR-182, and miR-205 emerged as promising biomarkers for outcome prediction in NMIBC. Their integration into liquid biopsy platforms could support non-invasive monitoring and personalized treatment strategies. These findings warrant validation in larger, prospective studies and through functional assays. Full article

Background/Objectives: This randomized controlled trial aimed to evaluate the effects of casein-enriched milk (CEM) consumption and its timing (presleep vs. during the day) in the early postoperative period on body composition, muscle strength, physical function, and biochemical parameters in individuals undergoing laparoscopic sleeve gastrectomy (SG). Methods: Forty-five adults (60% female, 40% male; mean age 35.1 ± 9.7 years; mean BMI 41.4 ± 4.9 kg/m²) undergoing SG were randomly assigned to three groups: (1) 15 g protein CEM (12 g casein) presleep, (2) the same CEM during the day, or (3) standard-protein diet without supplementation. The primary endpoint was change in fat-free mass (FFM) at 12 weeks; secondary endpoints included handgrip strength, 30 s sit-to-stand test, and serum total protein, albumin, and prealbumin. Assessments were performed preoperatively and at weeks 4, 8, and 12. Results: No significant differences were found between the groups in terms of body composition, muscle strength, or physical performance measurements (p > 0.05). However, a significant increase in handgrip strength was observed over time in Groups 1 and 2 (p < 0.05), which was not observed in Group 3. Prealbumin levels at week 12 were 0.3 ± 0.0 mg/dL in Group 1 and 0.2 ± 0.0 mg/dL in Group 2, both higher than 0.2 ± 0.0 mg/dL in Group 3 (p < 0.05). No significant differences were found in albumin and total protein levels (p > 0.05). Conclusions: Early postoperative CEM consumption following SG did not significantly affect body composition or physical performance; however, the higher prealbumin levels indicate that this marker may be more sensitive in detecting early protein response, highlighting its potential clinical relevance in monitoring nutritional status after bariatric surgery. Full article

Reference crop evapotranspiration (ETo) is a crucial component in calculating crop water requirements, and its accurate prediction is vital for effective agricultural water management and irrigation planning. Generally, the FAO Penman-Monteith 56 equation is recommended as the benchmark’s method for calculating Eto, but it requires extensive meteorological data—posing challenges in regions with sparse monitoring infrastructure. This review addresses a critical gap: the lack of systematic comparative analysis of machine learning (ML) methods for ETo estimation under data-limited conditions. We review 325 studies searched by Web of Science from 2001 to 2024, focusing on applications of machine learning models in ETo modeling and prediction. Then, this review evaluates these models regarding their characteristics, accuracy, and applicability, including artificial neural networks (ANN), support vector machines (SVM), ensemble learning (EL), and deep learning (DL). Crucially, EL models demonstrate superior stability and cost-effectiveness, with typical performance metrics of R² > 0.95 and RMSE ranging from 0.1 to 0.6 mm·d⁻¹. Notably, DL methods achieve the highest accuracy under conditions of data scarcity. Using only temperature data, they attain competitive performance (R² = 0.81, RMSE = 0.56 mm·d⁻¹). Additionally, we further synthesize optimal input variables, performance metrics, and domain-specific implementation guidelines. In summary, this study provides a comprehensive and up-to-date overview of machine learning methods for ETo modeling, thereby offering valuable insights for researchers in the field of evapotranspiration. Full article

With the increasing demand for urban rail transit capacity, shield tunneling has become the predominant method for constructing underground metro systems in densely populated cities. However, the spatial interaction between shield tunnels and adjacent retaining structures poses significant engineering challenges, potentially leading to excessive ground settlement, structural deformation, and even stability failure. This study systematically investigates the deformation behavior and associated risks of retaining systems during adjacent shield tunnel construction. An orthogonal multi-factor analysis was conducted to evaluate the effects of grouting pressure, grout stiffness, and overlying soil properties on maximum surface settlement. Results show that soil cohesion and grouting pressure are the most influential parameters, jointly accounting for over 72% of the variance in settlement response. Based on the numerical findings, a Bayesian network model was developed to assess construction risk, integrating expert judgment and field monitoring data to quantify the conditional probability of deformation-induced failure. The model identifies key risk sources such as geological variability, groundwater instability, shield steering correction, segmental lining quality, and site construction management. Furthermore, the effectiveness and cost-efficiency of various grouting reinforcement strategies were evaluated. The results show that top grouting increases the reinforcement efficiency to 34.7%, offering the best performance in terms of both settlement control and economic benefit. Sidewall grouting yields an efficiency of approximately 30.2%, while invert grouting shows limited effectiveness, with an efficiency of only 11.6%, making it the least favorable option in terms of both technical and economic considerations. This research provides both practical guidance and theoretical insight for risk-informed shield tunneling design and management in complex urban environments. Full article

This study presents a methodology to automatically assess visibility distance on secondary roads using mobile LiDAR systems. The method evaluates both braking and overtaking visibility distances based on the 3D geometry of the road, applying a dynamic analysis through a series of parametrised quadrangular pyramids that simulate the driver’s field of view. Road segments are classified into three risk levels, low, medium, and high, according to the feasibility of stopping or overtaking safely. The methodology was validated on three secondary roads in Spain, achieving an average accuracy of 92.7% when compared to existing road signage. These results demonstrate the method’s potential to improve road safety through continuous, data-driven visibility monitoring. Its application supports advanced driver assistance systems and offers road authorities a reliable tool for proactive risk assessment and road infrastructure planning. Full article

Optical coherence tomography (OCT) is a leading imaging technique for diagnosing retinal disorders such as age-related macular degeneration and diabetic retinopathy. Its ability to detect structural changes, especially in the optic nerve head, has made it vital for early diagnosis and monitoring. This paper surveys techniques for ocular disease prediction using OCT, focusing on both hand-crafted and deep learning-based feature extractors. While the field has seen rapid growth, a detailed comparative analysis of these methods has been lacking. We address this by reviewing research from the past 20 years, evaluating methods based on accuracy, sensitivity, specificity, and computational cost. Key diseases examined include glaucoma, diabetic retinopathy, cataracts, amblyopia, and macular degeneration. We also assess public OCT datasets widely used in model development. A unique contribution of this paper is the exploration of adversarial attacks targeting OCT-based diagnostic systems and the vulnerabilities of different feature extraction techniques. We propose a practical, robust defense strategy that integrates with existing models and outperforms current solutions. Our findings emphasize the value of combining classical and deep learning methods with strong defenses to enhance the security and reliability of OCT-based diagnostics, and we offer guidance for future research and clinical integration. Full article

This study focuses on a comprehensive analysis of the common methods for road infrastructure monitoring, as well as the perspective of various fiber-optic sensor (FOS) realization solutions in road monitoring applications. Fiber-optic sensors are a topical technology that ensures multiple advantages such as passive nature, immunity to electromagnetic interference, multiplexing capabilities, high sensitivity, and spatial resolution, as well as remote operation and multiple physical parameter monitoring, hence offering embedment potential within the road pavement structure for needed smart road solutions. The main key factors that affect FOS-based road monitoring scenarios and configurations are analyzed within this review. One such factor is technology used for optical sensing—fiber Bragg grating (FBG), Brillouin, Rayleigh, or Raman-based sensing. A descriptive comparison is made comparing typical sensitivity, spatial resolution, measurement distance, and applications. Technological approaches for monitoring physical parameters, such as strain, temperature, vibration, humidity, and pressure, as a means of assessing road infrastructure integrity and smart application integration, are also evaluated. Another critical aspect concerns spatial positioning, focusing on the point, quasi-distributed, and distributed methodologies. Lastly, the main topical FOS-based application areas are discussed, analyzed, and evaluated. Full article

Mountain glaciers are the most direct and sensitive indicators of climate change. In the context of global warming, monitoring changes in glacier elevation has become a crucial issue in modern cryosphere research. The Global Ecosystem Dynamics Investigation (GEDI) is a full-waveform laser altimeter with a multi-beam that provides unprecedented measurements of the Earth’s surface. Many studies have investigated its applications in assessing the vertical structure of various forests. However, few studies have assessed GEDI’s performance in detecting variations in glacier elevation in land ice in high-mountain Asia. To address this limitation, we selected the Southeastern Tibetan Plateau (SETP), one of the most sensitive areas to climate change, as a test area to assess the feasibility of using GEDI to monitor glacier elevation changes by comparing it with ICESat-2 ATL06 and the reference TanDEM-X DEM products. Moreover, this study further analyzes the influence of environmental factors (e.g., terrain slope and aspect, and altitude distribution) and glacier attributes (e.g., glacier area and debris cover) on changes in glacier elevation. The results show the following: (1) Compared to ICESat-2, in most cases, GEDI overestimated glacier thinning (i.e., elevation reduction) to some extent from 2019 to 2021, with an average overestimation value of about −0.29 m, while the annual average rate of elevation change was relatively close, at −0.70 ± 0.12 m/yr versus −0.62 ± 0.08 m/yr, respectively. (2) In terms of time, GEDI reflected glacier elevation changes at interannual and seasonal scales, and the trend of change was consistent with that found with ICESat-2. The results indicate that glacier accumulation mainly occurred in spring and winter, while the melting rate accelerated in summer and autumn. (3) GEDI effectively monitored and revealed the characteristics and patterns of glacier elevation changes with different terrain features, glacier area grades, etc.; however, as the slope increased, the accuracy of the reported changes in glacier elevation gradually decreased. Nonetheless, GEDI still provided reasonable estimates for changes in mountain glacier elevation. (4) The spatial distribution of GEDI footprints was uneven, directly affecting the accuracy of the monitoring results. Thus, to improve analyses of changes in glacier elevation, terrain factors should be comprehensively considered in further research. Overall, these promising results have the potential to be used as a basic dataset for further investigations of glacier mass and global climate change research. Full article

This study evaluates biogas production through the anaerobic digestion of food waste (FW), cow dung (CD), and green waste (GW), with the primary objective of determining the efficacy of co-digesting these organic wastes commonly generated by households and small farms in Central Queensland, Australia. The investigation focuses on both experimental and technoeconomic aspects to support the development of accessible and sustainable energy solutions. A batch anaerobic digestion process was employed using a 1 L jacketed glass digester, simulating small-scale conditions, while technoeconomic feasibility was projected onto a 500 L digester operated without temperature control, reflecting realistic constraints for decentralized rural or residential systems. Three feedstock mixtures (100% FW, 50:50 FW:CD, and 50:25:25 FW:CD:GW) were tested to determine their impact on biogas yield and methane concentration. Experiments were conducted over 14 days, during which biogas production and methane content were monitored. The results showed that FW alone produced the highest biogas volume, but with a low methane concentration of 25%. Co-digestion with CD and GW enhanced methane quality, achieving a methane yield of 48% while stabilizing the digestion process. A technoeconomic analysis was conducted based on the experimental results to estimate the viability of a 500 L biodigester for small-scale use. The evaluation considered costs, benefits, and financial metrics, including Net Present Value (NPV), Internal Rate of Return (IRR), and Dynamic Payback Period (DPP). The biodigester demonstrated strong economic potential, with an NPV of AUD 2834, an IRR of 13.5%, and a payback period of 3.2 years. This study highlights the significance of optimizing feedstock composition and integrating economic assessments with experimental findings to support the adoption of biogas systems as a sustainable energy solution for small-scale, off-grid, or rural applications. Full article

This study explores the effectiveness of 3D Digital Image Correlation (DIC) for measuring displacement and strain of a propeller undergoing angular motion. Traditional methods, such as strain gauges, face limitations including physical interference, technical difficulties in sensor connections, and restricted measurement points, leading to inaccuracies in capturing true conditions. To overcome these challenges, this research utilizes non-contact 3D DIC technology, enabling measurement of surface displacements and deformations without interfering with the tested component. Experiments were conducted using the model aircraft propellers mounted on a custom-built test stand for partial angular motion. The 1 Mpx high-speed cameras captured strain and displacement data across the propeller blades during motion. The DIC strain measurements were then compared to strain gauge data to evaluate their accuracy and reliability. The results demonstrate that 3D DIC enables precise displacement measurements, while strain measurements are subject to certain limitations. Displacement measurements were achieved with a noise level of ±10 μm, while strain measurement noise ranged from 26 to 174 µm/m depending on direction. Strain gauge measurements were also performed for verification of the DIC measurements and calibration of the filtering procedure. Two types of non-metallic materials were used in the study: Nylon LGF60 PA6 for the propeller and 3D-printed PC ABS for the cantilever beam used in strain measurement validation. This study underscores the potential of DIC for monitoring rotating components, with a particular focus on measuring strains that are often overlooked in publications addressing similar topics. Additionally, it focuses on comparing DIC strain measurements with strain gauge data on rotating components, addressing a critical gap in existing literature, as strain measurement in rotating structures remains underexplored in current research. Full article

As the largest carbon reservoir in terrestrial ecosystems, soil organic carbon (SOC) plays a critical role in the global carbon cycle and climate change mitigation. A promising approach to swiftly procuring geographically dispersed SOC data is the amalgamation of UAV-based multispectral imagery at the local scale and Sentinel-2 satellite imagery at the regional scale. This integrated approach is particularly well-suited for precision agriculture and real-time monitoring. In this study, we evaluated the performance of UAVs and Sentinel-2 imagery in predicting SOC using four machine-learning models: Multiple Linear Regression (MLR), Support Vector Regression (SVR), Random Forest (RF), and Artificial Neural Networks (ANNs). UAV imagery outperformed Sentinel-2, achieving more accurate detection of local SOC variability thanks to its finer spatial resolution (5–10 cm versus 10–20 m). Among the models tested, the Random Forest algorithm achieved the highest accuracy, with an R² of up to 0.85 using UAV data and 0.65 using Sentinel-2 data, along with low RMSE values. All models confirmed the superiority of UAV imagery based on key error metrics (SSE, MSE, RMSE, and NSE). Although Sentinel-2 remains valuable for regional assessments, UAV imagery combined with Random Forest provides the most reliable SOC estimates at local scales. The spatial SOC maps generated from both UAV and Sentinel-2 imagery showed more nuanced spatial variability than standard interpolation techniques. While prediction accuracy using UAV-based models was slightly lower in some cases, UAV imagery provided greater spatial detail in SOC distribution. However, this is associated with higher acquisition and processing costs compared to freely available Sentinel-2 imagery. Given their respective advantages, we recommend using UAV imagery for detailed, site-specific SOC estimations and Sentinel-2 data for broader regional-to-global SOC mapping efforts. Full article

This study aimed to monitor internal load, well-being, and recovery status in U16 male water polo players during a congested competitive period. Fourteen athletes from an Italian club played 12 matches (seven friendly, five official) over 7 days. The internal match load was measured using the session-RPE method (s-RPE). Perceived enjoyment was measured with the Enjoyment Likert Scale (ENJ), while recovery and well-being were evaluated using the Perceived Recovery Scale (PRS) and the Hooper Index (HI), respectively. No significant main effects were found on s-RPE, PRS, and HI considering friendly and official matches. However, ENJ was significantly higher during official matches (p < 0.005). PRS values were significantly affected by daytime matches (p < 0.005), with better perceived recovery reported for morning matches. Linear mixed model analysis revealed significant associations between s-RPE and HI (p = 0.001), the fatigue item (p = 0.001), and the PRS (p = 0.004). These results suggest that as internal load increases, players experience higher fatigue and report lower recovery and well-being scores. Employing simple, non-invasive tools like the RPE, PRS, and HI can help coaches and support staff to identify early signs of overtraining or insufficient recovery, allowing for more individualized load management and injury prevention in youth water polo athletes. Full article

Globally, cardiovascular diseases represent a major cause of morbidity and mortality, despite the availability of preventive, diagnostic, and therapeutic measures in contemporary allopathic medicine. In accordance with their ethnomedical applications, herbal medicines may offer valuable options for the prevention, treatment, and management of cardiovascular disorders. Considering that cardioprotective effects are associated with antioxidant mechanisms, and that our knowledge of the antioxidant properties of polyphenolic compounds, as well as of the effects of Melilotus species on the heart, is limited, the present study aimed to evaluate the cardioprotective potential of hydroalcoholic extracts of M. officinalis and M. albus aerial parts. The extracts were evaluated for total phenolic content (TPC), total flavonoid content (TFC), and total coumarin content (TCC) by spectrophotometric methods and by LC-MS/MS. The effect of pretreatment with Melilotus sp. extracts on the isoprenaline-induced infarct-like lesion in rats was evaluated by ECG monitoring and the assessment of serum oxidative stress markers and serum cardiac injury markers. Various polyphenolic compounds were identified by LC-MS/MS in M. officinalis and M. albus aerial parts: catechin, syringic acid, protocatechuic acid, and vanillic acid. Gallic acid and chlorogenic acid were found only in M. officinalis. The extracts showed good in vivo antioxidant activity: M. officinalis and M. albus extracts induced a significant decrease in the levels of oxidative stress index (OSI) and total oxidant status (TOS), while pre-treatment with M. albus extract induced a significant reduction in nitric oxide production, and pretreatment with M. officinalis increased total thiols (SH) levels. In the same way, ECG and cardiac injury markers were also improved. These results show that M. officinalis and M. albus extracts may exert cardioprotective effects against myocardial ischemia by reducing oxidative stress. Full article

This research explores the effect of a composite support of SiO₂ and Al₂O₃ with Fe and Co incorporated as catalysts for Fischer–Tropsch synthesis (FTS) using a 3D-printed stainless steel (SS) microchannel microreactor. Two mesoporous catalysts, FeCo/SiO₂Al₂O₃ and Co/SiO₂Al₂O₃, were synthesized via a one-pot (OP) method and extensively characterized using N₂ physisorption, XRD, SEM, TEM, H₂-TPR, TGA-DSC, FTIR, and XPS. H₂-TPR results revealed that the synthesis method significantly affected the reducibility of metal oxides, thereby influencing the formation of active FTS sites. SEM-EDS and TEM further revealed a well-defined hexagonal matrix with a porous surface morphology and uniform metal ion distribution. FTS reactions, carried out in the 200–350 °C temperature range at 20 bar with a H₂/CO molar ratio of 2:1, exhibited the highest activity for FeCo/SiO₂Al₂O₃, with up to 80% CO conversion. Long-term stability was evaluated by monitoring the catalyst performance for 30 h on stream at 320 °C under identical reaction conditions. The catalyst was initially active for the methanation reaction for up to 15 h, after which the selectivity for CH₄ declined. Correspondingly, the C₄⁺ selectivity increased after 15 h of time-on-stream, indicating a shift in the product distribution toward longer-chain hydrocarbons. This trend suggests that the catalyst undergoes gradual activation or restructuring under reaction conditions, which enhances chain growth over time. The increase in C₄⁺ products may be attributed to the stabilization of the active sites and suppression of methane or light hydrocarbon formation. Full article