Search Results (151)

The selection of process parameters for an ultra-high-pressure water jet directly affects the adhesion ability of the subsequent coating on the ship’s surface. This study investigates the effect of jet pressure, standoff distance, and nozzle traverse speed on the surface roughness of grade-A marine steel, aiming to optimize the process parameters and improve the quality of surface treatment. Based on single-factor experiments and orthogonal experiments, a three-factor, three-level experimental design was employed, considering jet pressure, standoff distance, and nozzle traverse speed. Scanning electron microscopy (SEM) and a confocal microscope were used to analyze the surface morphology and roughness of grade-A marine steel. The experimental results proved that surface roughness exhibited a nonlinear relationship with jet pressure, initially increasing and then decreasing as pressure rose. Conversely, surface roughness showed negative correlations with both standoff distance and nozzle traverse speed, progressively decreasing with increases in these parameters. Through hierarchical analysis, the effect hierarchy of the three factors on surface roughness was determined as follows: jet pressure > standoff distance > nozzle traverse speed. Parametric optimization revealed that a jet pressure of 150 MPa, a standoff distance of 25 mm, and a nozzle traverse speed of 180 mm/min collectively yielded a peak surface roughness of 62.549 μm. This value aligns with the pre-coating surface preparation standards for grade-A marine steel substrates, ensuring optimal adhesion for subsequent anti-corrosion treatments. Full article

Background/Objectives: Amelogenesis imperfecta (AI) represents a heterogeneous group of inherited disorders affecting the quality and quantity of dental enamel, making clinical diagnosis challenging. This study aimed to identify genetic variants in Slovenian patients with non-syndromic AI and to evaluate enamel morphology using radiographic parameters. Methods: Whole exome sequencing (WES) was performed on 24 AI patients and their families. Panoramic radiographs (OPTs) were analyzed using Fiji ImageJ to assess crown dimensions, enamel angle (EA), dentine angle (DA), and enamel–dentine mineralization ratio (EDMR) in lower second molar buds, compared to matched controls (n = 24). Two observers independently assessed measurements, and non-parametric tests compared EA, DA, and EDMR in patients with and without disease-causing variants (DCVs). Statistical models, including bootstrap-validated random forest and logistic regression, assessed variable influences. Results: DCVs were identified in ENAM (40% of families), AMELX (15%), and MMP20 (10%), including four novel variants. AI patients showed significant enamel deviations with high reproducibility, particularly in hypomineralized and hypoplastic regions. DA and EDMR showed significant correlations with DCVs (p < 0.01). A bootstrap-validated random forest model yielded a 90% (84.0–98.0%) AUC-estimated predictive power. Conclusions: These findings highlight a novel and reproducible radiographic approach for detecting developmental enamel defects in AI and support its diagnostic potential. Full article

This study investigates an aerodynamic optimization framework inspired by marine biological morphology, utilizing the sailfish profile as a basis for airfoil configuration. Through Latin hypercube experimental design combined with optimization algorithms, four key geometric variables governing the airfoil’s hydrodynamic characteristics were systematically analyzed. Parametric studies revealed that pivotal factors including installation angle significantly influenced the fluid dynamic performance metrics of lift generation and pressure drag. Response surface methodology was employed to establish predictive models for these critical performance indicators, effectively reducing computational resource consumption and experimental validation costs. The refined bio-inspired configuration demonstrated multi-objective performance improvements compared to the baseline configuration, validating the computational framework’s effectiveness for hydrodynamic profile optimization studies. Furthermore, a coaxial dual-rotor vertical axis turbine configuration was developed, integrating centrifugal and axial-flow energy conversion mechanisms through a shared drivetrain system. The centrifugal rotor component harnessed tidal current kinetic energy while the axial-flow rotor module captured wave-induced potential energy. Transient numerical simulations employing dynamic mesh techniques and user-defined functions within the Fluent environment were conducted to analyze rotor interactions. Results indicated the centrifugal subsystem demonstrated peak hydrodynamic efficiency at a 25° installation angle, whereas the axial-flow module achieves optimal performance at 35° blade orientation. Parametric optimization revealed maximum energy extraction efficiency for the centrifugal rotor occurs at λ = 1.25 tip-speed ratio under Re = 1.3 × 10⁵ flow conditions, while the axial-flow counterpart attained optimal performance at λ = 1.5 with Re = 5.5 × 10⁴. This synergistic configuration demonstrated complementary operational characteristics under marine energy conversion scenarios. Full article

Urban morphology critically shapes environmental performance, yet few studies integrate multiple sustainability targets within a unified modeling framework for its design optimization. This study proposes a data-driven, multi-scale approach that combines parametric simulation, artificial neural network-based multi-task learning (MTL), SHAP interpretability, and NSGA-II optimization to assess and optimize urban form across 18 districts in Hong Kong. Four key sustainability targets—photovoltaic generation (PVG), accumulated urban heat island intensity (AUHII), indoor overheating degree (IOD), and carbon emission intensity (CEI)—were jointly predicted using an artificial neural network-based MTL model. The prediction results outperform single-task models, achieving R² values of 0.710 (PVG), 0.559 (AUHII), 0.819 (IOD), and 0.405 (CEI), respectively. SHAP analysis identifies building height, density, and orientation as the most important design factors, revealing trade-offs between solar access, thermal stress, and emissions. Urban form design strategies are informed by the multi-objective optimization, with the optimal solution featuring a building height of 72.11 m, building centroid distance of 109.92 m, and east-facing orientation (183°). The optimal configuration yields the highest PVG (55.26 kWh/m²), lowest CEI (359.76 kg/m²/y), and relatively acceptable AUHII (294.13 °C·y) and IOD (92.74 °C·h). This study offers a balanced path toward carbon reduction, thermal resilience, and renewable energy utilization in compact cities for either new town planning or existing district renovation. Full article

Introduction: Infertility affects 15% of couples, with oxidative stress recognized as a key contributor to male infertility. Night-shift work, through circadian disruption, may exacerbate oxidative imbalance and impair reproductive function. This study investigates the impact of night-shift work on oxidative stress and semen quality and evaluates the potential benefits of antioxidant supplementation in this context. Materials and Methods: We retrospectively analysed 96 white-European men aged 18–45, seeking fertility assessment at a single academic centre. Participants were classified as day or night workers based on their shift schedule, and all underwent standardised clinical, hormonal, and semen evaluations. Oxidative stress was assessed using the d-ROMs test. A subgroup of 40 patients (20 per group) treated for 3 months with antioxidant supplementation (Drolessano) to evaluate changes in oxidative stress and semen parameters was also considered. Statistical comparisons were performed using non-parametric tests and logistic regression analyses. Results: Night-shift workers exhibit significantly higher oxidative stress levels compared to day workers (median D-ROMs values of 340 vs. 280 U.CARR, p = 0.01), and a greater proportion of men exceeding the oxidative stress threshold (74.4% vs. 24.4%, p = 0.01). Logistic regression confirmed night-shift work as an independent predictor of elevated oxidative stress (OR 2.1, p = 0.001), even after adjusting for age and smoking. Following three months of antioxidant supplementation with Drolessano, both groups experienced significant reductions in oxidative stress (all p < 0.01), but night workers showed a substantially greater decrease (mean change −58.5 vs. −15.4 U.CARR, p = 0.001). Improvements in semen quality, including sperm concentration, motility, and morphology, were also more pronounced in the night group after treatment. Conclusions: At baseline, night-shift workers had significantly higher oxidative stress than day workers, likely due to circadian disruption. Both groups improved after antioxidant treatment, but night workers showed a greater reduction in D-ROMs. This pilot study might suggest a potential benefit of antioxidant therapy particularly in night workers. Full article

Objective: We aimed to evaluate the feasibility, added value, and radiation dose of coronary computed tomography angiography (CCTA) and stress dynamic CT myocardial perfusion imaging (MPI) in patients with coronary artery disease (CAD) in a real-world setting. Materials and Methods: This retrospective study included 65 patients (mean age: 51.2 ± 11.5 years; 21 female) with moderate CAD, selected from the Radiological Database of our hospital between May 2022 and December 2024. All patients underwent CCTA and stress dynamic CT-MPI using a third-generation dual-source CT scanner. The shuttle-mode acquisition technique was used for CT-MPI with 60 mL of contrast (iopamidol, 370 mg iodine/mL) administered at a flow rate of 6 mL/s. The mean myocardial blood flow (MBF) and other quantitative parameters were measured for both CAD and reference segments (RSs). A 17-segment-based analysis was employed (excluding the apex). The MBF ratio, defined as the mean MBF value of CAD segments divided by that of RS, was used with a cut-off value of 0.85 to distinguish hypoperfused from non-hypoperfused segments within CAD territories. Non-parametric statistical tests were applied. Results: A total of 1040 segments were evaluated. In 62 segments, the mean MBF of CAD territories was found to have decreased. The mean MBF and myocardial blood volume (MBV) in hypoperfused CAD segments were 65.1 ± 19.8 mL/100 mL/min and 14.5 ± 2.7 mL/100 mL, respectively, both significantly lower compared to non-hypoperfused CAD segments and RSs (p < 0.001). The mean effective dose of the protocol was 6.3 ± 1.4 mSv, corresponding to an estimated individual lifetime cancer risk of approximately 0.06% per test, based on BEIR VII Phase 2 modeling. This risk is cumulative, with repeat testing over a 10-year period potentially increasing lifetime cancer risk in proportion to total radiation exposure. The mean total examination time was 26 ± 4 min. Conclusion: The combined CCTA and dynamic CT-MPI protocol is feasible in real-world clinical practice and offers a comprehensive morphological and functional assessment of moderate CAD, with a manageable radiation dose and examination time. Full article

Background/Objectives: To date, there are no validated tools that assess children’s performance in connected text dictation tasks in European Portuguese using automated analysis. International studies were identified, but these primarily involved word dictation tasks and did not use automatic scoring tools. The present study aims to assess the reliability of the Dita.te (internal consistency and inter-rater reliability), a written assessment test based on a dictation task with automatic spreadsheet analysis, and establish normative data for text dictation tasks for children from 3rd to 6th grade. Methods: This study included 315 European Portuguese-speaking children from the 3rd to 6th grades. The Dita.te tool was used to assess orthographic errors based on phonological, morphological, and prosodic criteria. Descriptive statistics, percentiles, the inter-rater reliability and internal consistency were analyzed. Non-parametric tests compared performance by gender and school year due to a non-normal data distribution. Results: The Dita.te had excellent internal consistency (α = 0.929). The correlation between items scored highly (Intraclass Correlation Coefficient = 0.925). The number of errors decreased as the school year progressed, with errors affecting the syllable nucleus being the most frequent across all school years. These were followed by orthographic substitution errors, with grapheme omission being the most prevalent. Conclusions: Our findings suggest that orthographic competence is mostly stable before the 3rd grade, and the mismatches found in children with typical development show residual error in their orthographic performance. Full article

This study investigates the seasonal and floral phenology, breeding strategies, and floral morphology of Azorina vidalii, an Azorean endemic Campanulaceae with hermaphroditic, protandrous flowers, dichogamy and secondary pollen presentation. Seasonal phenology was recorded in four field populations and floral phenology in a garden population. Reproductive strategies were assessed via controlled hand pollinations in one field population. Floral morphometrics were analysed using 23 floral and five pollen traits from 121 flowers across fourteen populations throughout the Azores archipelago. Non-parametric and parametric tests, discriminant analysis, and reproductive indices were used to infer answers to this study’s goals. Results showed that temperature and humidity influenced vegetative and reproductive phenophases. The male phase was shorter than the female, likely due to pollen dynamics, and some functional overlap suggested incomplete dichogamy. Geographic variation in floral traits indicated morphological differentiation across subarchipelagos, presumably linked to environmental factors or isolation. Reproductive indices suggested a mixed mating system, partial self–incompatibility and signs of inbreeding depression. Fertilisation was absent without pollinators, and spontaneous selfing was excluded due to an absence of pollen–pistil contact during stigma retraction. These findings contribute to understanding the reproductive biology and morphologic variation in A. vidalii. The implications of these findings for the conservation of this insular plant are discussed. Full article

Solar exposure and shading critically influence outdoor thermal comfort in residential areas, yet quantitative links between spatial morphology and microclimate remain insufficiently explored in cold-region cities. This study proposes a novel morphological indicator, the Insolation Shadow Ratio (ISR), to quantify sunlight–shade dynamics and investigates its correlation with outdoor thermal comfort (UTCI) in Xi’an, China. Combining field observations, microclimate simulations, and statistical analysis, we quantified ISR and UTCI across three representative outdoor spaces in a residential area. Photographic analysis and spatial parameterization were employed to calculate hourly ISR values. Significant correlations were observed between ISR and UTCI values. The measured data showed the strongest correlation at summer solstice at site C (Spearman’s r = 0.883, p < 0.01). GAM analysis of seasonal peak correlation data revealed that an optimal UTCI comfort range of 9 °C to 26 °C, corresponding to ISR thresholds of 0.0202–0.8384, achieved the highest autumn correlation at site C (r = 0.686, p < 0.01), while effectively balancing shade cooling effects and solar accessibility. The ISR framework provides a quantifiable tool for designers to optimize outdoor thermal environments and, when enhanced by parametric modeling tools, enables them to proactively optimize thermal performance during early-stage residential planning, offering a data-driven pathway for climate-resilient outdoor space design. Full article

This study explores how urban morphological and environmental factors influence Urban Heat Islands (UHIs) using a geospatial modeling approach. The aim of the research is to develop a methodology to assess UHI effects, emphasizing the role of urban morphology, land use, and vegetation in nighttime heat accumulation. A micro-scale analysis with a 50 m resolution is conducted by integrating a custom QGIS plugin with open-access data, ensuring broad applicability. The 50 m resolution was chosen because it allows for the capture of local variations in UHI intensity while maintaining the scalability of the urban analysis across different city contexts. Non-parametric statistical analyses (ANOVA, Kruskal–Wallis H test, and correlation assessments) were used to evaluate the relationships between the urban parameters—wind corridors, altitude, vegetation (NDVI), surface water (NDWI), and the Sky View Factor (SVF)—and Nighttime Land Surface Temperature (LST). Given that UHI variations during summer, particularly in cities of the Iberian Peninsula, are closely linked to summer heat severity, this factor was considered to classify the cities for the study. Correlation analyses confirm that all tested factors influence LST, with wind corridors being the least significant. The model performance evaluation shows the highest errors in cities with lower summer severity (RMSE = 1.586 °C, MAE = 1.2686 °C, MAPE = 6.99%) and the best performance in warmer cities (RMSE = 1.4 °C, MAE = 1.14 °C, MAPE = 4.5%). Validation in four cities of the Iberian Peninsula confirmed the model’s reliability, with the worst RMSE value of 2.04 °C. These findings contribute to a better understanding of the factors driving UHIs and provide a scalable assessment framework. Full article

This study collected site and spatial morphological data from 63 typical aging community activity spaces and extracted 12 spatial types through statistical analysis. A parametric modeling tool was used to generate spatial models. Based on clearly defined design variables and constraints, the NSGA-II multi-objective optimization algorithm was applied to minimize summer thermal discomfort, maximize winter thermal comfort, and maximize annual average sunlight duration, resulting in 342 Pareto optimal solutions. The study first explored the linear relationships between spatial morphology and environmental performance using the Spearman method. It then integrated ensemble learning and the interpretable machine learning model SHAP to reveal nonlinear relationships and boundary effects. The results of the two methods complemented and reinforced each other. Based on a comparison of these two approaches, morphological indicators showing significant differences were selected for attribution and sensitivity analyses, clarifying the mechanisms by which spatial morphological parameters influence environmental performance and identifying their critical thresholds. Key findings include the following: (1) the UTCI-S exhibits significant negative linear correlations with the open space ratio (OSR) and spatial crowding density (SCD); the UTCI-W shows negative linear correlations with canopy coverage (CVH) and wind speed (WS); and a positive linear correlation exists between the sky view factor (SVF) and AV.SH. (2) Boundary effects and threshold intervals of critical morphological parameters were identified as follows. The open space ratio should be controlled to 10–15%, the shrub–tree layer coverage to 0.013–0.0165%, and the average building height to 3.1–3.8 m. (3) Spatial layout principles demonstrate that placing fully enclosed spaces (E-2) and semi-enclosed spaces (S-1/S-3) on the northern side, as well as semi-enclosed spaces (S-1/S-2) and circulation spaces (C-3) on the southern side, significantly enhance microclimatic performance. These findings provide quantitative guidelines for community space design in cold regions and offer data support for creating outdoor environments that meet the comfort needs of the elderly. Full article

To address the challenges of detection and acquisition caused by trajectory prediction errors during the midcourse–terminal guidance handover phase in cross-domain unmanned aerial vehicles (CDUAV), this study proposes a collaborative multi-interceptor detection coverage optimization method based on predictive error pipeline modeling. Firstly, we employ nonlinear least squares to fit parameters for the motion model of CDUAV. By integrating error propagation theory, we derive a recursive expression for error pipelines under t-distribution and establish a parametric model for the target’s high-probability region (HPR). Next, we analyze target acquisition scenarios during guidance handover and reformulate the collaborative detection problem as a field-of-view (FOV) coverage optimization task on a two-dimensional detection plane. This framework incorporates the target HPR and the seeker detection FOV models, with an objective function defined for coverage optimization. Finally, inspired by wireless sensor network (WSN) coverage strategies, we implement the starfish optimization algorithm (SFOA) to enhance computational efficiency. Simulation results demonstrate that compared to Monte Carlo statistical methods, our parametric modeling approach reduces prediction error computation time from 15.82 s to 0.09 s while generating error pipeline envelopes with 99% confidence intervals, showing superior generalization capability. The proposed collaborative detection framework effectively resolves geometric coverage optimization challenges arising from mismatches between target HPR and FOV morphology, exhibiting rapid convergence and high computational efficiency. Full article

With the intensification of climate challenges driven by rapid urbanization, the microclimate and thermal comfort of residential blocks have attracted increasing attention. Current research predominantly focuses on isolated morphological factors—such as building orientation, layout patterns, and height-to-width ratios—while neglecting the synergistic effects of multifactorial spatial configurations on outdoor thermal comfort. This study addresses this gap by analyzing 36 residential block samples in Wuhan, a representative city in a hot-summer and cold-winter (HSCW) region. Utilizing the Honeybee plugin in Grasshopper (GH) alongside the Universal Thermal Climate Index (UTCI), we simulate outdoor thermal environments to identify critical influencing elements. The results reveal how multifactor interactions shape thermal performance, providing evidence-based design strategies to optimize microclimate resilience in high-density urban contexts. This work advances the understanding of spatial morphology–thermal dynamics and offers practical insights for sustainable residential planning. This study systematically investigates the thermal performance of residential blocks through parametric prototyping and seasonal simulations. Sixteen morphological prototypes were developed by combining four building layout typologies (arrayed, staggered, enclosed, and hybrid) with three critical variables: the height-to-width ratio (HWR), building orientation deviation angle (θ), and sky visibility factor (SVF). Key findings reveal the following: (1) the hybrid layout demonstrates superior annual thermal adaptability when integrating fixed orientation (θ = 0°), moderate H/W = 1, and SVF = 0.4; (2) increased H/W ratios enhance thermal comfort levels across all layout configurations, particularly in winter wind protection; and (3) moderate orientation deviations (15° < θ < 30°) significantly improve microclimate performance in modular layouts by optimizing solar penetration and aerodynamic patterns. These evidence-based insights provide actionable guidelines for climate-responsive residential design in transitional climate zones, effectively balancing summer heat mitigation and winter cold prevention through spatial configuration optimization. Full article

The growing global freshwater scarcity urgently requires innovative wastewater treatment technologies. This study hypothesized that biomimicry-inspired automated machine learning (AML) could effectively manage wastewater variability through adaptive processing techniques. Utilizing decentralized swarm intelligence, specifically the Respected Parametric Insecta Swarm (RPIS), the system demonstrated robust adaptability to fluctuating influent conditions, maintaining stable effluent quality without centralized control. Bio-inspired oscillatory control algorithms maintained stability under dynamic influent scenarios, while adaptive sensor feedback enhanced real-time responsiveness. Machine learning (ML) methods inspired by biological morphological evolution accurately classified influent characteristics (F1 score of 0.91), optimizing resource allocation dynamically. Significant reductions were observed, with chemical consumption decreasing by approximately 11% and additional energy usage declining by 14%. Furthermore, bio-inspired membranes with selective permeability substantially reduced fouling, maintaining minimal fouling for up to 30 days. Polynomial chaos expansions efficiently approximated complex nonlinear interactions, reducing computational overhead by approximately 35% through parallel processing. Decentralized swarm algorithms allowed the rapid recalibration of system parameters, achieving stable pathogen removal and maintaining effluent turbidity near 3.2 NTU (Nephelometric Turbidity Units), with total suspended solids consistently below 8 mg/L. Integrating biomimicry with AML thus significantly advances sustainable wastewater reclamation practices, offering quantifiable improvements critical for resource-efficient water management. Full article

Background/Objectives: Recent studies have highlighted the role of the gut–muscle axis, suggesting that modulation of the gut microbiota may indirectly benefit skeletal muscle. This study aimed to evaluate the effects of Lactobacillus fermentum (L. fermentum) supplementation in a model of muscle atrophy induced by chronic ethanol (EtOH) intake, focusing on inflammatory and antioxidant mechanisms. Methods: Sixty 12-month-old female Balb/c mice were divided randomly into three groups (n = 20/group): (1) Ethanol (EtOH) group, receiving ethanol daily for 8 and 12 weeks to induce systemic oxidative stress and inflammation; (2) Ethanol + Probiotic (EtOH + P) group, receiving both ethanol and L. fermentum supplementation for the same durations; and (3) Control (Ctrl) group, receiving only water. Muscle samples were analyzed for the fiber morphology, inflammatory markers, oxidative stress indicators, and satellite cell (SC) activity. All data were tested for normality using the Shapiro–Wilk test before applying a parametric analysis. A statistical analysis was performed using one-way ANOVA followed by a Bonferroni post-hoc test. The level of significance was set at p < 0.05. Results: EtOH exposure caused significant atrophy in all muscle fiber types (type I, IIa, and IIb), with the most pronounced effects on oxidative fibers. L. fermentum supplementation significantly reversed atrophy in type I and IIa fibers, accompanied by a significant reduction in IL-6, TNF-α, and Hsp60 expression levels, indicating the protective effect of L. fermentum against oxidative stress and inflammation. Moreover, the probiotic treatment increased MyoD expression in SCs, suggesting enhanced regenerative activity, without histological evidence of fibrosis. Conclusions: These findings suggest that L. fermentum supplementation could counteract EtOH-induced skeletal muscle damage by reducing inflammation and oxidative stress and promoting muscle repair, indicating its potential as an adjuvant, in the therapeutic strategy of models of muscle degeneration. Full article