Search Results (8,680)

This study explores how variations in mechanical alloying time and sintering temperature influence the microstructure, mechanical properties, and corrosion resistance of MnAlCuFeTi high-entropy alloys (HEAs). The MnAlCuFeTi alloy was produced by means of mechanical alloying for 5, 10, 15, and 20 h. Afterward, the alloy samples were sintered at two different temperatures: 550 °C and 650 °C. Structural properties were analyzed using X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDX). Analysis of grain sizes, calculated using the Scherrer formula from SEM images, confirmed that grain size had decreased to the nanostructured regime and that microstructural homogeneity had improved. Corrosion behavior was evaluated using polarization curves, corrosion current density (I_corr), and corrosion rate measurements. The results show that increasing the mechanical alloying time reduces the alloy’s grain size, thereby improving its mechanical and corrosion resistance. At a sintering temperature of 550 °C, I_corr and corrosion rate decrease with increasing grinding time, whereas at 650 °C, although high temperatures accelerate diffusion processes and increase phase homogeneity, they weaken corrosion resistance. These findings emphasize the importance of balancing alloying time and sintering temperature to optimize performance in high-corrosion-resistant HEA applications. Full article

Background/Objectives: This study aimed to characterize eyelid speculum-induced intraocular pressure (IOP) elevation during cataract surgery and identify ocular biometric factors that stratify susceptibility to this pressure response. This study was conducted at Zengyo Suzuki Eye Clinic, Kanagawa, Japan. Methods: In this retrospective observational study, we analyzed 100 eyes that underwent routine cataract surgery. IOP was measured immediately before and within 10 s of speculum opening in the seated position using a rebound tonometer. The eyelid speculum was opened to a maximal opening position, and the opening width was recorded. Biometric parameters included axial length (AL), central corneal thickness, white-to-white distance, anterior chamber depth, and temporal angle-opening distance. Associations between IOP elevation and biometric factors were analyzed. IOP elevation rate was quantified as the percentage increase from baseline. The discriminatory performance of axial length was evaluated using receiver operating characteristic (ROC) analysis. Results: Overall, 100 patients (100 eyes) were included in the analysis. Mean IOP increased significantly from 15.75 ± 2.77 mmHg before speculum placement to 21.42 ± 5.54 mmHg after placement. The mean IOP elevation rate was 36.0 ± 27.4%. Shorter AL was consistently associated with a greater proportional IOP elevation. ROC analysis demonstrated consistent stratification of IOP elevation susceptibility by AL (area under the curve [AUC] = 0.645), with eyes shorter than 23.84 mm showing greater pressure elevation (sensitivity, 73.1%; specificity, 56.0%). Eyes in the upper quartile of the IOP elevation rate exhibited relatively greater pressure elevation. Conclusions: Eyelid speculum placement imposes a clinically meaningful IOP load during cataract surgery, with shorter ALs making eyes more biomechanically susceptible to IOP elevation. Full article

Neurodegenerative diseases feature diverse pathological protein aggregates, including Lewy bodies in Alzheimer’s disease (AD) and skein-like filaments in amyotrophic lateral sclerosis (ALS). The physical mechanisms underlying this morphological diversity remain unclear. Here, we demonstrate that aggregation of the prion-like domain of hnRNPA1 (A1PrD), implicated in AD and ALS, is driven by solution composition and phase transition dynamics. Utilizing 3D timelapse and fluorescence lifetime imaging microscopy, we show that solution conditions modulate phase separation, gelation, and fibrillation, resulting in distinct structures such as fibril, gel, and starburst morphologies. Homotypic and heterotypic interactions between A1PrD and RNA were observed to shift the balance between pathological and physiological condensates. Importantly, amyloid-rich starbursts displayed prion-like infection capabilities toward amyloid-poor condensates. Our findings highlight how the interplay between solution composition and kinetic balances of liquid-liquid phase separation, gelation, and fibrillation shapes the diverse pathological aggregate morphologies characteristic of neurodegenerative diseases. Full article

Visual saliency modeling has achieved high predictive performance in natural image domains, yet its generalization to abstract art remains limited by the lack of explicit semantic structure and the scarcity of eye-tracking data. In such semantically ambiguous contexts, understanding the underlying drivers of attention is as critical as predictive accuracy. This paper presents an interpretable, ’white-box’ saliency framework tailored to abstract art, which constructs predictions through a weighted combination of 35 modular heuristics grounded in perceptual psychology and art theory, including contrast, grouping, isolation and symmetry. Heuristic weights are optimized via a genetic algorithm and refined by a context-aware modulation mechanism that adapts to image-level visual features. Evaluation against eye-tracking data from 40 abstract paintings demonstrates that the model with the expanded activation variant produces stable, meaningful predictions while achieving a competitive KL-divergence score (1.11 ± 0.55), which is comparable to the SalGAN baseline (1.11 ± 0.53). Analysis of the optimized weights reveals strong contributions from contrast, texture, and grouping mechanisms, while nearly half of the heuristics, including most horizontal symmetry heuristics are systematically pruned by the model. Moreover, context-aware modulation reveals that these weights are not static but shift dynamically based on image-level features such as edge density and intensity variation. By prioritizing transparency over raw predictive performance, this study demonstrates that explainable saliency models can function as robust investigative tools for decoding the principles of human visual perception in data-scarce domains. Full article

Conservation easements (CEs) represent a complex policy instrument designed to mediate the feedback loops within coupled human and natural systems in protected areas. However, their efficacy is often constrained by a lack of systemic understanding of the localized drivers of community support. Building upon the successful implementation of Forest Land Easements (FLEs) within China’s Qianjiangyuan National Park Pilot, this study investigates the potential to expand this policy model to other land types. This study investigates the multilevel factors influencing residents’ willingness to adopt three types of CEs, including forest land (FLE), agricultural land (ALE) and homestead land (HLE) easements in China’s Qianjiangyuan National Park Pilot, the country’s primary CE reform site. We conceptualize a hierarchical support model wherein community participation (CP) and human well-being (HW) interact with support for park management (SM), forming a subsystem that drives decisions within the broader land-use. Utilizing structural equation modelling (SEM) and stepwise regression analysis on survey data from 336 households, we tested this model. The results reveal that SM acts as a critical direct mediator and positive driver of CE acceptance, while CP and HW exert significant indirect effects through SM, demonstrating a key feedback pathway. Regression analyses further elucidate that support for different CE types is driven by distinct configurations of factors, highlighting the heterogeneous nature of subsystems. Notably, livelihood benefits and prior participation experiences emerged as consistent, cross-cutting systemic leverages. It demonstrates that leveraging the implementation experience and community support gained from existing forest land easements is crucial. This study concludes that effective CE design must move beyond one-size-fits-all approaches. It necessitates differentiated, adaptive policies that are coherently aligned with local livelihood subsystems and strategically strengthen participatory feedback mechanisms initiated by successful FLEs. Our findings provide an evidence-based framework for designing resilient, socially sustainable conservation policies in complex protected area systems, grounded in proven practice. Full article

This study evaluates the effects of Al₂O₃ and CeO₂ nanoparticles as additives to standard diesel and biodiesel fuels on the combustion and emissions characteristics of a CR diesel engine with split injection (pilot and main injections). Three nanoparticle dosing levels (50 ppm, 100 ppm, and 150 ppm) were compared with undoped standard diesel and biodiesel fuels. The results showed that the presence of both Al₂O₃ and CeO₂ in biodiesel increased the ignition delay of the pilot fuel by about 8.0% at low load and about 3.5% at high load. The addition of both nanoparticles to diesel and biodiesel fuels had an insignificant effect on the main injection fuel’s ignition delay, MBF50 position and combustion duration. The thermal efficiency was up to 1.0% lower. Al₂O₃ additive in diesel had no significant effect on NO_x emissions. CO emissions were higher by 4.4–7.5% in most cases. The Al₂O₃ additive in biodiesel reduced NO_x emissions by an average of 38%, 17.1%, and 9.4% at low, medium, and high engine loads, respectively. The reduction in CO emissions averaged 15%. The addition of CeO₂ nanoparticles to diesel fuel reduced NO_x emissions by 22.5%, 8.5%, and 3.1% on average across the corresponding load ranges. When the engine was operated on CeO₂-doped biodiesel, NO_x emissions were lower by an average of 25.7%, 9.6%, and 2.5% at low, medium, and high loads, respectively. Adding CeO₂ nanoparticles to diesel fuel increased CO emissions, whereas adding them to biodiesel significantly reduced CO emissions. Full article

This research investigates the capacity of Artificial Intelligence (AI) to serve as a generative and interpretative framework for revitalizing Al-Qatt Al-Asiri art. By developing sustainable design solutions for temporary exhibitions, the study seeks to reinforce Saudi Arabia’s cultural and touristic identity through a synthesis of heritage and technology. The study adopts a descriptive–analytical and applied methodology to examine the potential of AI to support creative design processes that integrate authenticity and innovation while preserving local heritage and meeting environmental sustainability requirements. Utilizing this descriptive–analytical and applied methodology. the study evaluates the efficacy of AI in augmenting creative design processes. The primary objective is to reconcile cultural authenticity with modern innovation, ensuring the preservation of local heritage while adhering to rigorous environmental sustainability standards. A controlled design experiment was executed for a temporary heritage exhibition, employing AI applications to simulate the complex decorative motifs of Al-Qatt Al-Asiri art. These technologies were used to generate sustainable exhibition units constructed from reusable local materials, bridging the gap between the digital generation and physical sustainability. This study presents a theoretical framework, a review of previous studies, the research methodology, quantitative and qualitative evaluation results, and an expert panel assessment. It involved three expert reviewers who evaluated the proposed design models based on eight sustainability criteria. This study also utilized a structured evaluation tool and AI applications, including ChatGPT-5.2, OpenAI and Gemini 3 Pro—Nano Banana. The results of the exploratory study indicate that the use of AI contributes to achieving a balance between preserving traditional aesthetic identity and promoting sustainable design practices derived from the characteristics of Al-Qatt Al-Asiri art. It also enhances cultural and tourism engagement by integrating AI applications into artistic design processes. The findings also revealed no statistically significant differences among the experts’ evaluations regarding the sustainability criteria of the implemented models. This study recommends integrating AI technologies into art and design education programs at Saudi universities and developing ethical and technical guidelines that ensure the preservation of heritage and cultural identity when applying AI in design practices. Full article

To address false detections in small object detection within remote sensing imagery caused by complex backgrounds and minute target sizes, we propose an enhanced YOLOv8s detection algorithm, named AL-YOLOv8. The detection head is designed based on Adaptive Spatial Feature Fusion (ASFF) to resolve issues where shallow-level detail features of small remote sensing targets are easily disrupted by backgrounds, while deep-level semantic features lack sufficient representation. We embed Large-Kernel Separate Attention (LSKA) in the deep feature layer to expand the receptive field and enhance the response intensity of small target features. Additionally, an IFIoU loss function is introduced by combining the dynamic attention mechanism from FocalerIoU with InnerIoU, mitigating regression bias for small target bounding boxes and improving small target localization accuracy. On the DIOR, RSOD, and NWPU VHR-10 datasets, the AL-YOLOv8 model achieves precision rates of 91.5%, 94.2%, and 91.8%, respectively, with mAP@0.5 scores of 89.8%, 96.9%, and 92.2%. These results demonstrate consistent improvements over YOLOv8s and show that AL-YOLOv8 effectively reduces false detections and enhances detection accuracy for small object detection in remote sensing applications. Full article

Prediabetes is a critical precursor to type 2 diabetes (T2DM) and cardiometabolic diseases, yet its burden in Oman remains understudied. Leveraging data from Oman’s 2023 National Screening Program, this study quantifies the prevalence of prediabetes and its risk profiles among adults in Muscat Governorate—providing urgent evidence to guide diabetes prevention strategies in the Gulf region. Objectives: To estimate the prevalence of prediabetes and identify associated risk factors among Omani adults screened at primary health centers in Muscat Governorate (2023), given its critical role in preventing type 2 diabetes mellitus (T2DM) progression. Methods: This cross-sectional study analyzed data from Oman’s national screening program. Socio-demographics, clinical parameters (blood pressure, body mass index [BMI]), and laboratory results (fasting glucose, lipids, renal function) were extracted from the Al-Shifa electronic health system and National Screening Register. Multivariable logistic regression was performed using SPSS 30.0 (IBM Corp., Armonk, NY, USA). Results: Among 4862 participants (mean age 43.2 ± 6.3 years; 61.7% female), prevalences were: prediabetes 29.0%, T2DM 5.5%, obesity (BMI 30–40 kg/m²) 35.7%, hypertension 42.0%, hypercholesterolemia 48.8%, and renal involvement 51.8%. Males had significantly higher prediabetes prevalence than females (35.4% vs. 24.7%; adjusted odds ratio [aOR] = 1.43; 95% confidence interval [CI]: 1.21–1.70). Independent risk factors included each 1-year age increase (aOR = 1.05; 95% CI: 1.03–1.08), each 1-unit BMI increase (aOR = 1.03; 95% CI: 1.01–1.05), and family history of diabetes (aOR = 1.28; 95% CI: 1.09–1.50). Conclusions: The high burden of prediabetes and comorbid non-communicable diseases in Oman necessitates urgent public health strategies, including enhanced screening, lifestyle interventions, and gender-specific approaches to curb the T2DM epidemic. Full article

Legumes (Fabaceae) are key functional components of tropical forests due to their role in nitrogen fixation and nutrient cycling. This study provides an integrated assessment of forest legume diversity and its relationship with soil physicochemical properties across three protected areas in the Peruvian upper Amazon: the Alto Mayo Protected Forest (BPAM), the Cordillera Escalera Regional Conservation Area (ACR-CE), and the Shunté and Mishollo Forests Regional Conservation Area (ACR-BOSHUMI). Floristic studies were conducted in nine sectors ranging from 618 to 1729 m a.s.l. Soil samples were analyzed, and vegetation cover was quantified using high-resolution drone imagery with four vegetation indices derived from RGB data. We recorded eleven legume species from eight genera within the sampling plots, identifying Inga as the most frequent genus. Species diversity was highest in the ACR-CE, whereas BPAM showed lower richness and abundance. Multivariate analyses revealed that legume diversity was positively associated with higher soil pH, cation concentrations, and cation exchange capacity, but negatively associated with elevated Al³⁺ and Fe³⁺ levels. Vegetation indices effectively distinguished between vegetated and degraded areas, indicating higher legume occurrence in sites with greater canopy cover. These findings emphasize that soil fertility and vegetation structure are key drivers of legume diversity, with significant implications for conservation in the upper Amazon. Full article

Hydrogen plasma heating, a unique method for heating and reducing iron ore, is distinguished by its high heat, rapid reduction, and high efficiency, making it a promising technique in the metallurgy field. In this study, a non-transferred arc plasma heating system was used with Ar-H₂ as the working gas and acidic pellets as the raw material. The microstructures and elemental distributions of the slag and iron phases during the reduction process were examined using electron microscopy and energy-dispersive X-ray. The variation patterns of Fe-containing phases in the reduction products were found using X-ray diffraction and full-spectrum fitting refinement. The conversion rate of the oxidized pellets and the deoxidation conversion rate per area were estimated for various gas flow rates and reduction times. A reaction kinetics model was also used to study the reaction controlling step. The results showed that during the reduction process, with an H₂ flow rate of 4.5 L min⁻¹ and a 40 min reduction, the conversion(α) reached 99.89% and the purity of the reduced metallic iron reached 99.9%, achieving the industrial-grade 3N standard. Si and Al in the melt bath generated fayalite (Fe₂SiO₄) and hercynite (FeAl₂O₄) with Fe_xO. The deoxidation conversion rate per unit area was 1.11 g (cm² min)⁻¹. A three-dimensional diffusion-controlled model was used to describe the reduction process, and the mechanism function was 2/3(1 + α)^3/2[(1 + α)^1/3]⁻¹. The values of the reduction reaction rate constant (K) were 12.6 × 10⁻² s⁻¹ and 12.8 × 10⁻² s⁻¹ when the flow rates of H₂ gas were 3 and 4.5 L min⁻¹, respectively. The apparent activation energy was 21.9 kJ mol⁻¹. The empirical equation for the specific reduction rate was calculated as ln r = −2637.5/T − 0.407. Full article

To address the problem of temperature cracking caused by the concentrated release of hydration heat in mass concrete, this study developed a low-heat composite cementitious material (CWCM) by partially replacing conventional mineral admixtures with construction spoil. A multi-factor synergistic optimization design based on response surface methodology (RSM) was conducted. The water–binder ratio, spoil replacement ratio, curing temperature, and ball-milling time were selected as influencing factors, while the 28-day flexural strength, 28-day compressive strength, and 72 h cumulative hydration heat were used as response variables. A four-factor, three-level Box–Behnken model was established. The results show that the regression model exhibits good fitting performance, and the prediction errors between the predicted and experimental values of all response variables are within a reasonable range. Under the optimized mixture proportion (15% spoil replacement), the system achieves a 28-day compressive strength of 61.03 MPa, while the 72 h cumulative hydration heat is reduced by approximately 15%, meeting the requirements for low-heat cement. Microstructural analyses using XRD, SEM, and TG/DTG indicate that a decrease in the Ca/Si ratio and an increase in the Al/Si ratio promote the formation of a denser C-(A)-S-H gel structure, enhancing the pozzolanic reaction. This mechanism plays a key role in achieving the synergistic regulation of strength enhancement and hydration heat reduction. Compared with conventional fly ash or slag systems, this study innovatively utilizes construction spoil as a partial substitute for traditional mineral admixtures. While maintaining satisfactory mechanical performance, the proposed system effectively reduces hydration heat release, providing a new pathway for temperature control design in mass concrete engineering and high-value resource utilization of construction waste. Full article

In this study, the effect of boron carbide (B₄C), hexagonal boron nitride (hBN), holy super graphene (HSG), and hybrid (B₄C + hBN + HSG) nano-additives on the tribological performance of SAE 5W-30 gasoline engine oil was investigated on Al-Si-based samples (Al 4032) prepared by cutting from a single-cylinder gasoline engine block. The addition of nano-additives regularly increased the kinematic viscosity; the 63.80 mm²/s (BO) value rose to 68.90 mm²/s at the highest level of B₄C and to 70.50 mm²/s in the hybrid oil (≈10.5% increase). The lowest and most stable friction performance was found in the hybrid 0.025 g/25 mL nano-additive oil, which remained between 0.03 and 0.05 during the entire COF test. The EDS mapping and line scan results confirmed the formation of tribofilm by identifying the additive elements (B for B₄C, B and N for hBN, C for HSG) in the wear scar, and the presence of increased O elements showed the restricted formation of tribo-oxidation. The results show that hybrid nano-additive oils provide the most effective friction and wear improvement, especially at low concentrations, while at high additive levels, performance does not show a consistent increase due to particle accumulation and third-body effects. Full article

Since the initiation of two variants of the bootstrap method by Efron and Rubin in the late 1970s, a variety of advancements has emerged in the literature. The subsampling of blocks enabled the estimation of the actual variance of the sample mean. The equivalence of the data-level and the estimator-level resampling is easily established for the sample mean and estimators alike. For Rubin’s variant of the bootstrap we apply an algorithm by Diniz et al. which allows for the numerically stable computation of the sample-based cumulative distribution function of the estimator under investigation. No actual Monte-Carlo resampling is necessary in this setting and we demonstrate how we get access to the very small probabilities of the tails and moreover to confidence intervals. We do this at the example of a well-known test model that exhibits geometrically decaying spatial correlations. The analysis naturally applies to temporally correlated systems or to the correlations occurring in Markov chains, as well. Full article

In this work, for the first time, we applied and determined the mechanical characteristics of protective coatings made of high-entropy alloy (TiZrVCrAl)N with different architectures onto the surface of Ti-6Al-4V alloy with the initial coarse-grained and ultrafine-grained structure using arc physical vapor deposition. We designed and prepared three coating architectures: a monolayer nitride coating (TiZrVCrAl)N, a multilayer coating consisting of nine alternating layers of TiZrVCrAl and (TiZrVCrAl)N, and a multilayer coating consisting of 720 alternating layers of (TiZrVCrAl)N and TiN, with a total thickness not exceeding 2 microns. We evaluated their protective performances by nanoindentation and scratch tests. Importantly, the effect of the substrate microstructure on the coatings’ performance is investigated by comparing their mechanical behavior on coarse-grained and ultrafine-grained Ti-6Al-4V. Our experimental results show that the coating performance improves with increasing number of layers in the coating, and this effect is even more pronounced for the multilayer coating deposited on the ultrafine-grained titanium alloy substrate. We also find that the (TiZrVCrAl)N/TiN (720 layers) multilayer coating deposited on the UFG Ti-6Al-4V alloy substrate exhibits the highest H/E- and H³/E²-values, indicating the coating’s high innovative potential for performance in extreme conditions. The origins of this phenomenon are analyzed and discussed. Full article