Search Results (22,733)

Understanding household vehicle ownership dynamics in the post-COVID-19 era is critical for designing equitable, resilient, and sustainable transportation policies. This study employs an interpretable machine learning framework to model household vehicle ownership using data from the 2022 National Household Travel Survey (NHTS)—the first nationally representative U.S. dataset collected after the onset of the pandemic. A binary classification task distinguishes between single- and multi-vehicle households, applying an ensemble of algorithms, including Random Forest, XGBoost, Support Vector Machines (SVM), and Naïve Bayes. The Random Forest model achieved the highest predictive accuracy (86.9%). To address the interpretability limitations of conventional machine learning approaches, SHapley Additive exPlanations (SHAP) were applied to extract global feature importance and directionality. Results indicate that the number of drivers, household income, and vehicle age are the most influential predictors of multi-vehicle ownership, while contextual factors such as housing tenure, urbanicity, and household lifecycle stage also exert substantial influence highlighting the spatial and demographic heterogeneity in ownership behavior. Policy implications include the design of equity-sensitive strategies such as targeted mobility subsidies, vehicle scrappage incentives, and rural transit innovations. By integrating explainable artificial intelligence into national-scale transportation modeling, this research bridges the gap between predictive accuracy and interpretability, contributing to adaptive mobility strategies aligned with the United Nations Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities), SDG 10 (Reduced Inequalities), and SDG 13 (Climate Action). Full article

Shaft deflection degrades roller alignment and intensifies stress concentration/edge effects at roller-ends and raceway edges, ultimately compromising service performance of tapered roller bearings (TRBs). Therefore, a dynamic model was developed for a TRB subjected to a deflected shaft in which Johnson’s load–deformation relationship was applied to reflect non-uniform cross-sectional structures of the tapered rollers and raceways, viscous damping was integrated into the roller/cage interaction, and friction actions at the raceways and flange areas were treated separately. Then, moment load and angular misalignment of the tapered roller were analyzed under various shaft deflection and operating conditions. Results indicate that tilt angle remains orders of magnitude smaller than skew angle. Shaft deflection amplifies both skew and tilt, and the influence level is proportional to the bearing size. Centrifugal effect primarily affects skew motion, whereas gyroscopic effect mainly influences tilt motion. Axial forces exert greater influence on roller skew than tilt. The flange typically constrains roller skew, whereas both raceways may induce bidirectional tilt/skew motion. Full article

The methylation of CpG sites with 5mC mark is a dynamic epigenetic modification. However, the relationship between the methylation and the surrounding genomic sequence context remains poorly explored. Investigation of the allele methylation provides an opportunity to decipher the interplay between differences in the primary DNA sequence and epigenetic variation. Here, we performed high-coverage long-read whole-genome direct DNA sequencing of one individual using Oxford Nanopore technology. We also used Illumina whole-genome sequencing of the parental genomes in order to identify allele-specific methylation sites with a trio-binning approach. We have compared the results of the haplotype-specific methylation detection and revealed that trio binning outperformed other approaches that do not take into account parental information. Also, we analysed the cis-regulatory effects of the genomic variations for influence on CpG methylation. To this end, we have used available Deep Learning models trained on the primary DNA sequence to score the cis-regulatory potential of the genomic loci. We evaluated the functional role of the allele-specific epigenetic changes with respect to gene expression using long-read Nanopore RNA sequencing. Our analysis revealed that the frequency of SNVs near allele-specific methylation positions is approximately four times higher compared to the biallelic methylation positions. In addition, we identified that allele-specific methylation sites are more conserved and enriched at the chromatin states corresponding to bivalent promoters and enhancers. Together, these findings suggest that significant impact on methylation can be encoded in the DNA sequence context. In order to elucidate the effect of the SNVs around sites of allele-specific methylation, we applied the Deep Learning model for detection of the cis-regulatory modules and estimated the impact that a genomic variant brings with respect to changes to the regulatory activity of a DNA loci. We revealed higher cis-regulatory impact variants near differentially methylated sites that we further coupled with transcriptomic long-read sequencing results. Our investigation also highlights technical aspects of allele methylation analysis and the impact of sequencing coverage on the accuracy of genomic phasing. In particular, increasing coverage above 30X does not lead to a significant improvement in allele-specific methylation discovery, and only the addition of trio binning information significantly improves phasing. We investigated genomic variation in a single human individual and coupled computational discovery of cis-regulatory modules with allele-specific methylation (ASM) profiling. In this proof-of-concept analysis, we observed that SNPs located near methylated CpG sites on the same haplotype were enriched for sequence features suggestive of high-impact regulatory potential. This finding—derived from one deeply sequenced genome—illustrates how phased genetic and epigenetic data analyses can jointly put forward a hypotheses about the involvement of regulatory protein machinery in shaping allele-specific epigenetic states. Our investigation provides a methodological framework and candidate loci for future studies of genomic imprinting and cis-mediated epigenetic regulation in humans. Full article

Saudi Arabia’s Vision 2030, unveiled by Crown Prince Mohammed bin Salman on 25 April 2016, aims to diversify the economy beyond oil dependency and engender robust foreign direct investment (FDI). This research investigates the primary economic challenges impeding foreign investors from entering the Saudi market and devises effective strategies to sustain FDI inflows. The study employs a comprehensive methodology, including an extensive literature review spanning from 2016 to 2023, supported by quantitative statistical analysis using a Multiple Linear Regression Model and qualitative insights derived from Delphi interviews with industry experts. The study’s outcomes reveal a significant disparity between the targeted FDI growth from 3.8% to 5.7% of GDP and the existing trajectory, highlighting pressing economic challenges that require immediate attention. Key findings indicate that factors such as population growth, government spending, and trade openness significantly influence FDI dynamics, with a particular emphasis on the positive impact of investment protection agreements. The integration of qualitative methodologies further elucidates the importance of robust legal frameworks and regulatory reforms in fostering an investor-friendly environment. Overall, this research provides strategic recommendations for improving the investment landscape in Saudi Arabia, aligning with the broader goals of Vision 2030, and enhancing the country’s attractiveness as a global investment destination. The commitment to fostering a conducive investment ecosystem serves as a pivotal mechanism for driving economic growth and achieving sustainable development goals within the Kingdom. Full article

To investigate the influence of surface films on the material removal mechanism of single-crystal silicon during nanogrinding, molecular dynamics (MD) simulations were performed under different surface-film conditions. The simulations examined atomic displacements, grinding forces, radial distribution functions (RDF), phase transformations, temperature distributions, and residual stress distributions to elucidate the damage mechanisms at the surface and subsurface on the nanoscale. In this study, boron nitride (BN) and graphene films were applied to the surface of single-crystal silicon workpieces for nanogrinding simulations. The results reveal that both BN and graphene films effectively suppress chip formation, thereby improving the surface quality of the workpiece, with graphene showing a stronger inhibitory effect on atomic displacements. Both films reduce tangential forces and mitigate grinding force fluctuations, while increasing normal forces; the increase in normal force is smaller with BN. Although both films enlarge the subsurface damage layer (SDL) thickness and exhibit limited suppression of crystalline phase transformations, they help to alleviate surface stress release. In addition, the films reduce the surface and subsurface temperatures, with graphene yielding a lower temperature. Residual stresses beneath the abrasive grain are also reduced when either film is applied. Overall, BN and graphene films can enhance the machined surface quality, but further optimization is required to minimize subsurface damage (SSD), providing useful insights for the optimization of single-crystal silicon nanogrinding processes. Full article

In this study, the nonlinear forced vibration response of fiber-reinforced laminated composite beams coated with functionally graded materials (FGMs) is investigated under the combined action of aero-thermoelastic loads and a concentrated harmonic excitation. The mathematical formulation is established using the Euler–Bernoulli beam theory, where von Kármán geometric nonlinearities are taken into account, along with the modified third-order piston theory to represent aerodynamic effects. By neglecting axial inertia, the resulting set of nonlinear governing equations is simplified into a single equation. This equation is discretized through the Galerkin procedure, yielding a nonlinear ordinary differential equation. An analytical solution is, then, obtained by applying the method of multiple time scales (MTS). Furthermore, a comprehensive parametric analysis is carried out to evaluate how factors such as the power-law index, stacking sequence, temperature field, load amplitude and position, free-stream velocity, and Mach number influence both the lateral dynamic deflection and the frequency response characteristics (FRCs) of the beams, offering useful guidelines for structural design optimization. Full article

Internal insulation plasters enable historic building renovation without altering the external appearance of the wall. However, the use of internal insulation must be verified case-by-case through dynamic hygrothermal simulation, and the influence of input parameters on the results is not always clear. This paper aims to (i) characterize a new lime-based insulating plaster with expanded recycled glass and aerogel through laboratory measurements, (ii) assess the damage criteria of the plaster under different boundary conditions through dynamic simulations, and (iii) identify the most impactful design conditions on the relative humidity behind insulation. This innovative plaster combines highly insulating properties (thermal conductivity of 0.0463 W/mK) with good capillary activity while also integrating recycled components without compromising performance. The relative humidity behind insulation remains below 95% in most simulated scenarios, with cases above this threshold found only in cold climates, particularly under high internal moisture loads. The parametric study shows that (i) in the analyzed stones, the thermal conductivity variation of the existing wall has a greater effect on the relative humidity behind insulation than the variation of the vapor resistance factor, (ii) the effect of insulation thickness on the relative humidity behind insulation depends on the difference in thermal resistance of the insulation and existing masonry layers, and (iii) internal moisture load and external climate directly impact the relative humidity behind insulation. Full article

In this study, the behavior of the spherical bearing component of the L-100 bridge part (AlfaTech LLC, Perm, Russia) is considered within the framework of a finite element model. The influence of the pattern of the coupling of the antifriction interlayer with the lower steel plate on the operation of the part is examined in terms of ideal contact, full adhesion, and frictional contact. The thickness of the antifriction interlayer varied from 4 to 12 mm. The dependencies of the contact parameters and the stress–strain state on the thickness were determined. Structurally modified polytetrafluoroethylene (PTFE) without AR-200 fillers was considered the material of the antifriction interlayer. The gradual refinement of the behavioral model of the antifriction material to account for structural and relaxation transitions was carried based on a wide range of experimental studies. The elastic–plastic and primary viscoelastic models of material behavior were constructed based on a series of homogeneous deformed-state experiments. The viscoelastic model of material behavior was refined using data from dynamic mechanical analysis over a wide temperature range [−40; +80] °C. In the first approximation, a model of the deformation theory of plasticity with linear elastic volumetric compressibility was identified. As a second approximation, a viscoelasticity model for the Maxwell body was constructed using Prony series. It was established that the viscoelastic model of the material allows for obtaining data on the behavior of the part with an error of no more than 15%. The numerical analog of the construction in an axisymmetric formulation can be used for the predictive analysis of the behavior of the bearing, including when changing the geometric configuration. Recommendations for the numerical modeling of the behavior of antifriction layer materials and the coupling pattern of the bearing elements are given in this work. A spherical bearing with an antifriction interlayer made of Arflon series material is considered for the first time. Full article

Insects use chemical compounds to communicate with conspecifics and other organisms. The corn leafhopper, Dalbulus maidis (Hemiptera: Cicadellidae) (DeLong & Wolcott), is an important pest in Brazilian maize crops due to its role as a vector of phytopathogens. Despite its economic importance, the chemical communication between sexes in this species remains to be elucidated. This research aimed to unveil whether D. maidis produces chemical compounds that influence the behavior of the opposite sex and may act as sex pheromones. To evaluate the influence of these volatiles, olfactometer bioassays were conducted as dynamic headspace volatile collections from live insects. Results showed that both male and female leafhoppers emit volatile compounds; however, no sex-specific compounds were detected. Females were attracted to male odors and male aeration extracts, suggesting males produce sex-specific volatiles. Interestingly, males avoided odors from non-acclimated females, which may indicate possible alarm pheromone release. Although the compounds were not identified, this is the first study to demonstrate intraspecific chemical communication in D. maidis mediated by volatiles, and the first such record in Membracoidea. These results contribute to understanding the pest’s biology and support the development of monitoring and control strategies in maize crops. Full article

RNA-targeting techniques have emerged as powerful tools in cancer research and therapeutics, offering precise and programmable control over gene expression at the post-transcriptional level. Once viewed as passive intermediates in the central dogma, RNA molecules are now recognized as dynamic regulators of cellular function, capable of influencing transcription, translation, and epigenetic regulation. Advances in high-throughput sequencing technologies, transcriptomics, and structural RNA biology have uncovered a diverse landscape of coding and non-coding RNAs involved in oncogenesis, drug resistance, and tumor progression. In response, several RNA-targeting strategies have been developed to modulate these transcripts, including antisense oligonucleotides (ASOs), RNA interference (RNAi), CRISPR-Cas13 systems, small molecules, and aptamers. This review provides a comparative analysis of these technologies, highlighting their molecular mechanisms, therapeutic potential, and current limitations. Emphasis is placed on the translational progress of RNA-targeting agents, including recent FDA approvals and ongoing clinical trials for cancer indications. Through a critical comparison of these strategies, this review underscores the growing significance of RNA-targeting technologies as a foundation for next-generation cancer therapeutics and precision oncology. Full article

Origin–destination (OD) passenger flow is a critical variable for metro system planning and operation. While numerous studies have investigated the influence of the built environment on passenger flow, most have focused on ingress or egress flows at metro stations. The impact of the built environment on OD flow dynamics, particularly the differences between origin-side and destination-side effects, remains poorly understood. This study proposes a novel method for exploring the non-linear effects of station-area built environments on OD flow in large-scale metro networks. First, hourly OD flows and station-area built environment features were extracted from multi-source data. Next, an analytical framework was developed to model the built environment–OD flow relationship using a gradient boosting decision tree model. Finally, the contributions of built environment variables and their non-linear effects on OD flows were systematically investigated. The proposed method was implemented on the Suzhou metro network in China. Test results show that most built environment variables exhibit time-varying, non-linear correlations with OD flows. Even the same variable demonstrates notable differences in its effect between the origin and destination sides. The findings of this study provide valuable guidance for metro planning and station-area urban development. Full article

To address the complex operating conditions and challenging dynamic characteristics of bearings in the main shaft transmission system of wind turbines, this study investigates a specific wind turbine model. By comprehensively considering factors such as main shaft structure, cumulative damage, and stochastic wind loads, we adopt a modular analysis framework integrating the wind field, aerodynamics, the structural response, and fatigue life prediction to establish a method for predicting the fatigue life of main shaft bearings under stochastic wind conditions. To verify this method, the fixed-end main shaft bearing of a 4.5 MW wind turbine was selected as a case study. The research results show the following: (1) Increases in both average wind speed and turbulence intensity significantly shorten the fatigue life of the bearing. (2) Higher turbulence intensity amplifies the dispersion of the speed and load of rolling elements, thereby increasing the probability of extreme operating conditions and exerting an adverse impact on fatigue life. (3) The average wind speed has a significant influence on the overall fatigue life: within a specific range, the fatigue failure probability of the main bearing increases as the average wind speed decreases. (4) The impact of wind speed fluctuations on the hub center load is much greater than that caused by rotational speed changes. (5) In addition, the modular design method adopted in this study calculates that the fatigue life of the fixed-end bearing is 28.8 years, with an overall error of only 0.8 years compared to the 29.6-year fatigue life obtained using Romax simulation software. This research provides important theoretical references and engineering value for improving the operational reliability of wind turbines and enhancing the accuracy of bearing fatigue life prediction. Full article

Aroma volatiles constitute the primary molecular basis of fruit flavor quality, governing sensory attributes and marketability. Based on their chemical states, aroma compounds are categorized into bound and free forms. Bound aroma compounds predominantly exist as non-volatile glycosides, which can be hydrolyzed enzymatically or through acid treatment to release volatile free aroma compounds, thereby enhancing fruit fragrance. Although the dynamic interconversion between free and bound aroma compounds is pivotal for fruit flavor development, the governing mechanisms, including the principal controlling factors, regulatory networks, and external influences, are still under investigation. This review primarily synthesizes recent advances regarding the structural diversity, analysis, biosynthesis, and regulation of bound aroma compounds. Additionally, it examines how key regulatory networks and environmental factors modulate the synthesis and transformation of these compounds. The integrated overview provides new insights for future regulation of aroma metabolism in fruits. Full article

Nitrogen is a critical nutrient that influences plant growth and resistance to pathogens; however, its impact on disease dynamics, particularly downy mildew infection, and the associated physiological responses in cucumber during early growth stages remains poorly understood. To evaluate the combined effects of downy mildew (caused by Pseudoperonospora cubensis) infection and nitrogen application on cucumber growth and physiological traits during the seedling and vine development stages, two downy mildew treatments— infected (B0) and non-infected(B1)—and three nitrogen levels—T1 (N-50%), T2 (N-100%), and T3 (N-150%)—were applied. Significant differences were observed between all treatments (p < 0.05). Among them, the B1T3 treatment had the most pronounced stimulatory effect, particularly on growth parameters (such as plant height, stem diameter, and leaf area). Without any disease infection (B1), the B1T2 treatment showed an increasing trend in photosynthetic rate and a more notable rise in stomatal conductance. In contrast, with downy mildew infection (B0), photosynthetic rates declined under B0T1 and B0T2. Moreover, with downy mildew infection (B0), the intracellular CO₂ concentration, stomatal conductance, and transpiration rate of cucumber leaves decreased in the B0T1, B0T2, and B0T3 treatments. Plant height, stem diameter, and leaf area responded variably to nitrogen levels and downy mildew infection. The total root length, root surface area, average root diameter, total root volume, and total root tips of cucumber plants were significantly different under different experimental conditions (p < 0.05). Consequently, this study provides a theoretical basis for stress-resistant cucumber cultivation in greenhouses and has practical implications for advancing the sustainable development of the greenhouse cucumber industry. Full article

With the rise in rural tourism, public space use has become more complex, causing significant weekday-weekend vitality imbalances. However, the factors shaping these dynamics in traditional villages remain unclear. This study uses Wi-Fi sensing method to analyze vitality variations across weekdays and weekends, and it develops a 13-metric evaluation framework to examine how built environment factors, from both internal and external dimensions, differentially influence the vitality of public spaces in traditional villages across various time periods. Using 17 public spaces in Yantou Village, Lishui, China, as a case, it finds: (1) Historical Element Proximity consistently and significantly drives public space vitality across all periods; (2) Leisure Facility Count and Decorative Element Count demonstrate strong positive effects during weekend morning peaks. (3) Retail Facility Count significantly reduces vitality during weekend morning peak but enhances it during midday off-peak, whereas Street Vendor Count shows the opposite pattern—increasing vitality in morning peak and decreasing it in midday off-peak. Using Wi-Fi sensing’s high-resolution, real-time, and non-invasive capabilities, this study provides a scientific method to accurately assess the variations in public space vitality and their impact factors between weekdays and weekends in traditional villages, offering technical support for enhancing public space vitality and sustainably revitalizing rural heritage. Full article