Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots.

Most problems within and beyond the scientific domain can be framed into one of the following three levels of complexity of function approximation. Type 1: Approximate an unknown function given input/output data. Type 2: Consider a collection of variables and functions, some of which are unknown, indexed by the nodes and hyperedges of a hypergraph (a generalized graph where edges can connect more than two vertices). Given partial observations of the variables of the hypergraph (satisfying the functional dependencies imposed by its structure), approximate all the unobserved variables and unknown functions. Type 3: Expanding on Type 2, if the hypergraph structure itself is unknown, use partial observations of the variables of the hypergraph to discover its structure and approximate its unknown functions. These hypergraphs offer a natural platform for organizing, communicating, and processing computational knowledge. While most scientific problems can be framed as the data-driven discovery of unknown functions in a computational hypergraph whose structure is known (Type 2), many require the data-driven discovery of the structure (connectivity) of the hypergraph itself (Type 3). We introduce an interpretable Gaussian Process (GP) framework for such (Type 3) problems that does not require randomization of the data, access to or control over its sampling, or sparsity of the unknown functions in a known or learned basis. Its polynomial complexity, which contrasts sharply with the super-exponential complexity of causal inference methods, is enabled by the nonlinear ANOVA capabilities of GPs used as a sensing mechanism.

Optimization of turbidity removal and floc formation for ballasted flocculation using magnetite-based agents by response surface methodology.

In this study, a static mixer was used as an alternative to the existing flash mixing method for ballasted flocculation to assess the turbidity removal and ballasted floc formation characteristics. Synthetic magnetite exhibits excellent properties, such as high specific gravity, hydrophobicity, and wear resistance, making it a suitable ballast agent (BA). The experimental design was optimized using the response surface methodology. To evaluate turbidity removal, a model based on polyaluminum chloride dosage, BA surface charge, and pH was developed. To assess the ballasted floc characteristics, the BA dosage, BA size, and G value of the static mixer were used. During ballasted flocculation, the impact of the zeta potential of the BA was minimal. Consequently, bonding primarily resulted from the viscosity of the floc caused by physical collisions rather than electrostatic forces stemming from the BA charge. The findings of this study demonstrated promising outcomes, including potential energy savings and process streamlining, by identifying crucial design elements for implementing a static mixer in the ballasted flocculation process.

Use of Statistics in Plant Cell Tissue Culture.

Statistics and experimental design are important tools for plant cell and tissue culture researchers and should be used when planning and conducting experiments as well as during the analysis and interpretation of experimental results. The chapter provides basic concepts important to the statistical analysis of data obtained from plant tissue culture experiments and illustrates the application of common statistical procedures to analyze binomial, count, and continuous data for experiments with different treatment factors as well as identifying trends of dosage treatment factors.

Measuring relational wellbeing: construct validity in pre-COVID-Era UK; generalizability across COVID-lockdown-Era India, Greece, and UK.

Aim: In the present studies, we examine the construct validity and criterion-related validity of a previously unpublished, eight-item measure of relational wellbeing. Methods: First, in two pre-COVID-Era pilot studies within the UK (n's = 207 and 146, respectively), results of exploratory factor analyses revealed that-with the possible exception of one item regarding close relationships-the items assessed individual differences along a single dimension (i.e., relational wellbeing), rather than two distinct dimensions (i.e., social connections and close relationships). Second, in an initial pre-COVID-Era main study within the UK (n = 192), results of confirmatory factor analyses provided support for the hypothesized one-dimensional factor pattern, although the same problematic item from the pilot studies continued to under-perform relative to the other seven items. Findings: In a subsequent COVID-Lockdown-Era main study across India (n = 205), Greece (n = 354), and the UK (n = 390), results of confirmatory factor analyses established that-after omitting the same problematic item that had surfaced in the preceding studies-a one-dimensional factor pattern provided equally satisfactory fit for the three samples. Original value: Although we had not set out to test a priori hypotheses regarding mean similarities or differences in relational wellbeing among our COVID-Lockdown-Era studies, results of an analysis of variance revealed that persons within the UK scored significantly lower in relational wellbeing than did persons in India or Greece. Limitations: As noted above, one particular item repeatedly performed poorly in factor analyses; this item ideally should be dropped from the relational wellbeing scale in future research.

Comparative evaluation of microhardness of three restorative materials after immersion in chlorhexidine mouthwash: An in vitro study.

Aim: To evaluate and compare the microhardness of Filtek Z250XT, Beautifil II, and Neo Spectra ST HV after immersion in chlorhexidine mouthwash. Materials and Methods: Thirty disc specimens (10 for each group) made of three different restorative materials, Group 1 - Filtek (3M ESPE), Group 2 - Beautifil II (Shofu), and Group 3 - Neo Spectra ST HV (Dentsply). To simulate 1 year of daily mouthwash use, 10 specimens from each group were immersed in chlorhexidine, kept in an incubator at 37°C for 12 h, and later subjected to microhardness measurement using Vicker's hardness test. Finally, analysis of variance and post hoc tests were used to analyze the results statistically. Results: A significant reduction in microhardness was observed after immersion in chlorhexidine in Groups 1 and 3 compared to Group 2. Conclusions: Filtek Z250XT exhibits the highest microhardness compared to the other two materials. However, Beautifil II is more resistant to chlorhexidine mouthwash and does not show a significant reduction compared to the other two restorative materials.

Experiment and Analysis of Variance for Stabilizing Fine-Grained Soils with Cement and Sawdust Ash as Liner Materials.

Due to volume change and low strength, fine-grained soils are problematic in construction. Stabilization with cement and sawdust ash (SDA) by-products can improve engineering properties. This study aimed to investigate the effectiveness of cement and sawdust ash (SDA) in stabilizing fine-grained soils for liner applications. Varying proportions of cement (0-9%) and SDA (0-10%) were added to soil samples (n = 24). Specimens were tested for unconfined compressive strength (UCS), hydraulic conductivity (HC), and volumetric shrinkage strain (VSS). Two-way ANOVA analyzed stabilization effects. Optimal stabilization occurred with 6% cement and 6% SDA, resulting in significant increases in UCS (51 to 375 kN/m2) and decreases in HC (1.7 × 10-8 to 4.7 × 10-10 m/s) and VSS (12.8 to 3.51%) compared to untreated soil. ANOVA indicated that both cement and SDA had statistically significant (p < 0.05) effects on improving all three engineering properties. The addition of 6% cement and 6% SDA significantly improved the expansive soil's strength, hydraulic conductivity, and volume change properties. ANOVA confirmed the quantitative improvements and the significance of both stabilizers. Stabilization using the by-product SDA has the potential to be a sustainable soil improvement method.

Changes in Black Truffle (Tuber melanosporum) Aroma during Storage under Different Conditions.

The enticing aroma of truffles is a key factor for their culinary value. Although all truffle species tend to be pricy, the most intensely aromatic species are the most sought after. Research into the aroma of truffles encompasses various disciplines including chemistry, biology, and sensory science. This study focusses on the chemical composition of the aroma of black truffles (Tuber melanosporum) and the changes occurring under different storage conditions. For this, truffle samples were stored under different treatments, at different temperatures, and measured over a total storage time of 12 days. Measurements of the truffle aroma profiles were taken with SPME/GC-MS at regular intervals. To handle the ample data collected, a systematic approach utilizing multivariate data analysis techniques was taken. This approach led to a vast amount of data which we made publicly available for future exploration. Results reveal the complexity of aroma changes, with 695 compounds identified, highlighting the need for a comprehensive understanding. Principal component analyses offer initial insights into truffle composition, while individual compounds may serve as markers for age (formic acid, 1-methylpropyl ester), freshness (2-Methyl-1-propanal; 1-(methylthio)-propane), freezing (tetrahydrofuran), salt treatment (1-chloropentane), or heat exposure (4-hydroxy-3-methyl-2-butanone). This research suggests that heat treatment or salt contact significantly affects truffle aroma, while freezing and cutting have less pronounced effects in comparison. The enrichment of compounds showing significant changes during storage was investigated with a metabolomic pathway analysis. The involvement of some of the enriched compounds on the pyruvate/glycolysis and sulfur pathways was shown.

Understanding Factorial Designs, Main Effects, and Interaction Effects: Simply Explained with a Worked Example.

A factorial design examines the effects of two independent variables on a single, continuous dependent variable. The statistical test employed to analyze the data is a two-way analysis of variance (ANOVA). This test yields three results: a main effect for each of the independent variables and an interaction effect between the two independent variables. This article explains factorial designs and two-way ANOVA with the help of a worked example using hypothetical data in a spreadsheet provided as a supplementary file. The main effects and interaction effects are explained and illustrated using tables and figures. A short discussion provides general notes about the concepts explained in this article, along with brief notes on repeated measures ANOVA and higher order ANOVAs. Many additional examples, with figures and explanations, are provided in the supplementary materials, which the reader is strongly encouraged to view.

Insights into "wheat aroma": Analysis of volatile components in wheat grains cultivated in saline-alkali soil.

The wheat grains that are cultivated in saline-alkali soil exhibit a richer "wheat aroma" compared to their counterparts. This study characterized the composition and content of volatiles in five wheat kernel varieties, harvested from two fields with varying pH levels and total salt content in the soil. The wheat grown in soil with high pH and total salt content had significantly lower levels (p < 0.05) of ethyl 3-methylbutanoate and 1-octen-3-one and significantly higher levels (p < 0.05) of 1-butanol and 1-octen-3-ol. Among all factors, plant site contributed the highest F-value contribution rate (more than 77 %) for these four volatile compounds. Six e-nose sensors responsive to these four compounds exhibited consistent trends. Therefore, the lower of ethyl 3-methylbutanoate and 1-octen-3-one, the higher of 1-butanol and 1-octen-3-ol in wheat, grown on saline-alkali soil, served as characteristic markers for "wheat aroma".

Anti-Drug Antibody Incidence Comparison of Therapeutic Proteins Administered Via Subcutaneous vs. Intravenous Route.

Subcutaneous (SC) administration of therapeutic proteins is perceived to pose higher risk of immunogenicity when compared with intravenous (IV) route of administration (RoA). However, systematic evaluations of clinical data to support this claim are lacking. This meta-analysis was conducted to compare the immunogenicity of the same therapeutic protein by IV and SC RoA. Anti-drug antibody (ADA) data and controlling variables for 7 therapeutic proteins administered by both IV and SC routes across 48 treatment groups were analyzed. RoA was the primary independent variable of interest while therapeutic protein, patient population, adjusted dose, and number of ADA samples were controlling variables. Analysis of variance was used to compare the ADA incidence between IV and SC RoA, while accounting for controlling variables and potential interactions. Subsequently, 10 additional therapeutic proteins with ADA data published for both IV and SC administration were added to the above 7 therapeutic proteins and were evaluated for ADA incidence. RoA had no statistically significant effect on ADA incidence for the initial dataset of 7 therapeutic proteins (p = 0.55). The only variable with a significant effect on ADA incidence was the therapeutic protein. None of the other controlling variables, including their interactions with RoA, was significant. When all data from the 17 therapeutic proteins were pooled, there was no statistically significant effect of RoA on ADA incidence (p = 0.81). In conclusion, there is no significant difference in ADA incidence between the IV and SC RoA, based on analysis of clinical ADA data from 17 therapeutic proteins.

Optimization of cassava peel ash concrete using central composite design method.

Cassava peel ash (CPA) is an abundant agricultural byproduct that has shown promise as an additional cementitious material in concrete manufacturing. This research study aims to optimize the incorporation of CPA in concrete blends using the central composite design (CCD) methodology to determine the most effective combination of ingredients for maximizing concrete performance. The investigation involves a physicochemical analysis of CPA to assess its pozzolanic characteristics. Laboratory experiments are then conducted to assess the compressive and flexural strengths of concrete mixtures formulated with varying proportions of CPA, cement, and aggregates. The results show that a mix ratio of 0.2:0.0875:0.3625:0.4625 for cement, CPA, fine, and coarse aggregates, respectively, yields a maximum compressive strength of 28.51 MPa. Additionally, a maximum flexural strength of 10.36 MPa is achieved with a mix ratio of 0.2:0.0875:0.3625:0.525. The experimental data were used to develop quadratic predictive models, followed by statistical analyses. The culmination of the research resulted in the identification of an optimal concrete blend that significantly enhances both compressive and flexural strength. To ensure the reliability of the model, rigorous validation was conducted using student's t-test, revealing a strong correlation between laboratory findings and simulated values, with computed p-values of 0.9987 and 0.9912 for compressive and flexural strength responses, respectively. This study underscores the potential for enhancing concrete properties and reducing waste through the effective utilization of CPA in the construction sector.

Experimental investigation on punch shear strength of poly lactic acid specimens for biomedical applications.

The designed biomedical implants require excellent shear strength primarily for mechanical stability against forces in human body. However, metallic implants undergo stress shielding with release of toxic ions in the body. Thus, Fused Deposition Modeling (FDM) has made significant progress in the biomedical field through the production of customized implants. The mechanical behavior is highly dependent on printing parameters, however, the effect of these parameters on punch shear strength of ASTM D732-02 standard specimens has not been explored. Thus, in the current study, the effect of infill density (IFD), printing speed (PTS), wall thickness (WLT), and layer thickness (LYT) has been investigated on the punch shear strength using Response Surface Methodology. The Analysis of Variance (ANOVA) has been performed for predicting statistical model with 95% confidence interval. During the statistical analysis, the terms with p-value lower than 0.05 were considered significant and the influence of process parameters has been examined using microscopic images. The surface plots have been used for discussing the effect of interactions between printing parameters. The statistical results revealed IFD as the most significant contributing factor, followed by PTS, LYT, and WLT. The study concluded by optimization of printing parameters for obtaining the highest punch shear strength.

Comparison of industrial engineering programs in Colombia based on standardized test results.

This study aims to evaluate the performance of industrial engineering programs across various Higher Education Institutions (HEIs) in Colombia, focusing on the SaberPRO test outcomes from 2016 to 2018. The evaluation considers three primary dimensions: the type of funding (public vs. private HEIs), geographical region, and program accreditation status. The methodology involved gathering and analyzing Saber Pro test results from students enrolled in industrial engineering programs at 82 Colombian HEIs during the specified period. In Colombia, the SaberPRO Exam, administered by the Colombian Institute for the Evaluation of Education (ICFES), is a critical measure for assessing the quality of future industrial engineering graduates. This research employs an analytical framework that includes Analysis of Variance (ANOVA) and hypothesis testing for mean comparisons to scrutinize the performance of these programs. Findings reveal notable disparities in performance between public and private institutions and between accredited and non-accredited programs. Additionally, through Multiple Factor Analysis (MFA), the study identifies the competencies with the highest discriminative capacity, recognizing 15 exemplary programs out of the 82 evaluated.

The impact of prior care experience on nursing students' compassionate values and behaviours: A mixed methods study.

BACKGROUND: Compassion is critical to the provision of high-quality healthcare and is foregrounded internationally as an issue of contemporary concern. Paid care experience prior to nurse training has been suggested as a potential means of improving compassion, which has been characterised by the values and behaviours of care, compassion, competence, communication, courage, and commitment. There is however a dearth of evidence to support the effectiveness of prior care experience as a means of improving compassion in nursing. OBJECTIVE: To explore the impact of paid prior care experience on the values and behaviours of pre-registration nursing students indicated as characterising compassionate care. DESIGN: Longitudinal mixed methods design employing a modified concurrent triangulation strategy, comprising two work packages. Work package 1 was qualitative, and work package 2 adopted a concurrent embedded strategy with a dominant quantitative component. Research is reported in accordance with the Good Reporting of a Mixed Methods Study framework. SETTING(S): Three United Kingdom universities. PARTICIPANTS: Pre-registration nursing students attending one of three universities, and individuals who had previously participated in a Health Education England paid prior care experience pilot. Participant numbers at time point 1 were questionnaires n = 220, telephone interviews n = 10, and focus groups n = 8. METHODS: Work package 1 consisted of longitudinal semi-structured telephone interviews. Work package 2 comprised validated online questionnaires measuring emotional intelligence, compassion satisfaction and fatigue, resilience, psychological empowerment, and career commitment (as proxies of compassionate values and behaviours), and focus groups. Qualitative data were thematically analysed. Quantitative data were analysed via Analysis of Variance in SPSS v 26. RESULTS: Qualitative findings suggest that prior care experience has both positive and negative effects on students' compassionate values and behaviours, however positive effects do not extend to qualification. No statistically significant differences were found in any of the quantitative outcome measures between participants with and without paid prior care experience. A statistically significant increase in compassion fatigue was identified in both groups of participants post-qualification. Paid prior care experience did not prevent participants from experiencing reality shock on becoming a student or on qualification. CONCLUSIONS: There is insufficient evidence of longitudinal beneficial impact to recommend paid prior care experience as an effective intervention to foster nursing students' compassionate values and behaviours. These findings do not support mandating a period of paid care experience as a prerequisite for entry into nurse education. REGISTRATION: N/A. Tweetable abstract Insufficient evidence of longitudinal beneficial impact to recommend prior care experience as an effective intervention to foster nursing student compassion @PriorCareExp @Sarah_F_R.

Application of analysis of variance to determine important features of signals for diagnostic classifiers of displacement pumps.

This paper presents the use of one-way analysis of variance ANOVA as an effective tool for ranking the features calculated from diagnostic signals and evaluates their impact on the accuracy of the machine learning system's classification of displacement pump wear.The first part includes a review of contemporary diagnostic systems and a description of typical damage of multi-piston displacement pumps and Its causes. The work also contains description of a diagnostic experiment which was conducted in order to obtain the matrix of vibration signals and the matrix of pressures measured at selected locations on the pump housing and at the pump pressure line. The measured signals were subjected to time-frequency analysis. The features of signals calculated in the time and frequency domains were ranked using the ANOVA. The next step involved the use the available classifiers in pump wear evaluation, conducting tests and assessing their effectiveness in terms of the ranking of features and the origin of diagnostic signals.

Role of Magnetic Resonance Imaging in the Evaluation of Age- and Gender-Related Changes in the Dimensions of the Pituitary Gland in the Indian Population.

Background MRI is the standard tool for imaging the pituitary gland. MRI is useful in detecting pathological conditions in the pituitary. Changes in the size and shape of the pituitary among different age groups are seen in MRI. Linear growth is seen in the pituitary during puberty except for growth spurts at the 1st, 10th, and 15th years, followed by a decline in pituitary height and cross-sectional area with increasing age. A convex upper margin was seen in females more than in males. There is a shortage of information about pituitary dimensions and volume in various age groups and among both genders in the Indian population. Hence, a study is needed to assess these parameters. Materials and methods A retrospective cross-sectional study was done in the MRI unit of Radiology, Saveetha Medical College and Hospital, Chennai. A total of 200 patients in the age group of 11-80 years who underwent MRI free from neuroendocrine, neurological, and psychiatric disorders were included in this study. Statistical analysis Measurements were made of the pituitary gland's height, volume, and anteroposterior and transverse dimensions. Using SPSS Statistics software (IBM Corp. IBM SPSS Statistics for Windows. Armonk, NY: IBM Corp.), the data was input and examined. The ANOVA test revealed the relationship between anteroposterior dimension, transverse dimension, height, and volume with age. In contrast, an independent t-test determined the association of the same parameters with sex. The Chi-square test was used to assess the association of the shape of the pituitary gland with age and sex. Results Anteroposterior dimension, height, and volume of the pituitary gland were found to be statistically significant with age (p<0.05), but the transverse dimension was not significant with age (p>0.05). However, the independent t-test showed highly significant differences between the anteroposterior dimension in males and females. The shape of the pituitary gland was found to be statistically significant with age and gender. In contrast, the pituitary gland's transverse diameter, height, and volume showed no significance. Conclusion The study helps identify the substantial changes in the pituitary gland during a person's lifespan, which are affected by age and gender. The pituitary height and volume will reflect physiological neuroendocrine differences between younger and older male and female subjects.

Insitu synthesis of Al- MgAl2O4 composites and parametric optimization of tribological characteristics.

In this research, multiobjective optimization of tribological characteristics of Al-4Mg/in-situ MgAl2O4 composites fabricated via ultrasonic cavitation treatment assisted stir casting technique was carried out. Al-4Mg alloy dispersed with 0.5, 1 and 2 wt% in-situ MgAl2O4 was prepared and the microstructural and mechanical characterisation of the same has been carried out. Reinforcement addition, load and sliding velocity at 3 different levels was considered to attain the responses wear rate and friction coefficient. To identify optimised process condition for the developed composites to attain reduced friction coefficient and wear rate condition, grey analysis is tried out. Experimental results analysed via Grey relation and analysis of variance (ANOVA) proved wt.% of MgAl2O4 particles as significant parameter trailed by load and speed. Based on grey relational grade, minimal wear loss at lowest frictional coefficient can be attained for the composite dispersed with 2 wt% of in-situ MgAl2O4 at 20 N load and 2 m/s sliding velocity. Mechanisms behind the wear loss was analysed from worn out surface micrographs.

Using a centered general linear model for detection of interactions among biomarkers.

The dummy variable based general linear model (gLM) is commonly used to model categorical factors and their interactions. However, the main factors and their interactions in a general linear model are often correlated even when the factors are independently distributed. Alternatively, the classical two-way factorial analysis of variance (ANOVA) model can avoid the correlation between the main factors and their interactions when the main factors are independent. But the ANOVA model is hardly applicable to a regular linear regression model especially in the presence of other covariates due to constraints on its model parameters. In this study, a centered general linear model (cgLM) is proposed for modeling interactions between categorical factors based on their centered dummy variables. We show that the cgLM can avoid the correlation between the main factors and their interactions as the ANOVA model when the main factors are independent. Meanwhile, similar to gLM, it can be used in regular regression and fitted conveniently using the standard least square approach by choosing appropriate baselines to avoid constraints on its model parameters. The potential advantage of cgLM over gLM for detection of interactions in model building procedures is also illustrated and compared via a simulation study. Finally, the cgLM is applied to a postmortem brain gene expression data set.

Safety climate in Pakistani universities' laboratories: an assessment of individual factors.

Objectives. Current research aims to identify factors that affect the occupational safety climate in university laboratories despite their perception as low-risk areas compared to industrial environments. Methods. A safety climate survey was conducted in science laboratories across various engineering universities in Pakistan. The survey questionnaire was administered to 406 personnel, and a quantitative method for analysis was selected to examine the socio-demographic variables. A 5-point Likert scale (1 = strongly disagree to 5 = strongly agree) was used to perceive responses from participants. Additionally, a scale reliability test was conducted, and multivariate analysis of variance was performed to determine the relationship between selected dependent and independent variables. Results. The study found an overall safety climate score of 3.16 ± 0.55, indicating a moderate to high perception of safety on a scale of 1-5. Parameters such as role in the laboratory, departments/disciplines, accident experience and safety training significantly affected the safety climate score, while gender, age group, duration in university and accident witnessing did not. Conclusion. Upper management involvement, safety communication and direct supervision are crucial for improving the safety climate of university laboratories. The study recommends the consideration of the identified significant safety climate dimensions in laboratory safety policy-making at academic institutes.

Field Measurement and Analysis on the Mechanical Response of Asphalt Pavement Using Large-Particle-Size Crushed Stone Base Treated with Fly Ash and Slag Powder.

The mechanical response of asphalt pavement under vehicular loading is an essential reference for crack-resistant pavement design. However, limited research focuses on the mechanical response measurement of asphalt pavement using a large-particle-size crushed stone base treated with fly ash and slag powder. Therefore, two types of asphalt pavements were constructed. The first type of asphalt pavement uses a large-particle-size crushed stone base treated with fly ash and slag powder, where the slag powder uses granulated blast furnace slag powder. The second type uses a conventional cement-stabilized crushed stone base and serves as a reference structure. Firstly, the strain gauges and temperature sensors were installed during the construction of asphalt pavements. Secondly, the mechanical response of the pavement was tested at different speeds and service time conditions. Then, sensitivity analysis and three-factor analysis of variance (ANOVA) were carried out. Finally, the prediction equations were developed. The results show that the longitudinal strain pulse of the asphalt layer exhibited a "compression-tension-compression" characteristic. For the transverse strain pulse of the asphalt layer, the base layer's transverse and longitudinal strain pulses were only shown as "tensile" characteristics. The vehicular speed significantly affected the strain values for the base and asphalt layers, showing a decreasing trend with increasing speed. For the asphalt layer, the strain values showed an increasing trend with increasing temperature; for the base layer, the strain values showed a decreasing trend with increasing service time. The type of base layer had a significant effect on the strain value. Compared with the conventional base layer, the large-particle-size crushed stone base treated with fly ash and slag powder had lower strain at the base layer and a lower position of the asphalt layer, which could better prevent bottom-up fatigue cracking. Finally, the strain prediction model of the pavement under the speed and temperature (service time) was fitted to obtain a model that can predict the mechanical response of the pavement under different operating conditions. The findings of this research can provide a reference for the design of asphalt pavement using a large-particle-size crushed stone base treated with fly ash and slag powder.