Secondary Influence Research Articles

Global Patterns of Parental Concerns About Children’s Education: Insights from WVS Data

Parental concerns about the education of children usually reflect deep-seated anxieties. This study identifies the most influential factors shaping these global concerns based on World Values Survey (WVS) data spanning several decades. Using advanced techniques, including feature selection (Adaptive and Gradient Boosting, Pairwise Correlations, LASSO, Bayesian Model Averaging), mixed-effects modeling, cross-validation procedures, different regressions and overfitting, collinearity, and reverse causality checks together with two-way graphical representations, this study identified three enduring predictors: fear of job loss, fear of war, and respondent age. These findings mainly underline the role of socio-economic and geopolitical stability and security and, in addition, that of generational perspectives in shaping global parental priorities. All three predictors were consistent across seven dataset versions, various subsets considering random (ten-folds) or non-random criteria (different values for socio-demographic variables in mixed-effects models), and distinct feature selection approaches. Secondary influences, including opinions regarding the priority of work in life, other fears, and socio-demographic variables (e.g., gender, number of children, marital and professional status, income, education level, community size, etc.) provided more nuances to this study and additional explanatory power. The findings have implications for designing socio-economically sensitive educational policies that address parental priorities and anxieties in diverse global contexts.

Multifactorial Analysis of the Collapse Process of Double Bubbles Based on the Coarse-Grained Force Field in Free Domain.

Cavitation has been a hot research topic for scholars in various fields because of the intense mechanical, chemical, and thermal effects of bubble collapse. It forms a cluster of bubbles, and the bubbles will affect, interfere with, and couple with each other. To grasp the main factors affecting bubble collapse and the interbubble mechanism, the paper adopts the molecular dynamics simulation combined with the coarse-grained force field to study the collapse process of the double bubble model and takes the dynamic shape change of the bubbles, the local velocity distribution, and the local pressure distribution as the object to summarize the position angle, the shock velocity, and the bubble distance on the collapse law and the primary and secondary influence relationship and then reveals the interbubble mechanism. The results show that with the increase of the position angle, the collapse velocity of the right side of bubble A gradually decreases compared with the left side, while bubble B has the opposite characteristics. When the angle is 0°, bubble A and bubble B collapse at the same time and the direction of the jet is the same as the shock direction. With the increase of the position angle, the direction of the jet is biased toward bubble B. The collapse time of bubble B gradually increases with the increase in the bubble distance. Taking the collapse time as the evaluation standard, the relationship between the three factors is shock velocity (u) > position angle (θ) > bubble distance (L). In this paper, it perfects the cavitation theory and provides technical support for the efficient application of hydrodynamic cavitation technology.

Impact of Operational and Financial Efficiency on Aviation Stock Prices: A Machine Learning Model with SHAP Interpretability

Using a machine learning approach, this study examines how operational and financial efficiency metrics influence stock prices in the aviation industry. A CatBoost regression model enhanced with SHapley Additive exPlanations (SHAP) was developed using data from 65 global aviation companies collected between 2015 and 2023. The model predicts stock prices based on various operational and financial indicators, including Total Revenue per Available Seat Mile (ASM), Passenger Load Factor, liquidity ratios, and debt-to-assets ratios. The findings suggest that operational efficiency metrics, particularly Total Revenue per ASM and Passenger Load Factor, play a significant role in predicting stock prices within the aviation sector. Financial metrics, such as the Quick Ratio and Debt-to-Assets Ratio, also contribute to the model but appear to have a secondary influence compared to operational factors. SHAP values provided interpretable insights into the model's predictions, allowing for a better understanding of the relative importance of different features. Furthermore, the study's findings offer support for the semi-strong form of the Efficient Market Hypothesis (EMH), demonstrating that operational and financial metrics are reflected in stock prices. These results indicate that aviation companies demonstrating higher operational efficiency may be better positioned for favorable stock market performance, although financial health remains important. This study contributes to the existing literature by integrating operational and financial metrics into a machine learning framework, offering a comprehensive and interpretable model for stock price prediction in the aviation industry.

Challenges and Strategies for Developing Henan’s Aviation Core Industry Using Entropy Weight and Grey Decision Analysis

As economic globalization progresses, air transport has become increasingly vital to economic development due to its speed and convenience. This study examines the driving forces of airside economic construction across four levels: primary, secondary, derivative, and permanent influences. It explores the dynamic interplay between the aviation industry and airside economic construction. Using the entropy weight method to optimize the grey situation decision-making theory, the paper investigates the development strategies for Henan Province’s airside economy. Results indicate that the H2 area should be prioritized as the key construction zone, achieving the highest effect measurement score of 0.9789. Furthermore, focusing on the development of the tertiary industry or the joint advancement of secondary and tertiary industries in the H2 area yields the most significant economic impact, with effect measurement scores of 0.755 and 0.749, respectively.

On the variability of the site-response parameters of the active rock slope in Brienz/Brinzauls (Switzerland)

Summary Unstable rock slopes, prone to collapse, pose an increasingly severe threat to both people and infrastructures, necessitating effective monitoring for risk mitigation. While many techniques rely on surface displacements to assess slope stability, seismic indicators such as resonant frequency, variations in seismic shear wave velocity, and site amplification offer valuable insights into the structural integrity of the slope, aspects not captured by surface deformation alone. Research has demonstrated that these site-response parameters can serve as monitoring tools to detect precursory signs of failure, such as a drop in resonant frequency and relative seismic velocity prior to collapse. Still, environmental factors like temperature, precipitation, snow melt, earthquakes, and freeze-thaw cycles transiently influence the seismic response. Our main objective is to understand the correlations and drivers between environmental parameters and seismic response, distinguishing between reversible and irreversible changes in dynamic behaviour. Over a five-year monitoring period, we continuously recorded ambient vibration data at the Brienz/Brinzauls landslide and monitored three different site-response parameters (resonant frequency, site amplification, relative seismic wave velocity variation) using enhanced frequency domain decomposition, site-to-reference spectral ratio, and single station ambient vibrations correlation techniques. Our results highlight a long-term increase in site amplification and a long-term decrease in first and second resonant frequencies, indicating ongoing structural weakening. Temperature was found to correlate with seasonal variations of seismic wave velocity with a few day’s time lag. Snow melting and rainfalls exerted a secondary influence, temporarily reducing relative seismic wave velocity during snowmelt and rainfall. Our findings suggest that single-station relative seismic velocity variations are mainly influenced by the shallow sub-surface (depth of about 30 m), limiting its application to study the stability of deep structures.

Sexual Self-Disclosure Styles: Understanding Differences in Discussing Sensitive Sexual Topics with Relationship Partners

ABSTRACT This study explored sexual self-disclosure styles. Using an online self-report survey, participants (n = 428) reported levels of conversational goals, disclosure-related variables, and likelihood to disclose a sexual topic to their romantic partner. Cluster analysis resulted in three distinct styles of sexual self-disclosure. A seasoned self-discloser is experienced and efficacious in their sexual self-disclosures. Relationally constrained disclosers report concern for secondary goals paired with avoidance-related contextual variables. Functional self-disclosers seem to use verbal disclosure as a preferred tool for managing sexual issues in relationships, with less regard for the secondary influences of impression management, identity, and relational goals.

Does the Diffusion Profile Differ Between Botulinum Toxin Type a Formulations? Implications for the Management of Post-Stroke Spasticity.

Botulinum toxin type A is a first-line treatment for post-stroke spasticity, with selective action at nerve endings and minimal effects beyond the injection site. However, concerns about potential adverse reactions due to toxin diffusion and spread can significantly influence physicians' therapeutic decisions in managing post-stroke spasticity. Current evidence shows that while the main formulations of botulinum toxin type A have different molecular weights and sizes, they do not exhibit differing diffusion profiles. Instead, the key factors determining botulinum toxin type A diffusion and spread in post-stroke spasticity management are the dose (i.e., the actual amount of 150 kDa neurotoxin protein injected), dilution, and injection volume. Other injection-related factors, such as the needle gauge and injection speed, have also been suggested to have a secondary influence on botulinum toxin type A diffusion and spread. The needs of patients with post-stroke spasticity may vary, and depending on treatment goals, botulinum toxin type A diffusion and spread can be something to avoid or may offer therapeutic benefits by reaching a greater number of nerve terminals in the target muscle, enhancing the toxin's effect. These factors should be carefully evaluated in spasticity clinics.

Chlorophyll-a and suspended matter variability in a data-scarce coastal-estuarine ecosystem

Analyzing the variability of chlorophyll-a (Chl-a) and total suspended matter (TSM) in estuarine and coastal environments is crucial for understanding ecosystem health, guiding environmental management decisions, and evaluating climate change impacts. Satellite remote sensing offers a powerful tool for this analysis due to its extensive spatial and temporal coverage. Although several algorithms exist for complex coastal and estuarine waters, long-term datasets such as GlobColor's Ocean Color (OC5) and neural network (NN) algorithms are frequently used for robust variability analysis. This study uses the GlobColor NN algorithm to investigate the seasonal and inter-annual variability of Chl-a and TSM in a data-scare region, namely the Meghna estuary in Bangladesh and its adjacent coastal fringe. The other algorithm (i.e. OC5), while offers the longest time series, cannot be used in this region due to the high number of invalid pixels. Therefore, this study examines different environmental factors (i.e. sea surface temperature (SST), photosynthetically active radiation (PAR), rainfall, zonal (ZWC) and meridional (MWC) wind components, and ocean currents) and climatic indices (i.e., El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD)) to understand their influence on the seasonal and inter-annual variability of Chl-a and TSM derived from the GlobColor NN algorithm. Empirical orthogonal function analysis identifies the seasonal signal as dominant in the study region. The seasonal cycle of Chl-a is influenced by factors including MWC, TSM, SST, and rainfall. In contrast, TSM seasonal variations are primarily driven by rainfall and MWC. Post-monsoon Chl-a inter-annual fluctuations are mainly linked to TSM inter-annual variability, with secondary influences from monsoon rainfall and the winter ENSO index. Inter-annual changes in TSM are primarily associated with the winter ENSO index and monsoon rainfall. This research elucidates the primary mechanisms influencing Chl-a and TSM variability in the Meghna estuary and its adjacent coast, thus advancing the understanding of the dynamics in the study region. The information obtained through this study is valuable for scientists, policymakers, and stakeholders involved in the sustainable management of the Meghna estuary and its coastal resources, particularly in the context of climate change.

Process‐Based Modeling of Ecosystem‐Level Monoterpene From a Japanese Larch (Larix kaempferi) Forest

AbstractGlobally, the emission of biogenic volatile organic compounds (BVOC) by plants represents the dominant source of volatile organic compounds emitted to the atmosphere. Monoterpenes, as the major BVOC group, can contribute to forming secondary organic aerosols and influence cloud properties. In this study, we developed a process‐based monoterpene module in the Vegetation Integrative SImulator for Trace gases (VISIT) model by considering the production, storage, and emission of monoterpene as three main processes. We further evaluated the modeled monoterpene emissions against the ecosystem‐level observation data at a half‐hour scale at a Japanese larch (Larix kaempferi) forest site on Mt. Fuji, Japan. The VISIT model performed with relatively higher accuracy with a Willmott's index of agreement at 0.61, a mean bias error (MBE) at 0.29, and a root mean squared error (RMSE) at 0.43, comparable to that of Model of Emissions of Gases and Aerosols from Nature model with a Willmott's index of agreement at 0.63, a MBE at 0.40, and a RMSE at 0.54. In a long‐term simulation under high CO2 emission scenarios, the ratio between monoterpene emission and gross primary production exhibited a stronger correlation with CO2 concentration than temperature. Our study provides a process‐based modeling approach for more accurately simulating monoterpene emissions from Japanese larch.

Ecosystem Size Drives Patterns and Control Mechanisms of Mixotrophs Success Across Tropical Lakes: A Large-Scale Assessment of the Grand Écart Hypothesis

Mixotrophy, a physiological trait combining autotrophy and heterotrophy in one organism, significantly contributes to energy and matter transfer in aquatic ecosystems. However, understanding how environmental factors influence mixoplankton success across freshwater ecosystems has been uncertain. The grand écart hypothesis (GEH) posits that light and nutrient availability are key components of mixotrophs' niche, suggesting that ecosystem properties determine opposing gradients of light and nutrients, creating environmental filtering for mixotrophs. We hypothesized that ecosystem size, a property of lake ecosystems, mediates the prevalence of patterns and control mechanisms predicted by the GEH on mixoplankton relative biomass (MRB). Using data from 98 tropical lakes, we demonstrated that lake size mediates the inverse relationship between light and nutrient availability across ecosystems. Larger lakes have more light but low nutrients, while smaller lakes have more nutrients but greater shading. Light availability better explains MRB in small lakes, and nutrients better explain MRB in large lakes, with MRB values being higher in small lakes, with secondary influence from zooplankton herbivory. Our results validate the GEH as a significant framework for explaining patterns and control mechanisms of mixoplankton across tropical lakes. This study highlights the significance of lake size as an ecosystem property that generates opposing light and nutrient gradients, further emphasizing its importance for understanding mechanisms regulating freshwater phytoplankton community structure and functioning. Integrating lake size within the conceptual framework of the GEH could aid in explaining mixoplankton success over macroecological scales.

Analysis and Optimization of Multi-Physical Field Coupling in Boom Flow Channel of Excavator Multiway Valves

The multiway valve is the core control element of the hydraulic system in construction machinery, such as excavators. Its complex internal structure, especially the flow channels, significantly impacts the machine’s efficiency and reliability. This study focuses on the boom flow channel of excavator multiway valves and establishes a multi-physical field coupling simulation model. We propose six key flow channel structural parameters and analyze changes in the valve’s flow field, temperature field, and structural field using orthogonal test simulation data. The range analysis method identifies the primary and secondary influences of structural parameters on pressure loss, temperature, stress, and strain. A multi-objective optimization model was developed using a neural network and the Non-dominated Sorting Genetic Algorithm II(NSGA-II), with pressure loss and maximum stress as the optimization objectives. The Pareto front solution set for key flow channel parameters was calculated. The optimization results showed a 9.0% reduction in pressure loss and a 40.7% reduction in maximum stress. A test bench verified the simulation model, achieving prediction accuracies of 94.8% for pressure loss in the inlet area and 92.3% in the return area. This method can provide a reference for the optimal design of the dynamic characteristics of high-pressure multiway valves.

P13-19 Development of a thymidylate synthase assay to investigate a genotoxicity risk arising from adverse secondary pharmacology and influence drug design

P13-19 Development of a thymidylate synthase assay to investigate a genotoxicity risk arising from adverse secondary pharmacology and influence drug design

Groundwater Dynamics in African Endorheic Basins in Arid to Semi-Arid Transition Zones: The Batha Aquifer System, NE Chad

This study investigates the Batha endorheic basin in Chad, situated east of the Lake Chad basin in the arid to semi-arid Sahelian zone. This region has not yet undergone comprehensive geological and hydrogeological studies. More broadly, the transition zone between semi-arid and arid climates has been minimally explored. This research aims to evaluate the resources and dynamics of this multi-layered system using a combined geology-hydrogeology-hydrochemistry-isotopes approach. The multilayer system includes sedimentary layers (Quaternary, Pliocene, and Eocene) over a crystalline basement. A piezometric investigation of the system shows a general SE–NW groundwater, indicating an interconnection between all layers. Hydrochemical analyses identifies four main facies (calcium-bicarbonate, sodium-bicarbonate, sulphate-sodium, and mixed), primarily controlled by water–rock interaction with secondary influences from base-exchange and evaporation. Saturation indices indicate that these waters are close to equilibrium with the calcite-Mg phases, gaylussite and gypsum. Stable isotopes (oxygen-18 and deuterium) categorize groundwater into three groups: ancient water, recent and older meteoric water mixtures affected by evaporation, and mixtures more heavily impacted by evaporation. Tritium contents reveal three groups: current rainwater, modern water, and sub-modern water. These results indicate that ionic and isotopic differentiations cannot be strictly linked to specific layers, confirming the interconnected nature of the Batha system. The observed heterogeneity is mainly influenced by lithological and climatic variations. This study, though still limited, enhances significantly the understanding of the basin’s functioning and supports the rational exploitation of its vital resources for the Batha area’s development. Future investigations to complete the present study are highlighted.

Decoupling of carbon burial from productivity in the northeast Indian Ocean

The concentration of atmospheric carbon dioxide (CO2) is a crucial climate parameter as it has far-reaching implications on global temperature. The oceans are a significant sink for CO2. Biologically mediated carbon sequestration, in the form of both inorganic (CaCO3) and organic carbon (Corg), and its subsequent burial in marine sediments play a vital role in regulating atmospheric CO2. Understanding the distribution of carbon in marine sediments under different environments can help predict the fate of excess CO2 in the future. We studied the factors affecting the basin scale variation in carbon burial in the climatically sensitive northeast Indian Ocean, by using the data [CaCO3, Corg, Corg/Nitrogen, and isotopic ratio (δ13C, δ15N) of organic carbon] from a total of 718 surface sediments. The entire continental shelf and slope contain <10 % CaCO3. The highest CaCO3 is in the deepest parts of the central northeast Indian Ocean, away from the mouth of major river systems. Despite of the high productivity, the low Corg on the continental shelf is attributed to the well-oxygenated coarse-grained sediments. The lowest Corg is found in the well-oxygenated deeper central northeast Indian Ocean. Interestingly, the highest total carbon is in the deeper central and equatorial regions, far away from the highly productive marginal marine regions. Our study reveals that the grain size, terrigenous dilution, dissolved oxygen, and water masses strongly influence carbon accumulation in the northeast Indian Ocean, with only secondary influence of the productivity.

Controls on Li partitioning and isotopic fractionation in inorganic calcite

The δ7Li of marine carbonates has been interpreted as an archive of the evolution of seawater δ7Li, and therefore continental weathering, through geological time. However, little is known about the incorporation of Li into calcium carbonate minerals and, consequently, the controls on Li partitioning (DLi) and isotopic fractionation (Δ7Lisolid-fluid) associated with Li incorporation. Crucially, we lack a fundamental understanding of how Li partitioning and Δ7Lisolid-fluid change in response to the chemical and physical conditions of crystal formation. Here, we present DLi and Δ7Lisolid-fluid data from a series of inorganic calcite precipitation experiments where temperature, and solution pH and dissolved inorganic carbon (DIC) were independently varied. We find DLi values in the range 0.8–1.5 × 10−3, which show no relationship with temperature, a strong positive correlation with pH, and a weak positive correlation with DIC. At face value, these patterns are inconsistent with the results of previous precipitation studies. However, the correlations with pH and DIC are consistent with a strong precipitation rate control on DLi that aligns well with previous data, with a likely secondary influence from the incorporation of Li-HCO30 ion pairs from solution. We find Δ7Lisolid-fluid values in the range −6 to −2 ‰, which show no relationship with temperature or pH, and a weak positive correlation with DIC and crystal precipitation rate. These results do not agree with previously published data. Considered alongside previously published data, we observe no consistent relationship between Δ7Lisolid-fluid and any reported physical or chemical experimental parameter, highlighting the need for substantial further work to determine whether systematic controls on Li isotopic fractionation exist in carbonate minerals, and whether they may be environmentally significant.

Forest floor environment overrules global change treatment effects on understorey communities in a mesocosm experiment.

Light availability profoundly influences plant communities, especially below dense tree canopies in forests. Canopy disturbances, altering forest floor light conditions, together with other environmental changes such as climate change, nitrogen deposition and legacy effects from previous land-use will simultaneously impact forest understorey communities. Yet, knowledge on the individual effects of these drivers and their potential interactions remains scarce. Here we performed a forest mesocosm experiment to assess the influence of warming, illumination (simulating canopy opening), nitrogen deposition and soil land-use history (comparing ancient and post-agricultural forest soil) on understorey community composition trajectories over a 7-year period. Strikingly, understorey communities primarily evolved in response to the deeply shaded ambient forest conditions, with experimental treatments exerting only secondary influences. The overruling trajectory steered all mesocosms towards slow-colonizing forest specialist communities dominated by spring geophytes with lower nutrient-demand. The illumination treatment and, to a lesser extent, warming and agricultural land-use legacy slowed down this trend by advancing fast-growing resource-acquisitive generalist species. Warm ambient temperatures induced thermophilization of plant communities in all treatments, including control plots, towards higher dominance of warm-adapted species. Nitrogen addition accelerated this thermophilization process and increased the community light-demand signature. Land-use legacy effects were limited in our study. Our findings underscore the essential role of limited light availability in preserving forest specialists in understorey communities and highlight the importance of maintaining a dense canopy cover to attenuate global change impacts. It is crucial to integrate this knowledge in forest management adaptation to global change, particularly in the face of increasing demands for wood and wood products and intensified natural canopy disturbances.

Temperate trees locally engineer decomposition and litter-bound microbiomes through differential litter deposits and species-specific soil conditioning.

Leaf decomposition varies widely across temperate forests, shaped by factors like litter quality, climate, soil properties, and decomposers, but forest heterogeneity may mask local treeinfluences on decomposition and litter-associated microbiomes. We used a 24-yr-old common garden forest to quantify local soil conditioning impacts on decomposition and litter microbiology. We introduced leaf litter bags from 10 tree species (5 arbuscular mycorrhizal; 5 ectomycorrhizal) to soil plots conditioned by all 10 species in a full-factorial design. After 6 months, we assessed litter mass loss, C/N content, and bacterial and fungal composition. We hypothesized that (1) decomposition and litter-associated microbiome composition would be primarily shaped by the mycorrhizal type of litter-producing trees, but (2) modified significantly by underlying soil, based on mycorrhizal type of the conditioning trees. Decomposition and, to a lesser extent, litter-associated microbiome composition, were primarily influenced by the mycorrhizal type of litter-producing trees. Interestingly, however, underlying soils had a significant secondary influence, driven mainly by tree species, not mycorrhizal type. This secondary influence was strongest under trees from the Pinaceae. Temperate trees can locally influence underlying soil to alter decomposition and litter-associated microbiology. Understanding the strength of this effect will help predict biogeochemical responses to forest compositional change.

Optimization of Cohesive Parameters in the Interfacial Transition Zone of Rubberized Concrete Based on the Response Surface Method.

Rubber concrete has been applied to a certain extent in fatigue-resistant structures due to its good durability. Based on a cohesive model of rubber composed of a five-phase material containing mortar, aggregate, rubber, aggregate-mortar interfacial transition zone (ITZ), and rubber-mortar ITZ, this paper studies the influence of the cohesive parameters in the rubber-mortar ITZ on the fatigue problem of rubber concrete on the mesoscopic scale. As the weak part of cement-based composite materials, the ITZ has a great influence on the mechanical properties and durability of concrete, but the performance of the ITZ is difficult to test in macro experiments, resulting in difficulties in determining its simulation parameters. Based on the cohesive model with a rubber content of 5%, this study uses Monofactor analysis and the Plackett-Burman test to quickly and effectively determine the primary and secondary influences of the cohesive model parameters in the rubber-mortar ITZ; further, the response surface method is used to optimize the cohesive parameters in the rubber-mortar ITZ, and the numerical simulation results after optimizing the cohesive parameters are compared and analyzed with the simulation results before optimization. The results show that, under the setting of the optimized parameters, the simulation results of each item of the optimal cohesive model parameters in the rubber-mortar ITZ are in line with the reality and closer to the experimental data, and they are also applicable to rubber concrete models with different rubber dosing.

Comparative analysis of gut microbiome of mangrove brachyuran crabs revealed patterns of phylosymbiosis and codiversification.

The acquisition of microbial symbionts enables animals to rapidly adapt to and exploit novel ecological niches, thus significantly enhancing the evolutionary fitness and success of their hosts. However, the dynamics of host-microbe interactions and their evolutionary implications remain largely underexplored in marine invertebrates. Crabs of the family Sesarmidae (Crustacea: Brachyura) are dominant inhabitants of mangrove forests and are considered keystone species there. Their rapid diversification, particularly after adopting a plant-feeding lifestyle, is believed to have been facilitated by symbiotic gut microbes, enabling successful colonization of intertidal and terrestrial environments. To investigate the patterns and mechanisms shaping the microbial communities and the role of microbes in the evolution of Sesarmidae, we characterized and compared the gut microbiome compositions across 43 crab species from Sesarmidae and other mangrove-associated families using 16S metabarcoding. We found that the gut microbiome assemblages in crabs are primarily determined by host identity, with a secondary influence from environmental factors such as microhabitat and sampling location, and to a lesser extent influenced by biological factors such as sex and gut region. While patterns of phylosymbiosis (i.e. when microbial community relationships recapitulate the phylogeny of their hosts) were consistently observed in all beta-diversity metrics analysed, the strength of phylosymbiosis varied across crab families. This suggests that the bacterial assemblages in each family were differentially shaped by different degrees of host filtering and/or other evolutionary processes. Notably, Sesarmidae displayed signals of cophylogeny with its core gut bacterial genera, which likely play crucial functional roles in their hosts by providing lignocellulolytic enzymes, essential amino acids, and fatty acids supplementation. Our results support the hypothesis of microbial contribution to herbivory and terrestrialization in mangrove crabs, highlighting the tight association and codiversification of the crab holobiont.

Mechanical Performance Optimization and Microstructural Mechanism Study of Alkali-Activated Steel Slag–Slag Cementitious Materials

The optimal proportion of alkali-activated steel slag–slag cementitious materials is investigated by considering the combined effects of steel slag content, alkali content, water glass modulus, and water–binder ratio using the Box–Behnken design in response surface methodology. Qualitative and semi-quantitative analyses of X-ray diffraction (XRD) patterns and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS) images are conducted. The microstructural mechanism is elucidated based on the chemical composition, surface morphology, and microscale pore (crack) structures of the samples. A microreaction model for the alkali-activated steel slag and slag is proposed. The optimal composition for alkali-activated steel slag–slag cementitious materials is as follows: steel slag content, 38.60%; alkali content, 6.35%; water glass modulus, 1.23; and water–binder ratio, 0.48. The strength values predicted by the response surface model are p1d = 32.66 MPa, p7d = 50.46 MPa, and p28d = 56.87 MPa. XRD analysis confirms that the compressive strength of the sample is not only influenced by the amount of gel formed, but also, to a certain extent, by the CaCO3 crystals present in the steel slag, which act as nucleation sites. The SEM-EDS results confirm that the gel phase within the system comprises a hydrated calcium silicate gel formed through the reaction of volcanic ash and geopolymer gel formed through geo-polymerization. Analysis of the pore (crack) structure reveals that the compressive strength of the specimens is primarily influenced by porosity, with a secondary influence of the pore fractal dimension.