Model Of Behavior Research Articles

Impact of Wettability on CO2 Dynamic Dissolution in Three-Dimensional Porous Media: Pore-Scale Simulation Using the Lattice Boltzmann Method.

Understanding the dissolution behavior of supercritical CO2 (scCO2) in porous media is crucial for efficient CO2 storage. However, the precise modeling of dynamic dissolution behavior at this pore scale remains a huge challenge, and the impact of wettability on this process still needs to be clarified. In this study, the influence of rock wettability on CO2 dynamic dissolution in the three-dimensional porous media is investigated using the lattice Boltzmann method (LBM). The LBM is coupled with scCO2-water two-phase flow, solute transport, and heterogeneous and homogeneous reactions. The size, number, and dissolution pattern of scCO2 bubbles during the dissolution process are observed under strongly water-wet, weakly water-wet, intermediate-wet, and mixed-wet conditions. The CO2(aq) concentration and pH are investigated, followed by a quantitative investigation of the impact of wettability on the specific interface area and the mass transfer coefficient. An empirical relationship between the specific interface area and scCO2 saturation is established. The findings reveal that under weakly water-wet and intermediate-wet conditions, the sizes of scCO2 clusters and monomers are small and mostly distributed at the dead end of the pores. In contrast, under strongly water-wet and mixed-wet conditions, the clusters are larger and interconnected, and distributed in the center of the pore. This results in a greater scCO2-water interface area, consequently enhancing the dissolution rate. Furthermore, a strong linear correlation is observed between scCO2 saturation and specific interface area. It is noted that as the hydrophilicity of the rock increases, the mass transfer coefficient initially rises and then declines.

Mechanism and modeling of car-following behavior under local multi-vehicle influence

Aiming at the limitations of single-dimensional car-following model to describe vehicle car-following behavior in local multi-vehicle environment, the mechanism of vehicles in adjacent lane influencing the subject vehicle car-following behavior is explored, and a vehicle car-following model more suitable for local multi-vehicle environment is attempted to be established. The driving behavior variable reflecting the influence of vehicles in adjacent lane was determined by correlation analysis. Vortisch indicator of similarity(VIS) was used to characterize the influence of vehicles in adjacent lane on car-following behavior. Chi-square independent test and kernel density curve were used to determine the VIS demarcation threshold reflecting whether the influence is significant. Recursive feature elimination was used to screen the variables related to car-following samples significantly affected by vehicles in adjacent lane. The influence mechanism of variables was determined according to the statistical analysis results. Based on the mechanism proposed, the car-following model suitable for local multi-vehicle environment was constructed and its prediction effect was evaluated. Results show that VIS between the speed of subject vehicle and following vehicle in adjacent lane can characterize the influence and the VIS threshold is 0.668. It is concluded that the attention mechanism and memory effect can explain the influence mechanism of car-following behavior in multi-vehicle environment. Considering the attention mechanism and memory effect, RMSE decrease by 65%in Full Velocity Difference Model (FVD) model and 62%in Intelligent Driver Model (IDM) model, MAE decrease by 65%and 59%and R2 increased by 180%and 288%respectively, which proved the rationality of the attention mechanism and memory effect in explaining the car following behavior of subject vehicle in local multi-vehicle environment.

ANALYSIS OF PATH NONPARAMETRIC TRUNCATED SPLINE MAXIMUM CUBIC ORDER IN BANKING CREDIT OF RISK BEHAVIOR MODEL

Path analysis tests the relationship between variables through cause and effect. The assumption of linearity must be met before conducting further tests on path analysis. If the shape of the relationship is nonlinear and the shape of the curve is unknown, a nonparametric approach is used, one of which is a truncated spline. The purpose of this study is to estimate the function and obtain the best model on the nonparametric truncated spline path of linear, quadratic, and cubic orders with 1 and 2-knot points and determine the significance of the best function estimator in banking credit of risk behavior model through the jackknife resampling method. This study uses secondary data through questionnaires to KPR debtor consumers, as many as 100 respondents. Based on the results of the analysis, it is known that the best-truncated spline nonparametric path model is the quadratic order of 2 knots with a coefficient of determination of 85.50%; the significance of the best-truncated spline nonparametric path estimator shows that all exogenous variables have a significant effect on endogenous variables.

The Role of Organizational Trust in Shaping Commitment and Reducing Turnover Intention in Aviation

In the contemporary business landscape, advancements in artificial intelligence and robotics are rapidly transforming industries, including air transportation. Although the demand for human resources may diminish with technological progress, the necessity for skilled personnel remains critical. The air transportation sector, in particular, relies heavily on qualified professionals, whose contribution to sustainable business practices is substantial. However, despite their importance, these trained professionals may occasionally exhibit a turnover intention their positions. Such turnover in an industry where technology plays a pivotal role represents a significant loss for organizations. Mitigating turnover intentions may depend on the application of effective organizational behavior models, one of which is fostering an environment of trust within the organization. Increased trust in the organization can enhance employees’ commitment and job satisfaction, thereby reducing their turnover intention. The primary aim of this study is to identify the factors influencing turnover intention, with a specific focus on whether organizational trust affects this intention. Furthermore, the study seeks to determine whether organizational commitment mediates the relationship between organizational trust and turnover intention. To explore these dynamics, a survey was conducted with 404 ground and flight personnel employed in both public and private aviation sectors in Türkiye. The research findings show that trust has important implications in an organizational setting. As a result of the analysis conducted within the scope of the research, it was determined that organizational trust has no effect on turnover intention. The reason for the different result from the literature may be the sensitivity of the aviation industry and the high staff turnover rate. Due to these characteristics of the sector, employees of the aviation industry may show turnover intention even if they trust their organizations.

Laboratory evaluation and FEM modeling of the rutting behavior of CR-enriched rejuvenator-modified RAP mixtures

Laboratory evaluation and FEM modeling of the rutting behavior of CR-enriched rejuvenator-modified RAP mixtures

A local–global principle for nonequilibrium steady states

The global steady state of a system in thermal equilibrium exponentially favors configurations with lesser energy. This principle is a powerful explanation of self-organization because energy is a local property of configurations. For nonequilibrium systems, there is no such property for which an analogous principle holds, hence no common explanation of the diverse forms of self-organization they exhibit. However, a flurry of recent empirical results has shown that a local property of configurations called "rattling" predicts the steady states of some nonequilibrium systems, leading to claims of a far-reaching principle of nonequilibrium self-organization. But for which nonequilibrium systems is rattling accurate, and why? We develop a theory of rattling in terms of Markov processes that gives simple and precise answers to these key questions. Our results show that rattling predicts a broader class of nonequilibrium steady states than has been claimed and for different reasons than have been suggested. Its predictions hold to an extent determined by the relative variance of, and correlation between, the local and global "parts" of a steady state. We show how these quantities characterize the local-global relationships of various random walks on random graphs, spin-glass dynamics, and models of animal collective behavior. Surprisingly, we find that the core idea of rattling is so general as to apply to equilibrium and nonequilibrium systems alike.

Phenomenology of TMD parton distributions in Drell-Yan and Z0 boson production in a hadron structure oriented approach

We present a first practical implementation of a recently proposed hadron structure oriented (HSO) approach to transverse momentum dependent (TMD) phenomenology applied to Drell-Yan-like processes, including lepton pair production at moderate Q2 and Z0 boson production. We compare and contrast general features of our methodology with other common practices and emphasize aspects that we view as improvements. Separately, we discuss the importance of treatments that preserve various theoretical properties of the nonperturbative parts of TMD parametrizations for future applications that have the extraction of hadron structure as a primary goal. These include the HSO’s preservation of a basic TMD parton-model-like framework even while accounting for full TMD factorization and evolution, explicit preservation of the integral relationship between TMD and collinear parton density functions, and the ability to meaningfully compare different theoretical models of nonperturbative TMD parton distributions. In our examples, we show that there is significant sensitivity at moderate Q2 to both the form of the nonperturbative transverse momentum dependence and the parametrization of collinear parton densities. However, we also find that evolving to Q2=MZ2, without fitting, results in a satisfactory postdiction of existing data for Z0 production, nearly independently of the modeling of nonperturbative transverse momentum behavior. We argue that this demonstrates that moderate Q measurements should be given greater weight than high Q measurements in extractions of nonperturbative transverse momentum dependence. We also obtain new extractions of the nonperturbative Collins-Soper kernel within the HSO approach. We discuss its features and compare with some earlier extractions. Published by the American Physical Society 2024

Occupational Exposure to Pesticides, Personal Protection, and Willingness to Reduce Chemical Sprayings Among Iranian Greenhouse Farmers

ABSTRACT Objectives The level of greenhouse farmers’ personal protection in pesticide use and the possibility of environmental protection through farmers’ willingness to reduce chemical sprayings were assessed in Khuzestan Province, Iran. Methods A survey of 80 active greenhouse vegetable growers was carried out in 2021 with face-to-face interviews. Willingness to reduce chemical sprayings was examined with the theory of planned behavior (TPB) model. Results Several intoxication symptoms were reported, with the most common symptom of pesticide intoxication being dizziness. Farmers showed unsafe or rather unsafe use of personal protective equipment (PPE) during pesticide handling. The maximum use of PPE pertained to the use of mask, spray clothing, and long-sleeved shirts. On a scale from 1 (= totally disagree) to 5 (= totally agree), the respondents showed negative attitudes towards reducing chemical sprayings (mean = 2.30), rather low levels of subjective norms (mean = 2.67), and rather low levels of perceived behavioral control over reduction of chemical sprayings (mean = 2.76). The TPB variables accounted for 73% of the variance in farmers’ behavioral intention. Overall, farmers’ behavioral intention to reduce chemical sprayings was almost neutral. Conclusion Increasing knowledge of the adverse effects of pesticides on health is necessary to promote safety behavior of farmers in the greenhouse.

Use of Advanced Constitutive Models for the Mechanical Behavior of Soft Soils With Diatoms From Bogotá (Colombia)

ABSTRACTMost constitutive models did not initially consider special behaviors in some soils with singular characteristics (e.g., soft soils with diatom content). For example, at first, these models did not consider the effect of soil structure and viscosity. However, in the last decades, these variables have been incorporated into several constitutive models to describe the mechanical behavior of the soil in its natural state. Structure and viscosity laws that adequately reproduce the soil behavior had to be developed to include these variables. This paper compares the mechanical behavior of soft soils in Bogotá with different constitutive models. Bogotá’s soft soils are lacustrine deposits with a high content of diatoms in their structure. Natural soil samples with intact structures show a high‐water content, which can be higher than 300%, liquid limits of up to 400%, void ratios higher than five, and friction angles of almost 40°. In addition, the model validations were made through the simulations of triaxial tests in compression and shear paths. Modified Cam Clay (MCC), hypoplastic (HP), and subloading Cam Clay (SCC) were the constitutive models used. Two models are based on an elastoplastic framework, and the third uses a HP framework. Several lessons were learned from the simulations regarding the strengths and weaknesses of the models compared to the tests carried out. Finally, the extensive discussion revolves around determining the most suitable model for simulating the mechanical behavior of soft soils containing diatoms in Bogotá.

Modelling of a Cylindrical Battery Mechanical Behavior under Compression Load

The extensive utilization of lithium-ion (Li-ion) batteries within the automotive industry necessitates rigorous measures to ensure their mechanical robustness, crucial for averting thermal runaway incidents and ensuring vehicle safety. This paper introduces an innovative methodology aimed at homogenizing the mechanical response of Li-ion batteries under compression load, using Finite Element Method (FEM) techniques to improve computational efficiency. A novel approach is proposed, involving the selective application of compression loads solely to the Jelly Roll and its casing, achieved by cutting the battery heads. Through this method, distinct mechanical behaviors are identified within the battery force displacement curve: an elastic region, a zone characterized by plastic deformation, and a segment exhibiting densification. By delineating these regions, our study facilitates a comprehensive understanding of the battery’s mechanical response under compression. Two battery models were employed in this study: one representing the battery as a solid volume, and another featuring the jelly roll as a solid volume enclosed by a shell representing the casing. The material utilized was LS Dyna MAT24, chosen for its piecewise characteristics’ definition, and its validation was primarily conducted through the curve fitting method applied to the force–displacement curve, taking in account the three regions of the compression force behavior. This approach not only optimizes computational resources but also offers insights crucial for enhancing the mechanical stability of Li-ion batteries in automotive applications.

Examining Multiculturals’ and Multilinguals’ Paradoxical Bridging Behaviors in Overcoming Cultural and Language Barriers in Organizations

Research has identified the usefulness of multicultural and multilingual employees in overcoming cultural and language barriers in international work contexts, but still needs to clarify why and how these employees engage in bridging behavior. Based on in-depth analyses of 154 interviews, we inductively develop a comprehensive model of bridging behaviors with novel and counterintuitive insights. We show that bridging behaviors are not only based on individual strengths, which multiculturals and multilinguals possess, but also—paradoxically—on their weaknesses. Multiculturals’ and multilinguals’ strengths and experience with weaknesses result in different determinants and enactments of bridging. Grounded in our inductive theory building, we propose four bridging behaviors: cultural teaching, language teaching, cultural facilitating, and language facilitating. Multiculturals and multilinguals cycle between these bridging behaviors depending on their capabilities and motivations in specific situations. We provide theoretical and practical implications of our findings.

Durability of Fiber-Reinforced Polymer (FRP) Bars: Progress, Innovations and Challenges Based on Bibliometric Analysis

This review systematically examines the literature on the Fiber-Reinforced Polymer (FRP) bars durability in concrete matrices using bibliometric analysis to understand progress, innovations, and challenges. The objective is to explore the durability of FRP bars, which are recognized for their strength-to-weight ratio, corrosion resistance, and non-conductivity, as a potential substitute to conventional steel reinforcement. Methods involved employing bibliometric tools such as Biblioshiny and VOSviewer to analyze trends, collaboration patterns, and the global distribution of publications. Findings reveal an increase in research activity over the past two decades, significant international collaboration, and leading contributions from key countries. Critical environmental factors like alkalinity, thermal conditions, and chemical aggressors affecting the interface of fiber-matrix mechanical properties were highlighted. Advances in predictive modeling for long-term behavior conditioned FRP bars are studied, steering future research towards improved durability and sustainable construction practices. This study contributes novelty by providing a comprehensive bibliometric perspective on FRP bar durability, identifying emerging trends, and suggesting areas for future suggested research to enhance the reliability and application of FRP bars in construction. Doi: 10.28991/CEJ-SP2024-010-09 Full Text: PDF

An Interactive Fluid–Solid Approach for Numerical Modeling of Composite Metal Foam Behavior under Compression

Composite metal foams (CMF) are renowned for their high strength‐to‐density ratio, high stiffness, and energy absorption capabilities. Homogenized finite element models of CMF have been numerically solved to understand the mechanical behavior of the material under a variety of external loading conditions. This work aims to pioneer a comprehensive finite element model for steel–steel composite metal foam by incorporating the interactions between embedded stainless‐steel hollow spheres with entrapped air inside stainless‐steel matrix. The material behavior of hollow spheres, surrounding matrix, and air are modeled using Johnson–Cook (JC) plasticity, Deshpande–Fleck (D–F) foam, and linear polynomial equation of state in LS DYNA. Further, the finite element model utilizes a combination of Lagrangian solid elements and meshfree smooth particles hydrodynamics with appropriate contacts to effectively model the interaction of entrapped air within stainless‐steel hollow spheres with surrounding metallic spheres and matrix. The strain rate and the crosshead velocity of 65 s−1 and 2.4765 m s−1 are used for quasistatic compression analysis. Finally, the results obtained from the computational model are compared and validated using previously reported experimental quasistatic compression data. The numerical model corroborates stress–strain response of CMF with 5.6% error for plateau stresses average within 25% and 30% strain.

Simulation of lithium hydroxide decomposition using deep potential molecular dynamics.

Chemical reactions and vapor-liquid equilibria for molten lithium hydroxide (LiOH) were studied using molecular dynamics simulations and a deep potential (DP) model. The neural network for the model was trained on quantum density functional theory data for a range of conditions. The DP model allows simulations over timescales of hundreds of ns, which provide equilibrium compositions for the systems of interest. Single-phase NPT simulations of the liquid show the decomposition of LiOH into lithium oxide (Li2O) and dissolved water (H2O). These DP results were validated by direct abinitio molecular dynamics simulations that confirmed the accuracy of the model with respect to reaction kinetics and equilibrium properties of the melt. The reactive vapor-liquid behavior of this system was subsequently studied using direct coexistence interfacial DP simulations. Partial pressures of H2O in the vapor are found to be in close agreement with available experimental measurements. By fitting temperature-dependent expressions for the reaction equilibrium and Henry's law constants, the equilibrium composition for any given initial composition and temperature can be quantitatively modeled. For high initial concentrations of Li2O or H2O, mixtures of LiOH + Li2O/H2O are found to undergo phase separation. The present study illustrates how DP-based molecular dynamics simulations can be used for quantitative modeling of multiphase reactive behavior with the accuracy of the underlying abinitio quantum chemical methods.

Hot Deformation Behavior and Constitutive Modeling of High Strength Low-Carbon Alloyed Steel Manufactured by Wire and Arc Additive Manufacturing

Hot Deformation Behavior and Constitutive Modeling of High Strength Low-Carbon Alloyed Steel Manufactured by Wire and Arc Additive Manufacturing

Study on the uniaxial tensile mechanical behavior and constitutive model of advanced high-strength steels for DP1180 and Q&P1180

With the increasing global demand for green and environmentally friendly materials, advanced high-strength steels (AHSS) produced using by cold rolling process are gaining more attention in the construction industry, such as in cold-formed thin-walled structures. To expand their engineering applications, the study of the mechanical behavior and constitutive models of AHSS is particularly important. This paper focuses on DP1180 and Q&P1180, employing experimental research and theoretical analysis to elucidate the patterns at various characteristic points and establish constitutive models for AHSS. The specific conclusions are as follows: 1) For DP1180 and Q&P1180, the average elongation after fracture is 8.9 % and 16.7 %, respectively, with strength-to-yield ratios ranging from 1.24 to 1.34 and 1.14–1.24, respectively. 2) Due to the insignificant nonlinearity exhibited by DP1180 and Q&P1180 near the nominal buckling strength, the modified nominal yield strength and equivalent ultimate strength was defined and adopted as the boundaries to divide the stress-strain curve into three segments. The mathematical expressions and relevant parameter models for each segment are established. Finally, the three-stage AHSS uniaxial tensile constitutive model was established. Compared to existing models, the proposed model demonstrates higher accuracy.

Tilianin obtained from Agastache mexicana inhibits monoamine oxidase and modifies depressive behavior in rats.

Agastache mexicana is used in traditional medicine to treat anxiety, insomnia, pain, among others. In a previous study, the methanolic extract exerted anxiolytic and sedative effects, as observed behaviorally, associated with one of its major components, tilianin. To assess the effect produced by the extracts and tilianin obtained from Agastache mexicana on depressive-induced behavior model and on the activity of monoamine oxidases (MAOs). The depression experimental model consisted of the forced swimming test in rats. MAOs activity was evaluated in cortex and hippocampus from the tilianin and Agastache extracts treated rats using specific inhibitors for each isoform. The quantification of monoamines was carried out using an High Performance Liquid Chromatography method. An increase in the swimming time was observed in rodents treated with doses of 16 (226.6±5.5 seconds) and 50mg/kg (237.8±5.7 seconds) of tilianin, methanolic (260.4±3 seconds), and hydroalcoholic extracts (249.6±2.6 seconds) at 100mg/kg. MAOs activity was significantly decreased in brain tissue from animals treated with 16 and 50mg/kg of tilianin, methanolic, and hydroalcoholic extracts at 100mg/kg. The tilianin effect on monoamine oxidases inhibition is confirmed, suggesting its potential use in the treatment of certain neurological disorders.

The place of strategic ecological communications in change management (based on the national project “Ecological Well-Being”)

Comprehensive improvement of the state of the environment is currently the subject of government decisions, programs and projects in Russia. This affects the interests of various audiences: business, the public, federal and regional influence groups, and hence requires strategic communications aimed at explaining, expanding the number of supporters, uniting efforts, legitimizing the governmental decisions, and changing the behavior of the audiences. The purpose of the study is to analyze the place of strategic environmental communications in the action program for the implementation of state environmental strategies. The author relies on theoretical studies of Russian and foreign authors on this issue. In the practical part, she analyzes communications in the process of forming the national project “Ecological Well-Being”. The results of the conducted study of the media and official resources of state authorities allow to consider several communicative models of behavior: public and non-public. The stage of formation of the national project is accompanied by non-public communication, which creates certain risks when information is released into the public space, since criticism and disagreement with the adoption of relevant decisions may arise from various groups. The author offers a list of possible conflict topics and examines the features of the formation of strategic environmental communications, based on M. Harvell’s matrix.

Costly calling: Marmots who alarm call at higher rates are less likely to survive the summer and live shorter lives

Abstract Emitting alarm calls may be costly, but few studies have asked whether calling increases a caller’s risk of predation and survival. Since observing animals calling and being killed is relatively rare, we capitalized on over 24,000 h of observations of marmot colonies and asked whether variation in the rate that yellow-bellied marmots (Marmota flaviventer) alarm called was associated with the probability of summer mortality, a proxy for predation. Using a generalized mixed model that controlled for factors that influenced the likelihood of survival, we found that marmots who called at higher rates were substantially more likely to die over the summer. Since virtually all summer mortality is due to predation, these results suggest that calling is indeed costly for marmots. Additionally, the results from a Cox survival analysis showed that marmots that called more lived significantly shorter lives. Prior studies have shown that marmots reduce the risk by emitting calls only when close to their burrows, but this newly quantified survival cost suggests a constraint on eliminating risks. Quantifying the cost of alarm calling using a similar approach in other systems will help us better understand its true costs, which is an essential value for theoretical models of calling and social behavior.

Trajectory generation for adhesive dispensing robots by modeling of material behavior

It is difficult for robots to manipulate flexible objects, and adhesive dispensing is one such task. In this task, the adhesive material is pulled by a dispensing robot, which is problematic to predict. In this paper, we propose an analysis-based and a learning-based model to predict the behavior of the adhesive material, and a method to explore the robot trajectory. While analysis-based models consider physical behavior and require less training data, they are limited to specific physical behaviors. Learning-based models, on the other hand, can model many physical behaviors, but require a lot of training data. Finally, we use the predictions of these models to perform experiments and evaluate the differences between the target adhesive trajectory and the actual application results.