Modeling Analysis Research Articles

Critical consciousness among undocumented immigrant college students: Responding to cultural stress and psychological distress.

Cultural stress is experienced by undocumented students when they encounter discrimination in higher education and society. In response, undocumented students engage in critical consciousness, while simultaneously experiencing psychological distress. A conceptual model is introduced to describe the links between cultural stress, critical consciousness development, and psychological distress. One hundred seventy-one undocumented college students were recruited to participate in this study and completed measures of cultural stress (discrimination). They also completed measures of psychological distress, critical consciousness, and social justice self-efficacy and outcome expectations. The proposed model was tested for global fit and path analysis in structural equation modeling. Indirect effects were probed to assess the mediating role of critical consciousness and psychological distress. The model fit the data excellently. Greater discrimination was associated with higher critical consciousness, which in turn was associated with elevated social justice self-efficacy and outcome expectations. Additionally, higher discrimination was also linked to greater psychological distress. The link between cultural stress and critical consciousness was not explained by psychological distress. This research expands theory by articulating the adaptive ways undocumented students respond to the conditions that cause cultural stress and psychological distress. This aligns with a growing literature documenting the psychology of undocumented immigrants' activism and advocacy. Findings may inform interventions by higher education institutional agents and research to offset cultural stress and psychological distress. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

AI-Powered Microfluidics: Shaping the Future of Phenotypic Drug Discovery.

Phenotypic drug discovery (PDD), which involves harnessing biological systems directly to uncover effective drugs, has undergone a resurgence in recent years. The rapid advancement of artificial intelligence (AI) over the past few years presents numerous opportunities for augmenting phenotypic drug screening on microfluidic platforms, leveraging its predictive capabilities, data analysis, efficient data processing, etc. Microfluidics coupled with AI is poised to revolutionize the landscape of phenotypic drug discovery. By integrating advanced microfluidic platforms with AI algorithms, researchers can rapidly screen large libraries of compounds, identify novel drug candidates, and elucidate complex biological pathways with unprecedented speed and efficiency. This review provides an overview of recent advances and challenges in AI-based microfluidics and their applications in drug discovery. We discuss the synergistic combination of microfluidic systems for high-throughput screening and AI-driven analysis for phenotype characterization, drug-target interactions, and predictive modeling. In addition, we highlight the potential of AI-powered microfluidics to achieve an automated drug screening system. Overall, AI-powered microfluidics represents a promising approach to shaping the future of phenotypic drug discovery by enabling rapid, cost-effective, and accurate identification of therapeutically relevant compounds.

Mid-season nitrogen management for winter wheat under price and weather uncertainty

ContextIn-season nitrogen (N) management tools are essential for optimizing N application rates, maximizing farmers’ economic returns and minimizing adverse environmental impacts. The primary limitation to developing such tools is the risk associated with uncertainties in weather forecasts and crop price projections required to estimate yields and returns for different N rates. Therefore, characterizing the risk associated with these uncertainties is crucial for determining optimum N rates in-season. ObjectiveThis study investigated the N application decision-making process for farmers, accounting for risks associated with weather and crop price uncertainties through crop modeling and economic analysis. MethodsWe used field trial data for winter wheat in Kansas to examine how optimal nitrogen rates and economic returns vary over sites, years, and differing farmers’ risk attitudes. First, the Environmental Policy Integrated Climate (EPIC) agroecosystem model was used to simulate the distribution of final yields under different N applications during early spring. Then, an autoregressive moving average (ARMA) model estimated the wheat price distribution at harvest based on historical prices. Finally, optimal N application rates for farmers with different risk appetites were estimated using two risk decision models: the constant-absolute-risk-averse (CARA) expected utility model, which treats upside (higher-than-expected returns) and downside (lower-than-expected returns) deviations equally, and the invariant-preference, generalized-deviation (IPGD) model, which focuses on downside risk. ResultsWe found that optimal N rates vary greatly between sites and years, as well as across farmers with different risk preferences. Due to the positive skewness of economic return distribution, farmers tend to apply lower N rates when considering downside risk. On average, the optimal N rate for farmers with a CARA coefficient of 0.002 is 77 kg/ha in the CARA model and 67 kg/ha in the IPGD model. Compared to the outcome of risk-neutral N usage, risk-averse N usage for a farmer with a CARA coefficient of 0.008 could reduce the uncertainty (standard deviation) of return by 6.2 %, on average, while the expected return decreased by only 1.2 %. ConclusionsBy lowering the N rate, risk-averse farmers would reduce the uncertainty of returns and incur a minor return loss, suggesting the possibility of improving agricultural resilience while also improving N use efficiency. Our analysis also underscores the importance of yearly site-specific N management, given the substantial variation in optimal rates across years and locations. SignificanceThis study provides the foundation for an N application decision framework that considers both weather and price uncertainty. The analysis also demonstrates the potential co-benefit of enhancing agriculture’s climate and market resilience while potentially lowering N losses.

Harnessing plant-beneficial bacterial encapsulation: A sustainable strategy for facilitating cadmium bioaccumulation in Medicago sativa

Plant-beneficial bacteria (PBB) have emerged as a promising approach for assisting phytoremediation of heavy metal (HM)-contaminated soils. However, their colonization efficiency is often challenged by complex soil environments. In this study, we screened one rhizobacterium (Klebsiella variicola Y38) and one endophytic bacterium (Serratia surfactantfaciens Y15) isolated from HM-contaminated soils and plants for their high resistance to Cd and strong growth-promoting abilities. These strains were encapsulated individually or in combination with alginate and applied with Medicago sativa in Cd-contaminated soil pot experiments. The effectiveness of different bacterial formulations in promoting plant growth and enhancing Cd bioconcentration in M. sativa was evaluated. Results showed that PBB application enhanced plant growth and antioxidant capacity while reducing oxidative damage. Encapsulated formulations outperformed unencapsulated ones, with combined formulations yielding superior results to individual applications. Quantitative PCR indicated enhanced PBB colonization in Cd-contaminated soils with alginate encapsulation, potentially explaining the higher efficacy of alginate-encapsulated PBB. Additionally, the bacterial agents modified Cd speciation in soils, resulting in increased Cd bioaccumulation in M. sativa by 217–337 %. The alginate-encapsulated mixed bacterial agent demonstrated optimal effectiveness, increasing the Cd transfer coefficient by 3.2-fold. Structural equation modeling and correlation analysis elucidated that K. variicola Y38 promoted Cd bioaccumulation in M. sativa roots by reducing oxidative damage and enhancing root growth, while S. surfactantfaciens Y15 facilitated Cd translocation to shoots, promoting shoot growth. The combined application of these bacteria leveraged the benefits of both strains. These findings contribute to diversifying strategies for effectively and sustainably remediating Cd-contaminated soils, while laying a foundation for future investigations into bacteria-assisted phytoremediation.

Tip of the iceberg? Three novel TOPLESS-interacting effectors of the gall-inducing fungus Ustilago maydis.

Ustilago maydis is a biotrophic pathogen causing smut disease in maize. It secretes a cocktail of effector proteins, which target different host proteins during its biotrophic stages in the host plant. One such class of proteins we identified previously is TOPLESS (TPL) and TOPLESS-RELATED (TPR) transcriptional corepressors. Here, we screened 297 U. maydis effector candidates for their ability to interact with maize TPL protein RAMOSA 1 ENHANCER LOCUS 2 LIKE 2 (RELK2) and their ability to induce auxin signaling and thereby identified three novel TPL-interacting protein effectors (Tip6, Tip7, and Tip8). Structural modeling and mutational analysis allowed the identification of TPL-interaction motifs of Tip6 and Tip7. In planta interaction between Tip6 and Tip7 with RELK2 occurs mainly in nuclear compartments, whereas Tip8 colocalizes with RELK2 in a compartment outside the nucleus. Overexpression of Tip8 in nonhost plants leads to cell death, indicating recognition of the effector or its activity. By performing infection assays with single and multideletion mutants of U. maydis, we demonstrate a positive role of Tip6 and Tip7 in U. maydis virulence. Transcriptional profiling of maize leaves infected with Tip effector mutants in comparison with SG200 strain suggests Tip effector activities are not merely redundant.

Embedding moderators of customer-brand love for affecting purchase intention of customers in hypermarket brand stores

Purpose This paper aims to illustrate the impact of brand love on customers’ purchase intention in the presence of store aesthetics, store price image and customers’ demographic variables as moderating variables for hypermarket brand stores. Design/methodology/approach For achieving the objectives, a survey is conducted on the sample of 515 respondents those are the customers of hypermarket brand stores. The collected sample is analysed through structural equation modelling and moderation analysis by using AMOS. Findings The findings indicate various insights in terms of the results of moderation analysis. This study explains a significant moderation of store aesthetics, customers’ age and their local region for the brand love-purchase intention relationship in the research context. Originality/value The present study examines relevant moderators for brand love-purchase intention relationship by empirical means for hypermarket brand stores that is an under-explored researched context in Indian context. It adds considerable insights for academics and managerial practices in the arena of customer-brand love and emotional affiliation.

A self-determination perspective on the relationships between EFL learners’ foreign language peace of mind, foreign language enjoyment, psychological capital, and academic engagement

An increasing attention has already been paid to learners’ positive emotions. However, investigating the role of foreign language peace of mind (FLPoM) in language learners’ academic engagement has received scant attention. The present study therefore aims to explore whether EFL learners’ FLPoM, foreign language enjoyment (FLE), and psychological capital (PsyCap) can impact their academic engagement. The participants were 200 EFL learners who completed four questionnaires. The results of structural equation modelling (SEM) analysis revealed that learners’ FLPoM, FLE, and PsyCap significantly contributed to their academic engagement. Moreover, FLE was identified as the strongest predictor of academic engagement. The results of the present study highlighted the criticality of positive emotions in expanding learners’ engagement in learning a foreign language. Regarding the tenets of self-determination theory, the findings imply that psychological resources coupled with positive relatedness can yield effective engagement. Finally, suggestions for future research were offered.

Integrated approaches for flash flood susceptibility mapping: spatial modeling and comparative analysis of statistical and machine learning models. A case study of the Rheraya watershed, Morocco

Integrated approaches for flash flood susceptibility mapping: spatial modeling and comparative analysis of statistical and machine learning models. A case study of the Rheraya watershed, Morocco

Fit Indices in Structural Equation Modeling and Confirmatory Factor Analysis: Reporting Guidelines

Fit Indices in Structural Equation Modeling and Confirmatory Factor Analysis: Reporting Guidelines

Organizational green culture and employees’ green behavior: a moderated mediation model with employees’ environmental awareness and organizational disseminative capacity

ABSTRACT Based on the social information processing theory, a conceptual model was proposed in which employees’ environmental awareness was considered a mediator and organizational knowledge disseminative capacity was considered a moderator to deeply analyze the effect of organizational green culture on employees’ green behavior. The method of multi-regression analysis and structural equation modeling were used to verify the hypotheses based on the results of the questionnaire of 321 employees. The results show that organizational green culture has a positive effect on employees’ green behavior; two dimensions of employees’ environmental awareness have a positive direct effect on employees’ green behavior; employees’ environmental awareness has a mediating effect on the relationship between organizational green culture and employees’ green behavior; and organizational knowledge disseminative capacity moderates the relationship between organizational green culture and employees’ environmental awareness.

Unveiling the interplay between EFL teachers’ cognitive flexibility, emotion regulation, and foreign language teaching anxiety: A structural equation modeling approach

The current study explored the association between EFL instructors’ cognitive flexibility (CF) and foreign language teaching anxiety (FLTA), with the mediating impact of emotion regulation strategies. In doing so, 330 participants (196 males and 134 females) voluntarily filled in a battery of scales. Results of a structural equation modeling analysis indicated that all facets of FLTA were negatively correlated with CF. Furthermore, the first component of emotion regulation, i.e., cognitive reappraisal, had a strong negative association with all facets of FLTA except time management challenges. The other component of emotion regulation, expressive suppression, exhibited significant positive correlations with all components of FLTA, except difficulties with time management. Next, we investigated how two components of emotion regulation strategies could potentially mediate the association between CF and L2 teaching anxiety. Results indicated that cognitive reappraisal mediates the relationship between CF and four sub-components of FLTA, viz., fear of negative evaluation, lack of student interest, teaching inexperience, and self-perception of language proficiency. Additionally, expressive suppression mediated the relationship between CF and the four components of FLTA. The findings are discussed in the context of educational theories, and implications are provided to enhance EFL instructors’ flexible cognition.

Temperature and strain rate-dependent compression properties of 3D-printed PLA: an experimental and modeling analysis

Temperature and strain rate-dependent compression properties of 3D-printed PLA: an experimental and modeling analysis

Adolescent Prosocial and Antisocial Behaviours: Simultaneous Effects of Self-control, Attitudes of Parents and Teachers

This study investigates the complex relationships between parental attitudes, teacher attitudes, and self-control and their associations with prosocial and antisocial behaviour among adolescents in Bali, Indonesia. The research utilises a correlational research design with structural equation modelling (SEM) analysis to examine the relationships among variables comprehensively. A sample of 260 high school students aged 14 to 16 in Bali, Indonesia, was selected using a multi-stage cluster random sampling technique with 104 male and 156 female. The standard deviation of age is 0.49. Data were collected using adapted instruments to measure prosocial behaviour, antisocial behaviour, parents’ attitudes, teachers’ attitudes, and self-control. The study found positive correlations between parental attitudes, teacher attitudes, self-control, and prosocial behaviour and negative correlations with antisocial behaviour. The SEM analysis produced a predictive model for adolescent prosocial and antisocial behaviour, demonstrating strong compatibility with the model. The results indicated that parents’ attitudes, teachers’ attitudes, and self-control contributed significantly to prosocial behaviour among adolescents. However, while teachers’ attitudes and self-control were significantly related to antisocial behaviour, no significant relationship was found between parents’ attitudes and antisocial behaviour. The findings provide valuable insights into the role of parent-child relationships and highlight the potential for fostering positive behavioural outcomes. The study’s contribution lies in its focus on multiple dimensions of relationships and its exploration of the impact of parental difficulties. Ultimately, this research deepens the understanding of prosocial and antisocial behaviour and its underlying mechanisms, shedding new light on the field of prosocial.

The Bridge Between Childhood Trauma and Alexithymia Among Adolescents with Depressive and Bipolar Disorders: A Network Bridge Analysis.

Childhood trauma and alexithymia are significant risk factors for adolescent mental health issues. Prior research has linked these factors to psychopathology, but the complexities of their interrelation remain underexplored. This study aims to elucidate the relationship between various forms of childhood trauma and alexithymia in adolescents with depressive and bipolar disorders. Structural Equation Modeling (SEM) and network analysis were utilized on data from 2343 Chinese adolescents (aged 12-18 years, 77.93% female) diagnosed with depression or bipolar disorder. Measures included the Childhood Trauma Questionnaire (CTQ) and the Toronto Alexithymia Scale (TAS-20). SEM demonstrated a significant correlation between childhood trauma and alexithymia. Network analysis identified emotional abuse and difficulty identifying feelings as central nodes. Emotional abuse emerged as a key factor for difficulty in emotional identification among adolescents. This study highlights the need for early intervention and the importance of emotional nurturing in childhood to prevent long-term socioemotional difficulties.

Transcriptional drift in aging cells: A global decontroller

As cells age, they undergo a remarkable global change: In transcriptional drift, hundreds of genes become overexpressed while hundreds of others become underexpressed. Using archetype modeling and Gene Ontology analysis on data from aging Caenorhabditis elegans worms, we find that the up-regulated genes code for sensory proteins upstream of stress responses and down-regulated genes are growth- and metabolism-related. We observe similar trends within human fibroblasts, suggesting that this process is conserved in higher organisms. We propose a simple mechanistic model for how such global coordination of multiprotein expression levels may be achieved by the binding of a single factor that concentrates with age in C. elegans. A key implication is that a cell's own responses are part of its aging process, so unlike wear-and-tear processes, intervention might be able to modulate these effects.

Insights into mechanisms of MALT1 allostery from NMR and AlphaFold dynamic analyses

Mucosa-associated lymphoid tissue lymphoma-translocation protein 1 (MALT1) is an attractive target for the development of modulatory compounds in the treatment of lymphoma and other cancers. While the three-dimensional structure of MALT1 has been previously determined through X-ray analysis, its dynamic behaviour in solution has remained unexplored. We present here dynamic analyses of the apo MALT1 form along with the E549A mutation. This investigation used NMR 15N relaxation and NOE measurements between side-chain methyl groups. Our findings confirm that MALT1 exists as a monomer in solution, and demonstrate that the domains display semi-independent movements in relation to each other. Our dynamic study, covering multiple time scales, along with the assessment of conformational populations by Molecular Dynamic simulations, Alpha Fold modelling and PCA analysis, put the side chain of residue W580 in an inward position, shedding light at potential mechanisms underlying the allosteric regulation of this enzyme.

Modeling the critical barrier factors to hindering sustainable construction: sampling the Turkish construction industry

PurposeConsidering the construction industry’s vital role in economic development and social consequences, this study seeks to pinpoint critical barriers hindering Turkey’s sustainable construction (SC). Although several studies highlighted the barriers to SC worldwide, none identified the critical factors. By identifying and understanding these barriers, the research aims to comprehensively understand practices and formulate strategic recommendations to promote sustainable construction.Design/methodology/approachA systematic approach is adopted to achieve the research objectives. The study involves identifying potential barriers to SC with a systematic literature review. A questionnaire was organized and distributed via e-mail to architects, civil engineers, and contractors. The criticality of identified barriers was determined with normalized mean value analysis, and critical barrier factors (CBFs) to SC were isolated with exploratory factor analysis. Finally, the effect size of these factors was quantified through structural equation modeling.FindingsThis study identified 32 critical barriers hindering the SC in the Turkish construction industry among 49 barriers. Furthermore, this study revealed six CBFs to SC that are “inadequate supervision and control of SC,” “fear of transition to sustainable construction and disruptions in adoption,” “lack of educational opportunities,” “return on investment and financial bias,” “awareness and knowledge gap about SC,” and “lack of demand from stakeholders.” Among them, “awareness and knowledge gap about SC,” “fear of transition to SC,” “lack of educational opportunities,” “lack of demand from stakeholders,” and “inadequate supervision and control of SC” were determined as the very highly crucial CBFs hindering SC.Originality/valueAlthough some studies have identified the barriers to SC qualitatively and quantitatively, studies have yet to provide insights into the critical barrier factors hindering SC. Therefore, this study comprehensively and quantitatively determines the relevant CBFs to SC using exploratory factor analysis and utilizes confirmatory factor analysis and structural equation modeling to present a structural model of how critical factors affect the SC.

The Impact of Smart Home Technologies on Energy Efficiency, Cost Savings, and Environmental Benefits

The results of this study addressed the effectiveness of smart home technologies in terms of energy consumption, cost reduction, and environmental advantages in Nigerian homes. Given the growing energy requirements and concern for the environment, assessing the efficiency of such technologies is critical for socioeconomic development. We collected data using a combination of surveys and statistical analysis in five major Nigerian cities: Lagos, Abuja, Kano, Port Harcourt, and Enugu. We evaluated smart home technologies such as smart thermostats, lighting systems, appliances, plugs, and energy monitoring systems based on their energy savings (%), monthly cost savings (NGN), kilogram of CO2 emissions cut, and percent adoption. We used descriptive analysis and regression modeling to analyze the data collected from the respondents. The introduction of smart technologies reduced general energy use by fifteen to twenty-five percent, with smart appliances recording the highest reduction of up to 25%. This feature demonstrated how monthly cost savings varied depending on the technology and geographical location, resulting in significant increases of up to 4000 NGN per household, each household saw a reduction in CO2 emissions by 500 kg to 700 kg annually, resulting in significant environmental benefits. According to the studies, smart home technologies can help promote energy conservation and therefore reduce CO2 emissions in Nigerian households. However, there are still widely recognized obstacles, like high initial costs and a low level of awareness. offering financial incentives, improving Information Promotion of existing policies and overhauling the distribution systems to increase the pace of uptake and impact returns.

Innovative Skin Structures: Synthesis, Void Analysis, and Hysteresis Modeling of Zero Poisson’s Ratio Skin for Span Morphing Wing

This paper explores the use of carbon fiber-reinforced elastomeric skins for advancing flexible morphing wing technologies, highlighting exceptional 1D morphing capabilities. The study focuses on synthesizing a specially engineered elastomer-based skin with a zero Poisson’s ratio, achieved through precise formulation and fabrication onto unidirectional carbon fiber. Poisson’s ratio of the 1D skin is confirmed to be zero via image analysis. Micro-CT tomography evaluates carbon fiber quality and voids under varied prestretch conditions, revealing proportional increases in void sizes. X-ray tomography also provides insights into void distribution and morphology during pre- and post-cyclic stretching. The innovative approach enables seamless 1D morphing, achieving an impressive 200% stretch with a slight increase in actuation force and hysteresis loss percentage. Inspired by continuum mechanics, the proposed “Exp-ln-ln” framework accurately models the loading–unloading stretching of the skin. An extensive parametric investigation assesses key parameters, advancing fiber-reinforced elastomeric materials for aerospace morphing skins.

Seismic Behavior of Steel Reinforced Ultra-High Strength Concrete Composite Frame: Experimental and Numerical Study

The seismic behavior of steel reinforced ultra-high strength concrete (SRUHSC) composite frame was investigated through finite element analysis (FEA) modeling. A FEA model for the seismic analysis of the SRUHSC frame was first established and verified with test results. The numerical model was subsequently used to study the seismic performance of the SRUHSC frame, including the P-Δ skeleton curves, the stiffness degradation, the failure mode, the subsequence mechanisms of plastic hinges and the stress–strain distribution. Finally, a parametric study was carried out to investigate the effect of salient parameters on the behavior of the SRUHSC frame. It was found that with the increment of the concrete strength, yield strength of steel, and linear stiffness ratio of beam to column, the horizontal load-bearing capacity and the elastic stiffness of the structure were improved, but there was no significant effect on the ductility. With the increment of the volume stirrup ratio and structural steel ratio, the horizontal load-bearing capacity and the ductility of the structure were both improved. However, with the increment of the axial-load ratio, there was no obvious change in the elastic stiffness of the structure, but the horizontal load bearing capacity and the ductility of the structure decreased obviously. In addition, the accuracy of a concrete constitutive model in the different degrees of constraint for the SRUHSC frame proposed by the authors was verified with the FEA model.