Growth Model Research Articles

A Longitudinal Study on the Influence of Peer Network Status on University and College Students’ Academic Records in Hurdle Class

Purpose: To examine the longitudinal impact and mechanism of peer network status on university students’ hurdle running academic records. Methods: Conduct a follow-up survey in the hurdle teaching, an experimental class, and analyze the data using the latent growth model. Results: (a) The intercept and slope of peer network status positively predict the slope of academic records. (b) Peer network status influences the slope of academic records through the slope of learning engagement, and the intercept of learning engagement acts as a masking effect between the two. (c) Personality traits moderated the relationship between peer network status and the academic records slope. Conclusions: (a) The impact of peer network status on academic records exhibits social effects. (b) The impact of peer network status on academic records has a double-edged sword effect. (c) Extroverted personality is most advantageous in enhancing peer network status and predicting the rate of improvement in academic records.

Evidence on an endogenous growth model with public R&D

ABSTRACT The empirical investigation of properties of an endogenous growth model by Huang, Lai, and Peretto ([2023]. “Public R&D, Private R&D and Growth: A Schumpeterian Approach.” public.econ.duke.edu mimeo) in this paper confirms important assumptions and results of the model for OECD countries. Labour-augmenting technical change is enhanced through private and public R&D stocks in fully modified and dynamic OLS mean-group and pooled mean-group estimations, also when adding the number of enterprises. The CES spillover functions in the growth model’s functions for R&D stock dynamics are supported through nonlinear estimation under the assumptions of identical or different spillover parameters for private and public R&D. We suggest strong public-to-private spillovers and weak private-to-public spillovers as well as high elasticities of substitution for private–public R&D stocks for private R&D processes and low CES for public R&D processes. We confirm the existence of private–public researcher interaction effects in the private R&D knowledge growth function and provide tentative evidence for the linear model relation between public researchers and firm-level R&D and the hump-shaped relation between public and private researchers (both as % labour force). A vector-autoregressive (VAR) panel model in growth rates produces results, which are in accordance with the impact of public R&D cuts on the steady state and the transitional dynamics of the HLP model.

The Growth of Complex Syntax in School-Age African American Children Who Speak African American English.

Syntax provides critical support for both academic success and linguistic growth, yet it has not been a focus of language research in school-age African American children. This study examines complex syntax performance of African American children in second through fifth grades. The current study explores the syntactic performances of African American children (N = 513) in Grades 2-5 on the Test of Language Development-Intermediate who speak African American English. Multilevel modeling was used to evaluate the growth and associated changes between dialect density and syntax. Analyzed data were compared both to the normative sample and within the recruited sample. The results suggest that dialect density exerted its impact early but did not continue to influence syntactic growth over time. Additionally, it was not until dialect density was accounted for in growth models that African American children's syntactic growth resembled normative expectations of a standardized language instrument. The current study suggests that failure to consider cultural language differences obscures our understanding of African American students' linguistic competence on standardized language assessments.

Analytical modeling of nucleation and growth of graphene layers on CNT array and its application in field emission of electrons

Carbon Nanotube (CNT) arrays and graphene have undergone several investigations to achieve efficient field emission (FE) owing to CNT’s remarkable large aspect ratio and graphene’s exceptional FE stability. However, when dense CNT arrays and planar graphene layers were used as field emitters, their field enhancement factor reduced dramatically. Therefore, in this paper, we numerically analyze the growth of a dense CNT array with planar graphene layers (PGLs) on top, resulting in a CNT-PGL hybrid and the associated field enhancement factor. The growth of the CNT array is investigated using Plasma Enhanced Chemical Vapor Deposition (PECVD) chamber in C2H2/NH3 environment with variable C2H2 flow, Ni catalyst film thickness, and substrate temperature followed by PGL precipitation on its top at an optimized cooling rate and Ni film thickness. The analytical model developed accounts for the number density of ions and neutrals, various surface elementary processes on catalyst film, CNT array growth, and PGLs precipitation. According to our investigation, the average growth rate of CNTs increases and then decreases with increasing C2H2 flow rate and catalyst film thickness. CNTs grow at a faster rate when the substrate temperature increases. Furthermore, as the chamber temperature is lowered from 750 °C to 250 °C in N2 environment and Ni film thickness grows, the number of the graphene layers increases. The field enhancement factors for the CNT array and hybrid are then calculated based on the optimal parameter values. The average height of the nanotubes, their spacing from one another, and the penetration of the electric field due to graphene coverage are considered while computing the field enhancement factor. It has been found that adding planar graphene layers to densely packed CNTs can raise its field enhancement factor. The results obtained match the current experimental observations quite well.

Leaf and twig traits predict habitat adaptation and demographic strategies in tropical freshwater swamp forest trees.

Differences in demographic and environmental niches facilitate plant species coexistence in tropical forests. However, the adaptations that enable species to achieve higher demographic rates (e.g. growth or survival) or occupy unique environmental niches (e.g. waterlogged conditions) remain poorly understood. Anatomical traits may better predict plant environmental and demographic strategies because they are direct measurements of structures involved in these adaptations. We collected 18 leaf and twig traits from 29 tree species in a tropical freshwater swamp forest in Singapore. We estimated demographic parameters of the 29 species from growth and survival models, and degree of association toward swamp habitats. We examined pairwise trait-trait, trait-demography and trait-environment links while controlling for phylogeny. Leaf and twig anatomical traits were better predictors of all demographic parameters than other commonly measured leaf and wood traits. Plants with wider vessels had faster growth rates but lower survival rates. Leaf and spongy mesophyll thickness predicted swamp association. These findings demonstrate the utility of anatomical traits as indicators of plant hydraulic strategies and their links to growth-mortality trade-offs and waterlogging stress tolerance that underlie species coexistence mechanisms in tropical forest trees.

Synergistically promoting enterprises to replace old growth drivers with new ones: The roles of market and government

As enterprises transition from traditional growth models to modern ones, the roles of the market and government are pivotal in facilitating this transformation. Based on the Chinese experience, this paper employs textual analysis methods to describe the transformation process from old to new growth drivers in enterprises and to identify the distinct influences of governmental and market forces. Empirical evidence demonstrates that effective government incentives and competitive market pressure both contribute significantly to development upgrades. A clear symbiotic relationship is evident between these two forces, with government intervention enhancing the effectiveness of market dynamics. However, the impact of these forces varies across different enterprises. The empirical findings suggest that by harnessing the efficient synergy between the "visible hand" of government intervention and the "invisible hand" of market forces, development modes can be upgraded, and endogenous growth can be more effectively fostered.

Conglomerate rock interface debonding characteristics and damage evolution based on cohesive phase-field method

Rock failure often occurs due to uneven mechanical strength and discontinuous strain at the interface. However, due to the complex interaction mechanism between different phases of conglomerate, it is necessary to improve the crack growth model at the conglomerates' interface. In view of the physical structure and mechanical properties of conglomerate materials, this paper innovatively adopts the cohesive phase field model to study the material deformation and crack growth of conglomerate materials. Different from the traditional phase field model, this model characterises the real structure of the interface by adding an interface phase field, which is used to simulate the debonding of the interface during crack propagation and damage evolution. The regularization of the phase field is carried out to ensure the smoothness of the interface. The transition state of the interface region is determined by the element and the additional phase field. The energy equation is coupled with the crack propagation process using the crack surface density function. The evolution of the damaged phase field and displacement field is driven by the principle of energy minimization. The innovative assumption is that there is a virtual crack at the crack tip, and the interface related elements show a certain cohesive softening form during the damage evolution, which is the main way to realize the particularity of interface mechanics. By controlling the crack dispersion state and stiffness degradation of the material, several ideal softening models are innovatively assumed according to the cohesive force change law to satisfy the mechanical properties and stress function constraints. When cutting blocks n=2.5×104, the errors of the linear model, exponential model, and compound inverse model are 1.76%, 7.48%, and 5.19%, respectively. The results of the exponential model agree well with the stress strength (the error is 2%) and interface crack kinking angle (68.89°). The simulation results indicate that the deformation process of the conglomerate can be divided into three stages: elastic deformation stage, crack propagation stage, and stable load stage. The tensile strength of conglomerate is positively correlated with interface's fracture toughness and proportion of gravel area, respectively.

Zonotopic state estimation and sensor fault detection for a wastewater treatment bioprocess

AbstractIn this paper, a fault diagnosis method for the basic process of microbial growth in wastewater treatment based on interval estimation technology is proposed. First, a nonlinear microbial growth model is converted into a linear time‐varying system. A time‐varying observer is then designed for the generated system, which takes into account an performance. Furthermore, a zonotope‐based set‐membership estimation algorithm is analyzed to synchronize interval estimation operations. In addition, interval residuals are computed from the generated interval state estimation and fault diagnosis is performed for a wastewater treatment bioprocess with sensor fault signals. Finally, the feasibility of the proposed fault diagnosis strategy for the wastewater treatment bioprocess is illustrated through numerical simulations.

Dynamic Evolution of Infarct Volumes at MRI in Ischemic Stroke Due to Large Vessel Occlusion.

The typical infarct volume trajectories in stroke patients, categorized as slow or fast progressors, remain largely unknown. This study aimed to reveal the characteristic spatiotemporal evolutions of infarct volumes caused by large vessel occlusion (LVO) and show that such growth charts help anticipate clinical outcomes. We conducted a secondary analysis from prospectively collected databases (FRAME, 2017-2019; ETIS, 2015-2022). We selected acute MRI data from anterior LVO stroke patients with witnessed onset, which were divided into training and independent validation datasets. In the training dataset, using Gaussian mixture analysis, we classified the patients into 3 growth groups based on their rate of infarct growth (diffusion volume/time-to-imaging). Subsequently, we extrapolated pseudo-longitudinal models of infarct growth for each group and generated sequential frequency maps to highlight the spatial distribution of infarct growth. We used these charts to attribute a growth group to the independent patients from the validation dataset. We compared their 3-month modified Rankin scale (mRS) with the predicted values based on a multivariable regression model from the training dataset that used growth group as an independent variable. We included 804 patients (median age 73.0 years [interquartile range 61.2-82.0 years]; 409 men). The training dataset revealed nonsupervised clustering into 11% (74/703) slow, 62% (437/703) intermediate, and 27% (192/703) fast progressors. Infarct volume evolutions were best fitted with a linear (r = 0.809; p < 0.001), cubic (r = 0.471; p < 0.001), and power (r = 0.63; p < 0.001) function for the slow, intermediate, and fast progressors, respectively. Notably, the deep nuclei and insular cortex were rapidly affected in the intermediate and fast groups with further cortical involvement in the fast group. The variable growth group significantly predicted the 3-month mRS (multivariate odds ratio 0.51; 95% CI 0.37-0.72, p < 0.0001) in the training dataset, yielding a mean area under the receiver operating characteristic curve of 0.78 (95% CI 0.66-0.88) in the independent validation dataset. We revealed spatiotemporal archetype dynamic evolutions following LVO stroke according to 3 growth phenotypes called slow, intermediate, and fast progressors, providing insight into anticipating clinical outcome. We expect this could help in designing neuroprotective trials aiming at modulating infarct growth before EVT.

Mathematical modeling of multi-component aerosol droplet evaporation and growth in indoor environments

Multi-component droplets from daily activities and production processes severely degrade indoor air quality. Their health hazards and removal efficiency depend on size and composition, significantly affected by evaporation and growth. The phase transition process is complex, involving a broad spectrum of droplet sizes with diverse heat and mass transfer characteristics. Components within the droplets experience simultaneous phase transitions at differing rates and mass transfer directions. This study aims to refine the existing evaporation model of single-component droplets in continuous flows by theoretically integrating the effects of varying droplet sizes and multiple components. A multi-component droplet evaporation/growth model that spans the entire range of droplet sizes has been developed, and predictions have been made based on this model. Utilizing MATLAB, this model accurately predicts the indoor dynamics of multi-component droplets, with deviations under 16 % from experiments. It improves accuracy by over 25 % across droplet sizes via dimensionless transfer coefficients and boosts precision by over 24 % for multi-component droplets with zero-diffusion transport. The radius of the droplet after phase change can reach 8.42 × 10−6 m and remains suspended in the air for an extended period. This study establishes a solid theoretical foundation for accurately predicting the indoor distribution of multi-component droplets.

LncRNA PVT1 facilitates the growth and metastasis of colorectal cancer by sponging with miR-3619-5p to regulate TRIM29 expression.

Colorectal cancer (CRC) is the second most common cause of cancer-related death worldwide. Long noncoding RNA (lncRNA) is involved in many malignant tumors. This study aimed to clarify the role of the lncRNA plasmacytoma variant translocation 1 (PVT1) in CRC growth and metastasis. Differentially expressed lncRNAs in CRC were analyzed using the Cancer Genome Atlas. Gene expression profiling interactive analysis and a comprehensive resource for lncRNAs from cancer arrays databases were used to analyze lncRNA PVT1 expression and CRC prognosis, respectively. Cell counting kit-8, wound healing, colony formation, Transwell, and immunofluorescence assays were used to evaluate CRC cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), respectively. Tumor growth and metastasis models were used to explore the PVT1 effect on the growth and metastasis of CRC in vivo. PVT1 was highly expressed in CRC, associated with a poor prognosis of CRC, and showed good diagnostic value. Transfection of sh-PVT1 or pcDNA3.1-PVT1 reduced or increased the proliferation, wound healing rate, colony formation, invasion, and EMT of CRC cells. PVT1 and miR-3619-5p were co-expressed in CRC cytoplasm, and PVT1 acted as a competitive endogenous RNA (ceRNA) by sponging miR-3619-5p to up-regulate tripartite motif containing 29 (TRIM29) expression. MiR-3619-5p overexpression and TRIM29 knockdown reduced proliferation, wound healing rate, invasion, and EMT of CRC cells. However, simultaneous PVT1 and miR-3619-5p overexpression or knockdown of miR-3619-5p and TRIM29 knockdown rescued the malignant phenotype of CRC cells. We first clarified the ceRNA mechanism of PVT1 in CRC, which induced growth and metastasis by sponging with miR-3619-5p to regulate TRIM29.

A Hessian Recovery Based Linear Finite Element Method for Molecular Beam Epitaxy Growth Model with Slope Selection

A Hessian Recovery Based Linear Finite Element Method for Molecular Beam Epitaxy Growth Model with Slope Selection

Longitudinal stability and change across a year in children's gender stereotypes about four different STEM fields.

Gender stereotypes about science, technology, engineering, and math (STEM) are salient for children and adolescents and contribute to achievement-related disparities and inequalities in STEM participation. However, few studies have used a longitudinal design to examine changes in gender stereotypes across a range of STEM fields. In a large, preregistered study, we examined the developmental trajectories of two gender stereotypes (involving interest and ability) in four STEM fields across three time points within a calendar year, starting in Grades 2-8. The diverse sample included 803 students ages 7-15 years old at the start of the study (50% girls; 8.5% Asian, 6.0% Black, 25.5% Hispanic/Latinx, 43.7% White, and 16.3% other). Multilevel growth modeling was used to examine developmental trajectories in students' stereotypes for four STEM fields (math, science, computer science, and engineering) while considering both gender and grade level. We found that different STEM disciplines displayed different developmental patterns: Math ability and science interest stereotypes more strongly favored girls over the year among elementary school participants, whereas computer science stereotypes less strongly favored boys over time, and engineering stereotypes (which largely favored boys) were stable across time. The results highlight that the development of stereotypes is not the same for all STEM fields as well as the need to understand the complexity and specificity of developmental change across fields and types of stereotypes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Is trait rumination associated with affective reactivity to the menstrual cycle? A prospective analysis.

A minority of naturally cycling individuals experience clinically significant affective changes across the menstrual cycle. However, few studies have examined cognitive and behavioral constructs that may maintain or worsen these changes. Several small studies link rumination with premenstrual negative affect, with authors concluding that a tendency to ruminate amplifies and perpetuates hormone-sensitive affective symptoms. Replication in larger samples is needed to confirm the validity of rumination as a treatment target. 190 cycling individuals (M = 30.82 years; 61.1% Caucasian) were recruited for moderate perceived stress, a risk factor for cyclical symptoms. They completed the Rumination Response Scale at baseline, then reported daily affective and physical symptoms across 1-6 cycles. Multilevel growth models tested trait rumination as a predictor of baseline levels, luteal increases, and follicular decreases in symptoms. The degree of affective cyclicity was normally distributed across a substantial range, supporting feasibility of hypothesis tests and validating the concept of dimensional hormone sensitivity. Contrary to prediction, higher brooding did not predict levels or cyclical changes of any symptom. In a subsample selected for luteal increases in negative affect, brooding predicted higher baseline negative affect but still did not predict affective cyclicity. An individual's trait-like propensity to engage in rumination may not be a valid treatment target in premenstrual mood disorders. State-like changes in rumination should still be further explored, and well-powered prospective studies should explore other cognitive and behavioral factors to inform development of targeted psychological treatments for patients with cyclical affective symptoms.

Cyclic Void Growth Model Parameter Calibration of Q460D Steel and ER55-G Welds after Exposure to High Temperatures

When high-strength steel is heated to high temperatures and then cooled naturally, its ductility decreases. In earthquake-prone areas, it is necessary to evaluate the ultra-low cycle fatigue fracture (ULCF) behavior of high-strength steel structures after a fire if these structures are used continuously. However, the ULCF fracture model of high-strength steel subjected to high temperatures followed by natural cooling has not been deeply studied. In view of this, twelve notched, round bar specimens fabricated from Q460D steel and ER55-G welds were heated to 900 °C followed by natural cooling and then cyclic loading experiments and finite element analyses (FEA) were performed on these specimens. The fracture deformation obtained from the experiments was used in the FEA to calibrate the damage degradation parameter of a Cyclic Void Growth Model (CVGM) of Q460D steel and ER55-G welds under this condition. The calibrated values were 0.30 and 0.20, respectively. The calibrated CVGM was employed to predict the number of cycles and the force and displacement at the fracture moment of the notched round bar specimens. The predicted results aligned closely with the experimental results, indicating that CVGM is effective in predicting the fracture of Q460D steel and ER55-G welds following exposure to 900 °C and subsequent natural cooling.

Generalized Model for Inhibitor-Modulated 2D Polymer Growth to Understand the Controlled Synthesis of Covalent Organic Frameworks

Generalized Model for Inhibitor-Modulated 2D Polymer Growth to Understand the Controlled Synthesis of Covalent Organic Frameworks

심리사회적 학교환경에 대한 인식이 학생의 성장에 미치는 영향

Purpose: This study analyzed whether the psychosocial school environment mitigates the detrimental effects of poverty and influences students' initial cognitive (Korean, math, and English grades) and emotional (self-esteem) development during elementary school, as well as their growth trajectories throughout middle and high school. Methods: This study used longitudinal data from the same cohort of students surveyed at three intervals: elementary, middle, and high school spanning a six-year period from 2015, to 2018 and 2021. Data were obtained from the Korea Welfare Panel Study Supplementary Survey on Children.Analysis was conducted using the Multilevel Growth Model to examine the cognitive and emotional development trajectories of students throughout their elementary, middle, and high school years. Results: In terms of cognitive development, the study found that teacher support within the psychosocial school environment positively influenced the growth rate of Korean language subject grades. Regarding emotional growth, factors such as teacher support, school atmosphere, and peer relationships within the psychosocial school environment all exhibited significant positive effects on the initial levels of self-esteem among elementary school students. Additionally, the school atmosphere positively impacted the growth rate of self-esteem. The negative impact of poverty was often diminished or mitigated with the inclusion of variables such as students’ learning attitudes and parental educational involvement and supervision. Furthermore, with the additional inclusion of psychosocial school environment variables, the adverse effects of poverty almost completely disappeared. However, the influence of poverty persisted, manifesting as a negative impact on the initial scores of English subject grades. Conclusion: The psychosocial school environment can positively contribute to students' cognitive and emotional development. Particularly, teacher support has a positive impact on both the cognitive and emotional growth of students, and school climate and peer relationships are positively associated with emotional development. Therefore, efforts should be made in schools to strengthen teacher support, and to foster a positive school climate and peer relationships, aiming for a positive direction in cognitive and emotional development.

Bio-ultrasonic synthesis of tin oxide quantum dots: effect of bio-carbon and their UV photocatalytic activity

An ecofriendly synthesis is realized to elaborate tin oxide quantum dots (SnO2 -QDs) using the plant aqueous extract of Aloe Barbadensis Miller (Aloe Vera) and SnCl4.5H2O at room temperature as a biological solvent and a precursor respectively. The effect of Aloe Vera extract concentration on the properties of SnO2-QDs has been studied. Morphological and structural properties of the as synthesized nanoparticles have been characterized using field effect-scanning electron microscopy (FE-SEM) and x-ray diffraction (XRD). The chemical composition of the nanoparticles was studied by Raman, energy dispersive x-ray (EDX) and Fourier transformation infra-red (FTIR) spectroscopy. The optical properties were investigated by UV–Vis spectrophotometer. The x-ray diffraction analysis showed that all samples have a tetragonal rutile structure, with an estimated crystal size closed to the exciton Bohr radius, indicating a strong confinement of the carriers in the material. The crystallite size of SnO2-QDs nanoparticles decreases as Aloe Vera plant extract concentration increases. The formation of SnO2-QDs and the presence of graphitic carbon in samples were confirmed by Raman spectroscopy, EDX analysis and Fourier transformation infra-red (FTIR) spectroscopy. The blue shift in absorption is the most likely due to the quantum confinement effect. An Ostwald-repining growth model based on the concept of surface energy has been proposed to explain the kinetic growth of SnO2 QDs. The photocatalytic activities of the as-prepared powders were confirmed by the fast and efficient degradation of methylene blue (MB).

다변량 잠재성장모델을 활용하여 부모 지원이 자녀의 자아개념을 매개로 진로성숙도에 미치는 영향 분석

This study sought to examine longitudinally how parental support affects career maturity through children's self-concept. For this purpose, data from the 3rd to 7th years of the KELS 2013 of the Korean Educational Development Institute were used. Descriptive statistics and a multivariate latent growth model were analyzed using five years of longitudinal data from 5,200 students nationwide from the first year of middle school to the second year of high school. As a result, first, parental support, children's self-concept, and career maturity showed a decreasing trend over time. Second, parental support at an early point in time had a positive effect on the children's self-concept and career maturity, and the children's initial self-concept had a positive effect on the initial career maturity. Additionally, changes in parental support had a significant positive effect on changes in children's self-concept. Meanwhile, changes in parental support appeared to be slowing down as they have a negative impact on changes in children's career maturity. Through this, it was confirmed that parental support is an important variable that determines a children's self-concept by influencing the children's self-concept from the beginning to the pattern of change. In addition, the higher the initial parental support, the higher the children's initial career maturity. However, changes in parental support showed a negative relationship with changes in career maturity, so the increase slowed. Based on this, it was suggested that follow-up research was needed to establish institutional alternatives to narrow the gap in students' self-concept and career maturity caused by differences in parental support in the educational field and, lastly, to identify the characteristics of each variable.

Application of growth models to South African Boer goat castrates and does under feedlot conditions

Mathematical models may aid researchers in describing biological processes, like growth, in animals. This study aimed to collect the body weight data of 18 Boer goat castrates and 20 Boer goat does, from birth until maturity, to model growth and determine growth trends. This is a novel investigation as sufficient information on an age-weight database for these two Boer goat sexes from birth to maturity, is lacking. Using age-weight data, four nonlinear models, namely the Brody, Gompertz, Logistic and Von Bertalanffy growth models, were plotted and evaluated. The model parameters of each growth model were compared for differences between the two sexes. The statistical effectiveness of fit was determined for each model using AIC and RMSE, with R2 also being considered. All models except the Brody model, predicted significantly heavier mature weights for castrates. The Brody model was deemed unfit to describe Boer goat growth as the function severely over-predict weights from birth until maturity for both sexes. The Von Bertalanffy (R2 = 91.3) and Gompertz functions (R2 = 91.3) showed the best fit for Boer goat castrates, while the Gompertz model (R2 = 95.1) showed the best fit for Boer goat does. The Gompertz function is the preferred model to depict Boer goat growth overall, as it accurately characterized growth of both sexes. According to the Gompertz model the age at which the inflection point of the growth curve was reached, did not differ significantly between castrates and does (141.80 days versus 136.31 days). There was also no significant difference in maturation rate between the two sexes.