Growth Model Research Articles

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

Endogenous growth and human capital accumulation in a data economy

We build an endogenous growth model featuring a new mode of human capital accumulation in a data economy. Data are generated as the byproducts of economic activities and then used by consumers for human capital accumulation apart from education. Although we find similar growth patterns compared with those in the related literature, economic growth is further accelerated by the new use of data factor. Quantitative analyses suggest that although the accumulation of human capital is promoted by the increasing importance of data, this promotion is not unlimited since data may over-absorb resources and crowd out education. In the transition dynamics, we see that consumers suffer temporary welfare loss. However, as data become a key factor in human capital accumulation, welfare ultimately increases. Our paper provides a first view of the effect of the data factor in the process of human capital accumulation.

Integrated deviance information criterion for spatial autoregressive models with heteroskedasticity

In this study, we introduce the integrated deviance information criterion (DIC) for nested and non-nested model selection problems in heteroskedastic spatial autoregressive models. In a Bayesian estimation setting, we assume that the idiosyncratic error terms of our spatial autoregressive model have a scale mixture of normal distributions, where the scale mixture variables are latent variables that induce heteroskedasticity. We first derive the integrated likelihood function by analytically integrating out the scale mixture variables from the complete-data likelihood function. We then use the integrated likelihood function to formulate the integrated DIC measure. We investigate the finite sample performance of the integrated DIC in selecting the true model in a simulation study. The simulation results show that the integrated DIC performs satisfactorily and can be useful for selecting the correct model in specification search exercises. Finally, in a spatially augmented economic growth model, we use the integrated DIC to choose the spatial weights matrix that leads to better predictive accuracy.

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.

Stochastic Optimization of the Management Schedule of Korean Pine Plantations

Korean pine is one of the most important tree species in northeastern China, where Korean pine plantations produce timber and edible seeds. Often, seeds create more income than timber. Predicting the timber and cone yields of alternative management schedules of the plantations involves uncertainty because the future climatic conditions for tree growth and cone production are unknown. This study developed a simulation model that generates stochastic variation around the predictions of tree growth and cone yield models, allowing the forest manager to seek cutting schedules that maximize the expected amounts of timber or cones, or the expected economic profit, under uncertain future states of nature. Stochastic analysis also facilitates management optimizations for different risk attitudes. The differential evolution algorithm and the developed stochastic simulation model were used to optimize the management of planted Korean pine. Timber and cone yields of a management schedule were calculated under 100 different scenarios for tree growth and cone production. When the growth and cone yield scenarios were stationary (no temporal trends), the optimal management schedules were similar to those of deterministic optimization. The benefits of stochastic optimization increased when it was assumed that the tree growth scenarios may contain climate-change-induced trends. Non-stationary growth variation led to shorter optimal rotation lengths than stationary growth variation. Increasing risk tolerance shortened optimal rotations.

An Attempt for a New Growth Model Based on Inter-class Mobility Probability

After Kuznets' pioneering study in 1955, the relationship between growth and income distribution attracted the attention of researchers. Approaches used to explain the relationship between growth and income distribution can be summarized as wealth and redistribution, international trade, technological development, macroeconomic volatility and political economy. In this study, firstly, the theoretical background and literature regarding these approaches are mentioned. Later, based on Akerlof and Yellen's theories on the fair wage-productivity relationship, a new model was tried to be developed that links economic growth with inter class mobility probability. The model is based on the hypothesis that in a hypothetical society of two-class without government, there will be an increase in the productivity of individuals belonging to the lower class as the probability of moving up the class increases. As the probability of individuals belonging to the lower class moving up increases, the probability of individuals belonging to the upper class falling down the class also increases. For this reason, the increase in the transition between classes will lead to an increase in the efforts of individuals belonging to the upper class. An increase in the effort of both classes will result in higher output and therefore higher growth. For this reason, as the income distribution becomes more fair, the growth rate will also increase, but if the income is distributed completely equally, the performance of individuals will decrease because there is no possibility of moving to upper class. Therefore, income inequality up to a certain level motivates individuals, while income inequality above the optimal level demotivates individuals. In other words, the relationship between income inequality and growth is non-linear. Finally, the game theory version of the model is introduced in the study.

Self‐Assembled Molecules Fostering Ordered Spatial Heterogeneity for Efficient Ruddlesden‐Popper Perovskite Solar Cells

Abstract2D Ruddlesden‐Popper perovskites (RPP) with formamidinium‐cesium (FAC) alloyed cations possess powerful thermal‐moisture stability. However, their photovoltaic performance is hindered by the elusive spatial heterogeneity at multiscale lengths, highly associated with their coupled charge selective contacts. Herein, it reports on how the rational formation of self‐assembly molecules (SAMs) govern the orderliness of the spatial heterogeneity and crystal growth model in FACs‐RPP films, which is proposed to dictate the charge‐carrier dynamics. Unlike the disordered RPP film driven by the amorphous polymeric contacts, the laterally ordered crystallized SAM contacts facilitate a spatially ordered 2D/3D heterogeneity of FACs‐RPP film in long range, where distinct minor 2D phases are tightly coupled in short range. Such ordered heterogeneity can improve the energy transfer efficiency, facilitating the charge‐carrier dynamics in a well‐aligned 2D/3D landscape is discovered. Finally, the champion solar cells using selective SAM‐based FACs‐RPP films (n = 5) yield an efficiency of 18.85% (certified 18.19%) and excellent damp‐heat/operational stability, ranking in the top league of reported 2D RPP solar cells. More importantly, this SAM‐based principle can be adapted to diverse 2D structures, active areas, and substrate types. This work provides design directions for leveraging bottom‐selective contacts to tune spatial heterogeneity in state‐of‐the‐art 2D RPP optoelectronics.

A Numerical Time Integration Procedure for Secondary Dendrite Arm Spacing in Hyper-Peritectic Steel Alloys

AbstractA numerical time integration procedure for the calculation of the secondary dendrite arm spacing (SDAS) in FeC hyper-peritectic alloys is presented, a preferred group of low-carbon casting steel. The procedure incorporates a three-stage thin arm dissolution model, which is solved at each time step using Newton–Raphson iteration. This is coupled to a coarsening model based on the integral forms of the dissolution model, which are solved using Gaussian quadrature, as well as a growth model for solid fraction evolution. The procedure can easily be embedded into numerical models for solidification, in which the space–time evolution of the SDAS is required for determining the dynamic permeability in the mushy zone. Higher order approximations for both growth and solute concentration evolution can easily be incorporated. Temperature dependence of thermophysical parameters is taken into account using inter-dendritic solidification empirical models, and an alloy-specific peritectic reaction constant is used to determine the isothermal peritectic holding time. The procedure is validated against experimental data presented in literature. Various cases of SDAS as a function of local solidification time, cooling rate and carbon composition are investigated. The method is compared to experimental results of SDAS obtained from test castings of a hyper-peritectic steel alloy and can be used to iteratively determine the alloy-specific peritectic reaction constant by comparing the solid fraction evolution during the peritectic reaction with that found from the experimental cooling curve.

Making Predictions Using Poorly Identified Mathematical Models

Many commonly used mathematical models in the field of mathematical biology involve challenges of parameter non-identifiability. Practical non-identifiability, where the quality and quantity of data does not provide sufficiently precise parameter estimates is often encountered, even with relatively simple models. In particular, the situation where some parameters are identifiable and others are not is often encountered. In this work we apply a recent likelihood-based workflow, called Profile-Wise Analysis (PWA), to non-identifiable models for the first time. The PWA workflow addresses identifiability, parameter estimation, and prediction in a unified framework that is simple to implement and interpret. Previous implementations of the workflow have dealt with idealised identifiable problems only. In this study we illustrate how the PWA workflow can be applied to both structurally non-identifiable and practically non-identifiable models in the context of simple population growth models. Dealing with simple mathematical models allows us to present the PWA workflow in a didactic, self-contained document that can be studied together with relatively straightforward Julia code provided on GitHub. Working with simple mathematical models allows the PWA workflow prediction intervals to be compared with gold standard full likelihood prediction intervals. Together, our examples illustrate how the PWA workflow provides us with a systematic way of dealing with non-identifiability, especially compared to other approaches, such as seeking ad hoc parameter combinations, or simply setting parameter values to some arbitrary default value. Importantly, we show that the PWA workflow provides insight into the commonly-encountered situation where some parameters are identifiable and others are not, allowing us to explore how uncertainty in some parameters, and combinations of parameters, regardless of their identifiability status, influences model predictions in a way that is insightful and interpretable.

Modeling dominant height growth of teak plantations in the Caribbean region of Colombia

Identifying sites with adequate biological productivity is a critical factor in ensuring timber production and the profitability of forest-based investments. The productivity of forest sites is influenced by climatic, edaphic and topographic variables, as well as by silvicultural practices. Site index is a phytocentric method widely used to assess site productivity and its estimation is based on dominant height growth modeling. Teak is the fifth most planted forest species in Colombia, and its importance is associated with high economic returns and profitability. This study aims to model dominant height growth using the generalized algebraic difference approach for teak plantations established in the Caribbean region of Colombia. The Lundqvist-Korf model, in which the correlation of the residuals was handled with a continuous autoregressive specification of the first order, resulted in a satisfactory statistical estimation of the dominant height growth. The results indicate that in the Caribbean region of Colombia, productive sites for the establishment of teak plantations can be found as productive as in some tropical American countries and better than some sites in Asian countries. This suggests a potential for the expansion of teak plantations and forest-based investments in Colombia.

Targeting BMP2 for therapeutic strategies against hepatocellular carcinoma

ObjectivesThis study aimed to investigate the role of BMP2 in hepatocellular carcinoma (HCC) growth and metastasis using a dual approach combining single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq. MethodsscRNA-seq data from the GEO database and bulk RNA-seq data from the TCGA database were analyzed. Differentially expressed marker genes of endothelial cells were identified and analyzed using enrichment analysis, PPI analysis, correlation analysis, and GSEA. In vitro, experiments were conducted using the Huh-7 HCC cell line, and in vivo, models of HCC growth and metastasis were established by knocking down BMP2. ResultsThe scRNA-seq analysis identified BMP2 as a key marker gene in endothelial cells of HCC samples. Elevated BMP2 expression correlated with poor prognosis in HCC. In vitro experiments showed that silencing BMP2 inhibited the proliferation, migration, and invasion of liver cancer cells. In vivo studies confirmed increased BMP2 expression in HCC tissues, promoting angiogenesis and HCC growth. ConclusionThis study highlights the role of BMP2 in tumor angiogenesis and HCC progression. Targeting BMP2 could be a promising therapeutic strategy against HCC.

ANALYSIS AND OPTIMAL CONTROL OF HIV GROWTH MODEL IN THE BODY WITH ANTIRETROVIRAL THERAPY

Human Immunodeficiency Virus (HIV) is a virus that affects the human immune system. HIV infection causes a decrease in the body's immunity because the virus attacks immune-building cells, especially T-CD4 cells. Currently, there is no treatment that can cure or eliminate HIV, but antiretroviral therapy can be done. This study discusses the growth model of HIV in the body that is given control in an effort to maximize healthy T-CD4 cells. In this model, the infection-free and infected equilibrium points are also discussed and their stability is analyzed. Then the optimal control is solved using the Pontryagin Maximum Principle method and solved numerically using the fourth-order Runge Kutta method. Based on the analysis and simulation results, the system is asymptotically stable around the infection-free equilibrium point and unstable around the infected equilibrium point. Simulation results show that with the control of antiretroviral therapy, the T-CD4 cell population grows significantly which can improve the quality of life of patients. And the growth of HIV in the body can be inhibited until it cannot reproduce itself.

Using moderated nonlinear factor models to adjust for differential item functioning in the Student-Teacher Relationship Scale from kindergarten to Grade 6

Prior research has demonstrated that children form developmentally salient relationships with teachers and that these relationships are uniquely predictive of subsequent functioning both in and outside of school. However, prior work estimating trajectories and predictors of teacher-student relationship quality has failed to test and adjust for bias in questionnaire items. The present study used longitudinal data from the NICHD Study of Early Child Care and Youth Development (SECCYD; N = 1140) to test and adjust for measurement bias in the Student-Teacher Relationship Scale (STRS; Pianta, 2001) across grades (K–6) and sociodemographic characteristics (i.e., birth sex, race/ethnicity, family income-to-needs ratio, and maternal education) to generate less biased estimates of trajectories of teacher-student relationship quality. Results identified differential item functioning for three of seven STRS items assessing conflict and three of eight STRS items assessing closeness, with items functioning differentially across child grade, birth sex, race/ethnicity, and maternal education level. Comparisons of growth models using non-adjusted and adjusted STRS scores highlight substantive differences between scoring approaches, such that the effects of race/ethnicity, maternal education, and maternal sensitivity on teacher-student relationship quality were masked prior to adjusting for item bias. These findings demonstrate the importance of testing and correcting for item bias in questionnaire-based assessments of teacher-student relationship quality to ensure valid conclusions.

Effect of growth rate on the incorporation of silicon impurity in single crystal diamond

In this paper, we systematically investigate the influence of growth rate on the incorporation of silicon in single crystal diamond. The intensity of SiV− center is significantly enhanced with the increase of methane flow rate. By analyzing the optical emission spectrum and photoluminescence spectrum of samples grown with different methane concentrations, the enhancement of SiV− intensity is not associated with the Si–C concentration in the precursor but with the higher growth rate. In addition, an increased oxygen flow rate significantly decreases the intensity of SiV− center, which is attributed to the formation of insoluble silicon oxide as well as the relatively lower growth rate. Finally, we propose a growth model to explain the effect of growth rate on the incorporation of silicon impurity.

Chemotherapy Regimen Optimization Using a Two-Archive Multi-Objective Squirrel Search Algorithm

Chemotherapy is one of the most effective treatments for cancer, but the efficacy of standard chemotherapy regimens is often limited by toxicities and the individual heterogeneity of cancers. Precise dosing is an important tool to improve efficacy and reduce significant differences in toxicity. However, most of the existing studies on chemotherapy optimization fail to fully consider the toxic side effects, drug resistance, and drug combinations, and thus the chemotherapy regimens obtained may face difficulty in achieving the expected efficacy and also affect the subsequent treatment. Therefore, this paper establishes a tumor growth model for the combination chemotherapy of cell cycle-specific and non-cycle-specific drugs and includes the factors of acquired drug resistance and toxic side effects, proposing an improved multi-objective Squirrel Search Algorithm, the TA-MOSSA, to solve the problem of accurate chemotherapy drug optimization. In this paper, experiments were conducted to analyze the efficacy of chemotherapy dosing regimens obtained by the TA-MOSSA based on the tumor growth model, and the results show that the TA-MOSSA can provide effective chemotherapy regimens for patients who take different treatment approaches.

Financial Development and Its Effect on Inclusive Growth in Kenya 2000 – 2022

Purpose: In the past decade, Kenya’s economy registered an average real GDP growth rate of 4.63 percent. Despite this growth, many people have been locked out of social and economic opportunities, with 19.1 percent of the Kenyan population living in poverty. This has intensified the need for inclusive growth, a growth model that promotes shared prosperity. Several studies have shown that financial systems that function well play a great role in the economy through the provision of key financial services that drive growth. However, there is a lack of substantial inquiry into financial development and inclusive growth in Kenya. This study sought to examine this relationship for the period 2000-2022. Methodology: The study employed a causal research design and used time series data that was collected from various databases. The level of inclusiveness in Kenya was analyzed using an inclusiveness matrix. An inclusive growth index was constructed, which was then used to empirically test the effect of financial development on inclusive growth. The data was presented in tables and figures. Findings: The inclusiveness matrix shows that despite positive economic growth rates, there is a low rate of equity growth, which shows that Kenya has a low level of inclusivity. The empirical results show that bank deposits and private-sector credit have a positive and statistically significant effect on inclusive growth. A 1% increase in bank deposits leads to a 0.074% increase in inclusive growth. When private-sector credit increases by 1%, inclusive growth expands by 0.070%. Bank return on assets has a positive but insignificant effect on inclusive growth. The study confirms that financial depth and access to financial services are the most conducive to inclusive growth in Kenya. Other determinants of inclusive growth include initial income, human capital development and macroeconomic stability. The overall findings suggest that financial development can be used to create economic opportunities for poor people in Kenya, thus reducing income disparities. Unique Contribution to Theory, Practice and Policy: The study has contributed to the ongoing conversation on inclusive growth, specifically on its measurement. The empirical results on the finance-inclusiveness nexus provide evidence-based policy interventions that can help in reducing income disparities and enhancing shared prosperity. The findings imply that policymakers and practitioners need to focus their attention on promoting financial access and financial depth in marginalized regions to create a significant impact on inclusive growth in Kenya.

Geometric growth of the normal human craniocervical junction from 0 to 18 years old.

The craniocervical junction (CCJ) forms the bridge between the skull and the spine, a highly mobile group of joints that allows the mobility of the head in every direction. The CCJ plays a major role in protecting the inferior brainstem (bulb) and spinal cord, therefore also requiring some stability. Children are subjected to multiple constitutive or acquired diseases involving the CCJ: primary bone diseases such as in FGFR-related craniosynostoses or acquired conditions such as congenital torticollis, cervical spine luxation, and neurological disorders. To design efficient treatment plans, it is crucial to understand the relationship between abnormalities of the craniofacial region and abnormalities of the CCJ. This can be approached by the study of control and abnormal growth patterns. Here we report a model of normal skull base growth by compiling a collection of geometric models in control children. Focused analyses highlighted specific developmental patterns for each CCJ bone, emphasizing rapid growth during infancy, followed by varying rates of growth and maturation during childhood and adolescence until reaching stability by 18 years of age. The focus was on the closure patterns of synchondroses and sutures in the occipital bone, revealing distinct closure trajectories for the anterior intra-occipital synchondroses and the occipitomastoid suture. The findings, although based on a limited dataset, showcased specific age-related changes in width and closure percentages, providing valuable insights into growth dynamics within the first 2 years of life. Integration analyses revealed intricate relationships between skull and neck structures, emphasizing coordinated growth at different stages. Specific bone covariation patterns, as found between the first and second cervical vertebrae (C1 and C2), indicated synchronized morphological changes. Our results provide initial data for designing inclusive CCJ geometric models to predict normal and abnormal growth dynamics.

The Longitudinal Mediating Role of Peer Attachment in the Relationship between Affective School Environment and Children's Sense of Community

The purpose of this study was to identify the longitudinal mediating effects of peer attachment on the relationship between psychological school environment and children's sense of community. Data on 1,088 children were obtained from the 10<sup>th</sup>, 11<sup>th</sup>, and 13<sup>th</sup> Panel Study on Korean Children in the 3rd 4th, and 6th grades. The data were analyzed using descriptive statistics, Cronbach's α, Pearson's correlation, a latent growth model, and a multivariate latent growth model. All analyses were conducted in SPSS 25.0 and AMOS 23.0. The principal results were as follows. First, children's peer attachment gradually decreased over time. Moreover, individual differences existed in the initial values and rates of change. Second, the psychological school environment in the 3rd grade positively influenced children's initial peer attachment, which then exerted a positive impact on children's sense of community in the 6th grade. Second, the psychological school environment in the 3rd grade negatively influenced children's rates of change, which also exerted a positive impact on children's sense of community in the 6th grade. Finally, the initial value and rates of change of peer attachment were significant mediating effects of the relationship between the psychological school environment in the 3rd grade and children's sense of community in the 6th grade. The findings highlight the necessity of creating a psychological school environment that develops peer attachment and a sense of community among children.

Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system

Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar’s anthesis and physiological maturity, with observed value falling within 5% of the model’s predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9–16%. The study also demonstrated the model's ability to accurately capture soil nitrate–N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop’s growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further.

Exercise, grit, and life satisfaction among Korean adolescents: a latent growth modeling analysis

BackgroundLife satisfaction among Korean students is declining substantially, and multifaceted improvement efforts are required.MethodsWe analyzed longitudinal change trajectories for exercise, grit, and life satisfaction levels among Korean adolescents using latent growth modeling with longitudinal data from the Korean Children and Youth Panel Surveys of 2,142 students (male: 1,070, female: 1,072) from sixth grade (2020) through eighth grade (2022).ResultsThe model, which tracked linear changes in the students’ exercise, grit, and life satisfaction, showed consistent declines over three school years for all variables. We also identified a longitudinal causal relationship among exercise, grit, and life satisfaction. A higher grit intercept was associated with higher intercept for—and a partial mediating effect between—exercise and life satisfaction. The grit slope was positively related to the life satisfaction slope, and both the intercept and exercise slope had positive effects on life satisfaction. Moreover, grit had a longitudinal mediating effect between exercise and life satisfaction.ConclusionsWe discuss the longitudinal change trajectories of exercise, grit, and life satisfaction, the causal and mediating effects among them, and the implications of the findings. These findings bolster our understanding of Korean adolescents’ life satisfaction and have practical significance for designing programs to improve their quality of life.