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.

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.

Innovating Regional Policy Frameworks in China: The Strategic Zone + Type Zone Model for Sustainable Growth

Innovating Regional Policy Frameworks in China: The Strategic Zone + Type Zone Model for Sustainable Growth

Cadherin Expression is Regulated by Mechanical Phenotypes of Fibroblasts in the Perivascular Matrix.

The influence of mechanical forces generated by stromal cells in the perivascular matrix is thought to be a key regulator in controlling blood vessel growth. Cadherins are mechanosensors that facilitate and maintain cell-cell interactions and blood vessel integrity, but little is known about how stromal cells regulate cadherin signaling in the vasculature. Our objective was to investigate the relationship between mechanical phenotypes of stromal cells with cadherin expression in 3D tissue engineering models of vascular growth. Stromal cell lines were subjected to a bead displacement assay to track matrix distortions and characterize mechanical phenotypes in 3D microtissue models. These cells included human ventricular cardiac (NHCF), dermal (NHDF), lung (NHLF), breast cancer-associated (CAF), and normal breast fibroblasts (NBF). Cells were embedded in a fibrin matrix (10mg/mL) with fluorescent tracker beads; images were collected every 30min. We also studied endothelial cells (ECs) in co-culture with mechanically-active or -inactive stromal cells and quantified N-Cad, OB-Cad, and VE-Cad expression using immunofluorescence. Bead displacement studies identified mechanically-active stromal cells (CAFs, NHCFs, NHDFs) that generate matrix distortions and mechanically-inactive cells (NHLFs, NBFs). Compared to ECs only, CAFs + ECs as well as NBFs + ECs in 3D co-culture significantly decreased expression of VE-Cad; in addition, the Pearson's Correlation Coefficient for N-Cad and VE-Cad showed a strong correlation (>0.7), suggesting cadherin colocalization. Using a microtissue model, we demonstrated that mechanical phenotypes associated with increased matrix deformations correspond to enhanced angiogenic growth. The results could suggest a mechanism to control tight junction regulation in developing vascular beds for tissue engineering scaffolds or understanding vascular growth during developmental processes. Our studies provide novel data for how mechanical phenotype of stromal cells in combination with secreted factor profiles is related to cadherin regulation, localization, and vascularization potential in 3D microtissue models.

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

Abstract 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 of absorption is the most likely attributed 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 improvement of photocatalytic activity of the photocatalyst for degradation of methylene blue (MB) might be caused by the size and the high surface area of the material.

Childhood anhedonia symptoms and stressful life events predict the development of reward-related brain activity across adolescence.

The reward positivity (RewP) is an event-related potential that indexes reinforcement learning and reward system activation. The RewP has been shown to increase across adolescence; however, most studies have examined the RewP across two assessments, and no studies have examined within-person changes across adolescence into young adulthood. Moreover, the RewP has been identified as a neurobiological risk factor for adolescent-onset depression, but it is unclear whether childhood psychosocial risk factors might predict RewP development across adolescence. In a sample of 317 8- to 14-year-old girls (Mage = 12.4, SD = 1.8), the present study examined self-report measures of depression symptoms and stressful life events at baseline and the ΔRewP during the doors guessing task across three timepoints. Growth modeling indicated that, across all participants, the ΔRewP did not demonstrate linear change across adolescence. However, baseline anhedonia symptoms predicted within-person changes in the ΔRewP, such that individuals with low anhedonia symptoms demonstrated a linear increase in the ΔRewP, but individuals with high anhedonia symptoms had no change in the ΔRewP across adolescence. Similar patterns were observed for stressful life events. The present study suggests that childhood risk factors impact the development of reward-related brain activity, which might subsequently increase risk for psychopathology.

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.

Dynamics of collisions and uptake of alcohol molecules with hydrated nitric acid clusters.

We investigate the collisions of different alcohol molecules with hydrated nitric acid clusters using a molecular beam experiment and molecular dynamics simulations. The uptake cross sections σp for the molecules evaluated from the experiment are in excellent agreement with the simulations. This suggests that (i) the nontrivial assumptions implemented in the evaluation procedure of the experimental data are valid, and (ii) the simulations describe correctly the major processes in the molecule-cluster collisions. We observe that σp decreases with the increasing alkyl chain length of the alcohol, and also with the branching of the molecules that have the same mass but different structures. These systematic trends can be rationalized based on the accessibility of the hydrophilic OH group, which decreases with the increasing chain length and steric hindrance. The observed trends and their interpretation differ significantly from the simple model of hard-sphere collisions. The obtained data shall be beneficial not only for the fundamental understanding of the molecule-cluster collisions, but also in the modelling of atmospheric new-particle formation and aerosol growth.

Universality of phenotypic distributions in bacteria

Some phenotypic properties in bacteria exhibit universal statistics, with distributions collapsing under scaling. The extent and origins of such universality are not well understood. Using phenomenological modeling of growth and division, we identify compound “shape factors” that describe the distributions throughout a large set of single-cell data. We find that the emergence of universal distributions is associated with the robustness of shape factors across conditions, explaining the universality of cell size and highly expressed protein content and the nonuniversality of times between consecutive divisions. A wide range of experimental data sets support our theory quantitatively. Published by the American Physical Society 2024

Commodity price volatility, institutions and economic growth: An empirical investigation

AbstractThis article investigates the role of institutional quality in transmitting effects of commodity price volatility to economic growth. To do so, we collect data on 107 primary commodity exporting countries in both developing and developed ones over the period 1976–2015. Our empirical approach is based on Solow growth model framework (Solow, R. M. (1956). The Quarterly Journal of Economics, 70(1), 65) and consists of estimating a dynamic panel model using the two‐step system GMM estimator. Our results show evidence that commodity price booms are associated with good economic performances that are unfortunately wiped out by the negative effects of price volatility in developing commodity‐dependent countries (CDCs). The main channel through which this volatility affects economic growth turns out to be through factor productivity. Finally, we have formally established that the negative effect of price volatility in CDCs is mainly due to the poor quality of institutions in these countries. These results suggest that it is important for commodity‐exporting economies, especially developing CDCs, to work on building strong economic and political institutions to guard against the risk of commodity price volatility.

Understanding the Impact of Changes in Application Characteristics on SRGM

Due to the increasing reliance on technology in nearly every industry over the past three decades, it has become necessary to evaluate the performance of a software product prior to its formal release in the market. The properties of a software application, such as its complexity and lines of code, are subject to change over time as a result of factors namely the testing environment, allocation of resources, testing efficiency, and testing team’s expertise. The assumption of constant Fault Detection Rate (FDR) may not accurately anticipate the potential number of bugs correctly. Keeping all these considerations in mind, a framework is developed to incorporate change point in the development of a testing effort-based Software Reliability Growth Model (SRGM) that takes into account the effect of application characteristics under both perfect and imperfect debugging settings. In addition, these outcomes are compared to the model without a change point. The proposed model is validated on two real-life software fault datasets. The results demonstrate that the proposed model performs better than the model without a change point.

Politics of household indebtedness in Turkey

ABSTRACT This paper deals with how Justice and Development Party (AKP) governments navigated the politics of household indebtedness in Turkey and utilized it towards the 2023 elections. It argues that household debt is a political tool with positive and negative consequences for incumbent governments. Households have been able to access debt instruments such as credit cards, consumer credit, car loans, and mortgages in Turkey since the onset of financialisation in the 2000s. AKP governments have benefited from the micro-level household wealth/debt accumulation as well as its macro-level economic implications for the construction-led, credit-dependent economic growth model. On the other hand, household debt has had destructive societal consequences such as bankruptcies, divorces, and suicides that became commonplace in the opposition narratives. Pinpointing the responsibility for indebtedness among households, financial system, regulatory agencies, and government, as well as devising policy solutions, has become a political struggle in the months leading up to the 2023 elections.

Endogenous Financial Friction and Growth

Abstract Financial frictions have been considered a crucial factor in explaining growth disparities across countries. These frictions are typically viewed as an exogenous constraint on borrowing capacity that is assumed to be invariant to economic conditions, such as the level of GDP and business cycle fluctuations. However, assuming the exogenous constraint on borrowing often leads to unrealistic dynamics in macroeconomic variables, such as constant investment-to-GDP and loan-to-value ratios. Motivated by these limitations, we develop a growth model in which the severity of the borrowing constraint is endogenously determined. The borrowing constraint adversely affects growth and amplifies the negative effect of volatility on growth. However, these growth effects gradually disappear as the economy continues to grow, because debtors become more willing to honor their debts along with economic growth, resulting in an endogenous relaxation of the borrowing constraint.

Should we be sceptical in the face of calls for degrowth?

In recent years, an ‘international’ unanimity has been reached as to the importance of collective collaboration to avoid the negative effects of climate change. This requires rethinking the old or traditional development model based on economic growth as the exclusive indicator of wealth. Thus, humanity has an urgent need to adopt a new, more humane and fairer economic model that constitutes an alternative to the models of exponential growth that have dominated in the last two centuries. To do so, humanity is looking to the Degrowth model as a potential concept that aims to reduce wealth from pollutants, seeks more justice (as equity), and the improvement of the capabilities of those who are poor and disadvantaged (in the sense of Amartya Sen and Martha Nussbaum). The purpose of this article is to question this model and whether it actually does improve environmental quality. Additionally, if the response is positive, another question arises: How to finance degrowth especially when we seek other less polluting energy sources whose costs seem to be very high?

Precision Regulation and Forecasting of Greenhouse Tomato Growth Conditions Using an Improved GA-BP Model

Tomatoes are annual herbaceous plants of the family Solanaceae. They have very stringent requirements for their growing environment and climate conditions. To precisely control the greenhouse environment for tomato growth, this project designed and implemented a monitoring system utilizing programmable logic controllers and a data acquisition system for monitoring. Sensors are installed at key locations in the greenhouse, such as near the ground, in the plant canopy, and under the roof, to monitor environmental parameters such as temperature, humidity, light intensity, and carbon dioxide concentration in real time. A three-layer feedforward GA-BP neural network model was established using soil temperature, soil humidity, air humidity, and illumination as predictive parameters. This technology predicts optimal environmental parameters and performs real-time monitoring and intelligent control, overcoming the traditional BP neural network’s drawbacks of slow convergence, susceptibility to disturbance, and poor generalization ability, with the current model’s average prediction error being less than 5%. It provides a theoretical basis and decision support for precision control and related environmental forecasting in agricultural projects. Based on the growth characteristics, physiological and morphological features of tomatoes, and the comprehensive impact of planting conditions, the technology enhances tomato yield and quality while reducing production costs and labor inputs. It mainly includes the establishment of tomato growth models, measurement and control of environmental parameters, and the design and optimization of intelligent decision control systems. Research outcomes in this field are significant for improving agricultural production efficiency, ensuring food security, and promoting sustainable agricultural development.

Bioeconomics of juvenile seahorse (Hippocampus erectus) culture: Optimal harvest time

AbstractThe culture of seahorses Hippocampus erectus in captivity represents a window of opportunity for the diversification of the aquaculture activity in the ornamental industry. In this study, we have constructed a bioeconomic model to evaluate the optimal harvest time (OHT) over a culture period of 562 days. The bioeconomic model was integrated with three submodels: biological, technological, and economic. Three different mortality rates were used for different periods in culture, registering a higher survival in the period from 0 to 60 days with a rate of 53.4%. The sensitivity analysis showed that the mortality rate in this period was the parameter with the greatest influence on the benefits. The Von Bertalanffy growth model was indicated to describe the growth of H. erectus given its statistical significance using Theil's inequality coefficient, registering parameters of (L∞ = 141.62 mm) and (k = 0.0049 month‐1). The bioeconomic model determined the OHT in the 4th month of culture, the time when the maximum profit is recorded. It is concluded that the culture presents challenges to be addressed although the bioeconomic model allows for demonstrating the OHT.

Uncovering the impact of cultural heritage on economic growth: empirical evidence from Greek regions, 2000–2019

AbstractThis paper brings empirical evidence on the role of cultural heritage assets in promoting economic growth. The case of Greece at regional level over the period 2000–2019 is taken as an example, owing to important cultural heritage endowment. Economic growth is approached by formulating a neoclassical growth model augmented with a dynamic cultural heritage index. The relationship between economic growth and cultural heritage is examined through a heterogeneous and cross-correlated panel data analysis. The empirical results reveal a positive impact of cultural heritage endowment on economic growth. Also, a significant positive influence of physical capital and a negative impact of unemployment on the economy are evidenced. The conclusions drawn could be useful to regions and countries to upgrade their cultural heritage endowment to accelerate economic growth.

Trajectory patterns and influencing factors of supportive care needs in stroke patients: A longitudinal study.

To investigate the trajectory patterns and influencing factors of supportive care needs in stroke patients. A longitudinal study. In total, 207 stroke patients who received treatment at the Department of Neurology in a hospital in Xuzhou between July 2022 and July 2023 were recruited using convenience sampling. Questionnaires including supportive care needs, hospital anxiety and depression scale, and the Barthel index were investigated at baseline and at 1, 3, and 6 months. A latent class growth model was applied to identify the supportive care needs trajectories. Multiple logistic regression was used to determine the predictors for membership. This study adheres to STROBE reporting guidelines. Three patterns of supportive care needs trajectories were identified: A high needs slow decline group (20.8%), a medium needs stable group (56.5%) and a medium needs rapid decline group (22.7%). Based on further analysis, the findings indicated that age, education level, monthly income, comorbidity, activities of daily living, anxiety and depression were associated with the trajectory categories of supportive care needs with stroke patients. This study demonstrates heterogeneity in changes in supportive care needs among stroke patients. Healthcare providers need to consider these different categories of needs and develop individualized care measures based on the characteristics of different patients. Healthcare providers should be aware of the fluctuations in care needs of stroke patients at various stages. Additionally, the study aimed to identify patients' specific needs based on their circumstances, monitor the rehabilitation process and establish a more personalized and optimized care plan through multidisciplinary collaboration. The ultimate goal was to alleviate symptomatic distress and address the long-term care needs of patients. No patient or public contribution.