Comparison of six statistical approaches in the selection of appropriate fish growth models

The performance of six statistical approaches,which can be used for selection of the best model to describe the growth of individual fish,was analyzed using simulated and real length-at-age data.The six approaches include coefficient of determination(R2),adjusted coefficient of determination(adj.-R2),root mean squared error(RMSE),Akaike's information criterion(AIC),bias correction of AIC(AICc) and Bayesian information criterion(BIC).The simulation data were generated by five growth models with different numbers of parameters.Four sets of real data were taken from the literature.The parameters in each of the five growth models were estimated using the maximum likelihood method under the assumption of the additive error structure for the data.The best supported model by the data was identified using each of the six approaches.The results show that R2 and RMSE have the same properties and perform worst.The sample size has an effect on the performance of adj.-R2,AIC,AICc and BIC.Adj.-R2 does better in small samples than in large samples.AIC is not suitable to use in small samples and tends to select more complex model when the sample size becomes large.AICc and BIC have best performance in small and large sample cases,respectively.Use of AICc or BIC is recommended for selection of fish growth model according to the size of the length-at-age data.

Crystal Growth Models of Dexamethasone Sodium Phosphate in a MSMPR Reactive Crystallizer

The reactive crystallization process of dexamethasone sodium phosphate was investigated in a continuous mixed-suspension, mixed-product-removal(MSMPR) crystallizer. Analyzing experimental data, it was found that the growth of product crystal was size-dependent. The Bransom, CR, ASL, M J2 and M J3 size-dependent growth models were discussed in details. Using experimental steady state population density data of dexamethasone sodium phosphate, parameters of five size-dependent growth models were determined by the method of non-linear least-squares. By comparison of experimental population density and linear growth rate data with those obtained from the five size-dependent growth models, it was found that the MJ3 model predicts the growth more accurately than do the other four models. Based on the theory of population balance, the crystal nucleation and growth rate equations of dexamethasone sodium phosphate were determined by non-linear regression method. The effects of different operation parameters such as supersaturation, magma density and temperature on the quality of product crystal were also discussed, and the optimal operation conditions were derived.

A Rice Growth Models (RGM) System by Object-Oriented Programming with Visual C++

Object-oriented programming divides the crop production into subsystems and simulates their behaviors. Many classes were designed to simulate the behaviors of different parts or different physiological processes in crop production system. At the same time, many classes have to be employed for bettering user's interface. But how to manage these classes on a higher level to cooperate them into a perfect system is another problem to study. The Rice Growth Models (RGM) system represents an effort to define and implement a framework to manage these classes. In RGM system, the classes were organized into the model-document-view architecture to separate the domain models, data management and user interface. A single document with multiple views interface frame window was adopted in RGM. In the architectures, the simulation models only exchange data with documents while documents act as intermediacies between simulation models and interfaces. Views get data from documents and show the results to users. The classes for the different functions can be grouped into different architectures. Different architectures communicate with each other through documents. The classes for the different functions can be grouped into different architectures. By using the architecture, communication between classes is more efficient. Modeler can add classes in architectures or other architectures to extend the system without having to change system structure, which is useful for construction and maintenance of agricultural system models.

Construction of Clonal Growth Models in Trifolium repens

The suitability of models for describing the clonal growth of Trifolium repens population was discussed. The results showed that deterministic models were inadequate for describing its clonal growth, but the diffusion models and the randomwalk models suited for the clonal growth characteristics of the population. And it was found that random-walk models were better than diffusion models for describing a population in an environment with rich natural resources, and the latter was better in a poor environment.

AIC-Based Selection of Growth Models: The Case of Piglets from Organic Farming

The selection and comparison of different growth models for describing weight gain of piglets raised in organic farming is investigated by using the Akaike’s Information Criterion (AIC). In total, 49,699 data points of 5188 piglets recorded between 2007 and 2013 were considered. From the day of birth, up to 40 days (i.e. until weaning) the model of von Bertalanffy was favored by the AIC. This model is with 60.32% more likely to truly reflect reality than any other of the analyzed models. Up to 105 days, the two-linear model was favored by the AIC (probability 99.75%). The intersection point of the two-linear model was calculated by 53.8 days, which fitted well to the actual change in the food situations.

Extensive numerical simulations on competitive growth between the Edwards–Wilkinson and Kardar–Parisi–Zhang universality classes

Extensive numerical simulations and scaling analysis are performed to investigate competitive growth between the linear and nonlinear stochastic dynamic growth systems, which belong to the Edwards–Wilkinson(EW) and Kardar–Parisi–Zhang(KPZ) universality classes, respectively. The linear growth systems include the EW equation and the model of random deposition with surface relaxation(RDSR), the nonlinear growth systems involve the KPZ equation and typical discrete models including ballistic deposition(BD), etching, and restricted solid on solid(RSOS). The scaling exponents are obtained in both the(1 + 1)-and(2 + 1)-dimensional competitive growth with the nonlinear growth probability p and the linear proportion 1-p. Our results show that, when p changes from 0 to 1, there exist non-trivial crossover effects from EW to KPZ universality classes based on different competitive growth rules. Furthermore, the growth rate and the porosity are also estimated within various linear and nonlinear growths of cooperation and competition.

Control of GaN inverted pyramids growth on c-plane patterned sapphire substrates

Growth of gallium nitride(GaN)inverted pyramids on c-plane sapphire substrates is benefit for fabricating novel devices as it forms the semipolar facets.In this work,GaN inverted pyramids are directly grown on c-plane patterned sapphire substrates(PSS)by metal organic vapor phase epitaxy(MOVPE).The influences of growth conditions on the surface morphol-ogy are experimentally studied and explained by Wulff constructions.The competition of growth rate among{0001},{1011},and{1122}facets results in the various surface morphologies of GaN.A higher growth temperature of 985 ℃ and a lowerⅤ/Ⅲratio of 25 can expand the area of{}facets in GaN inverted pyramids.On the other hand,GaN inverted pyramids with almost pure{}facets are obtained by using a lower growth temperature of 930℃,a higherⅤ/Ⅲratio of 100,and PSS with pattern arrangement perpendicular to the substrate primary flat.

The Impact of the Digital Economy on Financial Regulatory Costs: An Empirical Analysis Based on the Solow Growth Model

As a novel economic form,the digital economy is reshaping the financial regulatory landscape and significantly impacting regulatory costs.This paper incorporates the digital economy and financial regulatory costs into the classic Solow growth model,uncovering an inverted U-shaped relationship between them.A subsequent mechanism analysis explains the rationale behind this relationship.To empirically examine this relationship in China,the paper utilizes inter-provincial panel data from 2013 to 2021 and employs methodologies such as the two-way fixed effects and moderating effects models.These analyses have important implications for the sound and sustainable development of China’s financial industry.The findings indicate:(a)As China’s digital economy develops,its impact on financial regulatory costs follows an inverted U-shaped pattern,initially increasing and then declining.This conclusion remains valid after robustness tests.(b)The influence of the digital economy on regulatory costs depends on favorable external conditions.Specifically,the impact is more pronounced in regions and periods with better digital infrastructure and more abundant human capital.(c)Additionally,redundant resources moderate this impact,which can weaken the inverted U-shaped relationship.Our findings not only provide a theoretical foundation for understanding the impact of the digital economy on financial regulatory costs but also offer valuable policy insights for optimizing financial regulation in China.

Precise Asymptotics for Random Matrices and Random Growth Models

The author considers the largest eigenvaiues of random matrices from Gaussian unitary ensemble and Laguerre unitary ensemble, and the rightmost charge in certain random growth models. We obtain some precise asymptotics results, which are in a sense similar to the precise asymptotics for sums of independent random variables in the context of the law of large numbers and complete convergence. Our proofs depend heavily upon the upper and lower tail estimates for random matrices and random growth models. The Tracy-Widom distribution plays a central role as well.

Stability in terms of two measures for population growth models with impulsive perturbations

In this paper,we establish some criteria for the stability of trivial solution of population growth models with impulsive perturbations.The working tools are based on the theory of generalized ordinary differential equations.Here,the conditions concerning the functions are more general than the classical ones.

Characterization of grain growth behaviors by BP-ANN and Sellars models for nickle-base superalloy and their comparisons

In order to deeply understand the grain growth behaviors of Ni80A superalloy,a series of grain growth experiments were conducted at holding temperatures ranging from 1223 to 1423 K and holding time ranging from 0 to 3600 s.A back-propagation artificial neural network(BP-ANN)model and a Sellars model were solved based on the experimental data.The prediction and generalization capabilities of these two models were evaluated and compared on the basis of four statistical indicators.The results show that the solved BP-ANN model has better performance as it has higher correlation coefficient(r),lower average absolute relative error(AARE),lower absolute values of mean value(μ)and standard deviation(ω).Eventually,a response surface of average grain size to holding temperature and holding time is constructed based on the data expanded by the solved BP-ANN model,and the grain growth behaviors are described.

Modelling the response of larch growth to age,density,and elevation and the implications for multifunctional management in northwest China

Plantations of Rupprecht's larch(Larix principis-rupprechtii)have been widely established in the drylands of northwest and north China under traditional fastgrowing plantation management strategies.These strategies and the long-term logging ban have led to over-populated stands with lower structural and functional stability,less economic benefit and higher water consumption.To guide the sustainable management of larch plantations,field surveys and historical data compilation were undertaken in the Liupan Mountains of northwest China.The main influencing factors(stand structure and site condition)and their effects on mean tree height,mean DBH and timber volumes were determined based on up-boundary line analysis.Tree growth models coupling the effects of tree age,stand density,and elevation were established.Both height and DBH markedly increased initially and then slowly with tree age,decreased with stand density,and showed unimodal change with elevation.The coupled growth models accounted for72-78%of the variations in tree height,DBH and timber growth.Recommendations for future plantation management are:(1)prolong the rotation to at least 60 years to produce large-diameter,high-quality timber and maintain greater carbon stocks;(2)zone the target functions of stands by elevation;and,(3)reduce stand density for balanced supply of multiple ecosystem services.The growth models developed can predict growth response of larch plantations to density alteration under given ages and elevations,and assist the transformation from traditional management for maximum timber production to site-specific and multifunctional management with longer rotations and moderate tree density.

Growth phenology adjusts to seasonal changes in water availability in coexisting evergreen and deciduous mediterranean oaks

Different leaf(evergreen vs.deciduous habit)and xylem(diffuse-vs.ring-porous wood)traits represent contrasting strategies to face seasonal changes in water availability and temperature.However,how contrasting leaf and xylem habits of coexisting tree species affect stem wood formation and tree-ring development remains poorly understood.Here,we investigated the spatio-temporal patterns of wood formation in two deciduous oaks(Quercus faginea and Quercus petraea)and two evergreen oaks(Quercus ilex and Quercus suber)coexisting in seasonally dry Mediterranean forests along an aridity gradient in Spain.We hypothesized that growth responses to drought and intra-and inter-annual growth patterns would differ between functional groups.We simulated intra-and interannual growth using a modified version of the Vaganov-Shashkin(VS)process-based,growth model.The VS model simulations were used to estimate growth changes under a high emission scenario(RCP 8.5)for the current distribution of the study oak species and to forecast their future performance under warm(4.8℃)conditions in the Iberian Peninsula.Our simulations indicate that climate warming would induce a shortening of the ringgrowth season and a reduction of radial growth in evergreen and deciduous Mediterranean oaks,particularly in dry sites from southern and eastern Iberia currently occupied by Q.ilex and Q.faginea.Evergreen oaks may better recover after dry periods than deciduous oaks by resuming growth after the summer drought.Low soil water availability in spring would be more detrimental to growth of deciduous oaks.Process-based growth models should be refined and validated to better forecast changes in tree growth as a function of climate.

Problems with models assessing influences of tree size and inter-tree competitive processes on individual tree growth:a cautionary tale

In forest growing at any one site, the growth rate of an individual tree is determined principally by its size, which reflects its metabolic capacity, and by competition from neighboring trees. Competitive effects of a tree may be proportional to its size;such competition is termed ‘sym-metric’ and generally involves competition below ground for nutrients and water from the soil. Competition may also be ‘asymmetric’, where its effects are disproportionate to the size of the tree;this generally involves competition above ground for sunlight, when larger trees shade smaller, but the reverse cannot occur. This work examines three model systems often seen as exemplars relating individual tree growth rates to tree size and both competitive processes. Data of tree stem basal area growth rates in plots of even- aged, monoculture forest of blackbutt (Eucalyptus pilularis Smith) growing in sub-tropical eastern Australia were used to test these systems. It was found that none could distin-guish between size and competitive effects at any time in any one stand and, thus, allow quantification of the contribution of each to explaining tree growth rates. They were prevented from doing so both by collinearity between the terms used to describe each of the effects and technical problems involved in the use of nonlinear least-squares regression to fit the models to any one data set. It is concluded that quite new approaches need to be devised if the effects on tree growth of tree size and competitive processes are to be quantified and modelled successfully.

Availability growth models and verification of power equipment

The general availability growth models for large scale complicated repairable system such as electric generating units, power station auxiliaries, and transmission and distribution installations are presented. The calculation formulas for the maintenance coefficient, mathematical expressions for general availability growth models, ways for estimating, and fitting on checking the parameters of the model are introduced. Availability growth models for electric generating units, power station auxiliaries, and transmission and distribution installations are given together with verification examples for availability growth models of 320–1000 MW nuclear power units and 1000 MW thermal power units, 200–1000 MW power station auxiliaries, and 220–500 kV transmission and distribution installations. The verification results for operation availability data show that the maintenance coefficients for electric generating units, power station auxiliaries, transmission and distribution installations conform to the power function, and general availability growth models conform to rules of availability growth tendency of power equipment.

Studies on crop growth modelling and simulation models in China

There is a close relationship between agricultural production and environmental meteorological conditions. In the study of the correlation between them, the simulation models are paid more attention to the crop growth. In this paper the development of the studies on the crop growth dynamic simulation model in China is briefly reviewed. The relationships between meteorological conditions and each process of crop growth (such as photosynthesis, respiration, accumulation and distribution of assimilation products and growth of leaf area) are studied and simulated basing on the results from field experiments. Preliminary models for rice, wheat, maize and soybean have been developed, and some investigations about modelling methods, procedures and parameters in simulation models are made.

GROWTH AND YIELD MODELS FOR DAHURIAN LARCH PLANTATIONS

Growth and yield models were developed for individual tress and stands based on 336 temporary plots with 405 stem analysis trees of dahurian larch ( Larix gmelinii( Rupr. )Rupr.) plantations throughout Daxing'anling mountains. Several equations were selected using nonlinear regression analysis. Results showed that the Richards equation was the best model for estimating tree height, stand mean height and stand dominant height from age; The Power equation was the best model for prediction tree volume from DBH and tree height; The logarithmic stand volume equation was good for predicting stand volume from age, mean height, basal area and other stand variables. These models can be used to construct the volume table, the site index table and other forestry tables for dahurian larch plantations.

Bertalanffy-Pütter Models for the Growth of Tropical Trees and Stands

The Bertalanffy-Pütter (BP) five-parameter growth model provides a versatile framework for the modeling of growth. Using data from a growth experiment in literature about the average size-at-age of 24 species of tropical trees over ten years in the same area, we identified their best-fit BP-model parameters. While different species had different best-fit exponent-pairs, there was a model with a good fit to 21 (87.5%) of the data (“Good fit” means a normalized root-mean-squared-error NRMSE below 2.5%. This threshold was the 95% quantile of the lognormal distribution that was fitted to the NRMSE values for the best-fit models for the data). In view of the sigmoidal character of this model despite the early stand we discuss whether the setting of the growth experiment may have impeded growth.

Effects of site productivity on individual tree maximum basal area growth rates of Eucalyptus pilularis in subtropical Australia

Inventory data were available from 96 plots of even-aged,monoculture,tall-open forests of Eucalyptus pilularis Smith,aged 2-63 years,growing in sub-tropical regions along the east coast of Australia.A model was developed relating the maximum possible stem basal area growth rate of individual trees to their stem basal area.For any tree size,this maximum increased as site productivity increased.However,the size at which this maximum occurred decreased as productivity increased.Much research has shown that,at any stand age,trees of a particular stem basal area are taller on more productive sites than on less productive ones.Taller trees incur greater respiratory costs to ensure maintenance of the photo synthetic capacity of their canopies;this reduces their growth rates.It was concluded that trees with larger basal areas will have the maximum possible growth rate on a less productive site,whilst trees with smaller basal areas will have the maximum possible on a more productive site.The model developed may constitute the first stage of a complete individual tree growth model system to predict wood yields from these forests.

The trajectories of physical growth in 4 months postnatal corrected age among preterm infants discharged from neonatal intensive care units and associated factors: A prospective study

Objectives Growth retardation is a risk for premature infants.In addition to demographic and perinatal factors,preterm infants’physical growth may be affected by neonatal intensive care unit(NICU)stress,maternal postpartum depression,and mother-infant interaction.This study aimed to investigate the trajectories of physical growth in 4 months corrected age among preterm infants discharged from the NICU and the impactors on these trajectories.Methods A prospective study was conducted among 318 preterm infants from September 2019 to April 2021 in Shanghai,China.Latent growth modeling was applied to identify the weight,length,and head circumference growth trajectories in 4 months corrected age and explore the effects of demographic and medical characteristics,infant stress during NICU stay,maternal postpartum depression,and mother-infant interaction on each trajectory.Results Unconditional latent growth models showed curve trajectories with increasingly slower growth in weight,length,and head circumference until 4 months of corrected age.Conditional latent growth models showed that a longer length of stay in the NICU and more skin punctures were negatively associated with weight at 40 weeks corrected gestational age(β=−0.43 and−0.19,respectively,P<0.05).The maternal postpartum depression between 40 weeks corrected gestational age and 1 month corrected postnatal age was associated with a lower growth rate of length(β=−0.17,P=0.040),while between 2 and 3 months corrected postnatal age,there were lower growth rates of weight and head circumference(β=−0.15 and−0.19,respectively,P<0.05).The mother-infant interaction scores between 40 weeks corrected gestational age and 1 month corrected postnatal age negatively predicted the growth rate of weight(β=−0.19,P=0.020).Conclusion The physical growth trajectories of preterm infants discharged from the NICU were influenced by infant stress during the NICU stay,maternal postpartum depression and mother-infant interaction.