Pinus radiata(D.Don)dominates New Zealand's forestry industry,constituting 91%of plantations,and is among the world's most important plantation species.Given the socio-economic and environmental importance of ...Pinus radiata(D.Don)dominates New Zealand's forestry industry,constituting 91%of plantations,and is among the world's most important plantation species.Given the socio-economic and environmental importance of this species,it is important to have accurate and precise projections over time to make efficient decisions for forest management and greenfield investments in afforestation projects,especially for permanent carbon forests.Future projections of any natural resource systems rely on modeling;however,the acceleration of climate change makes future projections of yield less certain.These challenges also impact national expectations of the contribution planted forests will provide to address climate change and meet international commitments under the Paris Agreement.Using a large national-scale set of contemporary ground-measured data(2013–2023),this study investigates the performance of two growth models developed over 30 years ago that are widely used by NZ plantation growers:1)the Pumice Plateau Model 1988(PPM88)and 2)the 300-index(including a model variant of regional drift).Model simulations were made using the FORECASTER modeling suite with geographic boundaries to adjust for drift in space and time.Basal area(BA,m^(2)⋅ha^(-1))and volume(m^(3)⋅ha^(-1))were simulated,and standard errors and goodness-of-fit metrics calculated up to a typical rotation age of 30 years.Model residuals were then separated and analysed for the main plantation growing regions.The models overpredicted observed growth by between 6.8%and 16.2%,but model predictions and errors varied significantly between regions.The results of this study provided clear evidence of divergence between the outputs of both models and the measured data.Finally,this study suggests future measures to address challenges posed by these discrepancies that will provide better information for forest management and investment decisions in a changing climate.展开更多
Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Reg...Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Regression models and Neural network models,to perform multi-characteristic coupled displacement prediction because they fail to consider landslide creep characteristics.This paper integrates the creep characteristics of landslides with non-linear intelligent algorithms and proposes a dynamic intelligent landslide displacement prediction method based on a combination of the Biological Growth model(BG),Convolutional Neural Network(CNN),and Long ShortTerm Memory Network(LSTM).This prediction approach improves three different biological growth models,thereby effectively extracting landslide creep characteristic parameters.Simultaneously,it integrates external factors(rainfall and reservoir water level)to construct an internal and external comprehensive dataset for data augmentation,which is input into the improved CNN-LSTM model.Thereafter,harnessing the robust feature extraction capabilities and spatial translation invariance of CNN,the model autonomously captures short-term local fluctuation characteristics of landslide displacement,and combines LSTM's efficient handling of long-term nonlinear temporal data to improve prediction performance.An evaluation of the Liangshuijing landslide in the Three Gorges Reservoir Area indicates that BG-CNN-LSTM exhibits high prediction accuracy,excellent generalization capabilities when dealing with various types of landslides.The research provides an innovative approach to achieving the whole-process,realtime,high-precision displacement predictions for multicharacteristic coupled landslides.展开更多
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 inc...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.展开更多
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 g...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.展开更多
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 cr...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.展开更多
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...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.展开更多
The second-order backward differential formula(BDF2)and the scalar auxiliary variable(SAV)approach are applied to con‐struct the linearly energy stable numerical scheme with the variable time steps for the epitaxial ...The second-order backward differential formula(BDF2)and the scalar auxiliary variable(SAV)approach are applied to con‐struct the linearly energy stable numerical scheme with the variable time steps for the epitaxial thin film growth models.Under the stepratio condition 0<τ_(n)/τ_(n-1)<4.864,the modified energy dissipation law is proven at the discrete levels with regardless of time step size.Nu‐merical experiments are presented to demonstrate the accuracy and efficiency of the proposed numerical scheme.展开更多
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 ...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.展开更多
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 asymptotic...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.展开更多
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 eq...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.展开更多
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 3...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.展开更多
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 ...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.展开更多
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 cal...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.展开更多
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...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.展开更多
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'anli...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.展开更多
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 ...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 </span><span style="font-family:Verdana;">(</span><span style="font-family:""><span style="font-family:Verdana;">“Good fit” means a </span><span style="font-family:Verdana;">normalized root-mean-squared-error <i></span><i><span style="font-family:Verdana;">NRMSE</span></i><span style="font-family:Verdana;"></i> below 2.5%. This threshold was the 95% quantile of the lognormal distribution that was fitted to the <i></span><i><span style="font-family:Verdana;">NRMSE</span></i><span style="font-family:Verdana;"></i> values for the best-fit models for the data)</span></span><span style="font-family:Verdana;">.</span><span style="font-family:Verdana;"> In view of the sigmoidal character of this model despite the early stand we discuss </span><span style="font-family:Verdana;">whether </span><span style="font-family:Verdana;">the setting of the growth experiment may have impeded growth.展开更多
This study investigated forest recovery in the Atlantic Rainforest and Rupestrian Grassland of Brazil using the diffusive-logistic growth(DLG)model.This model simulates vegetation growth in the two mountain biomes con...This study investigated forest recovery in the Atlantic Rainforest and Rupestrian Grassland of Brazil using the diffusive-logistic growth(DLG)model.This model simulates vegetation growth in the two mountain biomes considering spatial location,time,and two key parameters:diffusion rate and growth rate.A Bayesian framework is employed to analyze the model's parameters and assess prediction uncertainties.Satellite imagery from 1992 and 2022 was used for model calibration and validation.By solving the DLG model using the finite difference method,we predicted a 6.6%–51.1%increase in vegetation density for the Atlantic Rainforest and a 5.3%–99.9%increase for the Rupestrian Grassland over 30 years,with the latter showing slower recovery but achieving a better model fit(lower RMSE)compared to the Atlantic Rainforest.The Bayesian approach revealed well-defined parameter distributions and lower parameter values for the Rupestrian Grassland,supporting the slower recovery prediction.Importantly,the model achieved good agreement with observed vegetation patterns in unseen validation data for both biomes.While there were minor spatial variations in accuracy,the overall distributions of predicted and observed vegetation density were comparable.Furthermore,this study highlights the importance of considering uncertainty in model predictions.Bayesian inference allowed us to quantify this uncertainty,demonstrating that the model's performance can vary across locations.Our approach provides valuable insights into forest regeneration process uncertainties,enabling comparisons of modeled scenarios at different recovery stages for better decision-making in these critical mountain biomes.展开更多
The tolerance of tree growth to drought in diverse mixed forests subjected to seasonal water shortage is understudied despite their ecological and economic relevance.By combining intra-and inter-annual analyses of rad...The tolerance of tree growth to drought in diverse mixed forests subjected to seasonal water shortage is understudied despite their ecological and economic relevance.By combining intra-and inter-annual analyses of radial growth responses to climate and drought at daily and monthly scales,different strategies to acclimate to hydroclimate variability of coexisting conifers and broadleaves were unveiled.We analyzed the growth patterns and responses to hydroclimate variability in two conifers(Pinus engelmannii,Juniperus deppeana)and two broadleaves(Quercus grisea,Arbutus arizonica)co-occurring in a Madrean pine-oak forest located in NW Mexico.The strongest positive response to daily precipitation was found in the two conifers,but this response peaked earlier in J.deppeana than in P.engelmannii,which presented a more delayed formation of radially-enlarging tracheids.The latest negative response to temperature was found in Q.grisea,which agrees with its more delayed xylogenesis than A.arizonica.P.engelmannii presented the highest responsiveness to water shortage,driven by lower precipitation and high maximum temperatures,responding to longer droughts ending in autumn(r=0.72),whilst A.arizonica showed the lowest responsiveness to short spring droughts(r=0.39).Growth of P.engelmannii was linked to climate-atmospheric circulation patterns over the near Pacific Ocean.Overall,P.engelmannii and A.arizonica showed high growth rates and earlier growth onset,whilst J.deppeana and Q.grisea showed slower growth rates and later growth onset.The Vaganov-Shashkin growth model evidenced that winterspring soil moisture was the key driver of growth.Under more arid conditions and more frequent and hotter droughts,pine stands could rapidly shift towards mixed pine-oak forests.展开更多
This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor gro...This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor growth is established.Nonlinear fitting is employed to obtain the optimal parameter estimation of the mathematical model,and the numerical solution is carried out using the Matlab software.By comparing the clinical data with the simulation results,a good agreement is achieved,which verifies the rationality and feasibility of the model.展开更多
The construction of intermetallic compounds(IMCs)connection layers with special compositions by adding small amounts of alloying elements has been proven to be an effective strategy for improving the reliability of el...The construction of intermetallic compounds(IMCs)connection layers with special compositions by adding small amounts of alloying elements has been proven to be an effective strategy for improving the reliability of electronic component interconnect.However,the synergistic effect mechanism of multi-component alloy compositions on the growth behavior of IMCs is not clear.Herein,we successfully prepared a new quaternary alloy solder with a composition of Sn-0.7Cu-0.175Pt-0.025Al(wt%)using the high-throughput screening(HTS)method.The results showed that it possesses excellent welding performance with an inhibition rate over 40%on the growth of IMCs layers.For Cu_(6)Sn_(5),the co-doping of Al and Pt not only greatly improves its thermodynamic stability,but also effectively suppresses the phase transition.Meanwhile,the co-doping of Al and Pt also significantly delays the generation time of Kirkendall defects.The substitution sites of Al and Pt in Cu_(6)Sn_(5)have been explored using atomic resolution imaging and advanced data informatics,indicating that Al and Pt preferentially substitute Sn and Cu atoms,respectively,to generate(Cu,Pt)_(6)(Sn,Al)_(5).A one-dimensional(1D)kinetic model of the IMCs layer growth at the Sn solder/Cu substrate interface was derived and validated,and the results showed that the error of the derived mathematical model is less than 5%.Finally,the synergistic mechanism of Al and Pt co-doping on the growth rate of Cu_(6)Sn_(5)was further elucidated.This work provides a feasible route for the design and development of multi-component alloy solders.展开更多
基金funded by Scion's Strategic Science Investment Fund(SSIF)the Forest Growers Levy Trust(FGLT)through the Resilient Forests Programme(Task No.A89220)。
文摘Pinus radiata(D.Don)dominates New Zealand's forestry industry,constituting 91%of plantations,and is among the world's most important plantation species.Given the socio-economic and environmental importance of this species,it is important to have accurate and precise projections over time to make efficient decisions for forest management and greenfield investments in afforestation projects,especially for permanent carbon forests.Future projections of any natural resource systems rely on modeling;however,the acceleration of climate change makes future projections of yield less certain.These challenges also impact national expectations of the contribution planted forests will provide to address climate change and meet international commitments under the Paris Agreement.Using a large national-scale set of contemporary ground-measured data(2013–2023),this study investigates the performance of two growth models developed over 30 years ago that are widely used by NZ plantation growers:1)the Pumice Plateau Model 1988(PPM88)and 2)the 300-index(including a model variant of regional drift).Model simulations were made using the FORECASTER modeling suite with geographic boundaries to adjust for drift in space and time.Basal area(BA,m^(2)⋅ha^(-1))and volume(m^(3)⋅ha^(-1))were simulated,and standard errors and goodness-of-fit metrics calculated up to a typical rotation age of 30 years.Model residuals were then separated and analysed for the main plantation growing regions.The models overpredicted observed growth by between 6.8%and 16.2%,but model predictions and errors varied significantly between regions.The results of this study provided clear evidence of divergence between the outputs of both models and the measured data.Finally,this study suggests future measures to address challenges posed by these discrepancies that will provide better information for forest management and investment decisions in a changing climate.
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd..(Grant No.H20230317)。
文摘Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Regression models and Neural network models,to perform multi-characteristic coupled displacement prediction because they fail to consider landslide creep characteristics.This paper integrates the creep characteristics of landslides with non-linear intelligent algorithms and proposes a dynamic intelligent landslide displacement prediction method based on a combination of the Biological Growth model(BG),Convolutional Neural Network(CNN),and Long ShortTerm Memory Network(LSTM).This prediction approach improves three different biological growth models,thereby effectively extracting landslide creep characteristic parameters.Simultaneously,it integrates external factors(rainfall and reservoir water level)to construct an internal and external comprehensive dataset for data augmentation,which is input into the improved CNN-LSTM model.Thereafter,harnessing the robust feature extraction capabilities and spatial translation invariance of CNN,the model autonomously captures short-term local fluctuation characteristics of landslide displacement,and combines LSTM's efficient handling of long-term nonlinear temporal data to improve prediction performance.An evaluation of the Liangshuijing landslide in the Three Gorges Reservoir Area indicates that BG-CNN-LSTM exhibits high prediction accuracy,excellent generalization capabilities when dealing with various types of landslides.The research provides an innovative approach to achieving the whole-process,realtime,high-precision displacement predictions for multicharacteristic coupled landslides.
基金Supported by the High Technology Research and Development Program of China (863 Program,No2006AA100301)
文摘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.
文摘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.
文摘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.
文摘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.
文摘The second-order backward differential formula(BDF2)and the scalar auxiliary variable(SAV)approach are applied to con‐struct the linearly energy stable numerical scheme with the variable time steps for the epitaxial thin film growth models.Under the stepratio condition 0<τ_(n)/τ_(n-1)<4.864,the modified energy dissipation law is proven at the discrete levels with regardless of time step size.Nu‐merical experiments are presented to demonstrate the accuracy and efficiency of the proposed numerical scheme.
文摘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.
基金NSF of China (No.10371109,10671176)the Royal Society K.C.Wong Education Foundation
文摘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.
基金Tliis research is supported by the Natural Science Foundation of Zhejiang Province(Grant No.LY19A010013)the National Natural Science Foundation of China(Grant No.11501507).
文摘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.
基金Project(cstc2018jcyjAX0459)supported by Chongqing Basic Research and Frontier Exploration Program,ChinaProjects(2019CDQYTM027,2019CDJGFCL003)supported by the Fundamental Research Funds for the Central Universities,China。
文摘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.
文摘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.
文摘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.
文摘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.
文摘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.
文摘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 </span><span style="font-family:Verdana;">(</span><span style="font-family:""><span style="font-family:Verdana;">“Good fit” means a </span><span style="font-family:Verdana;">normalized root-mean-squared-error <i></span><i><span style="font-family:Verdana;">NRMSE</span></i><span style="font-family:Verdana;"></i> below 2.5%. This threshold was the 95% quantile of the lognormal distribution that was fitted to the <i></span><i><span style="font-family:Verdana;">NRMSE</span></i><span style="font-family:Verdana;"></i> values for the best-fit models for the data)</span></span><span style="font-family:Verdana;">.</span><span style="font-family:Verdana;"> In view of the sigmoidal character of this model despite the early stand we discuss </span><span style="font-family:Verdana;">whether </span><span style="font-family:Verdana;">the setting of the growth experiment may have impeded growth.
基金financial support from the Brazilian National Council for Scientific and Technological Development(CNPq)and the Federal University of Ouro PretoFinancial support from the Minas Gerais Research Foundation(FAPEMIG)under grant number APQ-06559-24 is also gratefully acknowledged。
文摘This study investigated forest recovery in the Atlantic Rainforest and Rupestrian Grassland of Brazil using the diffusive-logistic growth(DLG)model.This model simulates vegetation growth in the two mountain biomes considering spatial location,time,and two key parameters:diffusion rate and growth rate.A Bayesian framework is employed to analyze the model's parameters and assess prediction uncertainties.Satellite imagery from 1992 and 2022 was used for model calibration and validation.By solving the DLG model using the finite difference method,we predicted a 6.6%–51.1%increase in vegetation density for the Atlantic Rainforest and a 5.3%–99.9%increase for the Rupestrian Grassland over 30 years,with the latter showing slower recovery but achieving a better model fit(lower RMSE)compared to the Atlantic Rainforest.The Bayesian approach revealed well-defined parameter distributions and lower parameter values for the Rupestrian Grassland,supporting the slower recovery prediction.Importantly,the model achieved good agreement with observed vegetation patterns in unseen validation data for both biomes.While there were minor spatial variations in accuracy,the overall distributions of predicted and observed vegetation density were comparable.Furthermore,this study highlights the importance of considering uncertainty in model predictions.Bayesian inference allowed us to quantify this uncertainty,demonstrating that the model's performance can vary across locations.Our approach provides valuable insights into forest regeneration process uncertainties,enabling comparisons of modeled scenarios at different recovery stages for better decision-making in these critical mountain biomes.
基金funding by the Science and Innovation Ministry(projects PID2021-123675OB-C43 and TED2021-129770B-C21).
文摘The tolerance of tree growth to drought in diverse mixed forests subjected to seasonal water shortage is understudied despite their ecological and economic relevance.By combining intra-and inter-annual analyses of radial growth responses to climate and drought at daily and monthly scales,different strategies to acclimate to hydroclimate variability of coexisting conifers and broadleaves were unveiled.We analyzed the growth patterns and responses to hydroclimate variability in two conifers(Pinus engelmannii,Juniperus deppeana)and two broadleaves(Quercus grisea,Arbutus arizonica)co-occurring in a Madrean pine-oak forest located in NW Mexico.The strongest positive response to daily precipitation was found in the two conifers,but this response peaked earlier in J.deppeana than in P.engelmannii,which presented a more delayed formation of radially-enlarging tracheids.The latest negative response to temperature was found in Q.grisea,which agrees with its more delayed xylogenesis than A.arizonica.P.engelmannii presented the highest responsiveness to water shortage,driven by lower precipitation and high maximum temperatures,responding to longer droughts ending in autumn(r=0.72),whilst A.arizonica showed the lowest responsiveness to short spring droughts(r=0.39).Growth of P.engelmannii was linked to climate-atmospheric circulation patterns over the near Pacific Ocean.Overall,P.engelmannii and A.arizonica showed high growth rates and earlier growth onset,whilst J.deppeana and Q.grisea showed slower growth rates and later growth onset.The Vaganov-Shashkin growth model evidenced that winterspring soil moisture was the key driver of growth.Under more arid conditions and more frequent and hotter droughts,pine stands could rapidly shift towards mixed pine-oak forests.
基金National Natural Science Foundation of China(Project No.:12371428)Projects of the Provincial College Students’Innovation and Training Program in 2024(Project No.:S202413023106,S202413023110)。
文摘This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor growth is established.Nonlinear fitting is employed to obtain the optimal parameter estimation of the mathematical model,and the numerical solution is carried out using the Matlab software.By comparing the clinical data with the simulation results,a good agreement is achieved,which verifies the rationality and feasibility of the model.
基金financially supported by the Innovation Team Cultivation Project of Yunnan Province(No.202005AE160016)the Key Research&Development Program of Yunnan Province(No.202103AA080017)Yunnan Ten Thousand Talents Plan Young&Elite Talents Project(No.YNWR-QNBJ2018-044)。
文摘The construction of intermetallic compounds(IMCs)connection layers with special compositions by adding small amounts of alloying elements has been proven to be an effective strategy for improving the reliability of electronic component interconnect.However,the synergistic effect mechanism of multi-component alloy compositions on the growth behavior of IMCs is not clear.Herein,we successfully prepared a new quaternary alloy solder with a composition of Sn-0.7Cu-0.175Pt-0.025Al(wt%)using the high-throughput screening(HTS)method.The results showed that it possesses excellent welding performance with an inhibition rate over 40%on the growth of IMCs layers.For Cu_(6)Sn_(5),the co-doping of Al and Pt not only greatly improves its thermodynamic stability,but also effectively suppresses the phase transition.Meanwhile,the co-doping of Al and Pt also significantly delays the generation time of Kirkendall defects.The substitution sites of Al and Pt in Cu_(6)Sn_(5)have been explored using atomic resolution imaging and advanced data informatics,indicating that Al and Pt preferentially substitute Sn and Cu atoms,respectively,to generate(Cu,Pt)_(6)(Sn,Al)_(5).A one-dimensional(1D)kinetic model of the IMCs layer growth at the Sn solder/Cu substrate interface was derived and validated,and the results showed that the error of the derived mathematical model is less than 5%.Finally,the synergistic mechanism of Al and Pt co-doping on the growth rate of Cu_(6)Sn_(5)was further elucidated.This work provides a feasible route for the design and development of multi-component alloy solders.
