Delineation of urban growth boundary based on FLUS model under the perspective of land use evaluation in hilly mountainous areas

With rapid economic development,the size of urban land in China is expanding dramatically.The Urban Growth Boundary(UGB)is an expandable spatial boundary for urban construction in a certain period in order to control the urban sprawl.Reasonable delineation of UGB can inhibit the disorderly spread of urban space and guide the normal development of the city.It is of practical significance for the construction of green urban space.The study utilizes GIS technology to establish a land construction suitability evaluation system for Nankang city,which is experiencing rapid urban expansion,and outlines the preliminary UGB under the future land use simulation(FLUS)model.At the same time,considering the coupled coordination of"Production-Living-Ecological Space",and based on the suitability evaluation,we revised the preliminary UGB by combining the advantages of the patch-generating land use simulation(PLUS)model and the convex hull model to delineate the final UGB.The results show that:1)the comprehensive score of the evaluation of the suitability of the construction of land from high to low shows the distribution of the center of the city to the surrounding circle type spread,the center of the city has the highest suitability score.The results of convex hull model show that the urban expansion type of Nankang is epitaxial.In the future,the urban expansion will mainly occur in the northern part of the city.The PLUS model predicts an increase of 3359.97 hm^(2)of construction land in Nankang by 2035,of which 2022.97 hm^(2)is urban construction land.2)The FLUS model has a prediction accuracy of 86.3%and delineates a preliminary UGB area of 9215.07 hm^(2).3)We used the results of the construction suitability evaluation,PLUS model simulation results,and convex hull model predictions to revise the originally delineated UGB.The final delineated UGB area is 8895.67 hm^(2)and it is capable of meeting the future development of the study area.The results of the delineation can promote sustainable urban development,and the delineation methodology can provide a reference basis for the preparation of territorial spatial planning.

Growth and inhibition of zinc anode dendrites in Zn-air batteries:Model and experiment

Zinc(Zn)-air batteries are widely used in secondary battery research owing to their high theoretical energy density,good electrochemical reversibility,stable discharge performance,and low cost of the anode active material Zn.However,the Zn anode also leads to many challenges,including dendrite growth,deformation,and hydrogen precipitation self-corrosion.In this context,Zn dendrite growth has a greater impact on the cycle lives.In this dissertation,a dendrite growth model for a Zn-air battery was established based on electrochemical phase field theory,and the effects of the charging time,anisotropy strength,and electrolyte temperature on the morphology and growth height of Zn dendrites were studied.A series of experiments was designed with different gradient influencing factors in subsequent experiments to verify the theoretical simulations,including elevated electrolyte temperatures,flowing electrolytes,and pulsed charging.The simulation results show that the growth of Zn dendrites is controlled mainly by diffusion and mass transfer processes,whereas the electrolyte temperature,flow rate,and interfacial energy anisotropy intensity are the main factors.The experimental results show that an optimal electrolyte temperature of 343.15 K,an optimal electrolyte flow rate of 40 ml·min^(-1),and an effective pulse charging mode.

Interpreting Larix principis-rupprechtii radial growth in northern China based on the Vaganov-Shashkin model

Changes in annual radial growth is an important indication of climate change. Dendroclimatology studies in northern China have focused on linear statistical analysis,but lacking studies based on the process of ring formation to clarify the radial growth of trees. Tree-ring width standard chronology(STD) was established using samples of Larix principis-rupprechtii collected at 2303 m altitude on Luya Mountain. Using the Vaganov-Shashkin(VS) model to simulate growth and development, the internal physiological mechanism of radial growth is identified. It was concluded that:(1) the growing season of L. principis-rupprechtii was May to September;(2) soil moisture was a significant factor in the early and late growing seasons, and temperature was the dominant factor in its main growth period;and(3) formation of narrow ring widths was closely related to drought stress, the development of wide ring widths will be restricted by increasing future temperatures. The VS model is applicable for radial growth simulation of subalpine coniferous forests and for guiding the cultivation of local tree species in the future.

Microbial Growth and Decay: A Commented Review of the Model

The paper reviews previous publications and reports some comments about a semi empirical model of the growth and decay process of a planktonic microbial culture. After summarizing and reshaping some fundamental mathematical expressions, the paper highlights the reasons for the choice of a suitable time origin that makes the parameters of the model self-consistent. Besides the potential applications to predictive microbiology studies and to effects of bactericidal drugs, the model allows a suitable proxy of the fitness of the microbial culture, which can be of interest for the studies on the evolution across some thousand generations of a Long Term Evolution Experiment.

Ecosystem service multifunctionality of mixed conifer-broad-leaved forests under climate change and forest management based on matrix growth modelling

Climate change and forest management are recognized as pivotal factors influencing forest ecosystem services and thus multifunctionality.However,the magnitude and the relative importance of climate change and forest management effects on the multifunctionality remain unclear,especially for natural mixed forests.In this study,our objective is to address this gap by utilizing simulations of climate-sensitive transition matrix growth models based on national forest inventory plot data.We evaluated the effects of seven management scenarios(combinations of various cutting methods and intensities)on the future provision of ecosystem services and multifunctionality in mixed conifer-broad-leaved forests in northeastern China,under four climate scenarios(SSP1-2.6,SSP2-4.5,SSP5-8.5,and constant climate).Provisioning,regulating,cultural,and supporting services were described by timber production,carbon storage,carbon sequestration,tree species diversity,deadwood volume,and the number of large living trees.Our findings indicated that timber production was significantly influenced by management scenarios,while tree species diversity,deadwood volume,and large living trees were impacted by both climate and management separately.Carbon storage and sequestration were notably influenced by both management and the interaction of climate and management.These findings emphasized the profound impact of forest management on ecosystem services,outweighing that of climate scenarios alone.We found no single management scenario maximized all six ecosystem service indicators.The upper story thinning by 5%intensity with 5-year interval(UST5)management strategy emerged with the highest multifunctionality,surpassing the lowest values by more than 20%across all climate scenarios.In conclusion,our results underlined the potential of climate-sensitive transition matrix growth models as a decision support tool and provided recommendations for long-term strategies for multifunctional forest management under future climate change context.Ecosystem services and multifunctionality of forests could be enhanced by implementing appropriate management measures amidst a changing climate.

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.

SAR Data Assimilation for Crop Biomass Simulation Based on Crop Growth Model

Biomass from SAR data was assimilated into crop growth model to describe relationship between crop biomass and crop growth time to improve estimation accuracy of biomass. In addition, inverse model was established in order to estimate biomass according to relationship between biomass and backscattering coefficients from SAR data. Based on cost function, parameters of growth model were optimized as per conjugate gradient method, minimizing the differences between estimated biomass and inversion values from SAR data. The results indicated that the simulated biomass using the revised growth model with SAR data was consistent with the measured one in time distribution and even higher in accuracy than that without SAR data. Hence, the key parameters of crop growth model could be revised by real-time growth information from SAR data and accuracy of the simulated biomass could be improved accordingly.

Phase-field modeling of dendritic growth under forced flow based on adaptive finite element method

A mathematical model combined projection algorithm with phase-field method was applied. The adaptive finite element method was adopted to solve the model based on the non-uniform grid, and the behavior of dendritic growth was simulated from undercooled nickel melt under the forced flow. The simulation results show that the asymmetry behavior of the dendritic growth is caused by the forced flow. When the flow velocity is less than the critical value, the asymmetry of dendrite is little influenced by the forced flow. Once the flow velocity reaches or exceeds the critical value, the controlling factor of dendrite growth gradually changes from thermal diffusion to convection. With the increase of the flow velocity, the deflection angle towards upstream direction of the primary dendrite stem becomes larger. The effect of the dendrite growth on the flow field of the melt is apparent. With the increase of the dendrite size, the vortex is present in the downstream regions, and the vortex region is gradually enlarged. Dendrite tips appear to remelt. In addition, the adaptive finite element method can reduce CPU running time by one order of magnitude compared with uniform grid method, and the speed-up ratio is proportional to the size of computational domain.

A Simplified Model with Soil Water Limitation on Spring Wheat Growth

The authors constructed a simplified model of spring wheat (Triticum aestivum L.) carbon assimilation and dry matter accumulation (DMA) process which consisted of two independent variables, day length (L) and total daily radiation (TDR). Leaf water potential (Ψ) was incorporated into the simplified growth model based on the assumption that both light use efficiency (α) and CO 2 conductance of assimilation (g c) were depressed by water limitation. Finally,Ψ was estimated from a regression equation in which the independent variables were relative soil water content in the upper 80 cm (θ R,80 ), ambient temperature (T a), vapor pressure deficit (VPD), the cumulative leaf water potential below thresholds of -1.5 MPa (Ψ c,1.5 ). Some applications in research program of field experiment of atmosphere_land surface processes in Heihe River region were tested. The simulated data agreed well with the data observed at Linze oasis in 1989 for various levels of water supply and at Zhangye oasis in 1992 in the field. The analysis and simulation using the model demonstrated that the simplified growth model could describe very well the DMA process of spring wheat with and without water limitation in the region of HEIFE (Heihe field experiment).

Study on height growth model of Pinus koraiensis

Growth model is an efficient way to study growing process of some factors of plants quantitatively. Height growth of Korean pine (Pinus koraiensis) was studied by using Hyperbola equation, Logistic equation, Richards equation with three parameters, and Richards equation with four parameters in this paper. The results showed that Richards equation with four parameters was the most suitable and could be turned into other theoretical equations when some parameters were given different value. The maximum height of trees could be given in advance when using Richards equation with four parameters, and it was even more corresponding to reality. In addition, a height growth model with real height of fixed age as a parameter was discussed in this paper. This kind of growth model could be used to calculate height growth of a given tree effectively.

Studies on stand dynamic growth model for larch in Jilin in China

The stand growth and yield dynamic models for Larch in Jilin Province were developed based on the forest growth theories with the forest continuous inventory data. The results indicated that the developed models had high precision, and they could be used for the updating data of inventory of planning and designing and optimal decision of forest management.

PROBABILISTIC MODELS FOR LONG FATIGUE CRACK GROWTH RATES OF LZ50 AXLE STEEL

Experimental study is performed on the probabilistic models for the long fatigue crack growth rates (da/dN) of LZ50 axle steel. An equation for crack growth rate was derived to consider the trend of stress intensity factor range going down to the threshold and the average stress effect. The probabilistic models were presented on the equation. They consist of the probabilistic da/dN-ΔK relations, the confidence-based da/dN-ΔK relations, and the probabilistic- and confidence-based da/dN-ΔK relations. Efforts were made respectively to characterize the effects of probabilistic assessments due to the scattering regularity of test data, the number of sampling, and both of them. These relations can provide wide selections for practice. Analysis on the test data of LZ50 steel indicates that the present models are available and feasible.

对《Plant Growth Modeling and Applications》一书的评介

农业信息技术能够快速完成农业科技、市场和政府等信息的传输和利用,加速科研成果的形成、规范、集成,缩短转化周期,科学指导和管理生产,从而改变传统农业高度分散、生产规模小、时空变异大、规模化程度差、稳定性和可控程度低等行业性弱点,提高农业生产者和管理者的素质和能力.农业信息化近些年来在我国有了快速的发展.2003年12月10日,我国科技部863计划支持的重大专项"智能化农业信息技术应用示范工程"(俗称"电脑农业")荣获世界信息峰会全球大奖,标志着中国在农业专家系统和智能化农业信息技术应用方面取得了重大成就.

Free dendritic growth model incorporating interfacial nonisosolutal nature due to normal velocity variation

Considering both the effects of the interfacial normal velocity dependence of solute segregation and the local nonequilibrium solute diffusion,an extended free dendritic growth model was analyzed.Compared with the predictions from the dendritic model with isosolutal interface assumption,the transition from solutal dendrite to thermal dendrite moves to higher undercoolings,i.e.,the region of undercoolings with solute controlled growth is extended.At high undercoolings,the transition from the mainly thermal-controlled growth to the purely thermal-controlled growth is not sharp as predicted by the isosolute model,but occurs in a range of undercooling,due to both the effects of the interfacial normal velocity dependence of solute segregation and the local nonequilibrium solute diffusion.Model test indicates that the present model can give a satisfactory agreement with the available experimental data for the Ni-0.7% B（mole fraction） alloy.

Optimizing Parameters of CSM-CERES-Maize Model to Improve Simulation Performance of Maize Growth and Nitrogen Uptake in Northeast China

Crop models can be useful tools ibr optimizing fertilizer management for a targeted crop yield while minimizing nutrient losses. In this paper, the parameters of the decision support system for agrotechnology transfer （DSSAT）-CERES-Maize were optimized using a new method to provide a better simulation of maize （Zea mays L.） growth and N upfake in response to different nitrogen application rates. Field data were collected from a 5 yr field experiment （2006-2010） on a Black soil （Typic hapludoll） in Gongzhuling, Jilin Province, Northeast China. After cultivar calibration, the CERES-Maize model was able to simulate aboveground biomass and crop yield of in the evaluation data set （n-RMSE=5.0-14.6%）, but the model still over-estimated aboveground N uptake （i.e., with E values from -4.4 to -21.3 kg N ha-~）. By analyzing DSSAT equation, N stress coefficient for changes in concentration with growth stage （CTCNP2） is related to N uptake. Further sensitivity analysis of the CTCNP2 showed that the DSSAT model simulated maize nitrogen uptake more precisely after the CTCNP2 coefficient was adjusted to the field site condition. The results indicated that in addition to calibrating 6 coefficients of maize cultivars, radiation use efficiency （RUE）, growing degree days for emergence （GDDE）, N stress coefficient, CTCNP2, and soil fertility factor （SLPF） also need to be calibrated in order to simulate aboveground biomass, yield and N uptake correctly. Independent validation was conducted using 2008-2010 experiments and the good agreement between the simulated and the measured results indicates that the DSSAT CERES-Maize model could be a useful tool for predicting maize production in Northeast China.

Coupled modeling of tumour angiogenesis, tumour growth,and blood perfusion

This paper proposes a more realistic mathematical simulation method to investigate the dynamic process of tumour angio-genesis by fully coupling the vessel growth,tumour growth and associated blood perfusion.The tumour growth and angiogenesis are coupled by the chemical microenvironment and the cell-matrix interaction.The haemodynamic calculation is carried out on the new vasculature,and an estimation of vessel collapse is made according to the wall shear stress criterion.The results are consistent with physiological observations,and further confirm the application of the coupled model feedback mechanism.The model is available to examine the interactions between angiogenesis and tumour growth,to study the change in the dynamic process of chemical environment and the vessel remodeling.

Evaluation of unconstrained and constrained mathematical functions to model girth growth of rubber trees (Hevea brasiliensis) using young agemeasurements

No attempt has been made to date to model growth in girth of rubber tree （Hevea brasiliansis）. We evaluated the few widely used growth functions to identify the most parsimonious and biologically reasonable model for describing the girth growth of young rubber trees based on an incomplete set of young age measurements. Monthly data for girth of immature trees （age 2 to 12 yearsi from two locations were sub- jected to modelling. Re-parameterized, unconstrained and constrained growth functions,of Richards （RM）, Gompertz （GM） and the monomo- lecular ＇model ^（MM） were fitted to data. Duration of growth was the firsf constraint introduced. In the stagel We attempted a population aver- age （PA） model to capture the trend in growth. The best PA model was fitted as a subject specific （SS） model. We used appropriate error vari- ance-covariance structure to account for correlation due to repeated measurements over time. Unconstrainecl functions underestimated the asymptotic maximum that did not reflective carrying capacity of the locations. Underestimafions were attributed to the partial set＇ of meas- urements made during the early growth phase of the trees. MM proved superior to RM and GM. In the randomcoefficient models, both Gf and Go appeared to be influenced by tree level effects. Inclusion of diagonal definite positive matrix removed the correlation between random effects. The results were similar at both locations. In the overall assessment MM appeared as the candidate model for studying the girth-age relationships in Hevea trees. Based on the fitted model we conclude that, in Hevea trees, growth rate is maintained at maximum value at to, then decreases until the final state at dG/dt 〉 0, resulting in yield curve with no period of accelerating growth. One physiological explanation is that photosynthetic activity in Hevea trees decreases as girth increases and constructive metabolism is larger than destructive metabolism.

Growth simulation and yield prediction for perennial jujube fruit tree by integrating age into the WOFOST model

Mathematical models have been widely employed for the simulation of growth dynamics of annual crops,thereby performing yield prediction,but not for fruit tree species such as jujube tree(Zizyphus jujuba).The objectives of this study were to investigate the potential use of a modified WOFOST model for predicting jujube yield by introducing tree age as a key parameter.The model was established using data collected from dedicated field experiments performed in 2016-2018.Simulated growth dynamics of dry weights of leaves,stems,fruits,total biomass and leaf area index(LAI) agreed well with measured values,showing root mean square error(RMSE) values of 0.143,0.333,0.366,0.624 t ha^-1 and 0.19,and R2 values of 0.947,0.976,0.985,0.986 and 0.95,respectively.Simulated phenological development stages for emergence,anthesis and maturity were 2,3 and 3 days earlier than the observed values,respectively.In addition,in order to predict the yields of trees with different ages,the weight of new organs(initial buds and roots) in each growing season was introduced as the initial total dry weight(TDWI),which was calculated as averaged,fitted and optimized values of trees with the same age.The results showed the evolution of the simulated LAI and yields profiled in response to the changes in TDWI.The modelling performance was significantly improved when it considered TDWI integrated with tree age,showing good global(R2≥0.856,RMSE≤0.68 t ha^-1) and local accuracies(mean R2≥0.43,RMSE≤0.70 t ha^-1).Furthermore,the optimized TDWI exhibited the highest precision,with globally validated R2 of 0.891 and RMSE of 0.591 t ha^-1,and local mean R2 of 0.57 and RMSE of 0.66 t ha^-1,respectively.The proposed model was not only verified with the confidence to accurately predict yields of jujube,but it can also provide a fundamental strategy for simulating the growth of other fruit trees.

Rice Yield Estimation by Integrating Remote Sensing with Rice Growth Simulation Model

Since remote sensing can provide information on the actual status of an agricultural crop, the integration between remote sensing data and crop growth simulation models has become an important trend for yield estimation and prediction.The main objective of this research was to combine a rice growth simulation model with remote sensing data to estimate rice grain yield for different growing seasons leading to an assessment of rice yield at regional levels. Integration between NOAA (National Oceanic and Atmospheric Administration) AVHRR (Advanced Very High Resolution Radiometer) data and the rice growth simulation model ORYZA1 to develop a new software, which was named as Rice-SRS Model, resulted in accurate estimates for rice yield in Shaoxing, China, with an estimation error reduced to 1.03% and 0.79% over-estimation and 0.79% under-estimation for early, single and late season rice, respectively. Selecting suitable dates for remote sensing images was an important factor which could influence estimation accuracy. Thus, given the different growing periods for each rice season, four images were needed for early and late rice, while five images were preferable for single season rice.Estimating rice yield using two or three images was possible, however, if images were obtained during the panicle initiation and heading stages.

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.