Evolution of Growth Model and Cultivation of Competitive Advantages Under the Ambidextrous Innovation Strategy: In the Case of China’s High-Tech Enterprises

This study focuses on the evolution of growth model and cultivation of competitive advantages under the ambidextrous innovation strategy.After a brief introduction of the connotation of ambidextrous innovation strategy,the evolution of growth model of high-tech enterprises under the conventional strategy and the ambidextrous innovation strategy is analyzed.Furthermore,a discussion is made on how to cultivate enterprises’competitive advantages under the ambidextrous innovation strategy,thereby enabling enterprises to stand out from competitors under this new strategic model and truly achieve the goal of sustainable development.

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.

Analysis of the inflection points of height-diameter models

The inflection point is an important feature of sigmoidal height-diameter(H-D)models.It is often cited as one of the properties favoring sigmoidal model forms.However,there are very few studies analyzing the inflection points of H-D models.The goals of this study were to theoretically and empirically examine the behaviors of inflection points of six common H-D models with a regional dataset.The six models were the Wykoff(WYK),Schumacher(SCH),Curtis(CUR),HossfeldⅣ(HOS),von Bertalanffy-Richards(VBR),and Gompertz(GPZ)models.The models were first fitted in their base forms with tree species as random effects and were then expanded to include functional traits and spatial distribution.The distributions of the estimated inflection points were similar between the two-parameter models WYK,SCH,and CUR,but were different between the threeparameter models HOS,VBR,and GPZ.GPZ produced some of the largest inflection points.HOS and VBR produced concave H-D curves without inflection points for 12.7%and 39.7%of the tree species.Evergreen species or decreasing shade tolerance resulted in larger inflection points.The trends in the estimated inflection points of HOS and VBR were entirely opposite across the landscape.Furthermore,HOS could produce concave H-D curves for portions of the landscape.Based on the studied behaviors,the choice between two-parameter models may not matter.We recommend comparing seve ral three-parameter model forms for consistency in estimated inflection points before deciding on one.Believing sigmoidal models to have inflection points does not necessarily mean that they will produce fitted curves with one.Our study highlights the need to integrate analysis of inflection points into modeling H-D relationships.

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.

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.

Novel models for simulating maize growth based on thermal time and photothermal units: Applications under various mulching practices

Maize (Zea mays L.) is one of the three major food crops and an important source of carbohydrates for maintaining food security around the world.Plant height (H),stem diameter (SD),leaf area index (LAI) and dry matter (DM) are important growth parameters that influence maize production.However,the combined effect of temperature and light on maize growth is rarely considered in crop growth models.Ten maize growth models based on the modified logistic growth equation (Mlog) and the Mitscherlich growth equation (Mit) were proposed to simulate the H,SD,LAI and DM of maize under different mulching practices based on experimental data from 2015–2018.Either the accumulative growing degree-days (AGDD),helio thermal units (HTU),photothermal units (PTU) or photoperiod thermal units (PPTU,first proposed here) was used as a single driving factor in the models;or AGDD was combined with either accumulative actual solar hours (ASS),accumulative photoperiod response (APR,first proposed here) or accumulative maximum possible sunshine hours (ADL) as the dual driving factors in the models.The model performances were evaluated using seven statistical indicators and a global performance index.The results showed that the three mulching practices significantly increased the maize growth rates and the maximum values of the growth curves compared with non-mulching.Among the four single factor-driven models,the overall performance of the Mlog_(PTU)Model was the best,followed by the Mlog_(AGDD)Model.The Mlog_(PPTU)Model was better than the Mlog_(AGDD)Model in simulating SD and LAI.Among the 10 models,the overall performance of the Mlog_(AGDD–APR)Model was the best,followed by the Mlog_(AGDD–ASS)Model.Specifically,the Mlog_(AGDD–APR)Model performed the best in simulating H and LAI,while the Mlog_(AGDD–ADL)and Mlog_(AGDD–ASS)models performed the best in simulating SD and DM,respectively.In conclusion,the modified logistic growth equations with AGDD and either APR,ASS or ADL as the dual driving factors outperformed the commonly used modified logistic growth model with AGDD as a single driving factor in simulating maize growth.

A Model of Cloud-Based Enterprise Resource Planning (ERP) for Small and Medium Enterprise

Cloud Computing is an uprising technology in the rapid growing IT world. The adaptation of cloud computing is increasing in very large scale business organizations to small institutions rapidly due to many advanced features of cloud computing, such as SaaS, PaaS and IaaS service models. So, nowadays, many organizations are trying to implement Cloud Computing based ERP system to enjoy the benefits of cloud computing. To implement any ERP system, an organization usually faces many challenges. As a result, this research has introduced how easily this cloud system can be implemented in an organization. By using this ERP system, an organization can be benefited in many ways;especially Small and Medium Enterprises (SMEs) can enjoy the highest possible benefits from this system.

MODELS OF THE SPATIAL EVOLUTION OF MULTI-PLANT ENTERPRISES

Since the 1970s, the studies on the geography of enterprise have become increasingly concerned with the spatial evolution of an enterprises in the West developed countries. However, little attention has so far been given to the spatial evolution of an enterprise in China. With China's ongoing economy and political reforms, a number of fundamental changes of enterprise behavior have occurred. These changes have certainly important influences on the evolution of industrial location. Therefore, there is a need for examining the spatial evolution of an enterprise in China. The purpose of the paper is to review the mapjor models of both the growth,and associated spatial evolution of an enterprise, with an illustrative case study of the HeaVy Automobile Enterprise Group of China. The paper is organized by three parts. The first examines the spoilal groWth and location adjustment of multi-plant enterprise. The second reviews mapjor models of the spatial evolution of an enterprise. And the third analyzes the spatial evolution, over a period of time, of a representative sample of the Heavy Automobile Enterprise Group of China, and illustrates the findings with case studies. It is suggested that the models of spatial evolution of an enterprise would provide more evidence about micro-mechanism for evolution of micro- regional economic systems.

The Study on Innovation Model Characteristics and Function Enhancement of “Leading Grain Enterprises+Farmers” in New Circumstances——an Investigation and Analysis on Major Grainproducing Areas in Hubei Province

ln the context of comprehensively deepening the reform, and integration of three The first, second and third industry sectors in rural areas, the research took major grain-producing areas in Hubei as an example, analyzed dominant grain in-dustrialization models “leading grain enterprises＋farmers”, and revealed its character-istics, advantages, and approaches for function reinforcement. The research is so meaningful, practical y or in future.

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.

基于FP-growth的老年行人交通事故损伤致因研究

为研究老年行人交通事故相关因素及其对损伤程度的影响,以中国交通事故深度调查数据库中2013—2023年710起机动车-老年行人事故为分析对象,利用FP-growth算法挖掘出4类影响因素28个类型变量共5594项关联规则。研究结果表明:行人年龄、碰撞速度、事故时间段及事故地点是影响老年行人事故死亡率的显著因素。特别是,行人年龄和碰撞速度对死亡率有显著影响,随着碰撞速度的增加,死亡率显著上升;60岁及以上老年行人年龄每增加1岁,其死亡率提升0.037倍。此外,事故发生在夜间、郊区或村庄的死亡率更高。研究结果可为提高老年行人交通安全,制定相关安全措施提供一定参考。

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.

Improving maize growth and development simulation by integrating temperature compensatory effect under plastic film mulching into the AquaCrop model

Temperature compensatory effect, which quantifies the increase in cumulative air temperature from soil temperature increase caused by mulching, provides an effective method for incorporating soil temperature into crop models. In this study, compensated temperature was integrated into the AquaCrop model to investigate the capability of the compensatory effect to improve assessment of the promotion of maize growth and development by plastic film mulching(PM). A three-year experiment was conducted from2014 to 2016 with two maize varieties(spring and summer) and two mulching conditions(PM and non-mulching(NM)), and the AquaCrop model was employed to reproduce crop growth and yield responses to changes in NM, PM, and compensated PM. A marked difference in soil temperature between NM and PM was observed before 50 days after sowing(DAS) during three growing seasons. During sowing–emergence and emergence–tasseling, the increase in air temperature was proportional to the compensatory coefficient, with spring maize showing a higher compensatory temperature than summer maize. Simulation results for canopy cover(CC) were generally in good agreement with the measurements, whereas predictions of aboveground biomass and grain yield under PM indicated large underestimates from 60 DAS to the end of maturity. Simulations of spring maize biomass and yield showed general increase based on temperature compensation, accompanied by improvement in modeling accuracy, with RMSEs decreasing from 2.5 to 1.6 t ha^(-1)and from 4.1 t to 3.4 t ha^(-1). Improvement in biomass and yield simulation was less pronounced for summer than for spring maize, implying that crops grown during low-temperature periods would benefit more from the compensatory effect. This study demonstrated the effectiveness of the temperature compensatory effect to improve the performance of the AquaCrop model in simulating maize growth under PM practices.

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.

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-△K relations, the confidence-based da/dN-△K relations, and the probabilistic- and confidence-based da/dN-△K 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.

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.

Predictive ability of genomic selection models for breeding value estimation on growth traits of Pacific white shrimp Litopenaeus vannamei

Genomic selection(GS)can be used to accelerate genetic improvement by shortening the selection interval.The successful application of GS depends largely on the accuracy of the prediction of genomic estimated breeding value(GEBV).This study is a fi rst attempt to understand the practicality of GS in Litopenaeus vannamei and aims to evaluate models for GS on growth traits.The performance of GS models in L.vannamei was evaluated in a population consisting of 205 individuals,which were genotyped for 6 359 single nucleotide polymorphism(SNP)markers by specifi c length amplifi ed fragment sequencing(SLAF-seq)and phenotyped for body length and body weight.Three GS models(RR-BLUP,Bayes A,and Bayesian LASSO)were used to obtain the GEBV,and their predictive ability was assessed by the reliability of the GEBV and the bias of the predicted phenotypes.The mean reliability of the GEBVs for body length and body weight predicted by the dif ferent models was 0.296 and 0.411,respectively.For each trait,the performances of the three models were very similar to each other with respect to predictability.The regression coeffi cients estimated by the three models were close to one,suggesting near to zero bias for the predictions.Therefore,when GS was applied in a L.vannamei population for the studied scenarios,all three models appeared practicable.Further analyses suggested that improved estimation of the genomic prediction could be realized by increasing the size of the training population as well as the density of SNPs.

GPU parallel computation of dendrite growth competition in forced convection using the multi-phase-field-lattice Boltzmann model

A graphics-processing-unit(GPU)-parallel-based computational scheme is developed to realize the competitive growth process of converging bi-crystal in two-dimensional states in the presence of forced convection conditions by coupling a multi-phase field model and a lattice Boltzmann model.The elimination mechanism in the evolution process is analyzed for the three conformational schemes constituting converging bi-crystals under pure diffusion and forced convection conditions,respectively,expanding the research of the competitive growth of columnar dendrites under melt convection conditions.The results show that the elimination mechanism for the competitive growth of converging bi-crystals of all three configurations under pure diffusion conditions follows the conventional Walton-Chalmers model.When there is forced convection with lateral flow in the liquid phase,the anomalous elimination phenomenon of unfavorable dendrites eliminating favorable dendrites occurs in the grain boundaries.In particular,the anomalous elimination phenomenon is relatively strong in conformation 1 and conformation 2 when the orientation angle of unfavorable dendrites is small,and relatively weak in conformation 3.Moreover,the presence of convection increases the tip growth rate of both favorable and unfavorable dendrites in the grain boundary.In addition,the parallelization of the multi-phase-field-lattice Boltzmann model is achieved by designing the parallel computation of the model on the GPU platform concerning the computerunified-device-architecture parallel technique,and the results show that the parallel computation of this model based on the GPU has absolute advantages,and the parallel acceleration is more obvious as the computation area increases.