Toward a sustainable growth path in Arab economies:an extension of classical growth model

Background/Objectives:Many economies are on the trajectory of alternative growth drivers other than conventional capital and labor.Access to credit facilities is a pertinent indicator of economic growth.In line with the United Nations Sustainable Development Goals(UNSDGs-8)agenda,the national goal for sustainable development for most economies and Arab economies is no exception.Therefore,the current study adopts a traditional growth model by exploring the relationship between gross domestic product(GDP)per capita,credit for private sectors,ratio of exports,real GDP,and per labor force participants for selected Arab economies annually from 2001 to 2020.Research design:This study leverages the Fourier Kwiatkowski–Phillips–Schmidt–Shin(KPSS)unit root test and second-generation panel econometrics as estimation techniques,such as Westerlund and Edgerton panel cointegration test,and the use of two estimators,namely the augmented mean group(AMG)and common correlated error mean group(CCEMG),to obtain robust results.Findings:Empirical findings from Westerlund and Edgerton panel cointegration tests validate the long-run equilibrium relationship among the outlined variables.Further empirical results indicate that the share of exports is negatively significant with economic growth in countries such as Kuwait,Lebanon,Tunisia,and Jordan.Additionally,savings and labor force participation have a positive relationship with economic growth in individual countries such as Algeria and Bahrain.As per the panel,there is no significant relationship between labor force participation and economic growth.This indicates that the skilled labor force enhanced economic growth.Conclusions:These findings come with inherent far-reaching policy suggestions for economies and panels.Further details on country-specific policy actions are presented in the concluding section.

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.

Growth model of cavity generated by the projectile impacting liquid-filled tank

The high-speed impact of a projectile on a liquid-filled tank causes the hydraulic ram,in which a cavity is formed.To study the growth characteristics of the cavity,the formation mechanism of the cavity is analyzed.The effect of Reynolds number and Mach number on drag coefficient is considered,the axial and radial growth models of the cavity are established respectively.The relative errors between the cavity length calculated by the axial growth model,the cavity diameter calculated by the radial growth model and Ma L.Y.test results are less than 20%,which verifies the effectiveness of the axial and radial growth models.Finally,numerical simulation is carried out to study the growth characteristics of the cavity caused by the projectile impacting the satellite tank at the velocity of 4000 m/s.The cavity length and diameter calculated by the axial and radial growth models agree well with those obtained by simulation results,indicating that the cavity length and diameter in satellite tank can be accurately calculated by the axial and radial growth models.

Discrete Software Reliability Growth Modeling for Errors of Different Severity Incorporating Change-point Concept

Several software reliability growth models （SRGM） have been developed to monitor the reliability growth during the testing phase of software development. In most of the existing research available in the literatures, it is considered that a similar testing effort is required on each debugging effort. However, in practice, different types of faults may require different amounts of testing efforts for their detection and removal. Consequently, faults are classified into three categories on the basis of severity： simple, hard and complex. This categorization may be extended to r type of faults on the basis of severity. Although some existing research in the literatures has incorporated this concept that fault removal rate （FRR） is different for different types of faults, they assume that the FRR remains constant during the overall testing period. On the contrary, it has been observed that as testing progresses, FRR changes due to changing testing strategy, skill, environment and personnel resources. In this paper, a general discrete SRGM is proposed for errors of different severity in software systems using the change-point concept. Then, the models are formulated for two particular environments. The models were validated on two real-life data sets. The results show better fit and wider applicability of the proposed models as to different types of failure datasets.

Effects of Lvy noise and immune delay on the extinction behavior in a tumor growth model

The combined effects of Ltvy noise and immune delay on the extinction behavior in a tumor growth model are explored, The extinction probability of tumor with certain density is measured by exit probability. The expression of the exit probability is obtained using the Taylor expansion and the infinitesimal generator theory. Based on numerical calculations, it is found that the immune delay facilitates tumor extinction when the stability index α〈 1, but inhibits tumor extinction when the stability index α 〉 1. Moreover, larger stability index and smaller noise intensity are in favor of the extinction for tumor with low density. While for tumor with high density, the stability index and the noise intensity should be reduced to promote tumor extinction.

A Knowledge Model-and Growth Model-Based Decision Support System for Wheat Management

By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management(WheatKnow)was developed. By adopting the soft component characteristics as non language relevance , re-utilization and portable system maintenance. and by further integrating the wheat growth simulation model(WheatGrow)and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management(MBDSSWM)was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.

Individual-tree diameter growth model for Korean pine plantations based on optimized interpolation of meteorological variables

To explore the influence of meteorological variables on the growth of Korean pine(Pinus koraiensis Sieb.et Zucc.) plantations and provide a scientific reference for the production and management of Korean pine,three approaches to interpolate meteorological variables during the growing season(i.e.,May-September) were compared in Heilongjiang Province,China.Optimized meteorological variable interpolation results were then combined with stand and individual tree variables,based on data from 56 sample plots and 2886 sample trees from Korean pine plantations in two regions of the province to develop an individualtree diameter growth model(Model I) and an individualtree diameter growth model with meteorological variables(Model Ⅱ) using a stepwise regression method.Moreover,an individual-tree diameter growth model with regional effects(Model Ⅲ) was developed using dummy variables in the regression,and the significance of introducing these dummy variables was verified with an F-test statistical analysis.The models were validated using an independent data set,and the predictive performance of the three models was assessed via the adjusted coefficient of determination(R_(a)^(2)) and root mean square error(RMSE).The results suggest that the growth increment in tree diameter of Korean pine plantations was significantly correlated with the natural logarithm of initial diameter(ln D),stand basal area(BAS),logarithmic deformation of the stand density index(ln SDI),ratio of basal area of trees larger than the subject tree to their initial diameter at breast height(DBH)(BAL/D),and the maximum growingseason precipitation(Pgmax).The individual-tree diameter growth models of Korean pine plantations developed in this study will provide a good basis for estimating and predicting growth increments of Korean pine forests over larger areas.

Unsuspected implications arising from assumptions in simulations: insights from recasting a forest growth model in system dynamics

Background:Familiarity with a simulation platform can seduce modellers into accepting untested assumptions for convenience of implementation.These assumptions may have consequences greater than commonly suspected,and it is important that modellers remain mindful of assumptions and remain diligent with sensitivity testing.Methods:Familiarity with a technique can lead to complacency,and alternative approaches and software can reveal untested assumptions.Visual modelling environments based on system dynamics may help to make critical assumptions more evident by offering an accessible visual overview and empowering a focus on representational rather than computational efficiency.This capacity is illustrated using a cohort-based forest growth model developed for mixed species forest.Results:The alternative model implementation revealed that untested assumptions in the original model could have substantial influence on simulated outcomes.Conclusions:An important implication is that modellers should remain conscious of all assumptions,consider alternative implementations that reveal assumptions more clearly,and conduct sensitivity tests to inform decisions.

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

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

An imputation/copula-based stochastic individual tree growth model for mixed species Acadian forests： a case study using the Nova Scotia permanent sample plot network

Background： A novel approach to modelling individual tree growth dynamics is proposed. The approach combines multiple imputation and copula sampling to produce a stochastic individual tree growth and yield projection system. Methods： The Nova Scotia, Canada permanent sample plot network is used as a case study to develop and test the modelling approach. Predictions from this model are compared to predictions from the Acadian variant of the Forest Vegetation Simulator, a widely used statistical individual tree growth and yield model. Results： Diameter and height growth rates were predicted with error rates consistent with those produced using statistical models. Mortality and ingrowth error rates were higher than those observed for diameter and height, but also were within the bounds produced by traditional approaches for predicting these rates. Ingrowth species composition was very poorly predicted. The model was capable of reproducing a wide range of stand dynamic trajectories and in some cases reproduced trajectories that the statistical model was incapable of reproducing. Conclusions： The model has potential to be used as a benchmarking tool for evaluating statistical and process models and may provide a mechanism to separate signal from noise and improve our ability to analyze and learn from large regional datasets that often have underlying flaws in sample design.

A growth model for a hyalid amphipod Hyale perieri in the coastal water of Alexandria(Egypt)

The growth rate of the hyalid amphipod Hyale perieri was studied on the bases of Ikeda'sgrowth model which is based on the inter moult period (IP) and moult increament (△BL). To apply this approach, laboratory experiments were carried out at three temperatures regimes (15℃, 20℃, 25℃ ) to gain accurate data of IP and BL. The total number of specimens used in this study was 86 at 15℃ , 24 at 20℃ and 70 at 25℃. The number of flagellar segments of both antennae of the Hyale perieri could not be used as an index of growth (instar criterion). The obtained results indicated that, the predicted IP of the specimens was inversely related to temperature and in good agreement with the observed values at the experimental temperatures. IP data obtained from laboratory-reared specimes are combined with ABL data to establish a growth model for Hyale perieri from its release from the mar-supium (1.64 mm BL ) to the maximum size (12.67 mm BL) as a function of temperature. The maximum numbers of consecutive moults recorded during the experiment were 13 moults (14 instar) at 15℃, 14 moults (15 instar) at 20℃ and 12 moults (13 instar) at 25℃ . The predicted life span for BL = 12.67 mm (moult 13) was 203.82 d at 15t, for BL = 11.75 mm (moult 14) was 138.94 d at 20℃ and for BL = 8.65 mm (moult 12) was 75.40 d at 25℃ respectively, thus confirming that the life span of the species is inversely proportional to temperature. Within the experimental temperatures tested, the optimum temperature for the growth of the species was 20℃.

Reliability Growth Modeling and Optimal Release Policy Under Fuzzy Environment of an N-version Programming System Incorporating the Effect of Fault Removal Efficiency

Failure of a safety critical system can lead to big losses. Very high software reliability is required for automating the working of systems such as aircraft controller and nuclear reactor controller software systems. Fault-tolerant softwares are used to increase the overall reliability of software systems. Fault tolerance is achieved using the fault-tolerant schemes such as fault recovery （recovery block scheme）, fault masking （N-version programming （NVP）） or a combination of both （Hybrid scheme）. These softwares incorporate the ability of system survival even on a failure. Many researchers in the field of software engineering have done excellent work to study the reliability of fault-tolerant systems. Most of them consider the stable system reliability. Few attempts have been made in reliability modeling to study the reliability growth for an NVP system. Recently, a model was proposed to analyze the reliability growth of an NVP system incorporating the effect of fault removal efficiency. In this model, a proportion of the number of failures is assumed to be a measure of fault generation while an appropriate measure of fault generation should be the proportion of faults removed. In this paper, we first propose a testing efficiency model incorporating the effect of imperfect fault debugging and error generation. Using this model, a software reliability growth model （SRGM） is developed to model the reliability growth of an NVP system. The proposed model is useful for practical applications and can provide the measures of debugging effectiveness and additional workload or skilled professional required. It is very important for a developer to determine the optimal release time of the software to improve its performance in terms of competition and cost. In this paper, we also formulate the optimal software release time problem for a 3VP system under fuzzy environment and discuss a the fuzzy optimization technique for solving the problem with a numerical illustration.

Construction of Clonal Growth Models in Trifolium repens

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

Studies on crop growth modelling and simulation models in China

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

Finite Element Simulation of In-Stent Restenosis with Tissue Growth Model

In this study, a finite element simulation of in-stent restenosis (ISR) is conducted to simulate the deployment and expansion of a stent in an occluded artery with a contact model and a mechanics-based growth model. A tissue growth model based on the multiplicative decomposition of deformation is applied to investigate the growth of the plaque and artery wall upon the stent’s implantation. Due to the high stresses at the contact points between the stent struts and the tissue, further tissue injury or restenosis is observed. The simulation results show that after the stent deployment, the von Mises stress is significantly larger in the plaque compared to the artery wall, especially in the region that is in contact with the stent. However, the growth of the plaque and artery tends to even out the stress concentration over time. The tissue growth is found to be more significant near the inner wall than the outer layer. A 0.77 mm restenosis is predicted, which agrees with published clinical observations. The features of the artery growth are carefully analyzed, and the underlying mechanism is discussed. This study is the first attempt to apply finite element analysis to artery restenosis, which establishes a framework for predicting ISR’s occurrence and severity. The results also provide insights into understanding the underlying mechanism of in-stent restenosis.

Striving For A New Growth Model

China will face some structural challenges in the next five years.Global interest rates will likely rise.The labor force in China is shrinking.Property and in-frastructure investments face constraints as growth is driven.Financial risks have reached alarming levels.Environmental constraints are also clear.President Xi Jinping has entered his second term.His speech during the 19th Party Congress suggests that China will strive for a new growth model in the next few years—focusing more on sustain-

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

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

Growth Model of Local Government Websites

To clarify the concept framework to assess web based information systems (WIS) evolution from an information perspective instead of the usual systems perspective, and to seek for in-depth understanding of maturing patterns of WISs based on the framework, several central concepts related to the information aspect of WIS are firstly discussed, then a growth model of local government websites based on a survey study is proposed.

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

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

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

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