Model fitting of the seasonal population dynamics of the soybean aphid, Aphis glycines Matsumura, in the field

The soybean aphid, Aphis glycines Matsumura(Hemiptera: Aphididae), is one of the greatest threats to soybean production, and both trend analysis and periodic analysis of its population dynamics are important for integrated pest management(IPM). Based on systematically investigating soybean aphid populations in the field from 2018 to 2020, this study adopted the inverse logistic model for the first time, and combined it with the classical logistic model to describe the changes in seasonal population abundance from colonization to extinction in the field. Then, the increasing and decreasing phases of the population fluctuation were divided by calculating the inflection points of the models, which exhibited distinct seasonal trends of the soybean aphid populations in each year. In addition, multifactor logistic models were then established for the first time, in which the abundance of soybean aphids in the field changed with time and relevant environmental conditions. This model enabled the prediction of instantaneous aphid abundance at a given time based on relevant meteorological data. Taken as a whole, the successful approaches implemented in this study could be used to build a theoretical framework for practical IPM strategies for controlling soybean aphids.

Spreading speed of a food-limited population model with delay

This paper is concerned with the spreading speed of a food-limited population model with delay.First,the existence of the solution of Cauchy problem is proved.Then,the spreading speed of solutions with compactly supported initial data is investigated by using the general Harnack inequality.Finally,we present some numerical simulations and investigate the dynamical behavior of the solution.

On the optimal harvesting of size-structured population dynamics

This work is concerned with a kind of optimal control problem for a size-structured biological population model.Well-posedness of the state system and an adjoint system are proved by means of Banach＇s fixed point theorem.Existence and uniqueness of optimal control are shown by functional analytical approach.Optimality conditions describing the optimal strategy are established via tangent and normal cones technique.The results are of the first ones for this novel structure.

Virtual population pharmacokinetic using physiologically based pharmacokinetic model for evaluating bioequivalence of oral lacidipine formulations in dogs

The aim of the present study was to investigate virtual population pharmacokinetic using physiologically based pharmacokinetic(PBPK) model for evaluating bioequivalence of oral lacidipine formulations in dogs. The dissolution behaviors of three lacidipine formulations including one commercial product and two self-made amorphous solid dispersions(ASDs)capsules were determined in 0.07% Tween 80 media. A randomized 3-period crossover design in 6 healthy beagle dogs after oral administration of the three formulations at a single dose of 4 mg was conducted. The PBPK modeling was utilized for the virtual bioequivalence study.In vitro dissolution experiment showed that the dissolution behaviors of lacidipine amorphous solid dispersions(ASDs) capsules, which was respectively prepared by HPMC-E5 or Soluplus, as polymer displayed similar curves compared with the reference formulation in 0.07% Tween 80 media. In vivo pharmacokinetics experiments showed that three formulations had comparable maximum plasma drug concentration(Cmax), and the time(Tmax) to reach Cmax of lacidipine tablet, which was prepared by Soluplus, as polymer was slower than other two formulations in consistency with the in vitro dissolution rate. The 90% confidence interval(CI) for the Cmax, AUC0–24 h and AUC0–∞ of the ratio of the test drug to the reference drug exceeded the acceptable bioequivalence(BE) limits(0.80–1.25). However, the 90% CI of the AUC0–24 h, AUC0–∞ and Cmax of the ratio of test to reference drug were within the BE limit,calculated using PBPK modeling when the virtual subjects reached 24 dogs. The results all demonstrated that virtual bioequivalence study can overcome the inequivalence caused by inter-subject variability of the 6 beagle dogs involved in in vivo experiments.

THE PERIODIC SOLUTIONS FOR TIME DEPENDENT AGE-STRUCTURED POPULATION MODELS

In this paper, the existence of periodic solutions for a time dependent age-structured population model is studied. The averaged net reproductive number is introduced as the main parameter to determine the dynamical behaviors of the model. The existence of a global parameterized branch of periodic solutions of the model is obtained by using the contracting mapping theorem in a periodic and continuous function space. The global stability of the trivial equilibrium is studied and a very practical stability criteria for the model is obtained. The dynamics of the linear time-periodic model is similar to that of the linear model.

Risk prediction models for hepatocellular carcinoma in different populations

Hepatocellular carcinoma （HCC） is a malignant disease with limited therapeutic options due to its aggressive progression. It places heaW burden on most low and middle income countries to treat HCC patients. Nowadays accurate HCC risk predictions can help making decisions on the need for HCC surveillance and antiviral therapy. HCC risk prediction models based on major risk factors of HCC are useful and helpful in providing adequate surveillance strategies to individuals who have different risk levels. Several risk prediction models among cohorts of different populations for estimating HCC incidence have been presented recently by using simple, efficient, and ready-to-use parameters. Moreover, using predictive scoring systems to assess HCC development can provide suggestions to improve clinical and public health approaches, making them more cost-effective and effort-effective, for inducing personalized surveillance programs according to risk stratification. In this review, the features of risk prediction models of HCC across different populations were summarized, and the perspectives of HCC risk prediction models were discussed as well.

Application of the Method of Characteristics to Population Balance Models Considering Growth and Nucleation Phenomena

The population balance modeling is regarded as a universally accepted mathematical framework for dynamic simulation of various particulate processes, such as crystallization, granulation and polymerization. This article is concerned with the application of the method of characteristics (MOC) for solving population balance models describing batch crystallization process. The growth and nucleation are considered as dominant phenomena, while the breakage and aggregation are neglected. The numerical solutions of such PBEs require high order accuracy due to the occurrence of steep moving fronts and narrow peaks in the solutions. The MOC has been found to be a very effective technique for resolving sharp discontinuities. Different case studies are carried out to analyze the accuracy of proposed algorithm. For validation, the results of MOC are compared with the available analytical solutions and the results of finite volume schemes. The results of MOC were found to be in good agreement with analytical solutions and superior than those obtained by finite volume schemes.

QUALITATIVE ANALYSIS OF BOBWHITE QUAIL POPULATION MODEL

In this paper, the qualitative behavior of solutions of the bobwhite quail pop-ulation modelwhere 0<a < 1 < a + 6,p, c ∈ (0, ∞) and k is a nonnegative integer, is investigated. Some necessary and sufficient as well as sufficient conditions for all solutions of the model to oscillate and some sufficient conditions for all positive solutions of the model to be nonoscillatory and the convergence of nonoscillatory solutions are derived. Furthermore, the permanence of every positive solution of the model is also showed. Many known results are improved and extended and some new results are obtained for G. Ladas' open problems.

Urban Agglomerations in China: Characteristics and Influencing Factors of Population Agglomeration

Urban agglomeration(UA)is an advanced spatial economic form formed and developed in the process of rapid industrialization and urbanization,and an important carrier of urbanization and economic development.The economy has developed rapidly in the recent decades of China,and the UAs have also developed rapidly.However,as a large population country,the population distribution and changes of UAs in China has unique characteristics.Using the fifth,sixth and seventh population census data,spatial auto-correlation and spatial econometric models,we analyzed the spatial-temporal evolution characteristics and influencing factors of population agglomeration in China’s UAs.Results revealed that:1)from 2000 to 2020,the population gradually converged into UAs,and the characteristics of population agglomeration in different development degree of UAs differ.The higher the development degree of UA,the higher the population agglomeration degree.Besides,UAs are the main area with the most significant population agglomeration degree,and the spatial autocorrelation show that the cities with similar degree tend to be concentrated in space.The urban population gathering in UAs has a certain positive spillover effect on population size of neighboring cities.2)Economic development and social conditions factors are important factors affecting population agglomeration degree in UAs.The main factors of population gather into UAs are similar with the outside UAs,but the positive promotion of urbanization rate and proportion of tertiary industry in GDP on population agglomeration of UAs in China are enhancing from 2000 to 2020.Meanwhile,the other factors,such as high-quality public services,good urban living environment conditions,high-quality medical and educational resources,are also important factors to promote urban population gather into UAs.This study provides a basis for formulating the development planning of UAs in China,and enriches the relevant theoretical research of population evolution and influencing factors of UAs.

QUALITATIVE ANALYSIS OF A DICRETE POPULATION MODEL

In this paper, authors study the qualitative behavior of solutions of the discrete population model xn-xn-1=xn (a+bxn-k-cx2n-k),where a ∈ (0, 1), b ∈ (-∞, 0),c ∈ (0,∞ ), and k is a positive integer. They hot only obtain necessary as well as sufficient and necessary conditions for the oscillation of ail eventually positive solutions about the positive equilibrium, but also obtain some sufficient conditions for the convergence of eventually positive solutions. Furthermore, authors also show that such model is uniformly persistent, and that all its eventually positive solutions are bounded.

Closed-loop control of epileptiform activities in a neural population model using a proportional-derivative controller

Epilepsy is believed to be caused by a lack of balance between excitation and inhibitation in the brain. A promising strategy for the control of the disease is closed-loop brain stimulation. How to determine the stimulation control parameters for effective and safe treatment protocols remains, however, an unsolved question. To constrain the complex dynamics of the biological brain, we use a neural population model（NPM）. We propose that a proportional-derivative（PD） type closed-loop control can successfully suppress epileptiform activities. First, we determine the stability of root loci, which reveals that the dynamical mechanism underlying epilepsy in the NPM is the loss of homeostatic control caused by the lack of balance between excitation and inhibition. Then, we design a PD type closed-loop controller to stabilize the unstable NPM such that the homeostatic equilibriums are maintained; we show that epileptiform activities are successfully suppressed. A graphical approach is employed to determine the stabilizing region of the PD controller in the parameter space, providing a theoretical guideline for the selection of the PD control parameters. Furthermore, we establish the relationship between the control parameters and the model parameters in the form of stabilizing regions to help understand the mechanism of suppressing epileptiform activities in the NPM. Simulations show that the PD-type closed-loop control strategy can effectively suppress epileptiform activities in the NPM.

Population dynamics modelling with spatial heterogeneity for yellow croaker(Larimichthys polyactis)along the coast of China

As one of the top four commercially important species in China,yellow croaker(Larimichthys polyactis)with two geographic subpopulations,has undergone profound changes during the last several decades.It is widely comprehended that understanding its population dynamics is critically important for sustainable management of this valuable fishery in China.The only two existing population dynamics models assessed the population of yellow croaker using short time-series data,without considering geographical variations.In this study,Bayesian models with and without hierarchical subpopulation structure were developed to explore the spatial heterogeneity of the population dynamics of yellow croaker from 1968 to 2015.Alternative hypotheses were constructed to test potential temporal patterns in yellow croaker’s population dynamics.Substantial variations in population dynamics characteristics among space and time were found through this study.The population growth rate was revealed to increase since the late 1980s,and the catchability increased more than twice from 1981 to 2015.The East China Sea’s subpopulation witnesses faster growth,but suffers from higher fishing pressure than that in the Bohai Sea and Yellow Sea.The global population and two subpopulations all have high risks of overfishing and being overfished according to the MSY-based reference points in recent years.More conservative management strategies with subpopulation considerations are imperative for the fishery management of yellow croaker in China.The methodology developed in this study could also be applied to the stock assessment and fishery management of other species,especially for those species with large spatial heterogeneity data.

Analysis and Study on Spatial Gravity Center of PM_(2.5) and Population Scale

With the rapid development of urbanization construction in China,population and industries are rapidly gathering in cities,bringing about economic development and also causing a large number of environmental problems,among which PM_(2.5) is the most concerned.In this paper,a spatial gravity center model was used to systematically analyze the spatiotemporal distribution characteristics of PM_(2.5) and population scale in China from 1999 to 2016.Conclusions were as below:(1)there were significant regional differences in PM_(2.5) pollution from 1999 to 2016,characterized by a spatial distribution of"high in the north and low in the south,and high in the inland and low in the coastal areas".(2)Nationwide,there was a significant spatial mismatch between the gravity center of PM_(2.5) pollution and the gravity center of population scale,with the two centers showing a trend of reverse dislocation development.

SPATIALIZATION MODEL OF POPULATION BASED ON DATASET OF LAND USE AND LAND COVER CHANGE IN CHINA

The spatialization of population of counties in China is significant. Firstly, we can gain the estimated values of population density adaptive to different kinds of regions. Secondly, we can integrate effectively population data with other data including natural resources, environment, society and economy, build 1km GRIDs of natural resources reserves per person, population density and other economic and environmental data, which are necessary to the national management and macro adjustment and control of natural resources and dynamic monitoring of population. In order to establish population information system serving national decision making, three steps ought to be followed:1) establishing complete geographical spatial data foundation infrastructure including the establishment of electric map of residence with high resolution using topographical map with large scale and high resolution satellite remote sensing data, the determination of attribute information of housing and office buildings, and creating complete set of attribute database and rapid data updating; 2) establishing complete census systems including improving the transformation efficiency from census data to digital database and strengthening the link of census database and geographical spatial database, meanwhile, the government should attach great importance to the establishment and integration of population migration database; 3) considering there is no GIS software specially serving the analysis and management of population data, a practical approach is to add special modules to present software system, which works as a bridge actualizing the digitization and spatialization of population geography research.

Exact Solutions of Fractional-Order Biological Population Model

在这份报纸， Adomian 的分解方法(ADM ) 被介绍因为发现一张更一般的生物人口的准确答案当模特儿。一个新答案在力量系列被构造。部分衍生物在 Caputo 意义被描述。说明方法的可靠性，一些例子被提供。

Nonlinear dynamical wave structures of Zoomeron equation for population models

The nonlinear dynamical exact wave solutions to the non-fractional order and the time-fractional order of the biological population models are achieved for the first time in the framwork of the Paul-Painlevéapproach method(PPAM).When the variables appearing in the exact solutions take specific values,the solitary wave solutions will be easily obtained.The realized results prove the efficiency of this technique.

A Guide to Population Modelling for Simulation

This paper outlines the fundamentals of a consistent theory of numerical modelling of a population system under study. The focus is on the systematic work to construct an executable simulation model. There are six fundamental choices of model category and model constituents to make. These choices have a profound impact on how the model is structured, what can be studied, possible introduction of bias, lucidity and comprehensibility, size, expandability, performance of the model, required information about the system studied and its range of validity. The first choice concerns a discrete versus a continuous description of the population system under study—a choice that leads to different model categories. The second choice is the model representation (based on agents, entities, compartments or situations) used to describe the properties and behaviours of the objects in the studied population. Third, incomplete information about structure, transitions, signals, initial conditions or parameter values in the system under study must be addressed by alternative structures and statistical means. Fourth, the purpose of the study must be explicitly formulated in terms of the quantities used in the model. Fifth, irrespective of the choice of representation, there are three possible types of time handling: Event Scheduling, Time Slicing or Micro Time Slicing. Sixth, start and termination criteria for the simulation must be stated. The termination can be at a fixed end time or determined by a logical condition. Population models can thereby be classified within a unified framework, and population models of one type can be translated into another type in a consistent way. Understanding the pros and cons for different choices of model category, representation, time handling etc. will help the modeller to select the most appropriate type of model for a given purpose and population system under study. By understanding the rules for consistent population modelling, an appropriate model can be created in a systematic way and a number of pitfalls can be avoided.

Risk factors for acute kidney injury following coronary artery bypass graft surgery in a Chinese population and development of a prediction model

BACKGROUND Acute kidney injury(AKI)after coronary artery bypass graft(CABG)surgery is associated with significant morbidity and mortality.This retrospective study aimed to establish a risk score for postoperative AKI in a Chinese population.METHODS A total of 1138 patients undergoing CABG were collected from September 2018 to May 2020 and divided into a derivation and validation cohort.AKI was defined according to the Kidney Disease Improving Global Outcomes(KDIGO)criteria.Multivariable logistic regression analysis was used to determine the independent predictors of AKI,and the predictive ability of the model was determined using a receiver operating characteristic(ROC)curve.RESULTS The incidence of cardiac surgery–associated acute kidney injury(CSA-AKI)was 24.17%,and 0.53%of AKI patients required dialysis(AKI-D).Among the derivation cohort,multivariable logistic regression showed that age≥70 years,body mass index(BMI)≥25 kg/m2,estimated glomerular filtration rate(eGFR)≤60 mL/min per 1.73 m2,ejection fraction(EF)≤45%,use of statins,red blood cell transfusion,use of adrenaline,intra-aortic balloon pump(IABP)implantation,postoperative low cardiac output syndrome(LCOS)and reoperation for bleeding were independent predictors.The predictive model was scored from 0 to32 points with three risk categories.The AKI frequencies were as follows:0-8 points(15.9%),9-17 points(36.5%)and≥18 points(90.4%).The area under of the ROC curve was 0.730(95%CI:0.691-0.768)in the derivation cohort.The predictive index had good discrimination in the validation cohort,with an area under the curve of 0.735(95%CI:0.655-0.815).The model was well calibrated according to the Hosmer-Lemeshow test(P=0.372).CONCLUSION The performance of the prediction model was valid and accurate in predicting KDIGO-AKI after CABG surgery in Chinese patients,and could improve the early prognosis and clinical interventions.

Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a serious threat worldwide.Although early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not optimistic.In China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been conducted.Therefore,it is necessary to develop a simple and efficient early screening model for CRC.AIM To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.METHODS Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively analyzed.The cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect data.Of 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were not.The participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve analysis.Finally,the model was validated internally using a bootstrap resampling technique.RESULTS Seven variables,including demographic,lifestyle,and family history information,were examined.Multifactorial logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P<0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P<0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P<0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P<0.001),and family history(OR:4.28,95%CI:4.04-4.54,P<0.001)were the most significant predictors of high-risk CRC.Healthy lifestyle was a protective factor,whereas family history was the most significant risk factor.The area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training set ROC curve.The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.CONCLUSION The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age,BMI,WC,lifestyle,and family history exhibited high accuracy.

Selection model of trip time for rural population

Referring to the 1 248 survey data of rural population in 14 provinces of China, the influencing factors of trip time choice were analyzed. Based on the basic theory of disaggregate model and its modelling method, nine grades were selected as the alternatives of trip time, the variables affecting time choice and the method getting their values were determined, and a multinomial logit (MNL) model was developed. Another 1 200 trip data of rural population were selected to testify the model's validity. The result shows that the maximum absolute error of each period between calculated value and statistic is 3.6%, so MNL model has high calculation accuracy.