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The complex interactions were performed among non-pharmaceutical interventions, vaccinations, and hosts for all epidemics in mainland China during the spread of COVID-19. Specially, the small-scale epidemic in the city described by SVEIR model was less found in the current studies. The SVEIR model with control was established to analyze the dynamical and epidemiological features of two epidemics in Jinzhou City led by Omicron variants before and after Twenty Measures. In this study, the total population (N) of Jinzhou City was divided into five compartments: the susceptible (S), the vaccinated (V), the exposed (E), the infected (I), and the recovered (R). By surveillance data and the SVEIR model, three methods (maximum likelihood method, exponential growth rate method, next generation matrix method) were governed to estimate basic reproduction number, and the results showed that an increasing tendency of basic reproduction number from Omicron BA.5.2 to Omicron BA.2.12.1. Meanwhile, the effective reproduction number for two epidemics were investigated by surveillance data, and the results showed that Jinzhou wave 1 reached the peak on November 1 and was controlled 7 days later, and that Jinzhou wave 2 reached the peak on November 28 and was controlled 5 days later. Moreover, the impacts of non-pharmaceutical interventions (awareness delay, peak delay, control intensity) were discussed extensively, the variations of infection scales for Omicron variant and EG.5 variant were also discussed. Furthermore, the investigations on peaks and infection scales for two epidemics in dynamic zero-COVID policy were operated by the SVEIR model with control. The investigations on public medical requirements of Jinzhou City and Liaoning Province were analyzed by using SVEIR model without control, which provided a possible perspective on variant evolution in the future.

Background: The structure of age groups and social contacts of the total population influenced infection scales and hospital-bed requirements, especially influenced severe infections and deaths during the global prevalence of COVID-19. Before the end of the year 2022, Chinese government implemented the national vaccination and had built the herd immunity cross the country, and announced Twenty Measures (November 11) and Ten New Measures (December 7) for further modifications of dynamic zero-COVID polity on the Chinese mainland. With the nation-wide vaccination and modified measures background, Fuzhou COVID-19 large wave (November 19, 2022–February 9, 2023) led by Omicron BA.5.2 variant was recorded and prevailed for three months in Fujian Province. Methods: A multi-age groups susceptible-exposed-infected-hospitalized-recovered (SEIHR) COVID-19 model with social contacts was proposed in this study. The main object was to evaluate the impacts of age groups and social contacts of the total population. The idea of Least Squares method was governed to perform the data fittings of four age groups against the surveillance data from Fujian Provincial Center for Disease Control and Prevention (Fujian CDC). The next generation matrix method was used to compute basic reproduction number for the total population and for the specific age group. The tendencies of effective reproduction number of four age groups were plotted by using the Epiestim R package and the SEIHR model for in-depth discussions. The sensitivity analysis by using sensitivity index and partial rank correlation coefficients values (PRCC values) were operated to reveal the differences of age groups against the main parameters. Results: The main epidemiological features such as basic reproduction number, effective reproduction number and sensitivity analysis were extensively discussed for multi-age groups SEIHR model in this study. Firstly, by using of the next generation matrix method, basic reproduction number R0 of the total population was estimated as 1.57 using parameter values of four age groups of Fuzhou COVID-19 large wave. Given age group k, the values of R0k (age group k to age group k), the values of R0k (an infected of age group k to the total population) and the values of R^0k (an infected of the total population to age group k) were also estimated, in which the explorations of the impacts of age groups revealed that the relationship R0k>R0k>R^0k was valid. Then, the fluctuating tendencies of effective reproduction number Rt were demonstrated by using two approaches (the surveillance data and the SEIHR model) for Fuzhou COVID-19 large wave, during which high-risk group (G4 group) mainly contributed the infection scale due to high susceptibility to infection and high risks to basic diseases. Further, the sensitivity analysis using two approaches (the sensitivity index and the PRCC values) revealed that susceptibility to infection of age groups played the vital roles, while the numerical simulation showed that infection scale varied with the changes of social contacts of age groups. The results of this study claimed that the high-risk group out of the total population was concerned by the local government with the highest susceptibility to infection against COVID-19. Conclusions: This study verified that the partition structure of age groups of the total population, the susceptibility to infection of age groups, the social contacts among age groups were the important contributors of infection scale. The less social contacts and adequate hospital beds for high-risk group were profitable to control the spread of COVID-19. To avoid the emergence of medical runs against new variant in the future, the policymakers from local government were suggested to decline social contacts when hospital beds were limited.

The estimation methods of reproduction numbers and serial intervals are important in the early stages of infectious diseases. During the COVID pandemic, China implemented a dynamic zero-COVID policy on the Chinese mainland until the end of 2022. This study compares three estimation methods of basic reproduction numbers on small-scale, short-duration COVID-19 epidemics in Fujian Province. Basic reproduction numbers were investigated using a varying-strain model via a next-generation matrix method. Serial intervals were derived using the infector–infectee pairs of two epidemics from the Fujian Provincial Center for Disease Control and Prevention. Basic reproduction numbers were estimated using the maximum likelihood estimation method and the exponential growth method. The curves of the effective reproduction numbers of the three epidemics were plotted by utilizing daily cases and the EpiEstim R package. The spatial heterogeneity of infection cases was described using the Gini coefficient. This study provides significant insights on the estimation methods of reproduction numbers for policymakers in the local government. The results reveal that social contacts between infectors and susceptible individuals should be reduced to avoid an increase in deaths and to fight against the spread of infectious diseases.

The epidemiological characteristics and distributions of two epidemics in Fujian Province of Southeast China were attributed to the complex interactions among variant, host, and non-pharmaceutical interventions (NPIs). All reported cases in the Putian epidemic (September 8–October 2, 2021, Delta variant B.1.617.2) and Fuzhou epidemic (October 22–November 18, 2022, Omicron variant BA.5.2) were classified by sex, age group, occupation, and location in this study. Using surveillance data from the Fujian Provincial Center for Disease Control and Prevention, we established a virus-oriented SVEIR (Susceptible–Vaccinated–Exposed–Infected–Recovered) model to investigate the dynamic evolution features of these two variants and the effects of NPIs. The optimal simulations were carried out with variants and scenario investigations. The scenario investigations showed that NPIs significantly reduced the transmission risk and infection scales of COVID-19, and that the Omicron variant was more infectious than the Delta variant. Moreover, the dynamic investigations revealed the increasing tendencies from Delta to Omicron, such as the basic reproduction number, infection rate, percentage of high-risk cases, and the growth rate. Decreasing tendencies were also identified, such as the average recovery period, the awareness delay, and the percentage of symptomatic cases. This study highlighted that NPIs played critical roles in successfully containing the two epidemics. Such interventions are strongly recommended to public health policymakers.

In this study, we proposed two, symptom-dependent, HIV/AIDS models to investigate the dynamical properties of HIV/AIDS in the Fujian Province. The basic reproduction number was obtained, and the local and global stabilities of the disease-free and endemic equilibrium points were verified to the deterministic HIV/AIDS model. Moreover, the indicators $ R_0^s $ and $ R_0^e $ were derived for the stochastic HIV/AIDS model, and the conditions for stationary distribution and stochastic extinction were investigated. By using the surveillance data from the Fujian Provincial Center for Disease Control and Prevention, some numerical simulations and future predictions on the scale of HIV/AIDS infections in the Fujian Province were conducted.

Background: A COVID-19 outbreak in the rural areas of Shijiazhuang City was attributed to the complex interactions among vaccination, host, and non-pharmaceutical interventions (NPIs). Herein, we investigated the epidemiological characteristics of all reported symptomatic cases by picking Shijiazhuang City, Hebei Province in Northern China as research objective. In addition, we established an age-group mathematical model to perform the optimal fitting and to investigate the dynamical profiles under three scenarios. Methods: All reported symptomatic cases of Shijiazhuang epidemic (January 2-February 3, 2021) were investigated in our study. The cases were classified by gender, age group and location, the distributions were analyzed by epidemiological characteristics. Furthermore, the reported data from Health Commission of Hebei Province was also analyzed by using an age-group mathematical model by two phases and three scenarios. Results: Shijiazhuang epidemic caused by SARS-CoV-2 wild strain was recorded with the peak 84 cases out of 868 reported symptomatic cases on January 11, 2021, which was implemented with strong NPIs by local government and referred as baseline situation in this study. The research results showed that R0 under baseline situation ranged from 4.47 to 7.72, and Rt of Gaocheng Distinct took 3.72 with 95% confidence interval from 3.23 to 4.35 on January 9, the declining tendencies of Rt under baseline situation were kept till February 3, the value of Rt reached below 1 on January 19 and remained low value up to February 3 for Gaocheng District and Shijiazhuang City during Shijiazhuang epidemic. This indicated Shijiazhuang epidemic was under control on January 19. However, if the strong NPIs were kept, but remote isolation operated on January 11 was not implemented as of February 9, then the scale of Shijiazhuang epidemic reached 9,482 cases from age group who were 60 years old and over out of 31,017 symptomatic cases. The investigation also revealed that Shijiazhuang epidemic reached 132,648 symptomatic cases for age group who were 60 years old and over (short for G2) under risk-based strategies (Scenario A), 58,048 symptomatic cases for G2 under late quarantine strategies (Scenario B) and 207,124 symptomatic cases for G2 under late quarantine double risk strategies (Scenario C), and that the corresponding transmission tendencies of Rt for three scenarios were consistently controlled on Jan 29, 2021. Compared with baseline situation, the dates for controlling Rt below 1 under three scenarios were delayed 10 days. Conclusions: Shijiazhuang epidemic was the first COVID-19 outbreak in the rural areas in Hebei Province of Northern China. The targeted interventions adopted in early 2021 were effective to halt the transmission due to the implementation of a strict and village-wide closure. However we found that age group profile and NPIs played critical rules to successfully contain Shijiazhuang epidemic, which should be considered by public health policies in rural areas of mainland China during the dynamic zero-COVID policy.

As of May 2024, the main strains of COVID-19 caused hundreds of millions of infection cases and millions of deaths worldwide. In this study, we consider the COVID-19 epidemics with the main strains in the Chinese mainland. We study complex interactions among hosts, non-pharmaceutical interventions, and vaccinations for the main strains by a differential equation model called SVEIR. The disease transmission model incorporates two strains and protection awareness of the susceptible population. Results of this study show that the protection awareness plays a crucial role against infection of the population, and that the vaccines are effective against the circulation of the earlier strains, but ineffective for emerging strains. By using the next generation matrix method, the basic reproduction number of the SVEIR model is firstly obtained. Our analysis by Hurwitz criterion and LaSalle's invariance principle shows that the disease free-equilibrium point is locally and globally asymptotically stable when the threshold value is below one. The existences of endemic equilibrium points are also established, and the global asymptotic stabilities are analyzed using the Lyapunov function method. Further, the SVEIR model is confirmed to satisfy the principle of competitive exclusion, of which the strain with the larger value of the basic reproduction number is dominant. Numerically, the surveillance data with the Omicron strain and the XBB strain are split by the cubic spline interpolation method. The fitting curves against the surveillance data are plotted using the least-squares method from MATLAB. The results indicate that the XBB strain dominates in this study. Moreover, a global sensitivity analysis of the key parameters is performed by using of PRCC. The numerical simulations imply that combination control strategy positively impacts on the infection scale than what separate control strategy does, and that the earlier time producing protection awareness for the public creates less infection scale, further that the increment of protection awareness also reduces the infection scale. Therefore, the policymakers of the local government are suggested to concern the changes of protection awareness of the public.

Since its emergence, SARS-CoV-2 virus, the causative agent of COVID-19, has undergone over three years of evolutionary changes. Throughout this evolutionary process, multiple variants, such as Alpha, Beta, Gamma, Delta, and Omicron, have emerged, leading to widespread outbreaks and pandemics. A comprehensive analysis of the evolution of SARS-CoV-2 over the past three years reveals its progression through three distinct stages.

A vector–host model of dengue with multiple stages and independent fluctuations is investigated in this paper. Firstly, the existence and uniqueness of the positive solution are shown by contradiction. When the death rates of aquatic mosquitoes, adult mosquitoes, and human beings respectively control the intensities of white noises, and if R0s>1, then the persistence in the mean for both infective mosquitoes and infective human beings is derived. When R0s>1 is valid, the existence of stationary distribution is derived through constructing several appropriate Lyapunov functions. If the intensities of white noises are controlled and φ<0 is valid, then the extinction for both infective mosquitoes and infective human beings is obtained by applying the comparison theorem and ergodic theorem. Further, the main findings are verified through numerical simulations by using the positive preserving truncated Euler–Maruyama method (PPTEM). Moreover, several numerical simulations on the infection scale of dengue in Fuzhou City were conducted using surveillance data. The main results indicate that the decrease in the transfer proportion from aquatic mosquitoes to adult mosquitoes reduces the infection scale of infective human beings with dengue virus, and the death rates of aquatic mosquitoes and adult mosquitoes affect the value of the critical threshold R0s. Further, the controls of the death rates of mosquitoes are the effective routes by the decision-makers of the Chinese mainland against the spread of dengue.

We study a switching heroin epidemic model in this paper, in which the switching of supply of heroin occurs due to the flowering period and fruiting period of opium poppy plants. Precisely, we give three equations to represent the dynamics of the susceptible, the dynamics of the untreated drug addicts and the dynamics of the drug addicts under treatment, respectively, within a local population, and the coefficients of each equation are functions of Markov chains taking values in a finite state space. The first concern is to prove the existence and uniqueness of a global positive solution to the switching model. Then, the survival dynamics including the extinction and persistence of the untreated drug addicts under some moderate conditions are derived. The corresponding numerical simulations reveal that the densities of sample paths depend on regime switching, and larger intensities of the white noises yield earlier times for extinction of the untreated drug addicts. Especially, when the switching model degenerates to the constant model, we show the existence of the positive equilibrium point under moderate conditions, and we give the expression of the probability density function around the positive equilibrium point.

The differences of SARS-CoV-2 variants brought the changes of transmission characteristics and clinical manifestations during the prevalence of COVID-19. In order to explore the evolution mechanisms of SARS-CoV-2 variants and the impacts of variant evolution, the classic SIR (Susceptible-Infected-Recovered) compartment model was modified to a generalized SVEIR (Susceptible-Vaccinated-Exposed-Infected-Recovered) compartment model with age-group and varying variants in this study. By using of the SVEIR model and least squares method, the optimal fittings against the surveillance data from Fujian Provincial Center for Disease Control and Prevention were performed for the five epidemics of Fujian Province. The main epidemiological characteristics such as basic reproduction number, effective reproduction number, sensitivity analysis, and cross-variant scenario investigations were extensively investigated during dynamic zero-COVID policy. The study results showed that the infectivities of the variants became fast from wild strain to the Delta variant, further to the Omicron variant. Meanwhile, the cross-variant investigations showed that the average incubation periods were shortened, and that the infection scales quickly enhanced. Further, the risk estimations with the new variants were performed without implements of the non-pharmaceutical interventions, based on the dominant variants XBB.1.9.1 and EG.5. The results of the risk estimations suggested that non-pharmaceutical interventions were necessary on the Chinese mainland for controlling severe infections and deaths, and also that the regular variant monitors were still workable against the aggressive variant evolution and the emergency of new transmission risks in the future.

The prediction system EpiSIX was used to study the COVID-19 epidemic in mainland China between November 2022 and January 2023, based on reported data from December 9, 2022, to January 30, 2023, released by The Chinese Center for Disease Control and Prevention on February 1, 2023. Three kinds of reported data were used for model fitting: the daily numbers of positive nucleic acid tests and deaths, and the daily number of hospital beds taken by COVID-19 patients. It was estimated that the overall infection rate was 87.54% and the overall case fatality rate was 0.078%–0.116% (median 0.100%). Assuming that a new COVID-19 epidemic outbreak would start in March or April of 2023, induced by a slightly more infectious mutant strain, we predicted a possible large rebound between September and October 2023, with a peak demand of between 800,000 and 900,000 inpatient beds. If no such new outbreak was induced by other variants, then the current COVID-19 epidemic course in mainland China would remain under control until the end of 2023. However, it is suggested that the necessary medical resources be prepared to manage possible COVID-19 epidemic emergencies in the near future, especially for the period between September and October 2023.

The World Health Organization (WHO) declared monkeypox as a public health emergency of international concern (PHEIC) on July 23, 2022, their highest level of alert. This raised concerns about the management of the global monkeypox outbreak, as well as the scientific analysis and accurate prediction of the future course of the epidemic. This study used EpiSIX (an analysis and prediction system for epidemics based on a general SEIR model) to analyze the monkeypox epidemic and to forecast the major tendencies based on data from the USA CDC (https://www.cdc.gov) and the WHO (https://www.who.int/health-topics/monkeypox). The global outbreak of monkeypox started in the UK on May 2, 2022, which marked the beginning of an epidemic wave. As of October 28, 2022, the cumulative number of reported cases worldwide was 77,115, with 36 deaths. EpiSIX simulations predict that the global monkeypox epidemic will enter a low epidemic status on March 1, 2023 with the cumulative number of confirmed cases ranging from 85,000 to 124,000, and the total number of deaths ranging from 60 to 87. Our analysis revealed that the basic reproduction number (R0) of monkeypox virus (MPXV) is near to 3.1 and the percentage of asymptomatic individuals is 13.1 %–14.5 %, both of which are similar to the data for SARS. The vaccination efficiency against susceptibility (VEs) of individuals who have had monkeypox is ∼ 79 %, and the vaccination efficiency against infectiousness (VEi) of individuals who have had monkeypox is ∼ 76 %–82 %. The mean incubation period for monkeypox is 8 days. In total, 94.7 % of infected individuals develop symptoms within 20 days and recover within 2 weeks after the confirmation of symptoms. Simulation results using EpiSIX showed that ring vaccination was remarkably effective against monkeypox. Our findings confirmed that a 20-day isolation for close contacts is necessary.

We propose stage-structured single-species population models with psychological effects and partial tolerance in polluted environments in this paper. First, the conditions of extinction and the time for extinction are investigated respectively. Especially, the time for extinction takes longer as the value of the psychological effects increases. Then the weak persistence in the mean around the pollution-free equilibrium and the stochastic permanence have been derived under some moderate conditions. Further, the existence of a periodic solution for the periodic single-species population has been determined. The corresponding numerical simulations verify the efficiency of the main theoretical results.

Regional persistent extreme cold events are meteorological disasters that cause serious harm to people’s lives and production; however, they are very difficult to predict. Low-temperature weather systems and their effects have a significant low-frequency oscillation period (10–20 d and 30–60 d). This paper uses deep learning to analyze the extended-range time scale and predict regional persistent extreme cold events. The dominant low-frequency oscillation components of cold events are obtained via wavelet transform and Butterworth filtering. The low-frequency oscillation component is decomposed via empirical orthogonal function decomposition to extract the main spatial mode and time coefficient. A convolutional neural network is used to establish the correlation between large-scale circulations and the time coefficient of the low-frequency oscillation component of the lowest temperature. The proposed deep learning model exhibits good prediction accuracy for regional persistent extreme cold events with low-frequency oscillations.

Abstract A stochastic susceptible–exposed–infected–recovered (SEIR) model with nonlinear incidence rate is investigated. Under suitable conditions, existence and uniqueness of a global solution, stationary distribution with ergodicity, persistence in the mean, and extinction of the disease are obtained. Numerical simulations and conclusions are separately carried out at the end of this paper.

Abstract We investigate the long-term properties of a stochastic Lotka–Volterra model with infinite delay and Markovian chains on a finite state space. We investigate that the stochastic model admits a unique positive global solution which stays in the way of stochastically ultimate boundedness by constructing Lyapunov functions. Furthermore, the main results that the growth of the solution is slower than time under moderate condition and moment estimation in time average with the power p could be controlled are derived, which modified the known ones in recent literatures.

The authors investigate the features of precipitation during the prerainy season in South China (PSCPRS) and the atmospheric circulation in the Southern Hemisphere (SH), which is expected to influence the PSCPRS significantly. The Morlet wavelet method revealed that the PSCPRS has significant interannual variability, especially in its quasi-biennial oscillation. The PSCPRS exhibits a significant monsoonal precipitation pattern. Using singular value decomposition (SVD) and composite analysis, the anomalous characteristics of SH atmospheric circulations and their impacts on the PSCPRS are studied. The results reveal that eastward movements or extensions of the Mascarene high (MH) and Australian high (AH), which have quasi-baroclinic geopotential height structures in the lower and middle troposphere, are the most significant factors affecting the PSCPRS. Their impacts on the PSCPRS anomalies are further studied using the index east of the MH (IEMH) and index east of the AH (IEAH). The IEMH and IEAH have notable significant positive correlations with the PSCPRS. When either the IEMH or IEAH is stronger (weaker), more (less) rainfall occurs during the prerainy season in South China.

The prediction of summer precipitation patterns (PPs) over eastern China is an important and topical issue in China. Predictors that are selected based on historical information may not be suitable for the future due to non-stationary relationships between summer precipitations and corresponding predictors, and might induce the instability of prediction models, especially in cases with few predictors. This study aims to investigate how to learn as much information as possible from various and numerous predictors reflecting different climate conditions. An objective prediction method based on the multinomial logistic regression (MLR) model is proposed to facilitate the study. The predictors are objectively selected from a machine learning perspective. The effectiveness of the objective prediction model is assessed by considering the influence of collinearity and number of predictors. The prediction accuracy is found to be comparable to traditionally estimated predictability, ranging between 0.6 and 0.7. The objective prediction model is capable of learning the intrinsic structure of the predictors, and is significantly superior to the prediction model with randomly-selected predictors and the single best predictor. A robust prediction can be generally obtained by learning information from plenty of predictors, although the most effective model may be constructed with fewer predictors through proper methods of predictor selection. In addition, the effectiveness of objective prediction is found to generally improve as observation increases, highlighting its potential for improvement during application as time passes.

A kind of delayed predator-prey system with harvesting is considered in this paper. The influence of harvesting and delay is investigated. Our results show that Hopf bifurcations occur as the delay τ passes through critical values. By using of normal form theory and center manifold theorem, the direction of Hopf bifurcation and the stability of the bifurcating periodic solutions are obtained. Finally, numerical simulations are given to support our theoretical predictions.

A kind of general stochastic nonautonomous Lotka-Volterra models with infinite delay is investigated in this paper. By constructing several suitable Lyapunov functions, the existence and uniqueness of global positive solution and global asymptotic stability are obtained. Further, the solution asymptotically follows a normal distribution by means of linearizing stochastic differential equation. Moment estimations in time average are derived to improve the approximation distribution. Finally, numerical simulations are given to illustrate our conclusions.

[Objectives] To study the effects of Chinese herbal medicine feed additives on the growth performance and dietary nutrient metabolic rate of black-one chickens. [Methods] 480 pieces of 1-day-old Donglan Black-bone Chickens were selected and divided into 4 groups, with 6 replicates in each group, with 20 pieces in each replicate. Among them, group A was the control group and was fed the basal diet; the groups B, C, and D were the experimental groups, which were separately supplemented with 0.25%, 0.50% and 1.00% of Chinese herbal medicine additives in the basal diet, and the experimental period was 70 d. At the end of the feeding experiment, 24 experimental chickens with similar body weight were selected from each group, and the same design of the feeding experiment was used to continue to feed the original diet for the metabolic experiment to determine the nutrient metabolic rate. [Results] Except the 50 -70 d stage, the average daily gain (ADG ) of group B in other stages was increased by 5.00% -9.15% (P < 0.05), and the average body weight of group B at 70 d was also increased by 4.86% (P <0.05); the ADG of group C at 36-49, 1-49 and 1 - 70 d and the average individual weight at 70 d were also higher than that of group A by 5.90%, 2.66%, 2.68% and 2.57%, respectively (< >0.05) ; at 36-49 d, the average daily feed intake (ADFI) of group A was higher than that of group Bby6.04% (P <0.01), and was also higher than that of groups C and D by 5.12% and 4.13% (P <0.05), respectively; at1-49d, the ADFI of group A was higher than that of group C by 2.86% (P <0.05), and there was no significant difference between the four groups of experimental chickens at each stage (P > 0.05) ; at 22 - 35 and 1 - 70 d, the feed to gain ratio (F/G) of group B was 6.32% and 3.41% lower than that of group A (P <0.05), and at 36 -49 and 1 - 49 d, the F/G of group B was even lower; at 36 -49 d, the F/G of group C was 10.15% lower than that of group A (P <0.05), and at 1-49 d, it was also lower than that of group A by 5.29% (P < 0.01) ; there was no significant difference between the two groups at other stages. In terms of nutrient metabolism % the three different amounts of this additive have increased the metabolic rate of DM, CP, CF, NFE, CA, Ca, P, TE and other nutrients in the diet to varying degrees, especially the addition of 0.25% and 0.50% had the significant increase. [Conclusions] The addition of 0.25% Chinese herbal medicine additives in the diet can significantly improve the growth performance and main nutrient metabolic rate of Donglan Black-bone Chickens. [ABSTRACT FROM AUTHOR]