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Objective To evaluate the diagnostic effect of vaginal micro-ecological evaluation system on bacterial vaginosis by using three detections: the vaginal microecological evaluation system, Amsel standard and Nugent standard classification. Methods 239 vaginal secretion samples within the inclusion criteria were detected by the same operator under the same experimental conditions, using the Amsel standard, Nugent standard and Vaginal micro-ecological evaluation system respectively. Results The overall positive rate was 29.29% using vaginal micro-ecological evaluation system, 23.43% using Amsel standard and 24.27% using Nugent standard, showing statistically difference (P < 0.05, P < 0.01), respectively. The validity, reliability and predictive value of vaginal micro-ecological evaluation system were better than those using the other two standards. Conclusion Compared with Amsel standard and Nugent standard, vaginal micro-ecological evaluation system is facile. The detection cost is low and can be carried out even in ordinary laboratories. Its biggest advantage lies in the completeness of evaluation indexes. Providing a precise and comprehensive evaluation, it is a more effective method to diagnose Bacterial Vaginosis. [ABSTRACT FROM AUTHOR]

In order to reveal the temporal and spatial variation characteristics of vegetation coverage in the Beiluo River Basin since the implementation of The Grain for Green Project, the spatial and temporal variation characteristics of photosynthetic vegetation coverage in the beiluo river basin from 2001 to 2017 were analyzed with the vegetation cover data retrieved by MODIS.The results show that a) during the three periods of 2001-2006, 2007-2012 and 2013-2017, the average vegetation coverage is 60.2%, 63.2% and 68.5% respectively. The spatial difference of vegetation coverage status is obvious and the three periods all show the characteristics of the lowest vegetation coverage in the gullied rolling loess area of the upper reaches and the highest vegetation coverage in the middle rocky-mountain region; b) in the past 17 years, the vegetation coverage in the whole basin, the gullied rolling loess area, gullied loess plateaus and mountainous region shows a significant increase trend, with the annual variation rate of 0.65%/a, 1.18%/a, 0.64%/a and 0.42%/a respectively. Among the 12 major counties in the basin, the vegetation coverage of Zhidan, Wuqi and Jingbian in the gullied rolling loess area has been increased the most rapidly, with a change range of 1.05 to 1.36%/a, and the change range of Huanglong, Huangling and Heshui in the middle mountainous region is the slowest, with a change range of 0.31 to 0.33%/a; c) the main contribution to the significant increase of vegetation coverage in the whole basin comes from the gullied rolling loess area, with a contribution rate of 46.3%. On the county aspect, the main sources come from Zhidan(23.1%), Wuqi(20.4%), Fuxian(10.6%) and Ganquan(10.2%) respectively. [ABSTRACT FROM AUTHOR]

Aiming at the shortcomings of the basic ant colony algorithm in the optimal path selection and slow convergence speed, a new improved method is proposed for the initial pheromone distribution and pheromone volatility.Firstly, the initial pheromone was reset according to the global path so that the blind search path is no longer used in the early stage of the algorithm and the convergence speed is accelerated.Then the second volatilization of pheromone was carried out to improve the precision and convergence of the algorithm. Finally, the effectiveness of the improved algorithm was tested by classical Traveling Salesman Problems. The simulation results show that the improved ant colony algorithm can speed up the algorithm’s convergence rate and improve its accuracy. [ABSTRACT FROM AUTHOR]

Foundation and rail construction must meet higher accuracy for high-speed railway, in order to effectively control projection distance deformation of a GPS control network and reduce the number of projection zone for the east-west highspeed railways, this paper discusses the processing method for the oblique Mercator projection to be applied to develop uniform plane coordinate system by the basic theoriessuch as ellipsoid transformation, projection from ellipsoid to sphere and spherical cylindrical projection. Through a practical engineering example analysis, we show that the oblique Mercator projection can control the length deformation and meet the 10ppm length deformation per kilometer for control network of nonballasted-track and 25ppm for ballast track, and avoid the divisions of too many projection zones. Comparing with normal Gaussian projection the oblique Mercator projection has more superiorities on the east-west high-speed railway and other route engineering control networks. [ABSTRACT FROM AUTHOR]

Crop model calibration and validation are essential for model evaluation and application. It is important for model application to accurately estimate the values of crop model parameters and further improve the capacity of model prediction. In the previous researches, trial-and-error method was widely used in model calibration and validation. The deficiency of this method was subjective selection of parameter values and time-consuming processes. To overcome these issues, the optimization methods such as general likelihood uncertainty estimation (GLUE), genetic algorithm (GA) and shuffled complex evolution (SCE-UA) algorithm were alternative method for model calibration and validation. However, it is a problem to decide which parameters for optimization. It is essential to select the most sensitive parameters among hundreds of parameters in the crop model for optimization. To avoid subjective selection of parameters for calibration and validation, we used the global sensitivity analysis method of model parameters and the Markov Chain Monte Carlo (MCMC) method based on Bayesian theory to optimize the crop genetic parameters in the WOFOST (world food studies), and the data of three-year winter wheat field experiment in Luancheng in the North China Plain were adopted. The main objectives were: 1) to analyze the sensitivity and uncertainty of WOFOST brought by 55 crop genetic parameters using the extended Fourier amplitude sensitivity test; 2) to calibrate and validate the WOFOST using the MCMC method after sensitivity analysis. We found that: 1) The most sensitive parameters for maximum leaf area index (MAXLAI) in the crop growth period were successively: specific leaf area at development stage of 0, 0.5, 0.6, and 0.75, maximum CO2 assimilation rate at development stage of 1.5, and maximum relative increase in LAI (RGTLAI); 2) The most sensitive parameters for total above ground production (TAGP) in the crop growth period were successively: maximum CO2 assimilation rate at development stage of 1.5 (AMAXTB150), specific leaf area at development stage of 0 (SLATB00), life span of leaves growing at 35oC, extinction coefficient for diffuse visible light at development stage of 0 (KDIFFTB00), maximum CO2 assimilation rate at development stage of 1.8 (AMAXTB180), efficiency of conversion into storage organs (CVO); 3) The parameter sensitivity for MAXLAI and TAGP in potential and rain-fed production level was almost coincident, which indicated that yield level didn’t influence the parameter sensitivity results; 4) Eleven sensitive parameters were selected for optimization by using the MCMC method. The first calibration and validation strategy (i.e. the data in 1998-1999 for calibration and those in 1999-2000 and 2000-2001 for validation), was better than other 2 strategies. 5) WOFOST simulation was much improved if the optimized parameters by the MCMC method were adopted. The index of agreement was higher than 0.9 and the relative root mean square error was less than 20%. However, WOFOST performed worse in rain-fed case because water stress factor was added to limit crop growth. The results indicate that more sensitive parameters should have priority in adjusting values for model calibration and validation. In addition, the MCMC method is a feasible optimization method for WOFOST calibration and validation. [ABSTRACT FROM AUTHOR]

“Grain for Green” program has been implemented in the Loess Plateau of China since 1999, in order to control excessive soil erosion and sediment production. There is a profound impact on the vegetation cover and land use structure in recent years. It is a high demand to analyze the potential of vegetation restoration, plantation suitability areas, and land use change for regional ecosystem restoration planning and ecological protection. Taking the Beiluo River Basin as an example, this work aims to clarify the potential of vegetation restoration, vegetation suitability area, and land use change in various geomorphological areas using the dataset of climate, geography, vegetation cover, and land use. The “similar habitat” was also introduced for the statistical and geographical spatial analysis. Results showed that: 1) The spatial distribution of vegetation cover varied significantly in the study area in 2020. The vegetation cover of the earth-rock mountain area was the highest at 88.8%, followed by the gully area at 84.1%, and the terrace plain area and hilly-gully area at 68.9% and 61.9%, respectively. A spatial distribution pattern of vegetation restoration potential was obtained with the “high in the northwest and low in the southeast”, particularly in the hilly-gully area in the upper reaches. The maximum recoverable vegetation cover of the hilly-gully area was 71.1%, where still 9.2% potential for the vegetation cover and the vegetation of 36.4% of the area continued to improve in the next 20-30 years. By contrast, the area with the vegetation to be improved accounted for about 11.5% of the earth-rock mountain area. The maximum recovery potential was achieved in the vegetation cover in the gully and terrace plain areas after 20 years of restoration. Therefore, there was no room to improve in the future. 2) The current land use types were dominated by cropland, forestland and grassland. The land use predictions showed that the land use change was mainly concentrated in the hilly-gully area in the next 20-30 years. The cropland decreased by 47.4% in the hilly-gully area, compared with 2020. The forestland and grassland increased by 0.7% and 15.8%, respectively. Since the cropland decreased by 23.0%, the forestland and grassland increased by 0.2% and 36.0%, respectively, in the earth-rock mountain area. Conversely, there was only a slight change in the future land use in the gully and terrace plain area. 3) The scenarios simulation was conducted to determine the plantation’s suitability using the principle of “Matching Tree Species with Site”. The suitable planting area in the gully and terrace plain area was 279.16 and 233.73 km2, respectively. A large area of returned cropland in the hilly-gully area was suitable for the natural restoration. There was relatively sporadic suitability for the planting area in the hilly-gully and earth-rock mountain areas. It implied that the hilly-gully area was the key area for future ecological restoration, which was the hotspot for ecological protection and high-quality development in the Yellow River Basin. Considering the limited rainfall and water carrying capacity, the ecological measures of “adaptation to local conditions” were proposed to avoid soil drying for future vegetation restoration in the Loess Plateau. [ABSTRACT FROM AUTHOR]

In autumn of 2022, the national average temperature was 10.9℃, which was the highest in the same period since 1961. The national average precipitation was 107.5mm, 8.5% less than the normal value. The national average sunshine duration was 575.2h, close to the same period of the normal years. The sunshine and temperature in most agricultural regions of China were suitable during autumn. The early frost in Northeast China occurred earlier than the normal years but its duration was shorter. There was no cold and dew wind in the late rice region. The meteorological conditions were generally favorable for crops grain-filling, maturing, harvesting, drying and autumn planting. The autumn harvest and sowing were generally progressing smoothly. The agricultural drought in Jiangxi, Hunan, eastern Guizhou and other regions occurred a wide spatial distribution and lasted for a long time, which resulted in difficulties for sowing and emergence of rape seedlings in some areas. So the yield and quality of some field crops and economic forests were also adversely affected. [ABSTRACT FROM AUTHOR]

Emergent plant Zizania latifolia, floating aquatic plant Eichornia crassipes and submerged plant Hydrilla verticillata were selected to investigate the effect of aquatic plant on quality of mild eutrophic water. The nutrient concentrations, phytoplankton chlorophyll a and other water quality physicochemical parameters in plant treatments and no plant treatment were determined during a five months indoor experiment. The results showed that the three plant treatments could significantly decrease the concentrations of nitrogen and phosphorus in the water column. The removal efficiency of total phosphorus was E.crassipes＞H.verticillata＞Z.latifolia, while the removal efficiency of total nitrogen was E.crassipes＞Z.latifolia＞H.verticillata. In addition, E.crassipes showed the strongest inhabiting effect on phytoplankton abundance; while Z.latifolia had the lowest effect on it. As compared with control group, H.verticillata increased the content of dissolved oxygen and pH and decreased the redox potential in the water, while E.crassipes had the opposite effect.Z.latifolia did not have a significant effect on water physicochemical parameters. These results could provide an insight in selection of plants for ecological restoration of mild eutrophic water bodies. [ABSTRACT FROM AUTHOR]

It is generally accepted that the model parameters calibration is an essential step before application. However, the traditional methods of obtaining a set of “optional parameters” based on a certain number of observations, fail to represent the uncertainties and get reliable estimates. To overcome this problem, we introduced the DE-MC (differential evolution Markov chain) algorithm with snooker update into the WOFOST (world food studies) model parameters calibration. The main objectives were: 1) to calibrate the WOFOST model by DE-MC algorithm with snooker update; 2) to evaluate the uncertainty of the model parameters after calibration; 3) to evaluate the uncertainty of the model outputs after calibration. Observational data including LAI (leaf area index) in different growth stages and the final yield of winter wheat in Zhengzhou Agrometeorological Experimental Station, were used to calibrate WOFOST model at potential mode with this algorithm. The crop parameters related to accumulated temperature were calculated directly from the crop phenological development date and near-surface temperature. The remaining crop parameters were analyzed by Sobol method. Taking Sobol global sensitivity index greater than 0.05 as the threshold for sensitive parameters, 14 parameters were then selected. The calibrated parameters were defined as the uniform distribution over their value interval. The likelihood function represented the mismatch of the model output with the measured observations, by which the parameters’ priori distribution converted to posterior distribution. The likelihood function for yield was set as a Gaussian distribution with the observational data as expected value and 10% of the observational data as standard deviation. Similarly, the likelihood function for LAI was set as a multidimensional Gaussian distribution with observational LAI as the expected vector and a diagonal matrix as the covariance matrix. At last, we found that: 1) Compared with the simulation results with model default parameters, the LAI simulation accuracy could be increased by 51.40%-53.07% after the parameter calibration, and the yield simulation accuracy is improved by 8.25%-8.88%; 2) The posterior distribution of life span of leaves growing at 35 Celsius (SPAN), specific leaf area at development stage of 0.7 (SLATB070), specific leaf area at development stage of 0.4 (SLATB040), maximum CO2 assimilation rate at development stage of 1.3 (AMAXTB130), and specific leaf area at development stage of 0 (SLATB00) could be approximated as a Gaussian distribution with SPAN having the minimum uncertainty; 3) Running model with the posterior parameters set, the uncertainty of simulated LAI from the three-leaf stage to the re-greening stage and from the jointing stage to the heading stage is larger; the uncertainty of the simulated yield increases with time before the milky ripe stage, stayed unchanged until maturity. It was concluded that DE-MC with snooker update was an effective algorithm for parameters estimation of WOFOST model, the calibration had the potential to reduce the uncertainty of the model parameters and the calibrated model was able to model the observational data with some degree of skill. The calibration data used in this study was the observation data from the agrometeorological site. Although the crop varieties were consistent, the inter-annual cultivation management measures were not strictly controlled (eg.: seeding density), and the accuracy of the calibration results might be affected. Subsequent experiments can be carried out in more areas using experimental data with quantitative control to further verify the effectiveness of this algorithm. [ABSTRACT FROM AUTHOR]

Crop model calibration and parameterization are essential for model evaluation and agricultural application. It is important for model application to accurately estimate the values of crop model parameters and further improve the performance of model prediction. WOFOST (world food studies) is a well-known, widely applied simulation model to analyze quantitatively the growth and production of field crops, which was originally developed for crops in European countries. It is the base model for Monitoring Agricultural Resources (MARS) Crop Growth Monitoring System (CGMS) in operational use for yield estimation in European Union. Dynamic simulation of WOFOST model in large regional scale is an important basis for regional crop modeling. In this study, we selected the main winter wheat production areas of China as the study area, and the data from 174 agricultural meteorological stations from 2011 to 2014 were used to calibrate several key WOFOST input parameters, especially 2 parameters related with variety, namely the effective accumulated temperature from emergence to flowering (TSUM1) and the effective accumulated temperature from flowering to maturity (TSUM2). On the basis of the zoning of the main winter wheat production areas, we used the meteorological data from 2012 to 2015 to drive the WOFOST model at a single-point scale, to simulate the winter wheat growth and dynamic development. The simulated phenology, LAI (leaf area index) and yield at the station level were evaluated with the field measured data. Results showed that the NRMSE (normalized root mean square error) of LAI ranged from 50% to 63%. The NRMSE of simulated days was 4%-7% from emergence to anthesis period and 8%-12% from anthesis to maturity period, and then CV (coefficient of variation) of the phenology was between 14% and 20%, which meant significant spatial variability. We simulated the yield respectively in irrigated area and rainfed area. And the NRMSE of simulated yield in irrigated area ranged from 11% to 23%, while the NRMSE of simulated yield in rain-fed area ranged from 22% and 28%, and the CV ranged from 14% to 22% for irrigated areas and from 25% to 40% for rain-fed areas, which exhibited significant spatial variability. The NRMSE of simulated LAI was between 58% and 63%, which could be explained that the LAI during different growth stages was all included into the accuracy analysis. Several important input parameters (such as TDWI (initial biomass) and SPAN (leaf senescence coefficient)) could be optimized through assimilating remote sensing data into crop model, which could greatly improve the performance of crop model at the regional scale. Our results showed that the WOFOST model is of great potential for simulating the dynamic growth process of winter wheat in China. The calibrated WOFOST provides the dynamic model basis for regional applications, such as assimilating remote sensing data into crop model for crop yield estimation and climate change prediction with crop model. [ABSTRACT FROM AUTHOR]