Assessment of rural sustainable development and analysis and prediction of obstacles and coupled coordinated development:A case study of Zaozhuang City

In China,the Innovation Demonstration Zone for the National Sustainable Development Agenda is a key initiative for executing the United Nations(UN)2030 Agenda for Sustainable Development.The Zone also plays critical roles in addressing the developmental bottlenecks that China faces and sharing Chinese insights into global sustainable development efforts.On July 15,2022,the State Council endorsed the Zone’s establishment in Zaozhuang City,Shandong Province,where it focuses on innovation-led sustainable development in rural areas.Research into the levels,impediments,interdependencies,and evolutionary trends of rural sustainable development is crucial.Therefore,this research aimed to assist in comprehensively assessing developmental challenges and facilitating the harmonious advancement of social,economic,and environmental aspects in rural areas.In pursuit of the three fundamental dimensions of the UN’s Sustainable Development Goals(SDGs),namely development’s drivers,quality,and equity,this study was grounded in China’s national Rural Revitalization Strategy and the demands of sustainable development strategies.It also aligns with the UN 2030 Agenda for Sustainable Development and the associated SDG indicators.Focusing on four key areas,namely production elements,natural elements,social elements,and rural governance,this study developed an evaluation index system for assessing the level of rural sustainable development.It employed a range of analytical models,including the game theory-based combination empowerment method,barrier degree model,coupling degree model,coupling coordination degree model,and gray prediction GM(1,1)model,to analyze the status and evolving trends of rural sustainable development in Zaozhuang City from 2015 to 2022.The key findings were as follows:①Relative to the baseline year 2015,the sustainable development level in Zaozhuang’s rural areas has shifted toward an improved state overall.②The primary barrier to achieving rural sustainable development in Zaozhuang is the city’s rural governance system.③While the components of rural sustainable development in Zaozhuang are in the early stages of both basic and moderate coordination,an overall enhancement has occurred in their integrative coordination.④Between 2023 and 2025,the level of integrative coordination in Zaozhuang is expected to rise steadily.However,reaching a state of advanced coordination will require additional time for development.

Weighted Markov chains for forecasting and analysis in Incidence of infectious diseases in jiangsu Province,China

This paper first applies the sequential cluster method to set up the classification standard of infectious disease incidence state based on the fact that there are many uncertainty characteristics in the incidence course.Then the paper presents a weighted Markov chain,a method which is used to predict the future incidence state.This method assumes the standardized self-coefficients as weights based on the special characteristics of infectious disease incidence being a dependent stochastic variable.It also analyzes the characteristics of infectious diseases incidence via the Markov chain Monte Carlo method to make the long-term benefit of decision optimal.Our method is successfully validated using existing incidents data of infectious diseases in Jiangsu Province.In summation,this paper proposes ways to improve the accuracy of the weighted Markov chain,specifically in the field of infection epidemiology.

Analysis and forecasts of investment scale and structure in upstream sector for oil companies based on system dynamics

Oil and gas exploration and production is the most important and key segment in the whole business chain of the petroleum industry.Therefore,oil companies always put much emphasis on making scientific and reasonable decisions about investment scale and structure in the upstream sector,so that they can minimise business risks and obtain high returns.According to the system dynamics theories and methods and based on the actual results from an oil company＇s practice in China,a system dynamics model is built in this paper for analyzing and forecasting the upstream investment scale and structure for an oil company.This model was used to analyze the investment effect of a large oil company in China, and the results showed that the total upstream investment scale will decline slowly in a short period and the investment proportion of different parts should be adjusted if some influencing factors are taken into account.This application practice was compared with the actual data and indicated that the system dynamics（SD） model presented in this paper is a useful tool for analyzing and forecasting of upstream investment scale and structure of oil companies in their investment decisions.

Forecasting promising technology using analysis of patent information:Focused on next generation mobile communications

In order to forecast promising technologies in the field of next generation mobile communication, various patent indicators were analyzed such as citation per patent, patent family information, patent share, increase rate, and patent activity. These indicators were quantified into several indexes and then integrated into an evaluation score to provide promising technologies. As a result of the suggested patent analysis, four technologies out of twenty two in details classification were selected, which showed outstanding technology competitiveness, high patent share and increasing rates as well as high recent-patent-ratios and triad-patent-family-ratios. Each of the selected technologies scored more than 10 points in total, and the following four technologies were suggested as promising ones in the field of next generation mobile communication: 1) 3GPP based mobile communication, 2) beyond 4G mobile communication, 3) IEEE 802.16 based mobile communication, which are in medium classification of broadband mobile communication system, and 4) testing/certification system of mobile communication, which is in medium classification of mobile communication testing/certification system.

ANALYSIS OF METEOROLOGICAL CONDITION AND RESEARCH ON FORECAST OF LANDSLIDES AND DEBRIS FLOWS IN ZHEJIANG PROVINCE

1 INTRODUCTION Meteorological factors, especially precipitation, have close links with geological calamities. According to the statistics, more than 70% of the geological calamities in China occur in rainy seasons. Many researchers are thus motivated to study extensively to determine their relationship in the prediction of geological calamltles . They either rely on single measurements of rainfall to seek basis for widespread occurrence of geological calamities or treat antecedent diurnal rainfall with equal importance, though with account of the accumulated effect of preceding rainfall. Furthermore, it is common for quite a number of models to use the rainfall recorded at hydrological or meteorological rain gauges as the one for the interested day, reducing the time validity of the prediction. In our analysis, it is found that the landslides and debris flows in Zhejiang province are related with the antecedent precipitation （but not by a simple accumulation）. Critical amounts of accumulated and effective rainfall are used in this work to tell whether there will be geological calamities. Moreover, MM5 is used to forecast rainfall, taking account in equations of the predictand for landslides and debris flows, in attempts to predict the appearance of meteorological condition for geological calamities and improve the rationality of forecasting procedures and time validity of forecasts.

Analysis of an Unsuccessful Forecast for a Heavy Rainfall Event in Yingkou

[Objective] The reason for the unsuccessful forecast of a heavy rainfall event in Yingkou was analyzed. [Method] Based on the precipitation data observed by automatic weather stations and MICAPS data, a heavy rainfall Event was studied in Yingkou from 19 July to 21 July in 2010. Then the analysis of an unsuccessful forecasting for the heavy rainfall on 21 July was illustrated by CINRAD-SA data, satellite data and numerical forecast products. [Result] The main reason for the unsuccessful forecast was that the duration of the rainfall was long and inconsecutive. The distribution was uneven. Strong precipitation on 21st was different from the one in previous two durations. It was regional short term strong precipitation. And the forecast difficulty was large; the numerical forecast was unstable and erroneous;strong precipitation occurred in the night on 20th, which was shortly before the strong precipitation in the evening of 21st. This would easily confuse the reporter. Besides, the short term stillness of radar and cloud during this time would form certain disturbance. The focus of rainstorm forecast should based on the numerical forecast instead of element forecast;insisting on situation analysis and taking element judgment as auxiliary;as for strong precipitation forecast, there was large error in numerical forecast and can not be relied. Reporter should report the correct one based on experience. [Conclusion] The study provided reference for the forecast of rainstorm.

Analysis of Chinese Power Market in 2007 and Its Forecast

Power supply and demand inJanuary-September, 2007Since 2007, the national economy developed continu-ously, showing a situation of rapid growth, more optimizedstructure, increased efficiency and improvement of people'slivelihood. In the first three quarters, GDP achieved 16.6043trillion Yuan, and its year-on-year growth rate was 11.5%;

Research on the Dynamic Volatility Relationship between Chinese and U.S. Stock Markets Based on the DCC-GARCH Model under the Background of the COVID-19 Pandemic

This study utilizes the Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) model to investigate the dynamic relationship between Chinese and U.S. stock markets amid the COVID-19 pandemic. Initially, a univariate GARCH model is developed to derive residual sequences, which are then used to estimate the DCC model parameters. The research reveals a significant rise in the interconnection between the Chinese and U.S. stock markets during the pandemic. The S&P 500 index displayed higher sensitivity and greater volatility in response to the pandemic, whereas the CSI 300 index showed superior resilience and stability. Analysis and model estimation suggest that the market’s dependence on historical data has intensified and its sensitivity to recent shocks has heightened. Predictions from the model indicate increased market volatility during the pandemic. While the model is proficient in capturing market trends, there remains potential for enhancing the accuracy of specific volatility predictions. The study proposes recommendations for policymakers and investors, highlighting the importance of improved cooperation in international financial market regulation and investor education.

Analyses and Forecasts of a Tornadic Supercell Outbreak Using a 3DVAR System Ensemble

As part of NOAA＇s ＂Warn-On-Forecast＂ initiative, a convective-scale data assimilation and prediction system was developed using the WRF-ARW model and ARPS 3DVAR data assimilation technique. The system was then evaluated using retrospective short-range ensemble analyses and probabilistic forecasts of the tornadic supercell outbreak event that occurred on 24 May 2011 in Oklahoma, USA. A 36-member multi-physics ensemble system provided the initial and boundary conditions for a 3-km convective-scale ensemble system. Radial velocity and reflectivity observations from four WSR-88 Ds were assimilated into the ensemble using the ARPS 3DVAR technique. Five data assimilation and forecast experiments were conducted to evaluate the sensitivity of the system to data assimilation frequencies, in-cloud temperature adjustment schemes, and fixed- and mixed-microphysics ensembles. The results indicated that the experiment with 5-min assimilation frequency quickly built up the storm and produced a more accurate analysis compared with the 10-min assimilation frequency experiment. The predicted vertical vorticity from the moist-adiabatic in-cloud temperature adjustment scheme was larger in magnitude than that from the latent heat scheme. Cycled data assimilation yielded good forecasts, where the ensemble probability of high vertical vorticity matched reasonably well with the observed tornado damage path. Overall, the results of the study suggest that the 3DVAR analysis and forecast system can provide reasonable forecasts of tornadic supercell storms.

一种实时的新型网络性能预警系统

设计了一种基于NetFlow流量分析的实时的新型网络性能预警系统,主要是利用基于NetFlow协议的高性能数据采集模式并运用统计学和预测学的相关算法,根据对当前网络流量值影响最大的在时间上最临近的流量值,预测下一时刻的流量数据。该系统能根据不同网络运行状态及时准确的预测出网络不同时间段的各种异常情况,有效分析网络运行效率并及时发现瓶颈,为优化网络性能提供了有力依据。

一种实时的新型网络性能预警系统

设计了一种基于NetFlow流量分析的实时的新型网络性能预警系统,它主要是利用基于NetFlow协议的高性能数据采集模式并运用统计学和预测学的相关算法,根据对当前网络流量值影响最大的在时间上最临近的流量值,预测下一时刻的流量数据。该系统能根据不同网络运行状态及时准确地预测出网络不同时间段的各种异常情况,有效分析网络运行效率并及时发现瓶颈,为优化网络性能提供了有力依据。

Tidal Level Response to Sea-Level Rise in the Yangtze Estuary

The rise of tidal level in tidal reaches induced by sea-level rise has a large impact on flood control and water supply for the regions around the estuary. This paper focuses on the variations of tidal level response along the tidal reaches in the Yangtze Estuary, as well as the impacts of upstream discharge on tidal level response, due to the sea-level rise of the East China Sea. Based on the Topex/Poseidon altimeter data obtained during the period 1993-2005, a stochastic dynamic analysis was performed and a forecast model was run to predict the sea-level rise of the East China Sea. Two- dimensional hydrodynamic numerical models downscaling from the East China Sea to estuarine areas were implemented to analyze the rise of tidal level along the tidal reaches. In response to the sea-level rise, the tidal wave characteristics change slightly in nearshore areas outside the estuaries, involving the tidal range and the duration of flood and ebb tide. The results show that the rise of tidal level in the tidal reaches due to the sea-level rise has upstream decreasing trends. The step between the stations of Zhangjiagang and Shiyiwei divides the tidal reaches into two parts, in which the tidal level response declines slightly. The rise of tidal level is 1-2.5 mm/a in the upper part, and 4-6 mm/a in the lower part. The stations of Jiangyin and Yanglin, as an example of the upper part and the lower part respectively, are extracted to analyze the impacts of upstream discharge on tidal level response to the sea-level rise. The relation between the rise of tidal level and the upstream discharge can be fitted well with a quadratic fimction in the upper part. However, the relation is too complicated to be fitted in the lower part because of the tide dominance. For comparison purposes, hourly tidal level observations at the stations of Xuliujing and Yanglin during the period 1993-2009 are adopted. In order to uniform the influence of upstream discharge on tidal level for a certain day each year, the hourly tidal level observations are corrected by the correlation between the increment of tidal level and the increment of daily mean upstream discharge. The rise of annual mean tidal level is evaluated. The resulting rise of tidal level at the stations of Xuliujing and Yanglin is 3.0 mm/a and 6.6 mm/a respectively, close to the rise of 5 mm/a according to the proposed relation between the rise of tidal level and the upstream discharge.

Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model

Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.

Forecast and Analysis of China's Lithium Battery Industry in the Next 5 Years

Ⅰ.Favorable factors(Ⅰ)Unveiling of industry norms and standards In the recent several years,portable power charger and portable power bank experienced rapid development,the market is brisk,it is supported by extremely wide population groups for application.Since portable power bank has low access requirements,the industry also

An air quality forecasting system in Beijing-Application to the study of dust storm events in China in May 2008

An air pollution forecast system,ARIA Regional,was implemented in 2007–2008 at the Beijing Municipality Environmental Monitoring Center,providing daily forecast of main pollutant concentrations.The chemistry-transport model CHIMERE was coupled with the dust emission model MB95 for restituting dust storm events in springtime so as to improve forecast results.Dust storm events were sporadic but could be extremely intense and then control air quality indexes close to the source areas but also far in the Beijing area.A dust episode having occurred at the end of May 2008 was analyzed in this article,and its impact of particulate matter on the Chinese air pollution index （API） was evaluated.Following our estimation,about 23 Tg of dust were emitted from source areas in Mongolia and in the Inner Mongolia of China,transporting towards southeast.This episode of dust storm influenced a large part of North China and East China,and also South Korea.The model result was then evaluated using satellite observations and in situ data.The simulated daily concentrations of total suspended particulate at 6：00 UTC had a similar spatial pattern with respect to OMI satellite aerosol index.Temporal evolution of dust plume was evaluated by comparing dust aerosol optical depth （AOD） calculated from the simulations with AOD derived from MODIS satellite products.Finally,the comparison of reported Chinese API in Beijing with API calculated from the simulation including dust emissions had showed the significant improvement of the model results taking into accountmineral dust correctly.