严把信息入口 将风险拒之门外——天津社保中心150台身份证阅读器投入使用

天津社保中心在社会保险参保登记环节,用以采集参保人员基本信息的150台身份证阅读器,于2013年4月下发至社保各区县分中心,并正式投入使用。第二代身份证阅读器的配备,不仅降低了经办机构逐项录入的难度,提高了工作效率,而且有效地保证了参保入口信息的及时、准确及安全。"参保人员基本信息是社会保险各项业务经办和管理服务的重要基础,其安全直接影响到广大参保人员的权益。

Numerical Simulation of a Landfall Typhoon Using a Bogus Data Assimilation Scheme

A typhoon bogus data assimilation scheme (BDA) using dimension-reduced projection four-dimen-sional variational data assimilation (DRP-4-DVar),called DRP-BDA for short,is built in the Advanced Regional Eta Model (AREM).As an adjoint-free approach,DRP-BDA saves time,and only several minutes are taken for the full BDA process.To evaluate its performance,the DRP-BDA is applied to a case study on a landfall ty-phoon,Fengshen (2008),from the Northwestern Pacific Ocean to Guangdong province,in which the bogus sea level pressure (SLP) is assimilated as a kind of observa-tion.The results show that a more realistic typhoon with correct center position,stronger warm core vortex,and more reasonable wind fields is reproduced in the analyzed initial condition through the new approach.Compared with the control run (CTRL) initialized with NCEP Final (FNL) Global Tropospheric Analyses,the DRP-BDA leads to an evidently positive impact on typhoon track forecasting and a small positive impact on typhoon inten-sity forecasting.Furthermore,the forecast landfall time conforms to the observed landfall time,and the forecast track error at the 36th hour is 32 km,which is much less than that of the CTRL (450 km).

AN OBJECTIVE PREDICTION SCHEME FOR TROPICAL CYCLONES MAKING LANDFALLS IN EASTERN CHINA

The landfall of tropical cyclones in the eastern part of China falls in the category of small probability events. Constructing a step function with intervals adequately divided can help reflect the non-linear distribution of conditional probability for a landfall event. For the prediction of landfall event probability, factors applying the step function in transformation are superior to the standardized factors that are linearly related. The prediction scheme discussed in the work uses transformation factors of step function to formulate prediction models for tropical cyclones making landfalls in eastern China, through screening with non-linear correlative ratios and REEP analysis. Classified models for statistic-synoptics, statistic-climatology and statistic-dynamics have been constructed using initial field data and numerical prediction output. Forecasting skills have been improved due to ensemble of predictions using these classified models. As shown in forecasting evaluations and experiments, the scheme is capable of predicting tropical cyclones that make landfalls in eastern China.

Log-normal censored regression model detecting prognostic factors in gastric cancer:A study of 3018 cases

AIM:To investigate the efficiency of Cox proportional hazard model in detecting prognostic factors for gastric cancer.METHODS:We used the log-normal regression model to evaluate prognostic factors in gastric cancer and compared it with the Cox model.Three thousand and eighteen gastric cancer patients who received a gastrectomy between 1980 and 2004 were retrospectively evaluated.Clinic-pathological factors were included in a log-normal model as well as Cox model.The akaike information criterion (AIC) was employed to compare the efficiency of both models.Univariate analysis indicated that age at diagnosis,past history,cancer location,distant metastasis status,surgical curative degree,combined other organ resection,Borrmann type,Lauren's classification,pT stage,total dissected nodes and pN stage were prognostic factors in both log-normal and Cox models.RESULTS:In the final multivariate model,age at diagnosis,past history,surgical curative degree,Borrmann type,Lauren's classification,pT stage,and pN stage were significant prognostic factors in both log-normal and Cox models.However,cancer location,distant metastasis status,and histology types were found to be significant prognostic factors in log-normal results alone.According to AIC,the log-normal model performed better than the Cox proportional hazard model (AIC value:2534.72 vs 1693.56).CONCLUSION:It is suggested that the log-normal regression model can be a useful statistical model to evaluate prognostic factors instead of the Cox proportional hazard model.

ESO-based robust predictive control of lunar module with fuel sloshing dynamics

An extended-state-observer(ESO) based predictive control scheme is proposed for the autopilot of lunar landing.The slosh fuel masses exert forces and torques on the rigid body of lunar module(LM),such disturbances will dramatically undermine the stability of autopilot system.The fuel sloshing dynamics and uncertainties due to the time-varying parameters are considered as a generalized disturbance which is estimated by an ESO from the measured attitude signals and the control input signals.Then a continuous-time predictive controller driven by the estimated states and disturbances is designed to obtain the virtual control input,which is allocated to the real control actuators according to a deadband logic.The 6-DOF simulation results reveal the effectiveness of the proposed method when dealing with the fuel sloshing dynamics and parameter perturbations.

Yearly tropical cyclone potential impact index in China

A new composite index called the yearly tropical cyclone potential impact(YTCPI)is introduced.The relationship between YTCPI and activities of tropical cyclones(TCs)in China,disaster loss,and main ambient fields are investigated to show the potential of YTCPI as a new tool for short-term climate prediction of TCs.YTCPI can indicate TC activity and potential disaster loss.As correlation coefficients between YTCPI and frequency of landfalling TCs,the frequency of TCs traversing or forming inside a 24 h warning line in China from 1971 to 2010 are 0.58 and 0.56,respectively(both are at a statistically significant level,aboveα=0.001).Furthermore,three simple indexes are used to compare with YTCPI.They all have very close relationships with it,with correlation coefficients 0.75,0.82 and 0.78.For economic loss and YTCPI,the correlation coefficient is 0.57 for 1994–2009.Information on principal ambient fields(sea surface temperature,850 and 500 hPa geopotential heights)during the previous winter is reflected in the relationship with YTCPI.Spatial and temporal variabilities of ambient fields are extracted through empirical orthogonal function(EOF)analysis.Spatial distributions of correlation coefficient between YTCPI and ambient fields match the EOF main mode.Correlation coefficients between YTCPI and the EOF time array for the three ambient fields are 0.46,0.44 and 0.4,respectively,all statistically significant,aboveα=0.01.The YTCPI has the overall potential to be an improved prediction tool.