RESEARCH ON IMPERFECTION SENSITIVE REGION OF SINGLE-LAYER LATTICED DOMES

The concept of the imperfection sensitive region is given. The advanced stochastic imperfection method is used to research the imperfection sensitive region of single-layer latticed domes. Taking a K6 single-layer latticed dome with a diameter of 50 m as an example, its imperfection sensitive region is made up of the first 12 kinds of joints. The influence of the imperfections of support joints on the stability of the K6 single-layer latticed dome is negligible. Influences of the joint imperfections of the main rib and the secondary rib on the structural stability are similar. The initial deviations of these joints all greatly lower the critical load of the dome. Results show that the method can analyze the structural imperfection sensitive region quantitatively and accurately.

Predictive factors for interferon and ribavirin combination therapy in patients with chronic hepatitis C

AIM： To confirm the predictive factors for interferon （IFN）-α and ribavirin combination therapy for chronic hepatitis patients with hepatitis C virus （HCV） genotype lb. METHODS： HCV RNA from 50 patients infected with HCV genotype lb was studied by cloning and sequencing of interferon sensitivity determining region （ISDR）, PKR- eIF2α phosphorylation homology domain （PePHD）. Patients were treated with IFN-α and ribavirin for 6 mo and grouped by effectiveness of the therapy. A variety of factors were analyzed. RESULTS： Our data showed that age, HCV RNA titer, and ISDR type could be used as the predictive factors for combined IFN-α and ribavirin efficacy. Characteristically, mutations in PePHD appeared only when the combination therapy was effective. Other factors, such as sex and alanine aminotransferase （ALT） level, were not related to its efficacy. Adjusting for age and HCV RNA titer indicated that the ISDR type was the most potent predictive factor. CONCLUSION： HCV RNA ISDR type is an important factor for predicting efficacy of IFN-α and ribavirin combination therapy in Korean patients.

A Comparison Study of the Contributions of Additional Observations in the Sensitive Regions Identified by CNOP and FSV to Reducing Forecast Error Variance for the Typhoon Morakot

The sensitive regions of conditional nonlinear optimal perturbations (CNOPs) and the first singular vector (FSV) for a northwest Pacific typhoon case are reported in this paper. A large number of probes have been designed in the above regions and the ensemble transform Kalman filter (ETKF) techniques are utilized to examine which approach can locate more appropriate regions for typhoon adaptive observations. The results show that, in general, the majority of the probes in the sensitive regions of CNOPs can reduce more forecast error variance than the probes in the sensitive regions of FSV. This implies that adaptive observations in the sensitive regions of CNOPs are more effective than in the sensitive regions of FSV. Furthermore, the reduction of the forecast error variance obtained by the best probe identified by CNOPs is twice the reduction of the forecast error variance obtained by FSV. This implies that dropping sondes, which is the best probe identified by CNOPs, can improve the forecast more than the best probe identified by FSV. These results indicate that the sensitive regions identified by CNOPs are more appropriate for adaptive observations than those identified by FSV.

The Sensitive Regions Identified by CNOPs of Three Typhoon Events

In this paper, several sets of observing system simulation experiments (OSSEs) were designed for three typhoon cases to determine whether or not the additional observation data in the sensitive regions identified by conditional nonlinear optimal perturbations (CNOPs) could improve the short-range forecast of typhoons. The results show that the CNOPs capture the sensitive regions for typhoon forecasts, which implies that conducting additional observation in these specific regions and eliminating initial errors could reduce forecast errors. It is inferred from the results that dropping sondes in the CNOP sensitive regions could lead to improvements in typhoon forecasts.

Regional moment-independent sensitivity analysis with its applications in engineering

Traditional Global Sensitivity Analysis（GSA） focuses on ranking inputs according to their contributions to the output uncertainty.However,information about how the specific regions inside an input affect the output is beyond the traditional GSA techniques.To fully address this issue,in this work,two regional moment-independent importance measures,Regional Importance Measure based on Probability Density Function（RIMPDF） and Regional Importance Measure based on Cumulative Distribution Function（RIMCDF）,are introduced to find out the contributions of specific regions of an input to the whole output distribution.The two regional importance measures prove to be reasonable supplements of the traditional GSA techniques.The ideas of RIMPDF and RIMCDF are applied in two engineering examples to demonstrate that the regional moment-independent importance analysis can add more information concerning the contributions of model inputs.

Test of the notch technique for determining the radial sensitivity of the optical model potential

Detailed investigations on the notch technique are performed on ideal data generated by the optical model potential parameters extracted from the 16O＋208spb system at the laboratory energy of 129.5 MeV, to study the sensitivities of this technique to the model parameters as well as the experimental data. It is found that for the perturbation parameters, a sufficiently large reduced fraction and an appropriate small perturbation width are necessary to determine the accurate radial sensitivity; while for the potential parameters, almost no dependence was observed. For the experimental measurements, the number of data points has little influence for heavy target systems, and the relative inner information of the nuclear potential can be derived when the measurement is extended to a lower cross section.

Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents by stochastic analysis

Identifying source information after river chemical spill occurrences is critical for emergency responses.However,the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated.To fill this gap,stochastic analysis approaches,including a regional sensitivity analysis method,identifiability plot and perturbation methods,were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework.Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules.For example,the release load can be most easily inverted,and the source location is responsible for the largest uncertainty among the source parameters.The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty.The differences among the different objective functions are smaller for instantaneous release than for continuous release cases.Small monitoring errors affect the inversion results only slightly,which can be ignored in practice.Interestingly,the estimated values of the release location and time negatively deviate from the real values,and the extent is positively correlated with the relative size of the mixing zone to the objective river reach.These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.

Research on Magnetomechanical Coupling Effect of Q235 Steel Member Specimens

In this study,magnetomechanical coupling tests were performed on Q235 solid round steel model specimens in NIM-200HF magnetomechanical coupling equipment.Hysteresis loops were obtained in different magnetic fields and stresses.Magnetization curves were also achieved at different stresses.Influence of the applied stresses on the hysteresis loops was investigated.The stress sensitive region and linear stress sensitive region of magnetic induction were determined for the model specimen according to the experimental data.The dependence relation of magnetic induction versus applied stresses was established,and the optimum magnetic field was determined in the stress sensitive range of magnetic induction,which builds a basis for nondestructive testing(NDT) of stress with the total magnetic flux for steel structure.Based on modified Jiles-Atherton's model of magnetic hysteresis,the hysteresis loop for Q235 steel 4-mm diameter model specimen was numerically simulated,which was well consistent with the experimental results.

Temperature characteristics research of SOI pressure sensor based on asymmetric base region transistor

Based on the asymmetric base region transistor, a pressure sensor with temperature compensation circuit is proposed in this paper. The pressure sensitive structure of the proposed sensor is constructed by a C-type silicon cup and a Wheatstone bridge with four piezoresistors（R_1, R_2, R_3 and R_4/locating on the edge of a square silicon membrane. The chip was designed and fabricated on a silicon on insulator（SOI） wafer by micro electromechanical system（MEMS） technology and bipolar transistor process. When the supply voltage is 5.0 V, the corresponding temperature coefficient of the sensitivity（TCS） for the sensor before and after temperature compensation are -1862 and -1067 ppm/℃, respectively. Through varying the ratio of the base region resistances r_1 and r_2, the TCS for the sensor with the compensation circuit is -127 ppm/℃. It is possible to use this compensation circuit to improve the temperature characteristics of the pressure sensor.