QSAR Study of the Action Strength of DOM of Phenyl-isopropyl-amine Dopes Using MLR and BP-ANN

Based on Hall et al. electrotopological state indices（EK） of atom types, two quantitative structure-activity relationship（QSAR） models were developed to estimate and predict the action strength（W） of D（OM）（dimethoxy-methyl-amphetamine） for 18 phenyl-isopropyl-amine dopes（PPAD） through linear method（multiple linear regression, MLR） and non-linear method（Back propagation artificial neural network, BP-ANN）. On the basis of EK, the optimal three-parameter（E14, E9, E7） QSAR model of W for 18 PPAD was constructed. The traditional correlation coefficient（R^2） and cross-validation correlation coefficient（Rcv^2） are 0.878 and 0.815, respectively. The result demonstrates that the model is highly reliable（from the point of view of statistics） and has good predictive ability by using R^2, Rcv^2, VIF, FIT, AIC and F tests. Form the three parameters of the model, it is known that the dominant influence factors of inhibited activity are the molecular structure fragments： =CH–（secondary carbon）, =C〈（tertiary carbon atom） in aromatic ring and –O–（phenol ether bond）. The results showed that the structure parameters E14, E9 and E7 have good rationality and efficiency for the W of phenyl-isopropyl-amine dope（PPAD） analogues. A BP-ANN with 3-3-1 architecture was generated by using three electrotopological state index descriptors（E14, E9, E7） appearing in the MLR model, the above descriptors were inputs and its output was action strength（W）. The nonlinear BP-ANN model has better predictive ability compared to the linear MLR model with R^2 and Rcv^2 of leave-one-out（LOO） to be 0.995 and 0.994, respectively. The regression method gave support to the neural network with physical explanation, which offers a more accurate model for QSAR. Those models can be used in the rational design of higher stimulating extent PPAD, which provide meaningful reference information to improve the detection methods of PPAD.

Multi-scale variation characteristics of polar vortex at 10 hPa in the Southern Hemisphere

By use of 1948-2007 NCEP/NCAR reanalysis monthly geopotential data, a set of circulation indices are defined to characterize the polar vortex at 10 hPa in the Southern Hemisphere, including area-（S）, intensity-（P） and centre position-（λc , φc） indices. Sea-sonal variation, interannual anomalies and their possible causes of 10 hPa polar vortex in the Southern Hemisphere are analyzed by using these indices, the relationship between 10 hPa polar vortex strength and the Antarctic Oscillation are analyzed as well. The results show that： （1） the polar region at 10 hPa in the Southern Hemisphere is controlled by anticyclone （cyclone） from Dec. to Jan. （from Mar. to Oct.）, Feb. and Nov. are circulation transition seasons. （2） Intensity index （P） and area index （S） of anticy-clone （cyclone） in Jan. （Jul.） show a significant spike in the late 1970s, the anticyclone （cyclone） enhances （weakens） from ex-tremely weak （strong） oscillation to near the climatic mean before a spike, anticyclone tends to the mean state from very strong oscillation and cyclone oscillates in the weaker state after the spike. （3） There is significant interdecadal change for the anticyclone center in Jan., while markedly interannual variation for cyclone center in July. （4） The ozone anomalies can cause the interannual anomaly of the polar anticyclone at 10 hPa in the Southern Hemisphere in Jan. （positive correlation between them）, but it is not related to the polar cyclone anomalies. （5） There is notable negative correlation between the polar vortex intensity index P and the Antarctic Oscillation index （AAOI）, thus AAOI can be represented by P.

Using electrotopological state indices to model the depuration rates of polychlorinated biphenyls in mussels of Elliptio complanata

A quantitative structure-activity relationship （QSAR） model on depuration rate constants （ka） of polychlorinated biphenyls （PCBs） in freshwater mussel Elliptio complanata was successfully constructed using electrotopological state indices （ESI） and partial least squares （PLS） regression. The cross validated 2 Qcum and the correlation coefficient R for the model were determined to be 0.845 and 0.954, respectively. The satisfactory Q2cum and R values indicated significantly high robustness and good predictive ability for the model. The model was tested and found acceptable for the prediction of logkd （the logarithm of the deputation rate constants） by validation set. According to the model, an increase in the values of Saasc, S5＇, S4, S5 and S4＇, led to increased logkd, and a decrease in the values of Na, S2, and S6 also resulted in increased logkd. Among these descriptors, Ncl, S aasC, S5＇,, S4 and S5 made significant contributions to the value of logkd. These significant descriptors showed that the depuration of PCBs in Elliptio complanata may be mainly attributed to an equilibrium partitioning process among compartments with different lipid contents, while the reactivity of PCBs with enzymes or other molecules may play a subordinate role.

Autonomous mission reconstruction during the ascending flight of launch vehicles under typical propulsion system failures

In recent years, Chinese Long March(LM) launchers have experienced several launch failures, most of which occurred in their propulsion systems, and this paper studies Autonomous Mission Reconstruction(AMRC) technology to alleviate losses due to these failures. The status of the techniques related to AMRC, including trajectory and mission planning, guidance methods,and fault tolerant technologies, are reviewed, and their features are compared, which reflect the challenges faced by AMRC technology. After a brief introduction about the failure modes of engines that can occur during flight, and the fundamentals of trajectory planning and joint optimization of the target orbit and flight path, an AMRC algorithm is proposed for geostationary transfer orbit launch missions. The algorithm evaluates the residual performance onboard, and plans new objectives and corresponding flight path by iterative guidance mode or segmented state triggered optimization methods in real-time. Three failure scenarios that have occurred during previous LM missions are simulated to check the robustness of the algorithm: imminent explosion risk of the boosters’ engines, thrust drop during the first stage of flight, and being unable to start the engine during the second stage. The payloads would fall from space according to the current design under these conditions, but they were saved with the AMRC algorithm in the simulations, which allowed the rocket to get into the target orbit as intended or the payloads were deployed in other orbits without crashing. Although spaceflight can be very unforgiving, the AMRC algorithm has the potential to avoid the total loss of a launch mission when faced with these kinds of typical failures.