A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data

An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. We discuss the main inputs, assumptions, theories, advantages and drawbacks of each model. Moreover, approaches to the extrapolation of instantaneous ET to the daily values are also briefly presented. In the final part, both associated problems and future trends regarding these remotely sensed ET models were analyzed to objectively show the limitations and promising aspects of the estimation of regional ET based on remotely sensed data and ground-based measurements

Expression and Significance of Nrf2 and Its Target Genes in Pulmonary Adenocarcinoma A549 Cells Resistant to Cisplatin

Background and objective Nuclear factor erythroid-2 related factor 2 (Nrf2) is a key transcription factor in oxidation-reduction reaction. It has been proved that Nrf2 is relevant to cisplatin-resistance in ovarian cancer cells. Up to now, little is know whether Nrf2 and it’s signal patheways play an important role in cisplatin-resistance in pulmonary adenocarcinoma cells or not. The aim of this study is to explore the expression levels of transcription factor Nrf2 and its target genes in A549 cells which are resistance to cisplatin and reveal the mechanism behind it. Methods A549/DDP and A549 were cultured in vitro. MTT was used to detect the drug resistance index of A549/DDP cells. Real-time PCR was used to evaluate the expression of transcription factor Nrf2 and its target genes mRNA. Results The drug resistance index of A549/DDP was 12.12, and its Keap1, Nrf2, NQO1, GSTP1, GCL, HO-1, MRP4 mRNA expressions were all significantly increased compared with A549 (P<0.01). On the other hand, MRP1, MRP2, MRP3 showd the crosscurrent (P<0.01). Conclusion It proves that the transcription factor Nrf2 and it’s signal pathways are closely related with drug resistance of tumors. Moreover, this provides a new direction to reverse drug resistance and have significance to avoid and overcome drug resistance of tumor

Research of single-phase fault line selection of power distribution network based on fifth harmonics energy and LM-Elman neural network

In view of the problem of low accuracy of amplitude comparing line selection method based on traditional fifth harmonic, a single-phase fault line selection method of power distribution network based on fifth harmonics energy and LM-Elman neural network was proposed. Firstly, wavelet packet was used for three-layer decomposition and reconstruction of fifth harmonics in zero-sequence current, and the total energy of the third layer reconstructed wavelet coefficients was obtained; then normalized energy values were used as input of Elman neural network, LM algorithm was used for training and testing. The simulation results show that the method can accurately select fault line in distribution network