Abbreviations & AcronymsObjective: To investigate the clinical significance of preoperative aspects and dimensions used for anatomic (PADUA) and radius exophytic/endophytic nearness anterior/posterior location (RENAL) scoring systems for renal neoplasms in patients undergoing laparoscopic partial nephrectomy. Methods: A retrospective analysis was carried out on clinical data of 245 Chinese patients with renal neoplasms undergoing laparoscopic partial nephrectomy from June 2008 to June 2012. The perioperative complications and variables, as well as PADUA and RENAL score, were compared. Results: The PADUA and RENAL scoring systems were significantly associated with percent change in estimated glomerular filtration rate (P = 0.032 and P = 0.026 respectively), whereas the RENAL scoring system was also significantly associated with warm ischemia time (P = 0.032). On multivariate analysis, both scores were able to predict percent change in estimated glomerular filtration rate (PADUA, P = 0.011; RENAL, P = 0.028). There were no significant associations between the two scoring systems assessed and the occurrence of complications or tumor stage. The correlation between PADUA classification and RENAL nephrometry score was significant (P < 0.0001). Fleiss' generalized kappa was 0.69-0.89 for the various components of the PADUA score and 0.67-0.89 for the RENAL nephrometry components. Conclusions:The PADUA classification and RENAL nephrometry score are comprehensive assessment tools for delineating renal tumor anatomy. The reproducibility of the PADUA and RENAL scores is substantial, but further research is required to evaluate its performance in more accurately predicting operative and patient-related outcomes.

This paper describes an ongoing research program on the seismic resistance performance of the double-wall precast concrete (DWPC) shear wall. Low-cyclic reversed loading test of three new full scale specimens are carried out based on the previous studies. The test results indicate that DWPC shear walls have higher initial stiffness, cracking load, yielding load and ultimate load. The displacement ductility ratios of DWPC shear walls are no less than that of cast-in-situ shear wall. The hysteretic curves of all specimens are plump, and the trend of skeleton curves is basically the same. The seismic energy dissipation capacities of DWPC specimens are close to those of cast-in-situ specimen. All the specimens have shown favorable seismic resistance performance.

A new method is developed for the aeroelastic stability analysis of a high-aspect-ratio wing based on the transfer function. First, the flutter governing equations for three types of wing elements including clear wing element, wing element with a control surface and that with an external store are, respectively, established by combining the corresponding bend-twist vibration model with the Theodrosen’s unsteady aerodynamic model. Then, in order to use the transfer function method, the element governing equations are processed by the Fourier transform and are formulated in a state-space form using state vector. Based on the finite element procedure, the global governing equations of the whole wing are obtained. Both the flutter velocity and flutter frequency are derived by solving a complex eigenvalue problem with the graphical approach. Additionally, the torsional divergence of the high-aspect-ratio wing is obtained by solving a real eigenvalue problem, which is a degenerated form of the wing flutter governing equations. Finally, illustrative examples are prepared to demonstrate the validity of the present method, which is insensitive to mesh density and does not require structural modal analysis for aeroelastic stability.

The detection of hydrophobicity is an important way to evaluate the performance of composite insulator, which is helpful to the safe operation of composite insulator. In this paper, the image processing technology and Back Propagation neural network is introduced to recognize the composite insulator hydrophobicity grade. First, hydrophobic image is preprocessed by histogram equalization and adaptive median filter, then the image was segmented by Ostu threshold method, and four features associated with hydrophobicity are extracted. Finally, the improved Back Propagation neural network is adopted to recognize composite insulator hydrophobicity grade. The experimental results show that the improved Back Propagation neural network can accurately recognize the composite insulator hydrophobicity

Through comparing and analyzing domestic and foreign research on soil infiltration in recent years, this article summarizes the research progress on soil infiltration, especially the innovation in theory, method and progress in practical use and gives the advantages and disadvantages among various methods. It can provide reference for the researchers engaged in the study of soil infiltration and efficient soil water utilization.