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Extensive studies have been carried out to study the performance of mangrove forests in wave height reduction. In this study, the reduction of the inundation and run-up of leading tsunami waves by mangrove forests was investigated through a series of laboratory experiments conducted in a long wave tank. The inundation and run-up were measured using a high speed CCD camera. Solitary waves were used to model the leading tsunami waves. Five vegetation models representing three forest densities and two tree distributions were examined on an impermeable sloping beach, and they were compared with the non-vegetated slope in view of wave reflection, transmission, and run-up. Results show that both incident wave height and run-up could be reduced by up to 50% when the vegetation was present on the slope. Dense vegetation reduced the wave transmission because of the increased wave reflection and energy dissipation into turbulence in vegetation. Normalized wave run-up on the beach decreased with the increase of both normalized incident wave height and forest density. Effect of forest density on the wave run-up on the sloping beach was further examined, and an empirical formula with the density incorporated was proposed. The study also highlighted the importance of tree distribution to wave interaction with vegetation on the slope when the forest density was unaltered, and run-up reduction difference between tandem and staggered arrangements of the trees could reach up to 20%.

Free radicals may attack cells or tissue, leading to chronic diseases, and antioxidant consumption is potentially useful for removing free radicals. Egg proteins may be used as potential sources of antioxidant considering their ability of scavenging free radicals to apply for food or cosmetics industry. In this study, we obtained a natural antioxidant protein from fertilized eggs, which was a dietary supplement in some Asian countries. Meanwhile, antioxidant activities of these proteins were evaluated using different oxidation systems. With increasing incubation time, the antioxidant activity of these proteins increased during 15 d of incubation. The samples on day 15 were performed for isolation of antioxidant protein. The protein, named P4-1 (MW, 45 kDa), was isolated and purified by consecutive chromatographic methods. P4-1 contained 17 amino acids, which was determined by liquid chromatography-mass spectrometry and Amino Acid Analyzer. Moreover, the amino acid sequence was highly similar to that of ovalbumin. Differential scanning calorimetry showed that the denaturation temperature of P4-1 was 57.16ºC. Furthermore, P4-1 suggested high oxygen radical-absorbance activity in ·OH assays, and its antioxidant activity was stable at 30-50ºC in acidic and neutral pH. Thus, these results revealed that P4-1 may be a potential resource as a natural antioxidant.

The vulnerability of low-lying reef-fringed atolls to coastal inundation in extreme wave events is of increasing concern in the context of global sea level rise. Wave-induced setup is an important component of wave runup along reef shorelines. We improved a semi-analytical model to investigate wave-induced setup over fringing reefs crested by a shallow reef. Using mass balance and hydraulics, we developed the model based on flow around reef crest kinematics. We proposed a scaling factor to account for flow unsteadiness and reef-crest shape effects. Our solution showed that wave setup on the reef flat is a function of both offshore wave steepness and the wave refection coefficient. Validation of the model by laboratory data shows that the model reproduces the maximum wave-induced setup on the reef flat in the presence of a reef crest with diffident crest widths. Applying the model to experimental data under various reef configurations and wave conditions were also successful. We found that the scaling factor in the model increased with increasing fore-reef slope but was insensitive to variations in reef-crest width. A key requirement for the model to do is that the reef-crest submergence must be small enough or nearly emergent so that an approximate critical flow condition exists.

Airport scene multi-service process(ASMP) state prediction is one of the important links to optimize airport ground resource allocation, improve collaborative release scheduling, and improve airport operation efficiency. In order to solve the problem of the slow response of existing prediction models, a Gaussian kernel probability density model of multi-service nodes in airport scenes is established. Then the one hidden layer neural network(OHLNN) is used to predict the nodes of ASMP. A study on the data of more than 20,000 flights at a large airport in China shows that: The mean absolute error (MAE) of the mixed flight prediction result is only 2.62911min, the mean root mean square error (RMSE) is only 3.24564min, and the response speed of the prediction model in the verification set is about 0.48s. When the results of MAE and RMSE are good, the response speed of the prediction model is greatly improved.