Accurate path loss (PL) prediction is essential for predicting transmitter coverage and optimizing wireless network performance. Traditional PL models are difficult to cope with the development trend of diversity, time-varying and mass wireless channels. In this work, the most widely used multilayer perceptron (MLP) neural network in artificial neural network (ANN) is employed to accurately predict PL. Three types of environmental features are defined and extracted, which describe the propagation environment only by considering limited environmental types instead of complex 3D environment modeling. Principal component analysis (PCA) is used to generate the low-dimensional environmental features, and eliminate redundant information among similar environmental types. Moreover, the information of base station (BS) and the receiver (Rx), including 3D locations, frequency, the transmitted power of BS, the antenna information, the feeder loss, and the received power of all the locations are obtained from the measurements. Different environmental features are combined with the information of BS and Rx to construct seven datasets for PL prediction models based on MLP neural networks. The impacts of the number of neurons in the hidden layer, the number of hidden layers, the number of training samples, and environmental features on PL prediction models are explored by considering the absolute value of mean error (AME), the mean absolute error (MAE), the standard deviation (STD) of error, the correlation coefficient, and the time ratio, respectively. This work aims to understand the propagation characteristics of radio waves, which can provide a theoretical basis for wireless network optimization and communication system design.
Abstract. Coastal floods are a consistent threat to oceanfront countries, causing major human suffering and substantial economic losses. Climate change is exacerbating the problem. An early warning system is essential to mitigate the loss of life and property from coastal flooding. The purpose of this study is to develop a coastal flooding early warning system (CoFEWs) by integrating existing sea-state monitoring technology, numerical ocean forecasting models, historical database and experiences, as well as computer science. The proposed system has capability of offering data for the past, information for the present and future. The system was developed for the Taiwanese coast due to its frequent threat by typhoons. An operational system without any manual work is the basic requirement of the system. Integration of various data sources is the system kernel. Numerical ocean models play an important role within the system because they provide data for assessment of possible flooding. The regional wave model (SWAN) that nested with the large domain wave model (NWW III) is operationally set up for coastal wave forecasting, in addition to the storm surge predicted by a POM model. Data assimilation technology is incorporated for enhanced accuracy. A warning signal is presented when the storm water level that accumulated from astronomical tide, storm surge, and wave-induced run-up exceeds the alarm sea level. This warning system has been in practical use for coastal flooding damage mitigation in Taiwan for years. An example of the system operation during the Typhoon Haitung which struck Taiwan in 2005 is illustrated in this study.
Perylene tetracarboxylic anhydride (PTCDA) was reacted with 6-aminocaproic acid to form the corresponding perylene bisimide (PBI). PBI was used as foundation an oligomerisation of glycidol in a ring-opening reaction of glycidol leading to a hyper branched, water soluble glycidol derivative of perylene (PBI-HPG). PBI-HPG was bound to the reduced graphene oxide via π-π stacking resulting in a compound termed PBI-HPG/RGO. The structure and morphology of PBI-HPG/RGO were investigated by infrared spectroscopy (FT-IR), wide angle X-ray diffractometry (WAXD), transmission electron microscopy (TEM), atomic force microscope (AFM) and X-ray photoelectron spectroscopy (XPS). PBI-HPG/RGO was blended into at different loadings in order to improve the thermal and mechanical properties of epoxy composites. The maximum Tg of the epoxy composites was about 20 o C and the decomposition temperature (Td) was 26 o C higher than that of neat epoxy. The incorporation of PBI-HPG/RGO yields a material with an impact strength of 39.6 KJ/m 2 and a tensile strength at 0.7 wt%. It increased by 50.8% and 62.3%, respectively, compared to the neat epoxy. ARTICLE RSC Adv.2 | RSC Adv., 2015, 00, 1-3This journal is
Ocean remote sensing is a useful way to obtain ocean wave information. Due to possible inhomogeneities from remotely sensed images, the current work proposes issues concerning ocean wave image analysis using the two-dimensional continuous wavelet transforms (2-D CWTs) to calculate local wave image spectra from inhomogeneous images. To optimize the algorithm of the 2-D CWT for wave image analysis, this work explores ideal parameter values for the wavelet function. The current study also analyses the limits of spatial image resolution and wave image size. After implementing the 2-D CWT on satellite and X-band radar images, this study presents local image spectra and ocean wave information from all the ocean images. These local image spectra reveal the phenomenon of wave refraction and wave nonlinearity nearshore. Compared to real wave spectra, the wavelet spectra present accurate results to describe local wave features in the spatial frequency domain.
SummaryThe aim of this study was to determine the role of ALDH2 in the injury of liver from brain-dead donors. Using brain-dead rabbit model and hypoxia model, levels of ALDH2 and apoptosis in tissues and cell lines were determined by Western blot, flow cytometry (FCM), and transferase (TdT)-mediated biotin-16-dUTP nick-end labeling (TUNEL) assays. After the expression of ALDH2 during hypoxia had been inhibited or activated, the accumulations of 4-hydroxynonenal (4-HNE) and molecules involved in mitogen-activated protein kinase (MAPK) signaling pathway were analyzed using ELISA kit and Western blot. The low expression of phosphorylated ALDH2 in liver was time-dependent in the braindead rabbit model. Immunohistochemistry showed ALDH2 was primarily located in endothelial, and the rates of cell apoptosis in the donation after brain-death (DBD) rabbit groups significantly increased with time. Following the treatment of inhibitor of ALDH2, daidzein, in combination with hypoxia for 8 h, the apoptosis rate and the levels of 4-HNE, P-JNK, and cleaved caspase-3 significantly increased in contrast to that in hypoxic HUVECs; however, they all decreased after treatment with Alda-1 and hypoxia compared with that in hypoxic HUVECs (P < 0.05). Instead, the levels of P-P38, P-ERK, P-JNK, and cleaved caspase-3 decreased and the ratio of bcl-2/bax increased with ad-ALDH2 (10 6 pfu/ml) in combination with hypoxia for 8 h, which significantly alleviated in contrast to that in hypoxic HUVECs. We found low expression of ALDH2 and high rates of apoptosis in the livers of brain-dead donor rabbits. Furthermore, decreased ALDH2 led to apoptosis in HUVECs through MAPK pathway.
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