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In the present study, elastic body wave propagation in fluid-saturated porous media is investigated, and the analytical model is solved in terms of the model of soil mechanics. The potential function expressions of elastic body waves in fluid-saturated porous media with different permeability (i.e., finite, zero, and infinity) are derived by using potential functions of solid- and liquid-phase displacements. Then, the elastic wave dispersion equations are obtained by using the complex forms of the plane harmonic wave. Furthermore, in the case of finite, zero, and infinite permeability, the plane wave solutions of the elastic waves are derived and the analytical formulations of propagation velocities and attenuation coefficients are calculated. Finally, numerical examples are carried out to analyze the dispersion and attenuation characteristics of three waves (fast compressional wave P1, low compressional wave P2, and shear wave S) in two-phase media. In addition, the effects of various properties (i.e., dynamic permeability coefficient, dissipation coefficient, porosity, and Poisson ratio) on the propagation characteristics of three waves are studied numerically. This study is of value to the wave propagation phenomenon as well as other related disciplines. [ABSTRACT FROM AUTHOR]

Sleep staging is a key process for evaluating sleep quality and diagnosing somnipathy-related diseases. Psychologists are required to do the traditional sleep stages identification. The manual work by these experts is often time-consuming and error-prone. In order to improve the performance of such a process, automatic Electroencephalography (EEG) signal analysis using machine learning approaches is often used. In this paper, a transitions-optimized Hidden Markov Model (HMM) model is proposed to improve the accuracy of prediction. Our proposed framework includes 4 key modules: feature extraction, feature selection, classification, and transition optimization. By applying, transition optimization process after a general GMM-HMM classification, our experimental results show a convincing improvement in the accuracy of classification. [ABSTRACT FROM AUTHOR]

The geological activity in Sichuan and Yunnan of China is intense, and large earthquakes such as the Tonghai earthquake in 1970 have caused huge casualties and economic losses. Therefore, it is significant to reduce the long-period earthquake damage of dams and high-rise buildings to reproduce the near-fault long-period ground motion characteristics of the Tonghai earthquake. In this paper, the finite difference method is used to predict the long-period characteristics of the Tonghai Ms 7.8 earthquake. Considering the uncertainty of the initial fracture point, number of asperities, and slip angle, 18 seismic scenarios are established. The predicted results are verified by comparing intensity, attenuation relation and pulse probability distribution. At the same time, based on the velocity pulse recognition method, the pulse probability distribution of the near-field is obtained. We selected six seismic scenarios with high probability from 18 seismic scenarios. Our results show that the spatial distribution and pulse probability distribution of near-field simulated ground motion is significantly affected by the initial rupture positions. After the characteristics of the largest asperity on the fault are determined, the remaining asperities have limited influence on the spatial distribution of simulated ground motion. This study expands the application scope of the finite difference method, which can simulate the seismic intensity characteristics of destructive earthquakes in areas with few seismic records. [ABSTRACT FROM AUTHOR]

Cadmium is one of the major heavy metal pollutions in coastal waters, and it is well known that cadmium at trace concentration is toxic to macroalgae. Change in marine carbonate system and ocean acidification caused by elevated atmospheric CO2 also alter physiological characteristics of macroalgae. However, less research is focused on the combined impacts of elevated CO2 and cadmium pollution on the growth and physiology in macroalgae. In this study, the maricultivated macroalga Pyropia haitanensis (Rhodophyta) was cultured at three levels of Cd2+ (control, 4 and 12 mg L−1) and two concentrations of CO2, the ambient CO2 (AC, 410 ppm) and elevated CO2 (HC, 1100 ppm). The results showed that 12 mg L−1 Cd2+ significantly suppressed the relative growth rate and superoxide dismutase activity in AC-grown P. haitanensis, while such inhibition extents by Cd2+ were alleviated in HC-grown algae. Cd2+ had no effects on efficiency of electron transport (α) and maximum electron transport rate (ETRmax), but α was increased by elevated CO2. Cd2+ dramatically suppressed the maximum net photosynthesis oxygen evolution rate (NPRm) and the minimum saturation irradiance (Ik) when the algal thalli were grown at AC, while such suppression of NPRm by Cd2+ was much decreased when the thalli were grown at HC. Collectively, our results suggested that elevated CO2 would alleviate Cd2+ toxicity on P. haitanensis. [ABSTRACT FROM AUTHOR]

This study proposes a novel approach, namely, skin flow complex algorithm (SFCA), to decompose the molecular skin surface into topological disks. The main contributions of SFCA include providing a simple decomposition and fast calculation of the molecular skin surface. Unlike most existing works which partition the molecular skin surface into sphere and hyperboloid patches, SFCA partitions the molecular skin surface into triangular quadratic patches and rectangular quadratic patches. Each quadratic patch is proven to be a topological disk and rendered by a rational Bézier patch. The skin surface is constructed by assembling all rational Bézier patches. Experimental results show that the SFCA is more efficient than most existing algorithms, and produces a triangulation of molecular skin surface which is decomposable, deformable, smooth, watertight and feature-preserved. [ABSTRACT FROM AUTHOR]

Interaction of myeloma cells with osteoclasts (OC) can enhance tumor cell expansion through activation of complex signaling transduction networks. Both cells reside in the bone marrow, a hypoxic niche. How OC-myeloma interaction in a hypoxic environment affects myeloma cell growth and their response to drug treatment is poorly understood. In this study, we i) cultured myeloma cells in the presence/absence of OCs under normoxia and hypoxia conditions and did protein profiling analysis using reverse phase protein array; ii) computationally developed an Integer Linear Programming approach to infer OC-mediated myeloma cell-specific signaling pathways under normoxic and hypoxic conditions. Our modeling analysis indicated that in the presence OCs, (1) cell growth-associated signaling pathways, PI3K/AKT and MEK/ERK, were activated and apoptotic regulatory proteins, BAX and BIM, down-regulated under normoxic condition; (2) β1 Integrin/FAK signaling pathway was activated in myeloma cells under hypoxic condition. Simulation of drug treatment effects by perturbing the inferred cell-specific pathways showed that targeting myeloma cells with the combination of PI3K and integrin inhibitors potentially (1) inhibited cell proliferation by reducing the expression/activation of NF-κB, S6, c-Myc, and c-Jun under normoxic condition; (2) blocked myeloma cell migration and invasion by reducing the expression of FAK and PKC under hypoxic condition. [ABSTRACT FROM AUTHOR]