Message Passing in C-RAN: Joint User Activity and Signal Detection

In cloud radio access network (C-RAN), remote radio heads (RRHs) and users are uniformly distributed in a large area such that the channel matrix can be considered as sparse. Based on this phenomenon, RRHs only need to detect the relatively strong signals from nearby users and ignore the weak signals from far users, which is helpful to develop low-complexity detection algorithms without causing much performance loss. However, before detection, RRHs require to obtain the realtime user activity information by the dynamic grant procedure, which causes the enormous latency. To address this issue, in this paper, we consider a grant-free C-RAN system and propose a low-complexity Bernoulli-Gaussian message passing (BGMP) algorithm based on the sparsified channel, which jointly detects the user activity and signal. Since active users are assumed to transmit Gaussian signals at any time, the user activity can be regarded as a Bernoulli variable and the signals from all users obey a Bernoulli-Gaussian distribution. In the BGMP, the detection functions for signals are designed with respect to the Bernoulli-Gaussian variable. Numerical results demonstrate the robustness and effectivity of the BGMP. That is, for different sparsified channels, the BGMP can approach the mean-square error (MSE) of the genie-aided sparse minimum mean-square error (GA-SMMSE) which exactly knows the user activity information. Meanwhile, the fast convergence and strong recovery capability for user activity of the BGMP are also verified.Comment: Conference, 6 pages, 7 figures, accepted by IEEE Globecom 201

A multidimensional and multiscale model for pressure analysis in a reservoir-pipe-valve system

Reservoir-pipe-valve (RPV) systems are widely used in many industrial processes. The pressure in an RPV system plays an important role in the safe operation of the system, especially during the sudden operations such as rapid valve opening or closing. To investigate the pressure response, with particular interest in the pressure fluctuations in an RPV system, a multidimensional and multiscale model combining the method of characteristics (MOC) and computational fluid dynamics (CFD) method is proposed. In the model, the reservoir is modeled as a zero-dimensional virtual point, the pipe is modeled as a one-dimensional system using the MOC, and the valve is modeled using a threedimensional CFD model. An interface model is used to connect the multidimensional and multiscale model. Based on the model, a transient simulation of the turbulent flow in an RPV system is conducted in which not only the pressure fluctuation in the pipe but also the detailed pressure distribution in the valve is obtained. The results show that the proposed model is in good agreement when compared with a high fidelity CFD model used to represent both large-scale and small-scale spaces. As expected, the proposed model is significantly more computationally efficient than the CFD model. This demonstrates the feasibility of analyzing complex RPV systems within an affordable computational time

Virtual Inertia Adaptive Control of a Doubly Fed Induction Generator (DFIG) Wind Power System with Hydrogen Energy Storage

This paper presents a doubly fed induction generator (DFIG) wind power system with hydrogen energy storage, with a focus on its virtual inertia adaptive control. Conventionally, a synchronous generator has a large inertia from its rotating rotor, and thus its kinetic energy can be used to damp out fluctuations from the grid. However, DFIGs do not provide such a mechanism as their rotor is disconnected with the power grid, owing to the use of back-to-back power converters between the two. In this paper, a hydrogen energy storage system is utilized to provide a virtual inertia so as to dampen the disturbances and support the grid’s stability. An analytical model is developed based on experimental data and test results show that: (1) the proposed method is effective in supporting the grid frequency; (2) the maximum power point tracking is achieved by implementing this proposed system; and, (3) the DFIG efficiency is improved. The developed system is technically viable and can be applied to medium and large wind power systems. The hydrogen energy storage is a clean and environmental-friendly technology, and can increase the renewable energy penetration in the power network

Biosynthesis of arsenolipids by the cyanobacterium Synechocystis sp. PCC 6803

Although methylated arsenic and arsenosugars have been verified in various freshwater organisms, lipid-soluble arsenic compounds have not been identified. Here, we report investigations with the model organism cyanobacterium Synechocystis sp. PCC 6803 wild type and arsM (arsenic(III) S-adenosylmethionine methyltransferase) mutant strain, which lacks the enzymes for arsenic methylation cultured in various concentrations of arsenate (As-V). Although Synechocystis accumulated higher arsenic concentrations at the higher exposure levels, the bioaccumulation factor decreased with increasing As-V. The accumulated arsenic in the cells was partitioned into water-soluble and lipid-soluble fractions; lipid-soluble arsenic was found in Synechocystis wild type cells (3-35% of the total depending on the level of arsenic exposure), but was not detected in Synechocystis arsM mutant strain showing that ArsM was required for arsenolipid biosynthesis. The arsenolipids present in Synechocystis sp. PCC 6803 were analysed by high performance liquid chromatography-inductively coupled plasma-mass spectrometry, high performance liquid chromatography-electrospray mass spectrometry, and high resolution tandem mass spectrometry. The two major arsenolipids were characterised as arsenosugar phospholipids based on their assigned molecular formulas C47H88O14AsP and C47H90O14AsP, and tandem mass spectrometric data demonstrated the presence of the phosphate arsenosugar and acylated glycerol groups

In-silico investigations into natural products as nonnucleoside DNA methyltransferase 1 inhibitors for treating epi-mutation in gastric cancer

Purpose: To explore in silico methods to search for the best reported non-nucleoside DNA methyltransferase 1 (DNMT1) inhibitor of epimutation in gastric cancer.Methods: A dataset of reported non-nucleoside DNMT1 inhibitors was used to target the active site of crystallized DNMT1 protein. Molecular docking simulations were carried out using AutoDock 4.2.6 l. The results were analyzed using Discovery studio visualizer.Results: In silico analysis of known natural non-nucleoside DNMT1 inhibitors gave genistein as the top ranked compound with ΔG of -6.39 Kcal/mol. Further, the results indicated that epigallocatechin gallate and curcumin are poor non-nucleoside DNMT1 inhibitors, as the in silico data suggest that they failed to bind to the catalytic site of DNMT1.Conclusion: The results indicate that genistein is the top rated compound for DNMT1 inhibition. Previous in vitro and in vivo work by other researchers seem to validate the findings of the study.Keywords: Epi-mutation, DNA methyltransferase, Non-nucleoside, DNMT1 inhibitor, Dockin

Biological behaviors and proteomics analysis of hybrid cell line EAhy926 and its parent cell line A549

<p>Abstract</p> <p>Background</p> <p>It is well established that cancer cells can fuse with endothelial cells to form hybrid cells spontaneously, which facilitates cancer cells traversing the endothelial barrier to form metastases. However, up to now, little is known about the biologic characteristics of hybrid cells. Therefore, we investigate the malignant biologic behaviors and proteins expression of the hybrid cell line EAhy926 with its parent cell line A549.</p> <p>Methods</p> <p>Cell counting and flow cytometry assay were carried out to assess cell proliferation. The number of cells attached to the extracellular matrix (Matrigel) was measured by MTT assay for the adhesion ability of cells. Transwell chambers were established for detecting the ability of cell migration and invasion. Tumor xenograft test was carried out to observe tumorigenesis of the cell lines. In addition, two-dimensional electrophoresis (2-DE) and mass spectrometry were utilized to identify differentially expressed proteins between in Eahy926 cells and in A549 cells.</p> <p>Results</p> <p>The doubling time of EAhy926 cell and A549 cell proliferation was 25.32 h and 27.29 h, respectively (P > 0.1). Comparing the phase distribution of cell cycle of EAhy926 cells with that of A549 cells, the percentage of cells in G0/G1 phase, in S phase and in G2/M phase was (63.7% ± 2.65%) VS (60.0% ± 3.17%), (15.4% ± 1.52%) VS (13.8% ± 1.32%), and (20.9% ± 3.40%) VS (26.3% ± 3.17%), respectively (P > 0.05). For the ability of cell adhesion of EAhy926 cells and A549 cells, the value of OD in Eahy926 cells was significantly higher than that in A549 cells (0.3236 ± 0.0514 VS 0.2434 ± 0.0390, P < 0.004). We also found that the migration ability of Eahy926 cells was stronger than that of A549 cells (28.00 ± 2.65 VS 18.00 ± 1.00, P < 0.01), and that the invasion ability of Eahy926 cells was significantly weak than that of A549 cells (15.33 ± 0.58 VS 26.67 ± 2.52, P < 0.01). In the xenograft tumor model, expansive masses of classic tumor were found in the A549 cells group, while subcutaneous inflammatory focuses were found in the EAhy926 cells group. Besides, twenty-eight proteins were identified differentially expressed between in EAhy926 cells and in A549 cells by proteomics technologies.</p> <p>Conclusion</p> <p>As for the biological behaviors, the ability of cell proliferation in Eahy926 cells was similar to that in A549 cells, but the ability in adhesion and migration of Eahy926 cells was higher. In addition, Eahy926 cells had weaker ability in invasion and could not form tumor mass. Furthermore, there were many differently expressed proteins between hybrid cell line Eahy926 cells and A549 cells, which might partly account for some of the differences between their biological behaviors at the molecular level. These results may help to understand the processes of tumor angiogenesis, invasion and metastasis, and to search for screening method for more targets for tumor therapy in future.</p