Cloud Computing and Big Data for Oil and Gas Industry Application in China

The oil and gas industry is a complex data-driven industry with compute-intensive, data-intensive and business-intensive features. Cloud computing and big data have a broad application prospect in the oil and gas industry. This research aims to highlight the cloud computing and big data issues and challenges from the informatization in oil and gas industry. In this paper, the distributed cloud storage architecture and its applications for seismic data of oil and gas industry are focused on first. Then,cloud desktop for oil and gas industry applications are also introduced in terms of efficiency, security and usability. Finally, big data architecture and security issues of oil and gas industry are analyzed. Cloud computing and big data architectures have advantages in many aspects, such as system scalability, reliability, and serviceability. This paper also provides a brief description for the future development of Cloud computing and big data in oil and gas industry. Cloud computing and big data can provide convenient information sharing and high quality service for oil and gas industry

Beamforming Design for IRS-and-UAV-aided Two-way Amplify-and-Forward Relay Networks

As a promising solution to improve communication quality, unmanned aerial vehicle (UAV) has been widely integrated into wireless networks. In this paper, for the sake of enhancing the message exchange rate between User1 (U1) and User2 (U2), an intelligent reflective surface (IRS)-and-UAV- assisted two-way amplify-and-forward (AF) relay wireless system is proposed, where U1 and U2 can communicate each other via a UAV-mounted IRS and an AF relay. Besides, an optimization problem of maximizing minimum rate is casted, where the variables, namely AF relay beamforming matrix and IRS phase shifts of two time slots, need to be optimized. To achieve a maximum rate, a low-complexity alternately iterative (AI) scheme based on zero forcing and successive convex approximation (LC-ZF-SCA) algorithm is put forward, where the expression of AF relay beamforming matrix can be derived in semi-closed form by ZF method, and IRS phase shift vectors of two time slots can be respectively optimized by utilizing SCA algorithm. To obtain a significant rate enhancement, a high-performance AI method based on one step, semidefinite programming and penalty SCA (ONS-SDP-PSCA) is proposed, where the beamforming matrix at AF relay can be firstly solved by singular value decomposition and ONS method, IRS phase shift matrices of two time slots are optimized by SDP and PSCA algorithms. Simulation results present that the rate performance of the proposed LC-ZF-SCA and ONS-SDP-PSCA methods surpass those of random phase and only AF relay. In particular, when total transmit power is equal to 30dBm, the proposed two methods can harvest more than 68.5% rate gain compared to random phase and only AF relay. Meanwhile, the rate performance of ONS-SDP-PSCA method at cost of extremely high complexity is superior to that of LC-ZF-SCA method

Precoding and Beamforming Design for Intelligent Reconfigurable Surface-Aided Hybrid Secure Spatial Modulation

Intelligent reflecting surface (IRS) is an emerging technology for wireless communication composed of a large number of low-cost passive devices with reconfigurable parameters, which can reflect signals with a certain phase shift and is capable of building programmable communication environment. In this paper, to avoid the high hardware cost and energy consumption in spatial modulation (SM), an IRS-aided hybrid secure SM (SSM) system with a hybrid precoder is proposed. To improve the security performance, we formulate an optimization problem to maximize the secrecy rate (SR) by jointly optimizing the beamforming at IRS and hybrid precoding at the transmitter. Considering that the SR has no closed form expression, an approximate SR (ASR) expression is derived as the objective function. To improve the SR performance, three IRS beamforming methods, called IRS alternating direction method of multipliers (IRS-ADMM), IRS block coordinate ascend (IRS-BCA) and IRS semi-definite relaxation (IRS-SDR), are proposed. As for the hybrid precoding design, approximated secrecy rate-successive convex approximation (ASR-SCA) method and cut-off rate-gradient ascend (COR-GA) method are proposed. Simulation results demonstrate that the proposed IRS-SDR and IRS-ADMM beamformers harvest substantial SR performance gains over IRS-BCA. Particularly, the proposed IRS-ADMM and IRS-BCA are of low-complexity at the expense of a little performance loss compared with IRS-SDR. For hybrid precoding, the proposed ASR-SCA performs better than COR-GA in the high transmit power region.Comment: 14pages,8figure

Three Efficient Beamforming Methods for Hybrid IRS plus AF Relay-aided Metaverse

In this paper, an optimization problem is formulated to maximize signal-to-noise ratio (SNR) by jointly optimizing the beamforming matrix at AF relay and the reflecting coefficient matrices at IRS subject to the constraints of transmit power budgets at the base station (BS)/AF relay/hybrid IRS and that of unit-modulus for passive IRS phase shifts. To achieve high rate performance and extend the coverage range, a high-performance method based on semidefinite relaxation and fractional programming (HP-SDR-FP) algorithm is presented. Due to its extremely high complexity, a low-complexity method based on successive convex approximation and FP (LC-SCA-FP) algorithm is put forward. To further reduce the complexity, a lower-complexity method based on whitening filter, general power iterative and generalized Rayleigh-Ritz (WF-GPI-GRR) is proposed, where different from the above two methods, it is assumed that the amplifying coefficient of each active IRS element is equal, and the corresponding analytical solution of the amplifying coefficient can be obtained according to the transmit powers at AF relay and hybrid IRS. Simulation results show that the proposed three methods can greatly improve the rate performance compared to the existing technology-aided metaverse, such as the passive IRS plus AF relay-aided metaverse and only AF relay-aided metaverse. In particular, a 50.0% rate gain over the existing technology-aided metaverse is approximately achieved in the high power budget region of hybrid IRS. Moreover, it is verified that the proposed three efficient beamforming methods have an increasing order in rate performance: WF-GPI-GRR, LC-SCA-FP and HP-SDR-FP

Two Rapid Power Iterative DOA Estimators for UAV Emitter Using Massive/Ultra-massive Receive Array

To provide rapid direction finding (DF) for unmanned aerial vehicle (UAV) emitter in future wireless networks, a low-complexity direction of arrival (DOA) estimation architecture for massive multiple input multiple output (MIMO) receiver arrays is constructed. In this paper, we propose two strategies to address the extremely high complexity caused by eigenvalue decomposition of the received signal covariance matrix. Firstly, a rapid power-iterative rotational invariance (RPI-RI) method is proposed, which adopts the signal subspace generated by power iteration to gets the final direction estimation through rotational invariance between subarrays. RPI-RI makes a significant complexity reduction at the cost of a substantial performance loss. In order to further reduce the complexity and provide a good directional measurement result, a rapid power-iterative Polynomial rooting (RPI-PR) method is proposed, which utilizes the noise subspace combined with polynomial solution method to get the optimal direction estimation. In addition, the influence of initial vector selection on convergence in the power iteration is analyzed, especially when the initial vector is orthogonal to the incident wave. Simulation results show that the two proposed methods outperform the conventional DOA estimation methods in terms of computational complexity. In particular, the RPIPR method achieves more than two orders of magnitude lower complexity than conventional methods and achieves performance close to CRLB. Moreover, it is verified that the initial vector and the relative error have a significant impact on the performance of the computational complexity

Restoration of Critical-Sized Defects in the Rabbit Mandible Using Autologous Bone Marrow Stromal Cells Hybridized with Nano- β

Nano-β-tricalcium phosphate/collagen (n-β-TCP/Col) is considered with good osteoconductivity. However, the therapeutic effectiveness of n-β-TCP/Col scaffolds in combination with autologous bone marrow stromal cells (BMSCs) remains to be elucidated for the repair of critical-sized bone defects. In this study, we found that n-β-TCP/Col scaffolds exhibited high biocompatibility in vitro. The introduction of BMSCs expanded in vitro to the scaffolds dramatically enhanced their efficiency to restore critical-sized bone defects, especially during the initial stage after implantation. Collectively, these results suggest that autologous BMSCs in n-β-TCP/Col scaffolds have the potential to be applied in bone tissue engineering

CD180 Ligation Inhibits TLR7- and TLR9-Mediated Activation of Macrophages and Dendritic Cells Through the Lyn-SHP-1/2 Axis in Murine Lupus

Activation of TLR7 and TLR9 by endogenous RNA- or DNA-containing ligands, respectively, can lead to hyper-activation of immune cells, including macrophages and DCs, subsequently contributes to the pathogenesis of SLE. CD180, a TLR-like protein, is specifically involved in the development and activation of immune cells. Our previous study and others have reported that CD180-negative B cells are dramatically increased in SLE patients and responsible for the production of auto-antibodies. However, the mode of CD180 expression on macrophages and DCs in SLE remains unclear and the role of CD180 on regulating TLR7- and TLR9-mediated activation of macrophages and DCs are largely unknown. In the present study, we found that the percentages of CD180-negative macrophages and DCs were both increased in SLE patients and lupus-prone MRL/lpr mice compared with healthy donors and wild-type mice, respectively. Notably, ligation of CD180 significantly inhibited the activation of TLR7 and TLR9 signaling pathways in macrophages and DCs through the Lyn-SHP-1/2 axis. What's more, injection of anti-CD180 Ab could markedly ameliorate the lupus-symptoms of imiquimod-treated mice and lupus-prone MRL/lpr mice through inhibiting the activation of macrophages and DCs. Collectively, our results highlight a critical role of CD180 in regulating TLR7- and TLR9-mediated activation of macrophages and DCs, hinting that CD180 can be regarded as a potential therapeutic target for SLE treatment

Genome-wide identification and analysis of heterotic loci in three maize hybrids

Heterosis, or hybrid vigour, is a predominant phenomenon in plant genetics, serving as the basis of crop hybrid breeding, but the causative loci and genes underlying heterosis remain unclear in many crops. Here, we present a large-scale genetic analysis using 5360 offsprings from three elite maize hybrids, which identifies 628 loci underlying 19 yield-related traits with relatively high mapping resolutions. Heterotic pattern investigations of the 628 loci show that numerous loci, mostly with complete–incomplete dominance (the major one) or overdominance effects (the secondary one) for heterozygous genotypes and nearly equal proportion of advantageous alleles from both parental lines, are the major causes of strong heterosis in these hybrids. Follow-up studies for 17 heterotic loci in an independent experiment using 2225 F2 individuals suggest most heterotic effects are roughly stable between environments with a small variation. Candidate gene analysis for one major heterotic locus (ub3) in maize implies that there may exist some common genes contributing to crop heterosis. These results provide a community resource for genetics studies in maize and new implications for heterosis in plants