This paper investigates the physical layer security of a satellite network, whose downlink spectral resource is shared with a terrestrial cellular network. We propose to employ a multi-antenna base ...station (BS) as a source of green interference to enhance secure transmission in the satellite network. By taking the mutual interference between these two networks into account, we first formulate a constrained optimization problem to maximize the instantaneous rate of the terrestrial user while satisfying the interference probability constraint of the satellite user. Then, with the assumption that imperfect channel state information (CSI) and statistical CSI of the link between the BS and satellite user are available at the BS, we present two beamforming (BF) schemes, namely, hybrid zero-forcing and partial zero-forcing to solve the optimization problem and obtain the BF weight vectors in a closed form. Moreover, we analyze the secrecy performance of primary satellite network by considering two practical scenarios, namely: Scenario I, the eavesdroppers CSI is unknown at the satellite and Scenario II, the eavesdroppers CSI is known at the satellite. Specifically, we derive the analytical expressions for the secrecy outage probability for Scenario I and the average secrecy rate for Scenario II. Finally, numerical results are provided to confirm the superiority of the proposed BF schemes and the validity of the performance analysis, as well as demonstrate the impacts of various parameters on the secrecy performance of the satellite network.
In this paper, we investigate secrecy-energy efficient hybrid beamforming (BF) schemes for a satellite-terrestrial integrated network, wherein a multibeam satellite system shares the millimeter wave ...spectrum with a cellular system. Under the assumption of imperfect angles of departure for the wiretap channels, the hybrid beamformer at the base station and digital beamformers at the satellite are jointly designed to maximize the achievable secrecy-energy efficiency, while satisfying signal-to-interference-plus-noise ratio constraints of both the earth stations (ESs) and cellular users. Since the formulated optimization problem is nonconvex and mathematically intractable, we propose two robust BF schemes to obtain approximate solutions with low complexity. Specifically, for the case of a single ES, we integrate the Charnes-Cooper approach with an iterative search algorithm to convert the original nonconvex problem into a solvable one and obtain the BF weight vectors. In the case of multiple ESs, by exploiting the sequential convex approximation method, we convert the original problem into a linear one with multiple matrix inequalities and second-order cone constraints, for which we obtain a solution with satisfactory performance. The effectiveness and superiority of the proposed robust BF design schemes are validated via simulations using realistic satellite and terrestrial downlink channel models.
It is known that there exist two kinds of methods for direction-of-arrival (DOA) estimation in the literature: the subspace-based method and the sparsity-based method. However, pervious works reveal ...that the former method cannot address the case in which the number of signals is larger than that of sensors, whereas the latter one always suffers from the influence of basis mismatch. In this paper, to overcome these two shortcomings, we propose a new method called covariance matrix reconstruction approach (CMRA) for both uniform linear array and sparse linear array. In particular, by exploiting the Toeplitz structure of the covariance matrix of the array output, we formulate a low-rank matrix reconstruction (LRMR) problem for covariance matrix recovery. The nonconvex LRMR problem is then relaxed by replacing the rank norm with the nuclear norm and solved using the optimization toolbox. Next, we retrieve the DOAs from the recovered covariance matrix by using the subspace-based methods and obtain an estimated number of signals as a byproduct. We also provide two algorithm implementations for the LRMR problem based on duality and alternating direction method of multipliers, respectively. It is shown that CMRA can be regarded as an atomic norm minimization model or a gridless version of the sparsity-based methods and can recover more signals than sensors with a well-designed array. Numerical experiments are provided to validate the effectiveness of the proposed method, in comparison with some of the existing methods.
Although the fates of microplastics (0.1-5 mm in size) and nanoplastics (<100 nm) in marine environments are being increasingly well studied
, little is known about the behaviour of nanoplastics in ...terrestrial environments
, especially agricultural soils
. Previous studies have evaluated the consequences of nanoplastic accumulation in aquatic plants, but there is no direct evidence for the internalization of nanoplastics in terrestrial plants. Here, we show that both positively and negatively charged nanoplastics can accumulate in Arabidopsis thaliana. The aggregation promoted by the growth medium and root exudates limited the uptake of amino-modified polystyrene nanoplastics with positive surface charges. Thus, positively charged nanoplastics accumulated at relatively low levels in the root tips, but these nanoplastics induced a higher accumulation of reactive oxygen species and inhibited plant growth and seedling development more strongly than negatively charged sulfonic-acid-modified nanoplastics. By contrast, the negatively charged nanoplastics were observed frequently in the apoplast and xylem. Our findings provide direct evidence that nanoplastics can accumulate in plants, depending on their surface charge. Plant accumulation of nanoplastics can have both direct ecological effects and implications for agricultural sustainability and food safety.
Risk Factors and Preventions of Breast Cancer Sun, Yi-Sheng; Zhao, Zhao; Yang, Zhang-Nv ...
International journal of biological sciences,
01/2017, Letnik:
13, Številka:
11
Journal Article
Recenzirano
Odprti dostop
Breast cancer is the second leading cause of cancer deaths among women. The development of breast cancer is a multi-step process involving multiple cell types, and its prevention remains challenging ...in the world. Early diagnosis of breast cancer is one of the best approaches to prevent this disease. In some developed countries, the 5-year relative survival rate of breast cancer patients is above 80% due to early prevention. In the recent decade, great progress has been made in the understanding of breast cancer as well as in the development of preventative methods. The pathogenesis and tumor drug-resistant mechanisms are revealed by discovering breast cancer stem cells, and many genes are found related to breast cancer. Currently, people have more drug options for the chemoprevention of breast cancer, while biological prevention has been recently developed to improve patients' quality of life. In this review, we will summarize key studies of pathogenesis, related genes, risk factors and preventative methods on breast cancer over the past years. These findings represent a small step in the long fight against breast cancer.
This paper first investigates the equivalence of the space and translation invariance of Stepanov-like doubly weighted pseudo almost automorphic stochastic processes for nonequivalent weight ...functions; secondly, based on semigroup theory, fractional calculations, and the Krasnoselskii fixed-point theorem, we obtain the existence and uniqueness of Stepanov-like doubly weighted pseudo almost automorphic mild solutions for a class of nonlinear fractional stochastic neutral functional differential equations under non-Lipschitz conditions. These results enrich the complex dynamics of Stepanov-like doubly weighted pseudo almost automorphic stochastic processes.
Rough set theory, a mathematical tool to deal with inexact or uncertain knowledge in information systems, has originally described the indiscernibility of elements by equivalence relations. Covering ...rough sets are a natural extension of classical rough sets by relaxing the partitions arising from equivalence relations to coverings. Recently, some topological concepts such as neighborhood have been applied to covering rough sets. In this paper, we further investigate the covering rough sets based on neighborhoods by approximation operations. We show that the upper approximation based on neighborhoods can be defined equivalently without using neighborhoods. To analyze the coverings themselves, we introduce unary and composition operations on coverings. A notion of homomorphism is provided to relate two covering approximation spaces. We also examine the properties of approximations preserved by the operations and homomorphisms, respectively.
This paper investigates the secure communication of a cognitive satellite terrestrial network with software-defined architecture, where a gateway is acting as a control center to offer the resource ...allocation for the wireless systems. Specifically, we propose beamforming (BF) schemes to utilize the interference from the terrestrial network as a green source to enhance the physical-layer security for the satellite network, provided that the two networks share the portion of millimeter-wave frequencies. Supposing that the satellite employs multibeam antenna while the base station is equipped with a uniform planar array, we first formulate a constrained joint optimization problem to minimize the total transmit power while satisfying both the quality-of-service requirement of the terrestrial user and the secrecy rate (SR) requirements of the satellite users. Since the formulated optimization problem is nonconvex and mathematically intractable, we then propose two BF schemes to obtain the optimal solutions with high computational efficiency. For the case of one eavesdropper (Eve), we present a method to convert the nonconvex SR constraint to a second-order cone one and then adopt a penalty function approach to obtain the BF weight vectors. In the case of multiple Eves, by introducing a list of auxiliary variables, we propose a two-layer iterative BF scheme using penalty function approach together with gradient-based method to calculate the BF weight vectors. Finally, simulation results are given to demonstrate the effectiveness and superiority of the proposed BF schemes.
The inherent limitation of the predefined spatial discrete grids greatly restricts the precision and feasibility of many sparse signal representation (SSR)-based direction-of-arrival (DOA) ...estimators. In this paper, we first propose a perturbed SSR-based model to alleviate this limitation by incorporating a bias parameter into the DOA estimation framework. Using this model, a perturbed sparse Bayesian learning-based algorithm, named PSBL, is developed to solve the DOA estimation problem, followed by a theoretical analysis of PSBL. We then present two algorithms based on the covariance matrix of the array output, named perturbed covariance matrix (PCM) and improved PCM (IPCM), respectively, to improve the convergence speed of PSBL. Extensive experiments show that the PSBL enjoys a high estimation accuracy in the cases of limited snapshots, low signal-to-noise-ratio, correlated, and spatially adjacent signals. In particular, PCM not only keeps the merits of PSBL, but also exhibits superiority over PSBL in terms of computational efficiency. IPCM has a better computational efficiency, but with a small sacrifice of its performance in a correlated signal scenario.
To satisfy the explosive access demands of Internet-of-Things (IoT) devices, various kinds of multiple access techniques have received much attention. In this article, we investigate the multicast ...communication of a satellite and aerial-integrated network (SAIN) with rate-splitting multiple access (RSMA), where both satellite and unmanned aerial vehicle (UAV) components are controlled by network management center and operate in the same frequency band. Considering a content delivery scenario, the UAV subnetwork adopts the RSMA to support massive access of IoT devices (IoTDs) and achieve desired performances of interference suppression, spectral efficiency, and hardware complexity. We first formulate an optimization problem to maximize the sum rate of the considered system subject to the signal-interference-plus-noise-ratio requirements of IoTDs and per-antenna power constraints at the UAV and satellite. To solve this nonconvex optimization problem, we exploit the sequential convex approximation and the first-order Taylor expansion to convert the original optimization problem into a solvable one with the rank-one constraint, and then propose an iterative penalty function-based algorithm to solve it. Finally, simulation results verify that the proposed method can effectively suppress the mutual interference and improve the system sum rate compared to the benchmark schemes.
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