Optimal Power Allocation by Imperfect Hardware Analysis in Untrusted Relaying Networks

CCBY By taking a variety of realistic hardware imperfections into consideration, we propose an optimal power allocation (OPA) strategy to maximize the instantaneous secrecy rate of a cooperative wireless network comprised of a source, a destination and an untrusted amplify-and-forward (AF) relay. We assume that either the source or the destination is equipped with a large-scale multiple antennas (LSMA) system, while the rest are equipped with a single-antenna. To prevent the untrusted relay from intercepting the source message, the destination sends an intended jamming noise to the relay, which is referred to as destination-based cooperative jamming (DBCJ). Given this system model, novel closed-form expressions are presented in the high signal-to-noise ratio (SNR) regime for the ergodic secrecy rate (ESR) and the secrecy outage probability (SOP). We further improve the secrecy performance of the system by optimizing the associated hardware design. The results reveal that by beneficially distributing the tolerable hardware imperfections across the transmission and reception radio-frequency (RF) front ends of each node, the system & #x2019;s secrecy rate may be improved. The engineering insight is that equally sharing the total imperfections at the relay between the transmitter and the receiver provides the best secrecy performance. Numerical results illustrate that the proposed OPA together with the most appropriate hardware design significantly increases the secrecy rate

Caching and UAV Friendly Jamming for Secure Communications With Active Eavesdropping Attacks

Natural Science Foundation of Sichuan under Grant 2022NSFSC0887; Fundamental Research Funds for the Central Universities under Grant 2682021ZTPY117 and 2682022CX020; ARC under Grant DP190100770; ARC Laureate Fellowship under Grant FL160100032; ARC under Grant DP190101988 and DP210103410

Secure Communications for UAV-Enabled Mobile Edge Computing Systems

In this paper, we propose a secure unmanned aerial vehicle (UAV) mobile edge computing (MEC) system where multiple ground users offload large computing tasks to a nearby legitimate UAV in the presence of multiple eavesdropping UAVs with imperfect locations. To enhance security, jamming signals are transmitted from both the full-duplex legitimate UAV and non-offloading ground users. For this system, we design a low-complexity iterative algorithm to maximize the minimum secrecy capacity subject to latency, minimum offloading and total power constraints. Specifically, we jointly optimize the UAV location, users’ transmit power, UAV jamming power, offloading ratio, UAV computing capacity, and offloading user association. Numerical results show that our proposed algorithm significantly outperforms baseline strategies over a wide range of UAV selfinterference (SI) efficiencies, locations and packet sizes of ground users. Furthermore, we show that there exists a fundamental tradeoff between the security and latency of UAV-enabled MEC systems which depends on the UAV SI efficiency and total UAV power constraints

Joint Optimization for Cooperative Computing Framework in Double-IRS-Aided MEC Systems

Natural Science Foundation of Sichuan Province under Grant 2022NSFSC0887; Fundamental Research Funds for the Central Universities under Grant 2682021ZTPY117 and 2682022CX020; National Natural Science Foundation of China under Grant 62201137; National Natural Science Foundation of China under Grant 62271419; Australian Research Council Laureate Fellowship grant number FL160100032; Australian Research Council Grant DP190101988 and DP210103410

Effects of Hydrogen Peroxide on Wound Healing in Mice in Relation to Oxidative Damage

10.1371/journal.pone.0049215PLoS ONE711

Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer

Many solid cancers are known to exhibit a high degree of heterogeneity in their deregulation of different oncogenic pathways. We sought to identify major oncogenic pathways in gastric cancer (GC) with significant relationships to patient survival. Using gene expression signatures, we devised an in silico strategy to map patterns of oncogenic pathway activation in 301 primary gastric cancers, the second highest cause of global cancer mortality. We identified three oncogenic pathways (proliferation/stem cell, NF-κB, and Wnt/β-catenin) deregulated in the majority (>70%) of gastric cancers. We functionally validated these pathway predictions in a panel of gastric cancer cell lines. Patient stratification by oncogenic pathway combinations showed reproducible and significant survival differences in multiple cohorts, suggesting that pathway interactions may play an important role in influencing disease behavior. Individual GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Predicting pathway activity by expression signatures thus permits the study of multiple cancer-related pathways interacting simultaneously in primary cancers, at a scale not currently achievable by other platforms

International entrepreneurship in SMEs: a study of influencing factors in the textile industry

The final publication is available at Springer via http://dx.doi.org/10.1007/s11365-012-0242-3International entrepreneurship is an incipient research area with a rapidly increasing body of knowledge and contributions. An important part of this literature has focused on the analysis of the contributing factors to IE development. From these studies, this work attempts to analyse and validate through an integrative model the effect on this construct in SME of some of the main factors proposed by the literature such as Skills and Competences, Attitude and Proactiveness, Creativity and Innovation, Networking, Employees and Activity. To proceed with this aim, we conducted an empirical research focused on 174 textile SME in Spain. The results obtained confirm a positive relationship between the studied factors and the IE development. 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