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In the era of 6G, given the emergence of heterogenous devices, diverse network scenarios, along with future deployment of cutting-edge applications that require high computation ability, how to establish trust in such complex network environment has become a demanding task. Current trust establishment process mostly relies on certificates issued by certificate authority (CA) or reputation derived from interaction and behavior history. However, these approaches may not be applicable to 6G scenarios due to several reasons, including but not limited to insufficient adaptability, lack of openness and transparency, and limited scalability. Hence, this article mainly proposes a novel approach, which is based on a claim-attestation-evidence framework and leverages both blockchain and artificial intelligence (AI) to build trust in highly open and dynamic future networks. Meanwhile, we also provide an overview on current trust establishment models, discuss about the advantages of our proposed model and suggest certain parts of our current design for improvements that can be considered by future research.

Recent years have witnessed a digital explosion in the deployment of 5G and the proliferation of 5G-enabled innovations. Compared with 5G, 6G is envisioned to achieve a much higher performance and experience a number of paradigm shifts, such as exploiting new spectrum, applying ubiquitous Machine Learning and Artificial Intelligence (ML/AI) technologies and building a space-air-ground-sea integrated network. However, these paradigm shifts may lead to numerous new security and privacy issues, that traditional security measures may not be able to address. Moreover, the expected high performance of 6G also challenges network reliability and energy efficiency. To tackle these issues and build a trustworthy 6G network, we introduce a novel trust framework called SIX-Trust. This framework is composed of three layers with an emphasis on distinct aspects: sustainable trust (S-Trust), with a particular focus on trust in applications of AI, novel trust evaluation methods and modeling of trust relationships; infrastructure trust (I-Trust), which is more focused on the trustworthiness of network infrastructure; and xenogenesis trust (X-Trust) paying special attention to the core technologies which form the backbone of 6G trust. Besides, the importance of each layer varies under different application scenarios of 6G. For each layer, we briefly introduce its related enabling technologies, and demonstrate how these technologies can be applied to enhance the trust and security of the 6G network. Finally, a use case is illustrated and analyzed. In general, SIX-Trust provides a holistic framework for defining and modeling trust in 6G, which can facilitate establishment of a trustworthy 6G network.

Trust is an essential concept in various scenarios enabled by Information and Communication Technologies (ICT). To facilitate the implementation of trust in these scenarios, different organizations have published a series of trust frameworks. However, most existing works on trust standards only focus on a specific application domain. Unlike these works, in this paper, we provide a comprehensive overview of the current available trust standards related to communication networks and future digital world from several main organizations. We categorize these trust standards into three layers: trust foundation, trust elements, and trust applications. We then analyze these trust standards and discuss their contributions in a systematic way. We also examine the motivations behind each enforced standard, analyze their frameworks and solutions, and present their role and impact on communication works and future digital world. Finally, we offer our suggestions on the trust work that needs to be standardized in the future.

With the rapid development of blockchain technology in recent years, all kinds of blockchain-based applications have emerged. Among them, the decentralized finance (DeFi) is one of the most successful applications, which is regarded as the future of finance. The great success of DeFi relies on the real-world data which is not directly available on the blockchain. However, due to the deterministic nature of blockchain, the blockchain cannot directly obtain indeterministic data from the outside world (off-chain). Thus, oracles have appeared as a viable solution to feed off-chain data to blockchain applications. In this paper, we carry out a comprehensive study on oracles, especially on DeFi oracles. We first briefly introduce the application scenarios of DeFi oracles, and then we talk about the past of DeFi oracles by categorizing them into several types based on their design features. After that, we introduce five popular DeFi oracles currently in use (such as Chainlink and Band Protocol), with the focus on their system architecture, data validation process, and their incentive mechanisms. Then, we compare these present DeFi oracles from their data trustworthiness, data source trustworthiness and their overall trust models. Finally, we propose a set of metrics for designing trustworthiness DeFi oracles, and propose a potential trust architecture and a few promising techniques for building future trustworthiness oracles.

Abstract Background Aberrant right subclavian artery (ARSA) with associated Kommerell diverticulum (KD) is a rare congenital aortic disease. KD patients have a high risk of rupture, dissection, and compression of adjacent structures. Although several treatment options have been proposed (traditional surgery, hybrid operation, and endovascular intervention), a consensus regarding optimal surgical management has not yet been established. Case presentation A case of successful hybrid repair of distal aortic arch dissection aneurysm by dissecting KD and ARSA with debranching of right and left common carotid arteries, left subclavian artery, and stent grafting was presented. Conclusions The hybrid operation is suitable for elderly patients or those with high risks. Along with intervention, the hybrid operation needs to be developed as a minimally invasive method.

With the fast development of digital technologies, we are running into a digital world. The relationship among people and the connections among things become more and more complex, and new challenges arise. To tackle these challenges, trust — a soft security mechanism — is considered a promising technology. Thus, in this survey, we do a comprehensive study on trust and trust modelling for the future digital world. We revisit the definitions and properties of trust, analyse the trust theories, and discuss their impact on digital trust modelling. We analyse the digital world and its corresponding environment where people, things, and infrastructure connect with each other. We detail the challenges that require trust in these digital scenarios. Under our analysis of trust and the digital world, we define different types of trust relationships and find out the factors that are needed to ensure a fully representative model. Next, to meet the challenges of digital trust modelling, comprehensive trust model evaluation criteria are proposed, and potential security and privacy issues of trust modelling are analysed. Finally, we provide a wide-ranging analysis of different methodologies, mathematical theories, and how they can be applied to trust modelling.

Less than 2% of the human genome DNA is composed of protein-coding genes, although the majority of the human genome is transcribed, indicating the transcripts mostly are noncoding RNAs. Those noncoding RNAs with length between 200 nt and 200 kb are categorized as long noncoding RNA (lncRNA). Around 30 000 lncRNAs have been predicted or identified, although little is known regarding the regulatory function for a vast majority of these sequences. Emerging evidence demonstrated that lncRNAs play crucial roles in regulation of many cancer types, including breast cancer, serving as oncogenes or tumor suppressors. Aberrant and differential expression of lncRNA in breast cancer has been frequently reported. Their regulation of breast cancer is still the beginning to be elucidated. This review collected those experimentally validated lncRNAs in human breast cancer, summarizing their biological function as well as the regulatory mechanism. In addition, the potential of lncRNAs as biomarkers for better diagnosis or therapeutic targets for cancer treatment was discussed. [ABSTRACT FROM AUTHOR]

Beta-blockers contribute to treatment of heart failure. Their mechanism of action, however, is incompletely understood. Gradients in beta-blocker sensitivity of helically aligned cardiomyocytes compared with counteracting transversely intruding cardiomyocytes seem crucial. We hypothesize that selective blockade of transversely intruding cardiomyocytes by lowdose beta-blockade unloads ventricular performance. Cardiac magnetic resonance imaging (MRI) 3D tagging delivers parameters of myocardial performance. We studied 13 healthy volunteers by MRI 3D tagging during escalated intravenous administration of esmolol. The circumferential, longitudinal, and radial myocardial shortening was determined for each dose. The curves were analyzed for peak value, time-to-peak, upslope, and area-under-the-curve. At low doses, from 5 to 25 μg·kg-1·min-1, peak contraction increased while timeto- peak decreased yielding a steeper upslope. Combining the values revealed a left shift of the curves at low doses compared with baseline without esmolol. At doses of 50 to 150 μg·kg-1·min-1, a right shift with flattening occurred. In healthy volunteers we found more pronounced myocardial shortening at low compared with clinical dosage of beta-blockers. In patients with ventricular hypertrophy and higher prevalence of transversely intruding cardiomyocytes selective lowdose beta-blockade could be even more effective. MRI 3D tagging could help to determine optimal individual beta-blocker dosing avoiding undesirable side effects. [ABSTRACT FROM AUTHOR]

Abstract In this article, fractional integral is considered. Some new upper bounds of the distance between the middle and left of Hermite–Hadamard type inequalities for fractional integrals are established for (s,m) $(s,m)$-convex or s-concave functions.

Ghd7 is an important rice gene that has a major effect on several agronomic traits, including yield. To reveal the origin of Ghd7 and sequence evolution of this locus, we performed a comparative sequence analysis of the Ghd7 orthologous regions from ten diploid Oryza species, Brachypodium distachyon, sorghum and maize. Sequence analysis demonstrated high gene collinearity across the genus Oryza and a disruption of collinearity among non-Oryza species. In particular, Ghd7 was not present in orthologous positions except in Oryza species. The Ghd7 regions were found to have low gene densities and high contents of repetitive elements, and that the sizes of orthologous regions varied tremendously. The large transposable element contents resulted in a high frequency of pseudogenization and gene movement events surrounding the Ghd7 loci. Annotation information and cytological experiments have indicated that Ghd7 is a heterochromatic gene. Ghd7 orthologs were identified in B. distachyon, sorghum and maize by phylogenetic analysis; however, the positions of orthologous genes differed dramatically as a consequence of gene movements in grasses. Rather, we identified sequence remnants of gene movement of Ghd7 mediated by illegitimate recombination in the B. distachyon genome.