As an emerging communication platform in the Internet of Things, IoV is promising to pave the way for the establishment of smart cities and provide support for various kinds of applications and ...services. Energy management in IoV has been attracting an upsurge of interest in both academia and industry. Currently, green IoV mainly focuses on two aspects: energy management of battery- enabled RSUs and EVs. However, these two issues are always resolved separately while ignoring their interactions. This standalone design may cause energy underutilization, a mismatch between traffic demands and energy supplies, as well as high deployment and sustainable costs for RSUs. Therefore, the integration of energy management between battery-enabled RSUs and EVs calls for comprehensive investigation. This article first provides an overview of several promising research fields for energy management in green IoV systems. Given the significance of efficient communications and energy management, we construct an intelligent energy-harvesting framework based on V2I communications in green IoV communication systems. Specifically, we develop a three-stage Stackelberg game to maximize the utilities of both RSUs and EVs in V2I communications. After that, a real-world trajectory-based performance evaluation is provided to demonstrate the effectiveness of our scheme. Finally, we identify and discuss some research challenges and open issues for energy management in green IoV systems.
Recent developments of edge computing and content caching in wireless networks enable the Intelligent Transportation System (ITS) to provide high-quality services for vehicles. However, a variety of ...vehicular applications and time-varying network status make it challenging for ITS to allocate resources efficiently. Artificial intelligence algorithms, owning the cognitive capability for diverse and time-varying features of Internet of Connected Vehicles (IoCVs), enable an intent-based networking for ITS to tackle the above-mentioned challenges. In this paper, we develop an intent-based traffic control system by investigating Deep Reinforcement Learning (DRL) for 5G-envisioned IoCVs, which can dynamically orchestrate edge computing and content caching to improve the profits of Mobile Network Operator (MNO). By jointly analyzing MNO's revenue and users' quality of experience, we define a profit function to calculate the MNO's profits. After that, we formulate a joint optimization problem to maximize MNO's profits, and develop an intelligent traffic control scheme by investigating DRL, which can improve system profits of the MNO and allocate network resources effectively. Experimental results based on real traffic data demonstrate our designed system is efficient and well-performed.
Fibroblast growth factor (FGF) belongs to a large family of growth factors. FGFs use paracrine or endocrine signaling to mediate a myriad of biological and pathophysiological process, including ...angiogenesis, wound healing, embryonic development, and metabolism regulation. FGF drugs for the treatment of burn and ulcer wounds are now available. The recent discovery of the crucial roles of the endocrine-acting FGF19 subfamily in maintaining homeostasis of bile acid, glucose, and phosphate further extended the activity profile of this family. Here, the applications of recombinant FGFs for the treatment of wounds, diabetes, hypophosphatemia, the development of FGF receptor inhibitors as anti-neoplastic drugs, and the achievements of basic research and applications of FGFs in China are reviewed.
Podocyte injury is a major determinant of proteinuric kidney disease and the identification of potential therapeutic targets for preventing podocyte injury has clinical importance. Here, we show that ...histone deacetylase Sirt6 protects against podocyte injury through epigenetic regulation of Notch signaling. Sirt6 is downregulated in renal biopsies from patients with podocytopathies and its expression correlates with glomerular filtration rate. Podocyte-specific deletion of Sirt6 exacerbates podocyte injury and proteinuria in two independent mouse models, diabetic nephropathy, and adriamycin-induced nephropathy. Sirt6 has pleiotropic protective actions in podocytes, including anti-inflammatory and anti-apoptotic effects, is involved in actin cytoskeleton maintenance and promotes autophagy. Sirt6 also reduces urokinase plasminogen activator receptor expression, which is a key factor for podocyte foot process effacement and proteinuria. Mechanistically, Sirt6 inhibits Notch1 and Notch4 transcription by deacetylating histone H3K9. We propose Sirt6 as a potential therapeutic target for the treatment of proteinuric kidney disease.Podocytes are essential components of the renal glomerular filtration barrier and podocyte dysfunction leads to proteinuric kidney disease. Here Liu et al. show that Sirt6 protects podocytes from apoptosis and inflammation by increasing autophagic flux through inhibition of the Notch pathway.
Small RNAs (sRNAs), an important type of pathogenicity factor, contribute to impairing host immune responses. However, little is known about sRNAs in Puccinia striiformis f. sp. tritici (Pst), one of ...the most destructive pathogens of wheat (Triticum aestivum L.). Here, we report a novel microRNA-like RNA (milRNA) from Pst termed microRNA-like RNA 1 (Pst milR1), which suppresses wheat defenses during wheat–Pst interactions.
We identified Pst-milR1 as a novel milRNA in Pst. Biological prediction and co-transformation showed that Pst-milR1 takes part in cross-kingdom RNA interference (RNAi) events by binding the wheat pathogenesis-related 2 (PR2) gene.
Silencing of the Pst-milR1 precursor resulted in increased wheat resistance to the virulent Pst isolate CYR31. PR2 knock-down plants increased the susceptibility of wheat to the avirulent Pst isolate CYR23. This suggests that Pst-milR1 represses the plant immune response by suppressing the expression of PR2.
Taking our findings together, we postulate that Pst-milR1 is an important pathogenicity factor in Pst, which acts as an effector to suppress host immunity. Our results provide significant new insights into the pathogenicity of the stripe rust pathogen.
A novel paradigm named Wireless Powered Mobile Edge Computing (WP-MEC) emerges recently, which integrates Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) technologies. It enables mobile ...clients to both extend their computing capacities by task offloading, and charge from edge servers via energy transmission. Existing studies generally focus on the centralized design of task scheduling and energy charging in WP-MEC networks. To meet the decentralization requirement of the near-coming 6G network, we propose an online learning algorithm for computation offloading in WP-MEC networks with a distributed execution manner. Specifically, we first define the delay minimization problem by considering task deadline and energy constraints. Then, we transform it into a primal-dual optimization problem based on the Bellman equation. After that, we design a novel neural model that learns both offloading and time division decisions in each time slot to solve the formulated optimization problem. To train and execute the designed algorithm distributivity, we form multiple learning models decentralized on edge servers and they work coordinately to achieve parameter synchronization. At last, both theoretical and performance analyses show that the designed algorithm has significant advantages in comparison with other representative schemes.
Two-dimensional ferroelectrics is attractive for synaptic device applications because of its low power consumption and amenability to high-density device integration. Here, we demonstrate that tin ...monosulfide (SnS) films less than 6 nm thick show optimum performance as a semiconductor channel in an in-plane ferroelectric analogue synaptic device, whereas thicker films have a much poorer ferroelectric response due to screening effects by a higher concentration of charge carriers. The SnS ferroelectric device exhibits synaptic behaviors with highly stable room-temperature operation, high linearity in potentiation/depression, long retention, and low cycle-to-cycle/device-to-device variations. The simulated device based on ferroelectric SnS achieves ∼92.1% pattern recognition accuracy in an artificial neural network simulation. By switching the ferroelectric domains partially, multilevel conductance states and the conductance ratio can be obtained, achieving high pattern recognition accuracy.
The circadian clock imposes daily rhythms in cell proliferation, metabolism, inflammation and DNA damage response. Perturbations of these processes are hallmarks of cancer and chronic circadian ...rhythm disruption predisposes individuals to tumour development. This raises the hypothesis that pharmacological modulation of the circadian machinery may be an effective therapeutic strategy for combating cancer. REV-ERBs, the nuclear hormone receptors REV-ERBα (also known as NR1D1) and REV-ERBβ (also known as NR1D2), are essential components of the circadian clock. Here we show that two agonists of REV-ERBs-SR9009 and SR9011-are specifically lethal to cancer cells and oncogene-induced senescent cells, including melanocytic naevi, and have no effect on the viability of normal cells or tissues. The anticancer activity of SR9009 and SR9011 affects a number of oncogenic drivers (such as HRAS, BRAF, PIK3CA and others) and persists in the absence of p53 and under hypoxic conditions. The regulation of autophagy and de novo lipogenesis by SR9009 and SR9011 has a critical role in evoking an apoptotic response in malignant cells. Notably, the selective anticancer properties of these REV-ERB agonists impair glioblastoma growth in vivo and improve survival without causing overt toxicity in mice. These results indicate that pharmacological modulation of circadian regulators is an effective antitumour strategy, identifying a class of anticancer agents with a wide therapeutic window. We propose that REV-ERB agonists are inhibitors of autophagy and de novo lipogenesis, with selective activity towards malignant and benign neoplasms.
A method was developed to magnetically align multi-walled carbon nanotubes (MWCNTs) as well as graphene nanoplates (GNPs) within a poly (dimethylsiloxane) (PDMS) matrix. The MWCNTs and GNPs polymer ...composites treated with magnetic field forming chain structures would be expected to produce anisotropic thermal conductivity. Firstly, the MWCNTs and GNPs were functionalized by γ-methacryloxy propyl trimethoxyl silane (KH570) in order to improve their compatibility with polymer matrix, and then different contents of the MWCNTs and GNPs were incorporated into PDMS and cured under a magnetic field up to 10 T to generate anisotropic MWCNTs/PDMS and GNPs/PDMS composites. The polarized Raman spectra and scanning electron microscopy (SEM) were applied to investigate the structures of MWCNTs and GNPs dispersion in the composites. The thermal conductivity of all samples was measured by using hot wire method. The results showed that the magnetically aligned MWCNTs/GNPs polymer composites feature high anisotropy in thermal conductivity. Thermal conductivity in the aligned direction of 10.0 T-treated PDMS composites with 3wt% GNPs content showed enhancements of 174% and 49%, compared to pure PDMS and non-magnetically treated GNP/PDMS composites, respectively. Compared with the MWCNTs fillers, the GNPs showed better performance in improvement of the thermal conductivity of the polymer composites.
Due to the heterogeneous and resource-constrained characters of Internet of Things (IoT), how to guarantee ubiquitous network connectivity is challenging. Although LTE cellular technology is the most ...promising solution to provide network connectivity in IoTs, information diffusion by cellular network not only occupies its saturating bandwidth, but also costs additional fees. Recently, NarrowBand-IoT (NB-IoT), introduced by 3GPP, is designed for low-power massive devices, which intends to refarm wireless spectrum and increase network coverage. For the sake of providing high link connectivity and capacity, we stimulate effective cooperations among user equipments (UEs), and propose a social-aware group formation framework to allocate resource blocks (RBs) effectively following an in-band NB-IoT solution. Specifically, we first introduce a social-aware multihop device-to-device (D2D) communication scheme to upload information toward the eNodeB within an LTE, so that a logical cooperative D2D topology can be established. Then, we formulate the D2D group formation as a scheduling optimization problem for RB allocation, which selects the feasible partition for the UEs by jointly considering relay method selection and spectrum reuse for NB-IoTs. Since the formulated optimization problem has a high computational complexity, we design a novel heuristic with a comprehensive consideration of power control and relay selection. Performance evaluations based on synthetic and real trace simulations manifest that the presented method can significantly increase link connectivity, link capacity, network throughput, and energy efficiency comparing with the existing solutions.
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