Meta-Reinforcement Learning for Timely and Energy-efficient Data Collection in Solar-powered UAV-assisted IoT Networks

Unmanned aerial vehicles (UAVs) have the potential to greatly aid Internet of Things (IoT) networks in mission-critical data collection, thanks to their flexibility and cost-effectiveness. However, challenges arise due to the UAV's limited onboard energy and the unpredictable status updates from sensor nodes (SNs), which impact the freshness of collected data. In this paper, we investigate the energy-efficient and timely data collection in IoT networks through the use of a solar-powered UAV. Each SN generates status updates at stochastic intervals, while the UAV collects and subsequently transmits these status updates to a central data center. Furthermore, the UAV harnesses solar energy from the environment to maintain its energy level above a predetermined threshold. To minimize both the average age of information (AoI) for SNs and the energy consumption of the UAV, we jointly optimize the UAV trajectory, SN scheduling, and offloading strategy. Then, we formulate this problem as a Markov decision process (MDP) and propose a meta-reinforcement learning algorithm to enhance the generalization capability. Specifically, the compound-action deep reinforcement learning (CADRL) algorithm is proposed to handle the discrete decisions related to SN scheduling and the UAV's offloading policy, as well as the continuous control of UAV flight. Moreover, we incorporate meta-learning into CADRL to improve the adaptability of the learned policy to new tasks. To validate the effectiveness of our proposed algorithms, we conduct extensive simulations and demonstrate their superiority over other baseline algorithms

Bruton's tyrosine kinase and protein kinase C µ are required for TLR7/9-induced IKKα and IRF-1 activation and interferon-β production in conventional dendritic cells

10.1371/journal.pone.0105420PLoS ONE981-

CoMP Transmission in Downlink NOMA-Based Cellular-Connected UAV Networks

In this paper, we study the integration between the coordinated multipoint (CoMP) transmission and the non-orthogonal multiple access (NOMA) in the downlink cellular-connected UAV networks with the coexistence of aerial users (AUs) and terrestrial users (TUs). Based on the comparison of the desired signal strength to the dominant interference strength, the AUs are classified into CoMP-AUs and Non-CoMP AUs, where the former receives transmissions from two cooperative BSs, and constructs two exclusive NOMA clusters with two TUs, respectively. A Non-CoMP AU constructs a NOMA cluster with a TU served by the same BS. By leveraging the tools from stochastic geometry, we propose a novel analytical framework to evaluate the performance of the CoMP-NOMA based cellular-connected UAV network in terms of coverage probability, and average ergodic rate. We reveal the superiority of the proposed CoMP-NOMA scheme by comparing with three benchmark schemes, and further quantify the impacts of key system parameters on the network performance. By harvesting the benefits of both CoMP and NOMA, we prove that the proposed framework can provide reliable connection for AUs by using CoMP and enhance the average ergodic rate through NOMA technique as well.Comment: 29 pages,10 figures, submitted to a transaction journa

Differentiation of canine distemper virus isolates in fur animals from various vaccine strains by reverse transcription-polymerase chain reaction-restriction fragment length polymorphism according to phylogenetic relations in china

In order to effectively identify the vaccine and field strains of Canine distemper virus (CDV), a new differential diagnostic test has been developed based on reverse transcription-polymerase chain reaction (RT-PCR) and restriction fragment length polymorphism (RFLP). We selected an 829 bp fragment of the nucleoprotein (N) gene of CDV. By RFLP analysis using BamHI, field isolates were distinguishable from the vaccine strains. Two fragments were obtained from the vaccine strains by RT-PCR-RFLP analysis while three were observed in the field strains. An 829 nucleotide region of the CDV N gene was analyzed in 19 CDV field strains isolated from minks, raccoon dogs and foxes in China between 2005 and 2007. The results suggest this method is precise, accurate and efficient. It was also determined that three different genotypes exist in CDV field strains in fur animal herds of the north of China, most of which belong to Asian type. Mutated field strains, JSY06-R1, JSY06-R2 and JDH07-F1 also exist in Northern China, but are most closely related to the standard virulent strain A75/17, designated in Arctic and America-2 genetype in the present study, respectively

High Throughput Sequencing Identifies MicroRNAs Mediating α-Synuclein Toxicity by Targeting Neuroactive-Ligand Receptor Interaction Pathway in Early Stage of Drosophila Parkinson\u27s Disease Model.

Parkinson\u27s disease (PD) is a prevalent neurodegenerative disorder with pathological features including death of dopaminergic neurons in the substantia nigra and intraneuronal accumulations of Lewy bodies. As the main component of Lewy bodies, α-synuclein is implicated in PD pathogenesis by aggregation into insoluble filaments. However, the detailed mechanisms underlying α-synuclein induced neurotoxicity in PD are still elusive. MicroRNAs are ~20nt small RNA molecules that fine-tune gene expression at posttranscriptional level. A plethora of miRNAs have been found to be dysregulated in the brain and blood cells of PD patients. Nevertheless, the detailed mechanisms and their in vivo functions in PD still need further investigation. By using Drosophila PD model expressing α-synuclein A30P, we examined brain miRNA expression with high-throughput small RNA sequencing technology. We found that five miRNAs (dme-miR-133-3p, dme-miR-137-3p, dme-miR-13b-3p, dme-miR-932-5p, dme-miR-1008-5p) were upregulated in PD flies. Among them, miR-13b, miR-133, miR-137 are brain enriched and highly conserved from Drosophila to humans. KEGG pathway analysis using DIANA miR-Path demonstrated that neuroactive-ligand receptor interaction pathway was most likely affected by these miRNAs. Interestingly, miR-137 was predicted to regulate most of the identified targets in this pathway, including dopamine receptor (DopR, D2R), γ-aminobutyric acid (GABA) receptor (GABA-B-R1, GABA-B-R3) and N-methyl-D-aspartate (NMDA) receptor (Nmdar2). The validation experiments showed that the expression of miR-137 and its targets was negatively correlated in PD flies. Further experiments using luciferase reporter assay confirmed that miR-137 could act on specific sites in 3\u27 UTR region of D2R, Nmdar2 and GABA-B-R3, which downregulated significantly in PD flies. Collectively, our findings indicate that α-synuclein could induce the dysregulation of miRNAs, which target neuroactive ligand-receptor interaction pathway in vivo. We believe it will help us further understand the contribution of miRNAs to α-synuclein neurotoxicity and provide new insights into the pathogenesis driving PD

Dramatic enhancement of superconductivity in single-crystalline nanowire arrays of Sn

Sn is a classical superconductor on the border between type I and type II with critical temperature of 3.7 K. We show that its critical parameters can be dramatically increased if it is brought in the form of loosely bound bundles of thin nanowires. The specific heat displays a pronounced double phase transition at 3.7 K and 5.5 K, which we attribute to the inner ‘bulk’ contribution of the nanowires and to the surface contribution, respectively. The latter is visible only because of the large volume fraction of the surface layer in relation to the bulk volume. The upper transition coincides with the onset of the resistive transition, while zero resistance is gradually approached below the lower transition. In contrast to the low critical field H(c) = 0.03 T of Sn in its bulk form, a magnetic field of more than 3 T is required to fully restore the normal state

Analysis of Long Noncoding RNAs in Aila-Induced Non-Small Cell Lung Cancer Inhibition

Non-small cell lung cancer (NSCLC) has the highest morbidity and mortality among all carcinomas. However, it is difficult to diagnose in the early stage, and current therapeutic efficacy is not ideal. Although numerous studies have revealed that Ailanthone (Aila), a natural product, can inhibit multiple cancers by reducing cell proliferation and invasion and inducing apoptosis, the mechanism by which Aila represses NSCLC progression in a time-dependent manner remains unclear. In this study, we observed that most long noncoding RNAs (lncRNAs) were either notably up- or downregulated in NSCLC cells after treatment with Aila. Moreover, alterations in lncRNA expression induced by Aila were crucial for the initiation and metastasis of NSCLC. Furthermore, in our research, expression of DUXAP8 was significantly downregulated in NSCLC cells after treatment with Aila and regulated expression levels of EGR1. In conclusion, our findings demonstrate that Aila is a potent natural suppressor of NSCLC by modulating expression of DUXAP8 and EGR1