Multi-Tenant Provisioning for Quantum Key Distribution Networks with Heuristics and Reinforcement Learning: A Comparative Study

Quantum key distribution (QKD) networks are potential to be widely deployed in the immediate future to provide long-term security for data communications. Given the high price and complexity, multi-tenancy has become a cost-effective pattern for QKD network operations. In this work, we concentrate on addressing the online multi-tenant provisioning (On-MTP) problem for QKD networks, where multiple tenant requests (TRs) arrive dynamically. On-MTP involves scheduling multiple TRs and assigning non-reusable secret keys derived from a QKD network to multiple TRs, where each TR can be regarded as a high-security-demand organization with the dedicated secret-key demand. The quantum key pools (QKPs) are constructed over QKD network infrastructure to improve management efficiency for secret keys. We model the secret-key resources for QKPs and the secret-key demands of TRs using distinct images. To realize efficient On-MTP, we perform a comparative study of heuristics and reinforcement learning (RL) based On-MTP solutions, where three heuristics (i.e., random, fit, and best-fit based On-MTP algorithms) are presented and a RL framework is introduced to realize automatic training of an On-MTP algorithm. The comparative results indicate that with sufficient training iterations the RL-based On-MTP algorithm significantly outperforms the presented heuristics in terms of tenant-request blocking probability and secret-key resource utilization

Improving mobility of silicon metal-oxide-semiconductor devices for quantum dots by high vacuum activation annealing

To improve mobility of fabricated silicon metal-oxide-semiconductor (MOS) quantum devices, forming gas annealing is a common method used to mitigate the effects of disorder at the Si/SiO2 interface. However, the importance of activation annealing is usually ignored. Here, we show that a high vacuum environment for implantation activation is beneficial for improving mobility compared to nitrogen atmosphere. Low-temperature transport measurements of Hall bars show that peak mobility can be improved by a factor of two, reaching 1.5 m^2/(Vs) using high vacuum annealing during implantation activation. Moreover, the charge stability diagram of a single quantum dot is mapped, with no visible disturbance caused by disorder, suggesting possibility of fabricating high-quality quantum dots on commercial wafers. Our results may provide valuable insights into device optimization in silicon-based quantum computing.Comment: 13 pages, 4 figure

Antibody dependent enhancement infection of Enterovirus 71 in vitro and in vivo

BACKGROUND: Human enterovirus 71 (EV71) has emerged as a significant cause of acute encephalitis and deaths in young children. The clinical manifestations caused by EV71 varied from mild hand, foot and mouth disease to severe neurological complications and deaths, but its pathogenesis remains elusive. Antibody dependent enhancement (ADE) infection has been reported in various viruses and has been shown to contribute to disease severity. RESULTS: In this study, the presence of sub-neutralizing antibody was demonstrated to enhance EV71 infection in THP-1 cells and increase the mortality of EV71 infection in a suckling mouse model. Further, a secondary infection model was established to characterize the correlation between ADE and disease severity, and primary asymptomatic EV71 infection was shown to increase the mortality of the secondary EV71 infection in suckling mice. CONCLUSIONS: Together, these in vitro and in vivo experiments strongly supported the hypothesis of ADE infection of EV71. The present findings indicate ADE might contribute to the pathogenesis of severe EV71 infection, and raise practical issues of vaccine development and antibody-based therapy

Melatonin Mediates Osteoblast Proliferation Through the STIM1/ORAI1 Pathway

Based on the positive correlation between bone mineral density and melatonin levels in blood, this study confirmed that melatonin supplementation prevents postmenopausal osteoporosis. We further confirmed that melatonin promotes an increase in intracellular calcium concentrations through the STIM1/ORAI1 pathway, thereby inducing the proliferation of osteoblasts.Introduction: Osteoporosis (OP) is a progressive, systemic bone disease that is one of the main causes of disability and death in elderly female patients. As an amine hormone produced by the human pineal gland, melatonin plays an important role in regulating bone metabolism. This study intends to investigate the relationship between melatonin levels in human blood and bone density and to suggest the efficacy of melatonin in treating osteoporosis by performing in vivo and in vitro experiments.Methods: We used liquid chromatography-tandem mass spectrometry to determine the serum melatonin levels in postmenopausal women with osteoporosis and young women with a normal bone mass. The bone density, BV/TV, Tb.Th, Tb.Sp and other indicators of postmenopausal osteoporosis and mice with a normal bone mass were detected by measuring bone density and micro-CT. The intracellular calcium ion concentration was detected using fluorescence microscopy and a full-wavelength multifunctional microplate reader, and the expression of SOCE-related genes and STIM1/ORAI1 proteins was detected using PCR and WB.Results: This study confirmed that bone density positively correlates with the melatonin level in human blood. In the animal model, melatonin supplementation reverses postmenopausal osteoporosis. We explored the internal mechanism of melatonin treatment of osteoporosis. Melatonin promotes an increase in intracellular calcium ion concentrations through the STIM1/ORAI1 pathway to induce osteoblast proliferation.Conclusions: This study provides an important theoretical basis for the clinical application of melatonin in patients with osteoporosis and helps to optimize the diagnosis and treatment of postmenopausal osteoporosis

I2P-Rec: Recognizing Images on Large-scale Point Cloud Maps through Bird's Eye View Projections

Place recognition is an important technique for autonomous cars to achieve full autonomy since it can provide an initial guess to online localization algorithms. Although current methods based on images or point clouds have achieved satisfactory performance, localizing the images on a large-scale point cloud map remains a fairly unexplored problem. This cross-modal matching task is challenging due to the difficulty in extracting consistent descriptors from images and point clouds. In this paper, we propose the I2P-Rec method to solve the problem by transforming the cross-modal data into the same modality. Specifically, we leverage on the recent success of depth estimation networks to recover point clouds from images. We then project the point clouds into Bird's Eye View (BEV) images. Using the BEV image as an intermediate representation, we extract global features with a Convolutional Neural Network followed by a NetVLAD layer to perform matching. The experimental results evaluated on the KITTI dataset show that, with only a small set of training data, I2P-Rec achieves recall rates at Top-1\% over 80\% and 90\%, when localizing monocular and stereo images on point cloud maps, respectively. We further evaluate I2P-Rec on a 1 km trajectory dataset collected by an autonomous logistics car and show that I2P-Rec can generalize well to previously unseen environments.Comment: Accepted by IROS 202

Integrated analysis of genes shared between type 2 diabetes mellitus and osteoporosis

BackgroundThe relationship between type 2 diabetes mellitus (T2DM) and osteoporosis (OP) has been widely recognized in recent years, but the mechanism of interaction remains unknown. The aim of this study was to investigate the genetic features and signaling pathways that are shared between T2DM and OP.MethodsWe analyzed the GSE76894 and GSE76895 datasets for T2DM and GSE56815 and GSE7429 for OP from the Gene Expression Omnibus (GEO) database to identify shared genes in T2DM and OP, and we constructed coexpression networks based on weighted gene coexpression network analysis (WGCNA). Shared genes were then further analyzed for functional pathway enrichment. We selected the best common biomarkers using the least absolute shrinkage and selection operator (LASSO) algorithm and validated the common biomarkers, followed by RT-PCR, immunofluorescence, Western blotting, and enzyme-linked immunosorbent assay (ELISA) to validate the expression of these hub genes in T2DM and OP mouse models and patients.ResultsWe found 8,506 and 2,030 DEGs in T2DM and OP, respectively. Four modules were identified as significant for T2DM and OP using WGCNA. A total of 19 genes overlapped with the strongest positive and negative modules of T2DM and OP. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed these genes may be involved in pantothenate and CoA biosynthesis and the glycosaminoglycan biosynthesis-chondroitin sulfate/dermatan sulfate and renin-angiotensin system signaling pathway. The LASSO algorithm calculates the six optimal common biomarkers. RT-PCR results show that LTB, TPBG, and VNN1 were upregulated in T2DM and OP. Immunofluorescence and Western blot show that VNN1 is upregulated in the pancreas and bones of T2DM model mice and osteoporosis model mice. Similarly, the level of VNN1 in the sera of patients with T2DM, OP, and T2DM and OP was higher than that in the healthy group.ConclusionBased on the WGCNA and LASSO algorithms, we identified genes and pathways that were shared between T2DM and OP. Both pantothenate and CoA biosynthesis and the glycosaminoglycan biosynthesis-chondroitin sulfate/dermatan sulfate and renin–angiotensin systems may be associated with the pathogenesis of T2DM and OP. Moreover, VNN1 may be a potential diagnostic marker for patients with T2DM complicated by OP. This study provides a new perspective for the systematic study of possible mechanisms of combined OP and T2DM