Cache-Enabled in Cooperative Cognitive Radio Networks for Transmission Performance

The proliferation of mobile devices that support the acceleration of data services (especially smartphones) has resulted in a dramatic increase in mobile traffic. Mobile data also increased exponentially, already exceeding the throughput of the backhaul. To improve spectrum utilization and increase mobile network traffic, in combination with content caching, we study the cooperation between primary and secondary networks via content caching. We consider that the secondary base station assists the primary user by pre-caching some popular primary contents. Thus, the secondary base station can obtain more licensed bandwidth to serve its own user. We mainly focus on the time delay from the backhaul link to the secondary base station. First, in terms of the content caching and the transmission strategies, we provide a cooperation scheme to maximize the secondary user’s effective data transmission rates under the constraint of the primary users target rate. Then, we investigate the impact of the caching allocation and prove that the formulated problem is a concave problem with regard to the caching capacity allocation for any given power allocation. Furthermore, we obtain the joint caching and power allocation by an effective bisection search algorithm. Finally, our results show that the content caching cooperation scheme can achieve significant performance gain for the primary and secondary systems over the traditional two-hop relay cooperation without caching

Deep learning-based edge caching for multi-cluster heterogeneous networks

© 2019, Springer-Verlag London Ltd., part of Springer Nature. In this work, we consider a time and space evolution cache refreshing in multi-cluster heterogeneous networks. We consider a two-step content placement probability optimization. At the initial complete cache refreshing optimization, the joint optimization of the activated base station density and the content placement probability is considered. And we transform this optimization problem into a GP problem. At the following partial cache refreshing optimization, we take the time–space evolution into consideration and derive a convex optimization problem subjected to the cache capacity constraint and the backhaul limit constraint. We exploit the redundant information in different content popularity using the deep neural network to avoid the repeated calculation because of the change in content popularity distribution at different time slots. Trained DNN can provide online response to content placement in a multi-cluster HetNet model instantaneously. Numerical results demonstrate the great approximation to the optimum and generalization ability

Tunable quantum dots in monolithic Fabry-Perot microcavities for high-performance single-photon sources

Cavity-enhanced single quantum dots (QDs) are the main approach towards ultra-high-performance solid-state quantum light sources for scalable photonic quantum technologies. Nevertheless, harnessing the Purcell effect requires precise spectral and spatial alignment of the QDs' emission with the cavity mode, which is challenging for most cavities. Here we have successfully integrated miniaturized Fabry-Perot microcavities with a piezoelectric actuator, and demonstrated a bright single photon source derived from a deterministically coupled QD within this microcavity. Leveraging the cavity-membrane structures, we have achieved large spectral-tunability via strain tuning. On resonance, we have obtained a high Purcell factor of approximately 9. The source delivers single photons with simultaneous high extraction efficiency of 0.58, high purity of 0.956(2) and high indistinguishability of 0.922(4). Together with a small footprint, our scheme facilitates the scalable integration of indistinguishable quantum light sources on-chip, and therefore removes a major barrier to the solid-state quantum information platforms based on QDs.Comment: 12 pages, 4 figure

Amplified role of potential HONO sources in O3 formation in North China Plain during autumn haze aggravating processes

Co-occurrences of high concentrations of PM2.5 and ozone (O-3) have been frequently observed in haze-aggravating processes in the North China Plain (NCP) over the past few years. Higher O-3 concentrations on hazy days were hypothesized to be related to nitrous acid (HONO), but the key sources of HONO enhancing O-3 during haze-aggravating processes remain unclear. We added six potential HONO sources, i.e., four groundbased (traffic, soil, and indoor emissions, and the NO2 heterogeneous reaction on ground surface (Het(ground))) sources, and two aerosol-related (the NO2 heterogeneous reaction on aerosol surfaces (Het(aerosol)) and nitrate photolysis (Phot(nitrate))) sources into the WRF-Chem model and designed 23 simulation scenarios to explore the unclear key sources. The results indicate that ground-based HONO sources producing HONO enhancements showed a rapid decrease with height, while the NO C OH reaction and aerosol-related HONO sources decreased slowly with height. Photnitrate contributions to HONO concentrations were enhanced with aggravated pollution levels. The enhancement of HONO due to Phot(nitrate) on hazy days was about 10 times greater than on clean days and Phot(nitrate) dominated daytime HONO sources (similar to 30 %-70% when the ratio of the photolysis frequency of nitrate (J(nitrate)) to gas nitric acid (JHNO(3)) equals 30) at higher layers (>800 m). Compared with that on clean days, the Phot(nitrate) contribution to the enhanced daily maximum 8 h averaged (DMA8) O-3 was increased by over 1 magnitude during the haze-aggravating process. Phot(nitrate) contributed only similar to 5% of the surface HONO in the daytime with a J(nitrate) =JHNO(3) ratio of 30 but contributed similar to 30 %-50% of the enhanced O-3 near the surface in NCP on hazy days. Surface O-3 was dominated by volatile organic compound-sensitive chemistry, while O-3 at higher altitudes ( >800 m) was dominated by NOx-sensitive chemistry. Phot(nitrate) had a limited impact on nitrate concentrations (Peer reviewe

High-risk genotypes for type 1 diabetes are associated with the imbalance of gut microbiome and serum metabolites

BackgroundThe profile of gut microbiota, serum metabolites, and lipids of type 1 diabetes (T1D) patients with different human leukocyte antigen (HLA) genotypes remains unknown. We aimed to explore gut microbiota, serum metabolites, and lipids signatures in individuals with T1D typed by HLA genotypes.MethodsWe did a cross-sectional study that included 73 T1D adult patients. Patients were categorized into two groups according to the HLA haplotypes they carried: those with any two of three susceptibility haplotypes (DR3, DR4, DR9) and without any of the protective haplotypes (DR8, DR11, DR12, DR15, DR16) were defined as high-risk HLA genotypes group (HR, n=30); those with just one or without susceptibility haplotypes as the non-high-risk HLA genotypes group (NHR, n=43). We characterized the gut microbiome profile with 16S rRNA gene amplicon sequencing and analyzed serum metabolites with liquid chromatography-mass spectrometry.ResultsStudy individuals were 32.5 (8.18) years old, and 60.3% were female. Compared to NHR, the gut microbiota of HR patients were characterized by elevated abundances of Prevotella copri and lowered abundances of Parabacteroides distasonis. Differential serum metabolites (hypoxanthine, inosine, and guanine) which increased in HR were involved in purine metabolism. Different lipids, phosphatidylcholines and phosphatidylethanolamines, decreased in HR group. Notably, Parabacteroides distasonis was negatively associated (p ≤ 0.01) with hypoxanthine involved in purine metabolic pathways.ConclusionsThe present findings enabled a better understanding of the changes in gut microbiome and serum metabolome in T1D patients with HLA risk genotypes. Alterations of the gut microbiota and serum metabolites may provide some information for distinguishing T1D patients with different HLA risk genotypes

Continuous and comprehensive atmospheric observations in Beijing : a station to understand the complex urban atmospheric environment

Peer reviewe

PD-1hi CD8+ resident memory T cells balance immunity and fibrotic sequelae

CD8+ tissue-resident memory T (TRM) cells provide frontline immunity in mucosal tissues. The mechanisms regulating CD8+ TRM maintenance, heterogeneity, and protective and pathological functions are largely elusive. Here, we identify a population of CD8+ TRM cells that is maintained by major histocompatibility complex class I (MHC-I) signaling, and CD80 and CD86 costimulation after acute influenza infection. These TRM cells have both exhausted-like phenotypes and memory features and provide heterologous immunity against secondary infection. PD-L1 blockade after the resolution of primary infection promotes the rejuvenation of these exhausted-like TRM cells, restoring protective immunity at the cost of promoting postinfection inflammatory and fibrotic sequelae. Thus, PD-1 serves to limit the pathogenic capacity of exhausted-like TRM cells at the memory phase. Our data indicate that TRM cell exhaustion is the result of a tissue-specific cellular adaptation that balances fibrotic sequelae with protective immunity