MMV-Based Sequential AoA and AoD Estimation for Millimeter Wave MIMO Channels

The fact that the millimeter-wave (mmWave) multiple-input multiple-output (MIMO) channel has sparse support in the spatial domain has motivated recent compressed sensing (CS)-based mmWave channel estimation methods, where the angles of arrivals (AoAs) and angles of departures (AoDs) are quantized using angle dictionary matrices. However, the existing CS-based methods usually obtain the estimation result through one-stage channel sounding that have two limitations: (i) the requirement of large-dimensional dictionary and (ii) unresolvable quantization error. These two drawbacks are irreconcilable; improvement of the one implies deterioration of the other. To address these challenges, we propose, in this paper, a two-stage method to estimate the AoAs and AoDs of mmWave channels. In the proposed method, the channel estimation task is divided into two stages, Stage I and Stage II. Specifically, in Stage I, the AoAs are estimated by solving a multiple measurement vectors (MMV) problem. In Stage II, based on the estimated AoAs, the receive sounders are designed to estimate AoDs. The dimension of the angle dictionary in each stage can be reduced, which in turn reduces the computational complexity substantially. We then analyze the successful recovery probability (SRP) of the proposed method, revealing the superiority of the proposed framework over the existing one-stage CS-based methods. We further enhance the reconstruction performance by performing resource allocation between the two stages. We also overcome the unresolvable quantization error issue present in the prior techniques by applying the atomic norm minimization method to each stage of the proposed two-stage approach. The simulation results illustrate the substantially improved performance with low complexity of the proposed two-stage method.Comment: Accepted by IEEE Transactions on Communication

Cost-Efficient Millimeter Wave Base Station Deployment in Manhattan-Type Geometry

This work is licensed under a Creative Commons Attribution 4.0 International License.Urban millimeter wave (mmWave) communications are limited by link outage due to frequent blockages by obstacles. One approach to this problem is to increase the density of base stations (BSs) to achieve macro diversity gains. Dense BS deployment, however, incurs the increased BS installation cost as well as power consumption. In this work, we propose a framework for connectivity-constrained minimum cost mmWave BS deployment in Manhattan-type geometry (MTG). A closed-form expression of network connectivity is characterized as a function of various factors such as obstacle sizes, BS transmit power, and the densities of obstacles and BSs. Optimization that attains the minimum cost is made possible by incorporating a tight lower bound of the analyzed connectivity expression. A low-complexity algorithm is devised to effectively find an optimal tradeoff between the BS density and transmit power that results in the minimum BS deployment cost while guaranteeing network connectivity. Numerical simulations corroborate our analysis and quantify the best tradeoff of the BS density and transmit power. The proposed BS deployment strategies are evaluated in different network cost configurations, providing useful insights in mmWave network planning and dimensioning

SIRT1 Activation by Resveratrol Alleviates Cardiac Dysfunction via Mitochondrial Regulation in Diabetic Cardiomyopathy Mice

Background. Diabetic cardiomyopathy (DCM) is a major threat for diabetic patients. Silent information regulator 1 (SIRT1) has a regulatory effect on mitochondrial dynamics, which is associated with DCM pathological changes. Our study aims to investigate whether resveratrol, a SRIT1 activator, could exert a protective effect against DCM. Methods and Results. Cardiac-specific SIRT1 knockout (SIRT1KO) mice were generated using Cre-loxP system. SIRT1KO mice displayed symptoms of DCM, including cardiac hypertrophy and dysfunction, insulin resistance, and abnormal glucose metabolism. DCM and SIRT1KO hearts showed impaired mitochondrial biogenesis and function, while SIRT1 activation by resveratrol reversed this in DCM mice. High glucose caused increased apoptosis, impaired mitochondrial biogenesis, and function in cardiomyocytes, which was alleviated by resveratrol. SIRT1 deletion by both SIRT1KO and shRNA abolished the beneficial effects of resveratrol. Furthermore, the function of SIRT1 is mediated via the deacetylation effect on peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), thus inducing increased expression of nuclear respiratory factor 1 (NRF-1), NRF-2, estrogen-related receptor-α (ERR-α), and mitochondrial transcription factor A (TFAM). Conclusions. Cardiac deletion of SIRT1 caused phenotypes resembling DCM. Activation of SIRT1 by resveratrol ameliorated cardiac injuries in DCM through PGC-1α-mediated mitochondrial regulation. Collectively, SIRT1 may serve as a potential therapeutic target for DCM

Genome-Wide Interaction and Pathway Association Studies for Body Mass Index

Objective: We investigated gene interactions (epistasis) for body mass index (BMI) in a European-American adult female cohort via genome-wide interaction analyses (GWIA) and pathway association analyses.Methods: Genome-wide pairwise interaction analyses were carried out for BMI in 493 extremely obese cases (BMI > 35 kg/m2) and 537 never-overweight controls (BMI < 25 kg/m2). To further validate the results, specific SNPs were selected based on the GWIA results for haplotype-based association studies. Pathway-based association analyses were performed using a modified Gene Set Enrichment Algorithm (GSEA) (GenGen program) to further explore BMI-related pathways using our genome wide association study (GWAS) data set, GIANT, ENGAGE, and DIAGRAM Consortia.Results: The EXOC4-1q23.1 interaction was associated with BMI, with the most significant epistasis between rs7800006 and rs10797020 (P = 2.63 × 10-11). In the pathway-based association analysis, Tob1 pathway showed the most significant association with BMI (empirical P < 0.001, FDR = 0.044, FWER = 0.040). These findings were further validated in different populations.Conclusion: Genome-wide pairwise SNP-SNP interaction and pathway analyses suggest that EXOC4 and TOB1-related pathways may contribute to the development of obesity

A Novel Mechanism of Mesenchymal Stromal Cell-Mediated Protection against Sepsis: Restricting Inflammasome Activation in Macrophages by Increasing Mitophagy and Decreasing Mitochondrial ROS

Sepsis, a systemic inflammatory response to infection, is the leading cause of death in the intensive care unit (ICU). Previous studies indicated that mesenchymal stromal cells (MSCs) might have therapeutic potential against sepsis. The current study was designed to investigate the effects of MSCs on sepsis and the underlying mechanisms focusing on inflammasome activation in macrophages. The results demonstrated that the bone marrow-derived mesenchymal stem cells (BMSCs) significantly increased the survival rate and organ function in cecal ligation and puncture (CLP) mice compared with the control-grouped mice. BMSCs significantly restricted NLRP3 inflammasome activation, suppressed the generation of mitochondrial ROS, and decreased caspase-1 and IL-1β activation when cocultured with bone marrow-derived macrophages (BMDMs), the effects of which could be abolished by Mito-TEMPO. Furthermore, the expression levels of caspase-1, IL-1β, and IL-18 in BMDMs were elevated after treatment with mitophagy inhibitor 3-MA. Thus, BMSCs exert beneficial effects on inhibiting NLRP3 inflammasome activation in macrophages primarily via both enhancing mitophagy and decreasing mitochondrial ROS. These findings suggest that restricting inflammasome activation in macrophages by increasing mitophagy and decreasing mitochondrial ROS might be a crucial mechanism for MSCs to combat sepsis

What Determines the Psychological Well-Being during Commute in Xi’an: The Role of Built Environment, Travel Attitude, and Travel Characteristics

The commute well-being (CWB) has been associated with the mental health and depends on the positive or negative emotions that occur during the daily commute. This paper analyzes the influencing factors and discusses the structural relationship between CWB and influencing factors, based on our evaluation of the results for daily CWB between different travel modes. We based our analyses on a CWB survey conducted in the central city proper of Xi’an. In contrast to previous studies, this paper investigates two commuting phases, in the morning and evening, to better analyze daily CWB. To conduct a more comprehensive analysis, in addition to considering multi-stage combined travel, the subjective and objective aspects of factors influencing CWB were deepened and expanded. The measurement was based on the Satisfaction with Travel Scale, which was developed based on a method for measuring subjective well-being. The average CWB level of each model was compared by analyzing the variances. The influencing factors were determined by stepwise regression, and the influence mechanism was analyzed using a structural equation model (SEM). The results indicate that CWB in Xi’an was highest for walking, which was followed, in order, by motorcycle, electric bicycle, staff shuttle bus, bicycle, metro, car, taxi, and bus. The result reflects that commuting by bus is associated with more negative emotions in Xi’an. The results of SEM indicate that the built environment does not directly affect CWB, but it will act on CWB by affecting other factors. The travel attitude, commute mode choice, and other travel characteristics affect each other and affect CWB directly and indirectly. Other travel characteristics has the largest total effect on CWB, and the travel attitudes have the largest direct effect. Without considering the travel attitude, reducing traffic congestion, commuting time, and transfer times can significantly improve CWB and reduce negative emotions in the future in Xi’an