Gender-Specific Differences on the Association of Hypertension with Subclinical Thyroid Dysfunction

© 2019 Jingkai Zhang et al. Objective. Both hypertension and subclinical thyroid dysfunction (STD) have high prevalence and clinical importance, but their relationship is still a matter of debate. We aimed to explore gender-specific difference on the association between hypertension and STD in Chinese. Methods. We recruited 13,380 ostensible healthy participants (8,237 men and 5,143 women). The associations between hypertension and STD were analyzed on a gender-based setting after dividing STD into subclinical hypothyroidism, subclinical hyperthyroidism and further subgrouped euthyroidism. Crude and adjusted odds ratios of STD for hypertension were analyzed by binary logistic regression. Results. An increasing trend of hypertension prevalence was found along with aging in both genders. Yet, higher male hypertension prevalence was found until 65 years, and then it intersected with female hypertension prevalence. Women had significantly higher propensity for STD than men. Yet, in elderly participants, this gender-specific difference became less obvious. We displayed detrimental effects for subclinical hypothyroidism in both genders after multiple-covariate adjustments, yet no such effects were shown for subclinical hyperthyroidism. Moreover, females with subclinical hypothyroidism were more likely to be associated with hypertension than males, and the corresponding odds ratios were 1.619 (

GDR: A Game Algorithm Based on Deep Reinforcement Learning for Ad Hoc Network Routing Optimization

Ad Hoc networks have been widely used in emergency communication tasks. For dynamic characteristics of Ad Hoc networks, problems of node energy limited and unbalanced energy consumption during deployment, we propose a strategy based on game theory and deep reinforcement learning (GDR) to improve the balance of network capabilities and enhance the autonomy of the network topology. The model uses game theory to generate an adaptive topology, adjusts its power according to the average life of the node, helps the node with the shortest life to decrease the power, and prolongs the survival time of the entire network. When the state of the node changes, reinforcement learning is used to automatically generate routing policies to improve the average end-to-end latency of the network. Experiments show that, under the condition of ensuring connectivity, GDR has smaller residual energy variance, longer network lifetime, and lower network delay. The delay of the GDR model is 10.5% higher than that of existing methods on average

A Delay-Optimal Task Scheduling Strategy for Vehicle Edge Computing Based on the Multi-Agent Deep Reinforcement Learning Approach

Cloudlet-based vehicular networks are a promising paradigm to enhance computation services through a distributed computation method, where the vehicle edge computing (VEC) cloudlet are deployed in the vicinity of the vehicle. In order to further improve the computing efficiency and reduce the task processing delay, we present a parallel task scheduling strategy based on the multi-agent deep reinforcement learning (DRL) approach for delay-optimal VEC in vehicular networks, where multiple computation tasks select the target threads in a VEC server to execute the computing tasks. We model the target thread decision of computation tasks as a multi-agent reinforcement learning problem, which is further solved by using a task scheduling algorithm based on multi-agent DRL that is implemented in a distributed manner. The computation tasks, with each selection acting on the target thread acting as an agent, collectively interact with the VEC environment and receive observations with respect to a common reward and learn to reduce the task processing delay by updating the multi-agent deep Q network (MADQN) using the obtained experiences. The experimental results show that the proposed DRL-based scheduling algorithm can achieve significant performance improvement, reducing the task processing delay by 40% and increasing the processing probability of success for computation tasks by more than 30% compared with the traditional task scheduling algorithms

Modeling and Analysis of FeICIC in OFDMA HetNets with Limited Backhaul Capacity

Heterogeneous networks (HetNets) with dense deployment of small cells in co-channel manner are recognized as a key solution to boost network capacity. However, in addition to the severe inter-Tier interference, the non-ideal backhaul is also a bottleneck in improving the performance of HetNets. This paper proposes an analytical model of further-enhanced intercell interference coordination (FeICIC) in orthogonal frequency division multiple access (OFDMA) HetNets with limited backhaul capacity, and further evaluates the performance of HetNets. Stochastic geometry is applied to derive the expression of rate coverage in two-Tier HetNets, while modeling the BS interference in the context of OFDMA. The accuracy of analytical results is validated by Monte Carlo simulation. The superiority of FeICIC for rate coverage of HetNets is demonstrated, and the proper parameter settings are further investigated to provide design guidelines for future dense networks

Computing Offloading Based on TD3 Algorithm in Cache-Assisted Vehicular NOMA–MEC Networks

In this paper, in order to reduce the energy consumption and time of data transmission, the non-orthogonal multiple access (NOMA) and mobile edge caching technologies are jointly considered in mobile edge computing (MEC) networks. As for the cache-assisted vehicular NOMA–MEC networks, a problem of minimizing the energy consumed by vehicles (mobile devices, MDs) is formulated under time and resource constraints, which jointly optimize the computing resource allocation, subchannel selection, device association, offloading and caching decisions. To solve the formulated problem, we develop an effective joint computation offloading and task-caching algorithm based on the twin-delayed deep deterministic policy gradient (TD3) algorithm. Such a TD3-based offloading (TD3O) algorithm includes a designed action transformation (AT) algorithm used for transforming continuous action space into a discrete one. In addition, to solve the formulated problem in a non-iterative manner, an effective heuristic algorithm (HA) is also designed. As for the designed algorithms, we provide some detailed analyses of computation complexity and convergence, and give some meaningful insights through simulation. Simulation results show that the TD3O algorithm could achieve lower local energy consumption than several benchmark algorithms, and HA could achieve lower consumption than the completely offloading algorithm and local execution algorithm

Gender- and Age-Specific Differences in the Association of Hyperuricemia and Hypertension: A Cross-Sectional Study

Objective. Both hyperuricemia and hypertension have important clinical implications, but their relationship in terms of gender and age is still a matter of debate. In this study, we aimed to explore gender- and age-specific differences in this association between hyperuricemia and hypertension in a Chinese population. Methods. A total of 78596 ostensibly healthy subjects (47781 men and 30815 women) were recruited. The association between hyperuricemia and hypertension was analyzed by multivariate logistic regression, and the analyses were stratified by gender and age. Results. Overall prevalence of hypertension and hyperuricemia was significantly higher in males than in females. Increasing trends of hypertension prevalence in both genders as well as hyperuricemia prevalence in females were found along with aging. However, males showed a reduced trend in hyperuricemia prevalence with aging. Higher hypertension and hyperuricemia prevalence was found in young and middle-aged men than in women, but not in elderly people older than 70 years. Significantly increased risk of hypertension from hyperuricemia was found only in men with an adjusted odds ratio of 1.131 (P<0.01), especially in the middle-aged male participants. However, such significant results were not found in women. Similarly, hyperuricemia was also an independent risk factor of increased systolic blood pressure and diastolic blood pressure in males, but not in females. Conclusion. We observed significantly higher overall prevalence of hyperuricemia and hypertension in men than in women. Men with hyperuricemia (particularly in middle age) had a significantly increased susceptibility of hypertension, while this significant association was not observed in women