Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach

Peer-to-peer communication has been recently considered as a popular issue for local area services. An innovative resource allocation scheme is proposed to improve the performance of mobile peer-to-peer, i.e., device-to-device (D2D), communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a reverse iterative combinatorial auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which as bidders compete to obtain business while the packages of the D2D pairs are auctioned off as goods in each auction round. We first formulate the valuation of each resource unit, as a basis of the proposed auction. And then a detailed non-monotonic descending price auction algorithm is explained depending on the utility function that accounts for the channel gain from D2D and the costs for the system. Further, we prove that the proposed auction-based scheme is cheat-proof, and converges in a finite number of iteration rounds. We explain non-monotonicity in the price update process and show lower complexity compared to a traditional combinatorial allocation. The simulation results demonstrate that the algorithm efficiently leads to a good performance on the system sum rate.Comment: 26 pages, 6 fgures; IEEE Journals on Selected Areas in Communications, 201

MiR-138 ameliorates myocardial ischemia/reperfusion injury by targeting intercellular cell adhesion molecule 1

Purpose: To explore the effect of miR-138 on regulating intercellular cell adhesion molecule 1 (ICAM-1) expression in endothelial cells to alleviate cardiac ischemia/reperfusion (I/R) injury and its related mechanisms. Methods: The left anterior descending artery of the heart was occluded for 30 min and then perfused for 2 h to induce a rat model of cardiac I/R injury. H9C2 cells were cultured in an anoxic medium without serum to establish the model of hypoxia/reoxygenation (H/R). Triphenyl tetrazolium chloride (TTC) staining was applied to measure myocardial infarction sizes in rat hearts. The mRNA expression levels of miR-138 and ICAM-1 were evaluated by quantitative real-time polymerase chain reaction (qRT-PCR). Dual luciferase reporter assay was used to identify the target of miR-138. The agomiR-138 and miR-138 mimics were transfected into H9C2 cells; exogenous ICAM-1 was also administered, and ROS accumulation, cell viability, and apoptosis were measured. Furthermore, the underlying mechanism was investigated. Results: MiR-138 was downregulated both in vitro and in vivo. AgomiR-138 reduced myocardial infarction area, decreased ROS production and suppressed cell apoptosis in a rat model of cardiac I/R injury. On the other hand, miR-138 mimics increased cell viability, enhanced ROS production and induced cell apoptosis in H/R-induced H9C2 cells. Further analysis verified ICAM-1 as a target of miR- 138. Besides, exogenous ICAM-1 inhibited the protective effect of miR-138 on H/R-induced apoptosis in vitro. Conclusion: MiR-138 may protect against injury of myocardial I/R by targeting ICAM-1. The results also provide insight into miR-138/ICAM-1 axis as new therapeutic targets for myocardial I/R injury. Keywords: Intercellular cell adhesion molecule 1, MicroRNA-138, Myocardial/ischemia reperfusion injury, Reactive oxygen specie

Fighting Pandemics with Augmented Reality and Smart Sensing-based Social Distancing

In a postpandemic world, remaining vigilant and maintaining social distancing are still crucial so societies can contain the virus and the public can avoid disproportionate health impacts. Augmented reality (AR) can visually assist users in understanding the distances in social distancing. However, integrating external sensing and analysis is required for social distancing beyond the users’ local environment. We present DistAR, an android-based application for social distancing leveraging AR and smart sensing using on-device analysis of optical images and environment crowdedness from smart campus data. Our prototype is one of the first efforts to combine AR and smart sensing technologies to create a real-time social distancing application.Peer reviewe

Mobile Augmented Reality: User Interfaces, Frameworks, and Intelligence

Mobile Augmented Reality (MAR) integrates computer-generated virtual objects with physical environments for mobile devices. MAR systems enable users to interact with MAR devices, such as smartphones and head-worn wearables, and perform seamless transitions from the physical world to a mixed world with digital entities. These MAR systems support user experiences using MAR devices to provide universal access to digital content. Over the past 20 years, several MAR systems have been developed, however, the studies and design of MAR frameworks have not yet been systematically reviewed from the perspective of user-centric design. This article presents the first effort of surveying existing MAR frameworks (count: 37) and further discuss the latest studies on MAR through a top-down approach: (1) MAR applications; (2) MAR visualisation techniques adaptive to user mobility and contexts; (3) systematic evaluation of MAR frameworks, including supported platforms and corresponding features such as tracking, feature extraction, and sensing capabilities; and (4) underlying machine learning approaches supporting intelligent operations within MAR systems. Finally, we summarise the development of emerging research fields and the current state-of-the-art, and discuss the important open challenges and possible theoretical and technical directions. This survey aims to benefit both researchers and MAR system developers alike.Peer reviewe

Diaqua­[5,5′-dicarb­oxy-2,2′-(propane-1,3-di­yl)bis­(1H-imidazole-4-carboxyl­ato)]manganese(II)

The complex mol­ecule of the title compound, [Mn(C13H10N4O8)(H2O)2] or [Mn(H4pbidc)(H2O)2] (H6pbidc = 2,2′-(propane-1,3-di­yl)bis­(1H-imidazole-4,5-dicarb­oxy­lic acid), has 2 symmetry with the twofold rotation axis running through the Mn2+ cation and the central C atom of the propanediyl unit. The cation is six-coordinated by two N atoms and two O atoms from one H4pbidc2− anion and two water O atoms in a considerably distorted octa­hedral coordination. In the crystal, adjacent mol­ecules are linked through O—H⋯O and N—H⋯O hydrogen bonds into a three-dimensional network

Bayesian Inference Federated Learning for Heart Rate Prediction

The advances of sensing and computing technologies pave the way to develop novel applications and services for wearable devices. For example, wearable devices measure heart rate, which accurately reflects the intensity of physical exercise. Therefore, heart rate prediction from wearable devices benefits users with optimization of the training process. Conventionally, Cloud collects user data from wearable devices and conducts inference. However, this paradigm introduces significant privacy concerns. Federated learning is an emerging paradigm that enhances user privacy by remaining the majority of personal data on users’ devices. In this paper, we propose a statistically sound, Bayesian inference federated learning for heart rate prediction with autoregression with exogenous variable (ARX) model. The proposed privacy-preserving method achieves accurate and robust heart rate prediction. To validate our method, we conduct extensive experiments with real-world outdoor running exercise data collected from wearable devices.Peer reviewe