Compressive Sensing Based Massive Access for IoT Relying on Media Modulation Aided Machine Type Communications

A fundamental challenge of the large-scale Internet-of-Things lies in how to support massive machine-type communications (mMTC). This letter proposes a media modulation based mMTC solution for increasing the throughput, where a massive multi-input multi-output based base station (BS) is used for enhancing the detection performance. For such a mMTC scenario, the reliable active device detection and data decoding pose a serious challenge. By leveraging the sparsity of the uplink access signals of mMTC received at the BS, a compressive sensing based massive access solution is proposed for tackling this challenge. Specifically, we propose a block sparsity adaptive matching pursuit algorithm for detecting the active devices, whereby the block-sparsity of the uplink access signals exhibited across the successive time slots and the structured sparsity of media modulated symbols are exploited for enhancing the detection performance. Moreover, a successive interference cancellation based structured subspace pursuit algorithm is conceived for data demodulation of the active devices, whereby the structured sparsity of media modulation based symbols found in each time slot is exploited for improving the detection performance. Finally, our simulation results verify the superiority of the proposed scheme over state-of-the-art solutions.Comment: submitted to IEEE Transactions on Vehicular Technology [Major Revision

Intravitreous injection of Lucentis combined with argon laser photocoagulation for treatment of retinal macroaneurysm

AIM: To evaluate the clinical efficacy of intravitreous injection of Lucentis combined with argon laser photocoagulation on retinal macroaneurysm.<p>METHODS: A retrospective observation about intravitreous injection of Lucentis combined with argon laser photocoagulation was performed on 9 patients(9 eyes)with retinal macroaneurysms with macular edema between January 2011 and July 2013. Through the collection of clinical data in patients best-corrected visual acuity, change of the retinal macroaneurysm, optical coherence tomography and fluoresce in fundus angiography before therapy and 1 mouth,3 mouths after therapy, comparative analysis the changes in best-corrected visual acuity and central macular retinal thickness(CMT)between before and after treatment.<p>RESULTS: Followed for more than 3 months, all patients' best-corrected visual acuity were improved obviously, the difference was significant(<i>P</i><0.05); The patients' macular edema was obviously absorbed and the average CMT was significantly lower, the difference was significant(<i>P</i><0.05). In fundus fluorescein angiography, the neoplasia body was atrophied inordinately after 3 months of treatment.<p>CONCLUSION:Intravitreous injection of Lucentis combined with argon laser photocoagulation is effective and security to improving visual acuity of retinal macroaneurysms with macular edema

Mutual Information Learned Regressor: an Information-theoretic Viewpoint of Training Regression Systems

As one of the central tasks in machine learning, regression finds lots of applications in different fields. An existing common practice for solving regression problems is the mean square error (MSE) minimization approach or its regularized variants which require prior knowledge about the models. Recently, Yi et al., proposed a mutual information based supervised learning framework where they introduced a label entropy regularization which does not require any prior knowledge. When applied to classification tasks and solved via a stochastic gradient descent (SGD) optimization algorithm, their approach achieved significant improvement over the commonly used cross entropy loss and its variants. However, they did not provide a theoretical convergence analysis of the SGD algorithm for the proposed formulation. Besides, applying the framework to regression tasks is nontrivial due to the potentially infinite support set of the label. In this paper, we investigate the regression under the mutual information based supervised learning framework. We first argue that the MSE minimization approach is equivalent to a conditional entropy learning problem, and then propose a mutual information learning formulation for solving regression problems by using a reparameterization technique. For the proposed formulation, we give the convergence analysis of the SGD algorithm for solving it in practice. Finally, we consider a multi-output regression data model where we derive the generalization performance lower bound in terms of the mutual information associated with the underlying data distribution. The result shows that the high dimensionality can be a bless instead of a curse, which is controlled by a threshold. We hope our work will serve as a good starting point for further research on the mutual information based regression.Comment: 28 pages, 2 figures, presubmitted to AISTATS2023 for reviewin

Compressive Sensing-Based Grant-Free Massive Access for 6G Massive Communication

The advent of the sixth-generation (6G) of wireless communications has given rise to the necessity to connect vast quantities of heterogeneous wireless devices, which requires advanced system capabilities far beyond existing network architectures. In particular, such massive communication has been recognized as a prime driver that can empower the 6G vision of future ubiquitous connectivity, supporting Internet of Human-Machine-Things for which massive access is critical. This paper surveys the most recent advances toward massive access in both academic and industry communities, focusing primarily on the promising compressive sensing-based grant-free massive access paradigm. We first specify the limitations of existing random access schemes and reveal that the practical implementation of massive communication relies on a dramatically different random access paradigm from the current ones mainly designed for human-centric communications. Then, a compressive sensing-based grant-free massive access roadmap is presented, where the evolutions from single-antenna to large-scale antenna array-based base stations, from single-station to cooperative massive multiple-input multiple-output systems, and from unsourced to sourced random access scenarios are detailed. Finally, we discuss the key challenges and open issues to shed light on the potential future research directions of grant-free massive access.Comment: Accepted by IEEE IoT Journa

Na+-induced Ca2+ influx through reverse mode of Na+-Ca2+ exchanger in mouse ventricular cardiomyocyte

BACKGROUND: Dobutamine is commonly used for clinical management of heart failure and its pharmacological effects have long been investigated as inotropics via β-receptor activation. However, there is no electrophysiological evidence if dobutamine contributes inotropic action due at least partially to the reverse mode of Na+-Ca2+ exchanger (NCX) activation. METHODS: Action potential (AP), voltage-gated Na+ (INa), Ca2+ (ICa), and K+ (Ito and IK1) currents were observed using whole-cell patch technique before and after dobutamine in ventricular cardiomyocytes isolated from adult mouse hearts. Another sets of observation were also performed with Kb-r7943 or in the solution without [Ca2+]o. RESULTS: Dobutamine (0.1-1.0 μM) significantly enhanced the AP depolarization with prolongation of AP duration (APD) in a concentration-dependent fashion. The density of INa was also increased concentration-dependently without alternation of voltage-dependent steady-status of activation and inactivation, reactivation as well. Whereas, the activities for ICa, Ito, and IK1 were not changed by dobutamine. Intriguingly, the dobutamine-mediated changes in AP repolarization were abolished by 3 μM Kb-r7943 pretreatment or by simply removing [Ca2+]o without affecting accelerated depolarization. Additionally, the ratio of APD50/APD90 was not significantly altered in the presence of dobutamine, implying that effective refractory period was remain unchanged. CONCLUSIONS: This novel finding provides evidence that dobutamine upregulates of voltage-gated Na+ channel function and Na+ influx-induced activation of the reverse mode of NCX, suggesting that dobutamine may not only accelerate ventricular contraction via fast depolarization but also cause Ca2+ influx, which contributes its positive inotropic effect synergistically with β-receptor activation without increasing the arrhythmogenetic risk

Suppression of Laccase 2 severely impairs cuticle tanning and pathogen resistance during the pupal metamorphosis of Anopheles sinensis (Diptera: Culicidae)

Amino acid sequence identity of Cu-oxidase domains of LAC2 orthologs. (PDF 109 kb