Spatial Modulation-Based Ambient Backscatter: Bringing Energy Self-Sustainability to Massive Internet of Everything in 6G

Ambient backscatter communications(AmBC)is a new ultra-low-power communication paradigm,which holds great promise for enabling energy self-sustainability(ESS)to massive data-intensive Internet of Everything(IoE)devices in 6G.Recent advances improve throughput and reliability by adopting multiple-antenna techniques in conventional backscatter communications(CoBC),but they cannot be directly applied to AmBC devices for high spectral and energy efficiency due to the unknown RF source and minimalist design in backscatter tag.To fill this gap,we propose SM-backscatter,an AmBC-compatible system that greatly improves spectral efficiency while maintaining ultra-low-power consumption.Specifically,the SM-backscatter consists of two novel components:i)a multiple-antenna backscatter tag that adopts spatial modulation(SM),and ii)a joint detection algorithm that detects both backscatter and source signals.To this end,we theoretically obtain an optimal detector and propose two suboptimal detectors with low complexity.Subsequently,we derive the BERs of both the backscatter and source signals to analyze the communication performance by introducing a two-step algorithm.Our simulation results verify the correctness of the theoretical analysis and indicate that our system can significantly outperform existing solutions.

Pervasive intelligent endogenous 6G wireless systems:Prospects,theories and key technologies

The worldwide large-scale commercial deployment of 5G has commenced in 2020 for supporting enhanced Mobile BroadBand(eMBB),ultra-Reliable and Low-Latency Communications(uRLLC),and massive Machine-Type Communications(mMTC)services.Nevertheless,the upsurge of Artificial Intelligence(AI)-powered applications,the developmental law of one-decade-one-generation of wireless communications and the inherent limitations of 5G have also been spurring the industry and academia to dedicate their efforts to the research of future 6G wireless systems.6G will be a disruptive,pervasive,intelligent,and endogenous wireless system,which will revolutionize all walks of life and accelerate the transformation and innovation of the global society.In this paper,we present a forward-looking,comprehensive and in-depth analysis and technical identification of 6G.Specifically,we firstly introduce the fundamental theories of 6G in terms of potential requirements.Then,we focus our attention on the discussion of promising key technologies in terms of spectrum,air interface,delay,access,energy consumption,coverage,AI,electromagnetism,interaction,etc.

The Relationship Between Neuroimmunity and Bipolar Disorder:Mechanism and Translational Application

Neuroimmune system may be involved in the pathological process of bipolar disorder(BD),but the essential association is not fully understood.Accumulating evidence has shown that BD involves the activation of immune cells and the release of inflammatory substances in the central nerve system(CNS).Meanwhile,neuroimmune responses also interact with other hypothesis of the etiology of BD that are widely recognized,such as neurotransmitter systems,neuroendocrine systems,neurotrophic factors,and oxidative stress.Simultaneously,related genes and immune changes in peripheral blood vary with it.Overall,neuroimmunity may play an important role in the pathogenesis of BD,and the inflammatory cytokines,especially interleukin-6 and tumor necrosis factor-alpha,have potential value for the clinical diagnosis and prognosis of BD,as well as predicting the therapeutic effects of drugs.Large-scale studies are needed to extend the evidence on neuroimmunity in BD,and to examine its clinical value for applications such as early prediction and treatment.

Hypothalamic-Pituitary-End-Organ Axes:Hormone Function in Female Patients with Major Depressive Disorder

Classic hypothalamic-pituitary-end-organ feedback loops–the hypothalamic-pituitary-adrenal axis(HPAA),hypothalamic-pituitary-thyroidal axis(HPTA),and hypothalamic-pituitary-gonadal axis(HPGA)–are associated with the neuroendocrine and immune systems in major depressive disorder(MDD).Female patients with MDD present with evident neuroendocrine and immunological changes.Glucocorticoid,thyroid hormone,and reproductive steroid levels fluctuate with menstrual cycles,which might lead to glucocorticoid receptor resistance,impairment of triiodothyronine conversion,and sex hormone secretion disorders.In this review,we summarize the independent and interactive functions of these three axes in female MDD patients.The similar molecular structure of steroids implies an interrelationship between the hypothalamic-pituitary-end-organ axes and the competitive inhibitory effects at the receptor level,especially when considering the HPAA and HPGA.

Early Diagnosis of Bipolar Disorder Coming Soon:Application of an Oxidative Stress Injury Biomarker(BIOS)Model

Early distinction of bipolar disorder(BD)from major depressive disorder(MDD)is difficult since no tools are available to estimate the risk of BD.In this study,we aimed to develop and validate a model of oxidative stress injury for predicting BD.Data were collected from 1252 BD and 1359 MDD patients,including 64 MDD patients identified as converting to BD from 2009 through 2018.30 variables from a randomly-selected subsample of 1827(70%)patients were used to develop the model,including age,sex,oxidative stress markers(uric acid,bilirubin,albumin,and prealbumin),sex hormones,cytokines,thyroid and liver function,and glycolipid metabolism.Univariate analyses and the Least Absolute Shrinkage and Selection Operator were applied for data dimension reduction and variable selection.Multivariable logistic regression was used to construct a model for predicting bipolar disorder by oxidative stress biomarkers(BIOS)on a nomogram.Internal validation was assessed in the remaining 784 patients(30%),and independent external validation was done with data from 3797 matched patients from five other hospitals in China.10 predictors,mainly oxidative stress markers,were shown on the nomogram.The BIOS model showed good discrimination in the training sample,with an AUC of 75.1%(95%CI:72.9%–77.3%),sensitivity of 0.66,and specificity of 0.73.The discrimination was good both in internal validation(AUC 72.1%,68.6%–75.6%)and external validation(AUC 65.7%,63.9%–67.5%).In this study,we developed a nomogram centered on oxidative stress injury,which could help in the individualized prediction of BD.For better real-world practice,a set of measurements,especially on oxidative stress markers,should be emphasized using big data in psychiatry.