Statistical Channel Modeling for Indoor VLC Communications Based on Channel Measurements

Visible light communication(VLC)has attracted much attention in the research of sixthgeneration(6G)systems.Furthermore,channel modeling is the foundation for designing efficient and robust VLC systems.In this paper,we present extensive VLC channel measurement campaigns in indoor environments,i.e.,an office and a corridor.Based on the measured data,the large-scale fading characteristics and multipath-related characteristics,including omnidirectional optical path loss(OPL),K-factor,power angular spectrum(PAS),angle spread(AS),and clustering characteristics,are analyzed and modeled through a statistical method.Based on the extracted statistics of the above-mentioned channel characteristics,we propose a statistical spatial channel model(SSCM)capable of modeling multipath in the spatial domain.Furthermore,the simulated statistics of the proposed model are compared with the measured statistics.For instance,in the office,the simulated path loss exponent(PLE)and the measured PLE are 1.96and 1.97,respectively.And,the simulated medians of AS and measured medians of AS are 25.94°and 24.84°,respectively.Generally,the fact that the simulated results fit well with measured results has demonstrated the accuracy of our SSCM.

The Spectrum of Kidney Disease in Type Two Diabetic Patients: A Single-Center Study

Background: Diabetic nephropathy (DN) is the dominant reason for end-stage kidney disease linked with a rise in cardiovascular mortality rate. However, besides DN, type 2 diabetic patients may also suffer from various non-diabetic renal diseases (NDRD). Aim: The objective of the current research was to assess the occurrence and type of NDRD diagnosed by kidney biopsy in type 2 diabetic subjects, evaluate the association of various clinical and laboratory characteristics with histopathology findings, and identify essential predictors of NDRD. Methods: Retrospective analysis has been performed through medical record revision of 101 patients with type 2 diabetes undergoing percutaneous renal biopsy at Qilu Hospital of Shandong University (Jinan, China) between January 2015 and December 2020. Results: Renal biopsy results showed that NDRD was found in 59 patients (58.42%), while DN existed in 32 patients (31.68%) and 10 patients (9.90%) showed DN complicated with NDRD. Membranous nephropathy was prevailing NDRD (42%), followed by focal segmental glomerulosclerosis (11.6%) and IgA nephropathy (10.1%). In univariate analysis, patients with NDRD had older age (p Conclusions: Clinical parameters such as short duration of diabetes, older age, higher hemoglobin level, and lower proteinuria might be associated with NDRD in type 2 diabetic patients. An early diagnosis of NDRD poses a favorable renal prognosis because it requires a different approach than DN, further larger multicenter randomized prospective investigations focused on identifying possible risk markers of NDRD are still in priority.

Vision,Requirements and Network Architecture of 6G Mobile Network beyond 2030

With the 5th Generation(5G)Mobile network being rolled out gradually in 2019,the research for the next generation mobile network has been started and targeted for 2030.To pave the way for the development of the 6th Generation(6G)mobile network,the vision and requirements should be identified first for the potential key technology identification and comprehensive system design.This article first identifies the vision of the society development towards 2030 and the new application scenarios for mobile communication,and then the key performance requirements are derived from the service and application perspective.Taken into account the convergence of information technology,communication technology and big data technology,a logical mobile network architecture is proposed to resolve the lessons from 5G network design.To compromise among the cost,capability and flexibility of the network,the features of the 6G mobile network are proposed based on the latest progress and applications of the relevant fields,namely,on-demand fulfillment,lite network,soft network,native AI and native security.Ultimately,the intent of this article is to serve as a basis for stimulating more promising research on 6G.

The SOLIDS 6G Mobile Network Architecture:Driving Forces,Features,and Functional Topology

With the large-scale commercial launch of fifth generation(5G)mobile network,the development of new services and applications catering to the year 2030,along with the deep convergence of information,communication,and data technologies(ICDT),and the lessons and experiences from 5G practice will drive the evolution of the next generation of mobile networks.This article surveys the history and driving forces of the evolution of the mobile network architecture and proposes a logical function architecture for sixth generation(6G)mobile network.The proposed 6G network architecture is termed SOLIDS(related to the following basic features:soft,on-demand fulfillment,lite,native intelligence,digital twin,and native security),which can support self-generation,self-healing,self-evolution,and self-immunity without human involvement and address the primary issues in the legacy 5G network(e.g.,high cost,high power consumption,and highly complicated operation and maintenance),significantly well.

Differentiation of human adipose-derived stem cells into neuron-like cells by Radix Angelicae Sinensis

Human adipose tissues are an ideal source of stem cells. It is important to find inducers that can safely and effectively differentiate stem cells into functional neurons for clinical use. In this study, we investigate the use of Radix Angelicae Sinensis as an inducer of neuronal differentiation. Primary human adipose-derived stem cells were obtained from adult subcutaneous fatty tissue, then pre-induced with 10% Radix Angelicae Sinensis injection for 24 hours, and incubated in serum-free Dulbecco＇s modified Eagle＇s medium/Nutrient Mixture F-12 containing 40% Radix Angelicae Sinensis to induce its differentiation into neuron-like cells. Butylated hydroxyanisole, a common in- ducer for neuronal differentiation, was used as the control. After human adipose-derived stem cells differentiated into neuron-like cells under the induction of Radix Angelicae Sinensis for 24 hours, the positive expression of neuron-specific enolase was lower than that of the butylated hydroxyani- sole-induced group, and the expression of glial fibrillary acidic protein was negative. Alter they were induced for 48 hours, the positive expression of neuron specific enolase in human adipose-derived stem cells was significantly higher than that of the butylated hydroxyanisole-induced group. Our experimental findings indicate that Radix Angelicae Sinensis can induce human adipose-derived stem cell differentiation into neuron-like cells and produce less cytotoxicity.

AI-Enhanced Constellation Design for NOMA System: A Model Driven Method

Grant-free Non-orthogonal Multiple Access(GF-NOMA)is a promising technology for massive access users and sporadic small-packet transmission for Beyond the 5th Generation mobile communication system(B5G)/the 6th Generation mobile communication system(6G).One of the key aspects in GF-NOMA system is the signature/constellation design.However,due to the channel variation and random activation of users,conventional optimization approaches seem unsuitable for such complex models.In this paper,as an initial attempt,we propose a human intelligence(HI)-guided artificial intelligence(AI)-enhanced signature/constellation design method.By separate design of modulation and power allocation inspired by prior knowledge,the proposed deep neuron network(DNN)for NOMA signature/constellation design not only has smaller size of DNN and less training data,but also has stronger interpretability.In the last section,via simulations we demonstrate that in terms of bit error rate,the proposed scheme can achieve significant performance gain over the conventional NOMA schemes.

Propagation Characteristics of Elevation Angles and Three Dimensional Fading Channel Model with Angle Offset

Three dimensional(3D)Multiple Input and Multiple Output(MIMO)is one of the most promising techniques for the 5th generation(5G)mobile communication system.To support its research,the property of elevation angle in 3D channel model should be accurately modeled.Conventionally,3D channel is modeled with an assumption that the mean elevation angle of multipaths is coincided with the line-of-sight(LOS)direction.In order to investigate its authenticity and give the reliable 3D channel model,extensive 3D multiple antenna field channel measurements with 100 MHz bandwidth are conducted in three typical scenarios,including outdoor to indoor(O2I),urban microcell(UMi)and urban macrocell(UMa).The statistical characteristics and parameters are extracted and analyzed based on the measurement data.It is found that the assumption holds in the LOS condition.However,for non-line-of-sight(NLOS)condition,a difference exists between the mean elevation angle and the direction connecting transmitter and receiver,which is defined as the elevation angle offset.Then,the eigenvalue distribution and capacity are compared between the reconstructed 3D channels with and without elevation angle offset.Results show that the performance of 3D channel with angle offset fits the measurement data better whereas that without angle offset is underestimated.

Synaptic and blood-brain barrier structural changes in a rat epilepsy model induced by coriaria lacton Replication experiment with animals

BACKGROUND： Structural and functional synaptic changes, as well as blood-brain barrier （BBB） changes, affect the micro-environment of nervous tissue and excitation, both of which play an important role in epilepsy. OBJECTIVE： To observe synaptic and BBB ultrastructural changes in the motor cortex of a rat epilepsy model induced by coriaria lacton, and to investigate the synaptic and BBB effects on the mechanism of epilepsy. DESIGN： A randomized controlled animal experiment. SETTING： Department of Histology and Embryology, Luzhou Medical College; and Electron Microscopy Laboratory, Luzhou Medical College. MATERIALS： Twenty healthy male Sprague Dawley rats, aged 8 weeks, were chosen for this study. The rats weighed （280 ± 50） g and were supplied by the Experimental Animal Center of Luzhou Medical College. Experimentation was performed in accordance with the ethical guidelines for the use and care of animals. The animals were randomly divided into a control group and an epilepsy group, with 10 rats in each group. METHODS： This study was performed at the Department of Histology and Embryology, and Electron Microscopy Laboratory, Luzhou Medical College between February and December 2006. According to the protocol, the epilepsy group was injected with 10 μ L/100 g coriaria lacton into the lateral ventricles to establish an epileptic model. The control group rats were not administered anything. Eight days after the model was established, all rats were anesthetized with ether. The motor cortex was removed and sectioned into ultrathin sections. Synaptic and BBB ultrastructural changes were observed by electron microscopy. MAIN OUTCOME MEASURES： （1）Structural changes of three different parts of the synapses, synaptic cleft width, postsynaptic density thickness, proportion of perforation synapses, curvature of synaptic interface, and length of active zones. （2）Capillary and BBB changes （endothelium, basement membrane, pericyte, and the astrocyte endfeet）. RESULTS： （1）Curvature of synaptic interface, length of active zones, thickness of postsynaptic density, and percentage of perforation synapses increased significantly. （2）There was significant edema in the endothelium, basement membrane, and the pericyte of the epilepsy group; the electron density of the basement membrane was reduced. CONCLUSION： （1） The coriaria lacton treatment altered synaptic ultrastructure, as well as BBB characteristics, in the epileptic rat model, and also improved synaptic transmission efficiency, as well as BBB permeability; （2）Synaptic and BBB ultrastructural changes might play an important role in the mechanism of epilepsy.

Signal Clipping at Transmitter and Receiver of O-OFDM for VLC under Optical Power Constraint

Visible light communications(VLC)is considered as an effective supplement technology for next-generation(6G)communications due to its abundant spectrum,high power efficiency and easy deployment.Optical orthogonal frequency division multiplexing(O-OFDM)is a common technology to obtain further promotion.In this paper,two typical O-OFDM schemes direct current biased O-OFDM(DCO-OFDM)and asymmetrically clipped O-OFDM(ACO-OFDM)are analyzed in terms of signal clipping at both transmitter and receiver under the constraints of maximum optical power and non-negative optical power.And effective electrical SNR models after signal clipping are proposed and verified by link simulation.Then a noise cancellation scheme is proposed based on received signal clipping and is proved to bring a significant gain for ACO-OFDM.By system simulation,we find that under a certain optical power limitation,most users can achieve above 4 Gbps in indoor scenario when modulation bandwidth of the light emit diode(LED)or laser diode(LD)is 1 GHz.Therefore,it can be expected that the throughput could reach tens Gbps when the LED/LD modulation bandwidth is increased and multiple LEDs/LDs are deployed.

5G Features from Operation Perspective and Fundamental Performance Validation by Field Trial

The fast deployment and penetration of 4 G has cultivated human behaviors on mobile data consumption, leading to explosive growth in mobile traffic and stimulating new requirements on the capabilities of mobile networks. To meet the requirements of mobile networks toward year 2020, the next generation of mobile networks(termed as IMT-2020, or 5 G) is designed to support 100 Mbps–1 Gbps user-experienced data rate, 1 ms radio transmission latency, and 1 million connections per square kilometer. Recalling the vision and requirements of 5 G targeting for commercial launch in 2020, this article overviews the key features of 5 G and compares with those of 4 G, and reports the world first field trials conducted to validate the key performance of 5 G radio interface in 3.5 GHz band. The trial results show that a 1 ms transmission latency and 1 Gbps data rate are achievable.

Optimal therapeutic dose and time window of picroside II in cerebral ischemic injury

A preliminary study from our research group showed that picroside II inhibited neuronal apop- tosis in ischemic penumbra, reduced ischemic volume, and improved neurobehavioral function in rats with cerebral ischemia. The aim of the present study was to validate the neuroprotective effects of picroside II and optimize its therapeutic time window and dose in a rat model of cerebral ischemia. We found that picroside Ⅱ inhibited cell apoptosis and reduced the expression of neuron-specific enolase, a marker of neuronal damage, in rats after cerebral ischemic injury. The optimal treatment time after ischemic injury and dose were determined, respectively, as follows： （1） 2.0 hours and 10 mg/kg according to the results of toluidine blue staining; （2） 1.5 hours and 10 mg/kg according to early apoptotic ratio by flow cytometry; （3） 2.0 hours and 10 mg/kg according to immunohistochemical and western blot analysis; and （4） 1.5 hours and 10 mg/kg according to reverse transcription polymerase chain reaction. The present findings suggest that an intraperitoneal injection of 10 mg/kg picroside II 1.5-2.0 hours after cerebral ischemic injury in rats is the optimal dose and time for therapeutic benefit.

Environment Information-Based Channel Prediction Method Assisted by Graph Neural Network

Recently,whether the channel prediction can be achieved in diverse communication scenarios by directly utilizing the environment information gained lots of attention due to the environment impacting the propagation characteristics of the wireless channel.This paper presents an environment information-based channel prediction(EICP)method for connecting the environment with the channel assisted by the graph neural networks(GNN).Firstly,the effective scatterers(ESs)producing paths and the primary scatterers(PSs)generating single propagation paths are detected by building the scatterercentered communication environment graphs(SCCEGs),which can simultaneously preserve the structure information and highlight the pending scatterer.The GNN-based classification model is implemented to distinguish ESs and PSs from other scatterers.Secondly,large-scale parameters(LSP)and small-scale parameters(SSP)are predicted by employing the GNNs with multi-target architecture and the graphs of detected ESs and PSs.Simulation results show that the average normalized mean squared error(NMSE)of LSP and SSP predictions are 0.12 and 0.008,which outperforms the methods of linear data learning.

Service Scheduling Based on Edge Computing for Power Distribution IoT

With the growing amounts of multi-micro grids,electric vehicles,smart home,smart cities connected to the Power Distribution Internet of Things(PD-IoT)system,greater computing resource and communication bandwidth are required for power distribution.It probably leads to extreme service delay and data congestion when a large number of data and business occur in emergence.This paper presents a service scheduling method based on edge computing to balance the business load of PD-IoT.The architecture,components and functional requirements of the PD-IoT with edge computing platform are proposed.Then,the structure of the service scheduling system is presented.Further,a novel load balancing strategy and ant colony algorithm are investigated in the service scheduling method.The validity of the method is evaluated by simulation tests.Results indicate that the mean load balancing ratio is reduced by 99.16%and the optimized offloading links can be acquired within 1.8 iterations.Computing load of the nodes in edge computing platform can be effectively balanced through the service scheduling.

Micro-Service-Based Radio Access Network

The convergence of information,communication,and data technologies(ICDT)has been identified as one of the developing trends of the sixth generation(6G)network.Service-based architecture(SBA)as one of the promising information technology,has been preliminarily introduced into the fifth generation(5G)core network(CN)and successfully commercialized,which verifies its feasibility and effectiveness.However,SBA mainly focuses on the control plane of CN at present and the SBA-CN user plane is being studied by the industry.In addition to further evolving the SBA-CN,SBA radio access network(RAN)should also be considered to enable an end-toend SBA,so as to meet more comprehensive and extreme requirements of future applications,as well as support fast rollout requirements of RAN devices.

6G移动信息网络架构:从通信到一切皆服务的变迁

5G与大数据、云计算和AI等技术的融合正在赋能千行百业的数字化转型,加速整个社会走向数字化和智慧化.面向2030年,社会发展的愿景将是“数字孪生、智慧泛在”,更加差异化和碎片化的业务场景将对移动通信网络提出全新的挑战,未来网络将从提供信息传输服务,拓展到信息感知、传输、存储、处理、利用等全过程服务,实现从传统通信网络向移动信息网络的重大转变.为了高效实现这一转变,6G网络将通过通信、感知、大数据、计算、AI和安全等多领域技术的跨界融合,实现柔性、按需服务、至简、智慧内生、数字孪生和安全内生的网络设计,带来“按需服务”和“一切皆服务”的范式转变.本文从面向2030年的新应用需求、新技术趋势,以及5G网络面临的问题与挑战出发,分析6G网络发展的三大驱动力,提出6G网络架构的整体设计思路,并设计了“三层六面”6G网络逻辑功能架构和实际部署架构,打造一站式提供通信、感知、计算、AI、大数据和安全等服务的全新能力,全面提升6G网络的业务和场景适应能力,实现面向全行业、全场景、全生态的按需服务,在有效解决5G网络面临的高成本、高功耗、操作和维护难等主要问题的同时,全面赋能“数字孪生、智慧泛在”社会发展愿景的实现.

Altered mitochondria and Bcl-2 expression in the hippocampal CA3 region in a rat model of acute epilepsy

BACKGROUND： Previous studies have shown that the mitochondrial structure and function are damaged in animal models of epilepsy. In addition, the Bcl-2 protein is capable of regulating mitochondrial stability. OBJECTIVE： To observe and validate changes in mitochondrial structure and Bcl-2 expression, and to analyze these characteristics in the hippocampal CA3 region of rat models of epilepsy. DESIGN, TIME AND SETTING： This randomized, controlled, animal experiment was performed at the Laboratory of Electron Microscopy and Department of Histology and Embryology, Luzhou Medical College between 2007 and 2008. MATERIALS： Coriamyrtin was provided by the Pharmacy Factory of West China University of Medical Sciences. The primary and secondary antibodies were provided by Zhongshan Goldenbridge Biotechnology, Beijing. METHODS： A total of 44 adult, male, Sprague Dawley rats were randomly divided into control （n = 11） and epilepsy （n = 33） groups. Rats in the epilepsy group were induced by coriamyrtin （50 μ g/kg）, which was injected into the lateral ventricles. The rats were then observed at 3, 6, and 24 hours after epilepsy induction, with 11 rats at each time point. Epilepsy was not induced in rats from the control group. MAIN OUTCOME MEASURES： Pathological changes in the hippocampal CA3 region were observed by light microscopy; Bcl-2 expression was analyzed by immunohistochemistry; and mitochondrial changes in the hippocampus were observed under transmission electron microscopy. RESULTS： （1） The control group displayed very little Bcl-2 protein expression in the hippocampal CA3 region. However, after 3 hours of epilepsy, expression was visible. By 6 hours, expression peaked and then subsequently decreased after 24 hours, but remained higher than the control group （P 〈 0.05）. （2） Mitochondria were damaged to varying degrees in the epilepsy groups. For example, mitochondria edema, cristae space increase, and disappearance of mitochondria were apparent. Moreover, mitochondrial damage occurred prior to pathological changes in the neurons and nucleolus. CONCLUSION： Bcl-2 expression and mitochondrial damage increased in the hippocampal CA3 region in rats with epilepsy. Moreover, mitochondrial damage occurred prior to increased Bcl-2 expression and nucleolus damage.

Cloud-Assisted Distributed Edge Brains for Multi-Cell Joint Beamforming Optimization for 6G

In 5G networks,optimization of antenna beam weights of base stations has become the key application of AI for network optimization.For 6G,higher frequency bands and much denser cells are expected,and the importance of automatic and accurate beamforming assisted by AI will become more prominent.In existing network,servers are“patched”to network equipment to act as a centralized brain for model training and inference leading to high transmission overhead,large inference latency and potential risks of data security.Decentralized architectures have been proposed to achieve flexible parameter configuration and fast local response,but it is inefficient in collecting and sharing global information among base stations.In this paper,we propose a novel solution based on a collaborative cloud edge architecture for multi-cell joint beamforming optimization.We analyze the performance and costs of the proposed solution with two other architectural solutions by simulation.Compared with the centralized solution,our solution improves prediction accuracy by 24.66%,and reduces storage cost by 83.82%.Compared with the decentralized solution,our solution improves prediction accuracy by 68.26%,and improves coverage performance by 0.4 dB.At last,the future research work is prospected.

Frequency-angle two-dimensional reflection coefficient modeling based on terahertz channel measurement

Terahertz(THz)channel propagation characteristics are vital for the design,evaluation,and optimization of THz communication systems.Moreover,reflection plays a significant role in channel propagation.In this correspondence,the reflection coefficients of the THz channel are researched based on extensive measurement campaigns.

Dynamic user-centric multi-dimensional resource allocation for a wide-area coverage signaling cell based on DQN

The rapid development of communications industry has spawned more new services and applications.The sixth-generation wireless communication system(6G)network is faced with more stringent and diverse requirements.While ensuring performance requirements,such as high data rate and low latency,the problem of high energy consumption in the fifth-generation wireless communication system(5G)network has also become one of the problems to be solved in 6G.The wide-area coverage signaling cell technology conforms to the future development trend of radio access networks,and has the advantages of reducing network energy consumption and improving resource utilization.In wide-area coverage signaling cells,on-demand multi-dimensional resource allocation is an important technical means to ensure the ultimate performance requirements of users,and its effect will affect the efficiency of network resource utilization.This paper constructs a user-centric dynamic allocation model of wireless resources,and proposes a deep Q-network based dynamic resource allocation algorithm.The algorithm can realize dynamic and flexible admission control and multi-dimensional resource allocation in wide-area coverage signaling cells according to the data rate and latency demands of users.According to the simulation results,the proposed algorithm can effectively improve the average user experience on a long time scale,and ensure network users a high data rate and low energy consumption.