面向6G的无线通信信道特性分析与建模

针对6G全覆盖、全频谱、全应用的发展愿景,对面向6G的全频谱全场景无线信道测量、信道特性与信道模型方面的进展进行了全面概述,侧重于毫米波、太赫兹、光波段、卫星、无人机、海洋、水声、高铁、车对车、大规模/超大规模天线、轨道角动量以及工业物联网等通信信道,并展示了6G信道的相关测量与建模结果。最后,指出了6G无线信道测量与建模研究的未来挑战。

癌症患者内外向性格测验的初步报告

此研究采用心理测验测试 1982年北京部分癌症患者与正常对照者内外向性格的特点。结果是上述两组之间无显著性差别 ( 0 .10 >P>0 .0 5 )

Radio Propagation and Wireless Coverage of LSAA-Based 5G Millimeter-Wave Mobile Communication Systems

Millimeter-wave(mm Wave) communications will be used in fifth-generation(5G) mobile communication systems, but they experience severe path loss and have high sensitivity to physical objects, leading to smaller cell radii and complicated network architectures. A coverage extension scheme using large-scale antenna arrays(LSAAs) has been suggested and theoretically proven to be cost-efficient in combination with ultradense small cell networks. To analyze and optimize the LSAA-based network deployments, a comprehensive survey of recent advances in statistical mmWave channel modeling is first presented in terms of channel parameter estimation, large-scale path loss models, and small-scale cluster models. Next, the measurement and modeling results at two 5G candidate mmWave bands(e.g., 28 GHz and 39 GHz) are reviewed and compared in several outdoor scenarios of interest, where the propagation characteristics make crucial contributions to wireless network designs. Finally, the coverage behaviors of systems employing a large number of antenna arrays are discussed, as well as some implications on future mmWave cellular network designs.

Machine-Learning-Assisted Optimization and Its Application to Antenna Designs: Opportunities and Challenges

With the rapid development of modern wireless communications and radar, antennas and arrays are becoming more complex, therein having, e.g., more degrees of design freedom, integration and fabrication constraints and design objectives. While fullwave electromagnetic simulation can be very accurate and therefore essential to the design process, it is also very time consuming, which leads to many challenges for antenna design, optimization and sensitivity analysis(SA). Recently, machine-learning-assisted optimization(MLAO) has been widely introduced to accelerate the design process of antennas and arrays. Machine learning(ML) methods, including Gaussian process regression, support vector machine(SVM) and artificial neural networks(ANNs), have been applied to build surrogate models of antennas to achieve fast response prediction. With the help of these ML methods, various MLAO algorithms have been proposed for different applications. A comprehensive survey of recent advances in ML methods for antenna modeling is first presented. Then, algorithms for ML-assisted antenna design, including optimization and SA, are reviewed. Finally, some challenges facing future MLAO for antenna design are discussed.

Action potential-simulated weak electric fields can directly initiate myelination

BACKGROUND： Myelination is a process whereby glial cells identify, adhere, wrap and enclose axons to form a spiral myelin sheath. OBJECTIVE： To investigate the effects of action potential-simulated weak electric fields on myelination in the central nervous system. DESIGN AND SETTING： This single-sample observation study was performed at the 324 Hospital of Chinese PLA. MATERIALS： Two 5 μm carbon fibers were provided by the Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. One Sprague Dawley rat, aged 1 day, was used. METHODS： Cerebral cortex was harvested from the rat to prepare a suspension [（1 2）× 10^5/mL] containing neurons and glial cells. To simulate the axon, carbon fibers were placed at the bottom of the neuron-glial cell coculture dish, and were electrified with a single phase square wave current, 1×10^-2, 1×10^-3, 1×10^-4, and 1×10^-5 seconds, 1 Hz, 40 mV, and 10 μA, 30 minutes each, once a day for 10 consecutive days to simulate weak negative electric fields during action potential conduction. MAIN OUTCOME MEASURES： Glial cell growth and wrapping of carbon fibers were observed by phase contrast microscopy and immunohistochemistry. RESULTS： On culture day 7, cell groups were found to adhere to negative carbon fibers in the 1 × 10^-3 seconds square wave group. Cell membrane-like substances grew out of cell groups, wrapped the carbon fibers, and stretched to the ends of carbon fibers. Only some small and round cells close to negative carbon fibers were found on culture day 12. In the 1 × 10^-4 and 1 × 10^-3 seconds square wave groups, the negative carbon fibers were wrapped by oligodendrocytes or their progenitor cells. CONCLUSION： The local negative electric field which is generated by action potentials at 1×（10^-4-10^-3） seconds, 40 mV can directly initiate and participate in myelination in the central nervous system.

Zinc influences on brain development, pituitary and thyroid function in iodine-deficient pregnant and neonatal rats

BACKGROUND： Zinc （Zn） has been shown to greatly influence brain development. Zn supplements may reduce injury to cell membranes of the thyroid gland due to iodine deficiency. OBJECTIVE： To establish an iodine deficiency rat model using low-iodine food, which was supplemented with compound Zn and Zn gluconate, to observe the effects of Zn on brain development, as well as pituitary gland and thyroid gland function in iodine-deficient rats. DESIGN, TIME AND SETTING： Randomized grouping study of neural development was performed in the central laboratory of Shandong Institute for Prevention and Treatment of Endemic Disease from 1998 to 1999. MATERIALS： A total of 270 Wistar, female rats, one month after weaning, were used in this study, including 150 pregnant and 120 neonatal rats. Rats were randomly divided into six groups： normal control, model, iodine, compound Zn, iodine and compound Zn, and zinc gluconate. Each group contained 25 pregnant rats and 20 neonatal rats. METHODS： The pregnant rats and 20 neonatal rats, and well as the normal group, were fed standard chow and allowed free access to tap water （containing 5 u g/L iodine and 1 mg/L Zn）. The remaining five groups were fed low-iodine chow. However, the model group received distilled water, the iodine group received potassium-iodide distilled water （containing 300 u g/L iodine）, the compound Zn group received distilled water and intragastrically administrated 10 mL/kg compound Zn solution, once per day, the iodine and compound Zn group received distilled water with 300 u g/L iodine and intragastrically administrated 10 mL/kg compound Zn solution, once per day. All treatments lasted 90 days. MAIN OUTCOME MEASURES： All pregnant rats were sacrificed on the day 21 of pregnancy. Body mass number and rate of fetal absorption, as well as fetal death and malformation, were determined. Thyroid and pituitary gland weights were measured, as well as serum levels of thyroid hormone, gonadotropin, and sex hormones. In the experimental study of neonatal rats, the animals normally gave birth at day 21. At day 45 after birth of the neonatal rats, thyroid and pituitary gland weights were measured, and protein, DNA, and RNA concentrations were measured. RESULTS： Pregnant rats in the iodine group exhibited decreased urine iodine and body mass （F = 7.37, P 〈 0.01 ）, increased thyroid absolute and relative weight （F= 7.01, 50.27, P 〈 0.01）, as well as decreased T4 and FF4 （F = 7.01, 29.32, P 〈 0.01 ） and increased T3 and VI＇3 （F = 41.20, 5.94, P 〈 0.01）. Gonadotropic and sexual hormones were abnormal. The pregnant rats displayed decreased weight gain, and the rates of malformation, dead, and absorbed fetuses were increased. Compared with the control group, the neonatal rats with iodine deficiency exhibited lower brain weights （P 〈 0.01 ）. Brain protein, DNA, and RNA, concentrations were decreased, with a rate of RNA/DNA （F = 5.70, 55.86, 25.65, 5.44, P 〈 0.01）. Body mass was gradually increased （F= 6.74, P 〈 0.01）, and the thyroid glands were enlarged （F= 50.01, 76.13, P 〈 0.01）. Following Zn administration, thyroid gland weight was decreased in pregnant rats （P 〈 0.01 ）. Thyroid hormone, gonadotropic hormones, and sexual hormones were restored to some degree. Fetal weight was increased, and the rates of malformation, dead, and absorbed fetuses were decreased. At the same time, neonatal rats gained body weight, displayed decreased thyroid gland weight, as well as increased protein, DNA, and RNA concentrations in the brain. The ratio of RNA/DNA and protein/DNA increased following Zn administration （P 〈 0.01 ）. CONCLUSION： Zn supplementation may decrease the degree of goiter, ameliorate thyroid hormone disorder, as well as gonadotropic and sexual hormone disorders, and increase protein, DNA, and RNA content. Zn supplementation antagonized reproductive abnormalities in pregnant rats, decreased fetal growth,and disturbed brain development in neonatal rats as a result of iodine deficiency.

Ensemble-transfer-learning-based channel parameter prediction in asymmetric massive MIMO systems

Asymmetric massive multiple-input multiple-output(MIMO)systems have been proposed to reduce the burden of data processing and hardware cost in sixth-generation mobile networks(6G).However,in the asymmetric massive MIMO system,reciprocity between the uplink(UL)and downlink(DL)wireless channels is not valid.As a result,pilots are required to be sent by both the base station(BS)and user equipment(UE)to predict doubledirectional channels,which consumes more transmission and computational resources.In this paper we propose an ensemble-transfer-learning-based channel parameter prediction method for asymmetric massive MIMO systems.It can predict multiple DL channel parameters including path loss(PL),multipath number,delay spread(DS),and angular spread.Both the UL channel parameters and environment features are chosen to predict the DL parameters.Also,we propose a two-step feature selection algorithm based on the SHapley Additive exPlanations(SHAP)value and the minimum description length(MDL)criterion to reduce the computation complexity and negative impact on model accuracy caused by weakly correlated or uncorrelated features.In addition,the instance transfer method is introduced to support the prediction model in new propagation conditions,where it is difficult to collect enough training data in a short time.Simulation results show that the proposed method is more accurate than the back propagation neural network(BPNN)and the 3GPP TR 38.901 channel model.Additionally,the proposed instancetransfer-based method outperforms the method without transfer learning in predicting DL parameters when the beamwidth or the communication sector changes.

The frontier of microplastics and nanoplastics: Soil health and carbon neutrality

Microplastics and nanoplastics(MNPs)in soil have drawn increasing concerns about their potential threats to soil ecosystems due to their ubiquitous occurrence and persistence.The interactions of MNPs with soil components,microbial community,plants,and fauna determine their impacts on soil biogeochemical processes and food security.However,they are not largely explored.Further research is also needed to develop reliable and standardized techniques and methods to characterize the relevant MNPs interacting with different types of soil ecosystems and to deeply examine their impacts on soil health,food security,and climate changes.In addition,mitigation protocols and regulation guidelines need to be developed.New findings will provide scientific and technological support for the understanding and management of soil health and carbon neutrality as influenced by MNPs.

Research on practical power system stability analysis algorithm based on modified SVM

Stable and safe operation of power grids is an important guarantee for economy development.Support Vector Machine(SVM)based stability analysis method is a significant method started in the last century.However,the SVM method has several drawbacks,e.g.low accuracy around the hyperplane and heavy computational burden when dealing with large amount of data.To tackle the above problems of the SVM model,the algorithm proposed in this paper is optimized from three aspects.Firstly,the gray area of the SVM model is judged by the probability output and the corresponding samples are processed.Therefore the clustering of the samples in the gray area is improved.The problem of low accuracy in the training of the SVM model in the gray area is improved,while the size of the sample is reduced and the efficiency is improved.Finally,by adjusting the model of the penalty factor in the SVM model after the clustering of the samples,the number of samples with unstable states being misjudged as stable is reduced.Test results on the IEEE 118-bus test system verify the proposed method.

Direct load control by distributed imperialist competitive algorithm

Demand side management techniques have drawn significant attentions along with the development of smart grid.This paper proposes a new direct load control(DLC)model for scheduling interruptible air conditioner loads.The model is coordinated with the unit commitment and economic dispatch to minimize the total operation cost over the whole dispatch horizon.The network constraints are also considered in the model.To ensure the thermal comfort of the occupants,we are among the first to incorporate the advanced two-parameter thermal inertia dynamical model of customer houses into the DLC model to calculate the indoor temperature variation.This paper also proposes a distributed imperialist competitive algorithm to effectively solve the model.The simulation studies prove the efficiency of the proposed methodology.

Optimization method for dynamics of non-holonomic system based on Gauss’ principle

The real-time control of the non-holonomic wheel robot has put forward higher requirements for the accuracy and speed of dynamical simulation,so it is necessary to study the new dynamic modeling and calculation methods adapting to modern information processingtechnology.Different from the traditional method solving differential-algebraic equation,the objective is to establish optimization model and effective calculating scheme for dynamics of non-holonomic system based on basic dynamical principle.The optimization model cannot be obtained directly from the traditional Gauss'principle.By using Gauss'principle of variational form,this paper deduces the minimum principle in the form of generalized coordinates and quasi-coordinates,respectively,thus allowing dynamical problems of non-holonomic systems to be incorporated into the framework of solving constrained or unconstrained optimization problems.Furthermore,we study a numerical calculation scheme that uses an optimization algorithm for the second form of the above optimization models.As an example,the dynamical problem of a differential-driven wheeled mobile-robot system is discussed.The optimization dynamic model of a non-holonomic robot system and the calculation model of the optimization algorithm are established.Comparing theresults of the optimization calculation with the differential-algebraic equations commonly used in dynamical problem for non-holonomic system reveals that the method in this paper is superior in terms of calculation speed and can more effectively handle constraint violations without extra constraint revision needed.

Pathogenesis of premature coronary artery disease:Focus on risk factors and genetic variants

The development of premature coronary artery disease(PCAD)is dependent on both genetic predisposition and traditional risk factors.Strategies for unraveling the genetic basis of PCAD have evolved with the advent of modern technologies.Genome-wide association studies(GWASs)have identified a considerable number of common genetic variants that are associated with PCAD.Most of these genetic variants are attributable to lipid and blood pressure-related single-nucleotide polymorphisms(SNPs).The genetic variants that predispose individuals to developing PCAD may depend on race and ethnicity.Some characteristic genetic variants have been identified in Chinese populations.Although translating this genetic knowledge into clinical applications is still challenging,these genetic variants can be used for CAD phenotype identification,genetic prediction and therapy.In this article we will provide a comprehensive review of genetic variants detected by GWASs that are predicted to contribute to the development of PCAD.We will highlight recent findings regarding CAD-related genetic variants in Chinese populations and discuss the potential clinical utility of genetic variants for preventing and managing PCAD.

Multiple-Sized Amphiphilic Janus Gold Nanoparticles by Ligand Exchange at Toluene/Water Interface

Amphiphilic Janus gold nanoparticles （GNPs） are prospected to encapsulate drug molecules in cancer therapy and to serve as heterogeneous catalysts at oil/water interfaces, where Janus GNPs with differ- ent sizes are required. In this work, multiple-sized precursor GNPs were synthesized by seeded growth method protected with tris（hydroxymethyl）phosphine oxide （THPO） ligand molecule, and a ligand ex- change reaction with triphenylphosphine （PPh3） at the toluene/water interface was employed to prepare amphiphilic Janus GNPs. UV-vis and transmission electron microscopy （TEM） analyses indicate that the as-prepared GNPs are nanocrystals with average diameters of 2.3 nm, 9.5 nm, 16.1 nm and 18.8 nm, re- spectively. Contact angle, Raman and X-ray photonic spectroscopy （XPS） analyses reveal that the self- assembled GNP films exhibit hydrophilic on one side and hydrophobic on another, owing to the adsorption of hydrophilic ligands （THPO and THP） and a similar amount of hydrophobic ligands （PPh3 and PPh30）. Angle-resolved XPS analysis further demonstrates that the individual GNPs actually possess hydro- philic and hydmphobic compartments on the surface, which regularly packed by supramolecular interactions at toluene/water interface to form the self-assembled GNP films.

Thin Film Assembly of Gold Nanoparticles for Vapor Sensing via Droplet Interfacial Reaction

A facile approach to prepare a thin film vapor sensor is demonstrated through droplet interracial reaction on an IDA microelectrode. Scanning electron microscopy, atomic force microscopy and transmission electron microscopy analyses show that the film of the vapor sensor is composed of self-assembled gold nanocrystals in an average diameter of about 4.3 nm. The as-prepared sensor was examined by potential step method and impedance measurement, which exhibited significant △R/Ri responses and excellent cycle performance to the volatile organic compound （VOC） vapors of acetone, methanol, styrene, benzene, toluene and ethanol. The selectivity to the VOCs with benzene ring or organic solvents suggests that the sensor is probably in line with the swelling and dielectric sensing mechanisms.

Synergistic protection of Si anode based on multi-dimensional graphitic carbon skeletons

Inspired by the natural corn structure,a Si@hollow graphene shell@graphene(Si@GS@G)anode material was prepared in which silicon nanoparticles were preliminarily anchored onto the surface of an elastic graphene shell and further constrained using graphene sheets.Hollow graphene oxide shells with abundant surficial hydrogen bonds,which were synthesized using a novel bottom-up method,were used as an intermediate material to anchor positively charged silicon nanoparticles via electrostatic attraction and achieve a rational spatial distribution.The inner hollow graphene shell anchorage and outer graphene constraint synergistically constituted a porous and robust conductive corn-like structure.The as-fabricated Si@GS@G anode afforded efficient electron and ion transport pathways and improved structural stability,thereby enhancing Li+storage capability(505 mAh·g^(−1)at 10 A·g^(−1))and extending the lifespan compared to the single hollow graphene shell or graphene sheet-protected Si anode(72%capacity retention after 500 cycles).The improved kinetics of the Si@GS@G anode were investigated using electro impedance spectroscopy,galvanostatic intermittent titration,and pseudocapacitance contribution rate analysis,and the structural evolution was analyzed using ex situ electron microscopy.This study proposes a novel hollow graphene oxide shell as an activated intermediate material for designing a porous electrode structure that facilitates an enhanced electrochemical performance.

Radio propagationmeasurement and cluster-based analysis formillimeter-wave cellular systems in dense urban environments

The deployment of millimeter-wave(mmWave)cellular systems in dense urban environments with an acceptable coverage and cost-efficient transmission scheme is essential for the rollout of fifth-generation and beyond technology.In this paper,cluster-based analysis of mmWave channel characteristics in two typical dense urban environments is performed.First,radio propagation measurement campaigns are conducted in two identified mmWave bands of 28 and 39 GHz in a central business district and a dense residential area.The customdesigned channel sounder supports high-efficiency directional scanning sounding,which helps collect sufficient data for statistical channel modeling.Next,using an improved auto-clustering algorithm,multipath clusters and their scattering sources are identified.An appropriate measure for inter-and intra-cluster characteristics is provided,which includes the cluster number,the Ricean K-factor,root-mean-squared(RMS)delay spread,RMS angular spread,and their correlations.Comparisons of these parameters across two mmWave bands for both line-of-sight(LoS)and non-light-of-sight(NLoS)links are given.To shed light on the blockage effects,detailed analysis of the propagation mechanisms corresponding to each NLoS cluster is provided,including reflection from exterior walls and diffraction over building corners and rooftops.Finally,the results show that the cluster-based analysis takes full advantage of mmWave beamspace channel characteristics and has further implications for the design and deployment of mmWave wireless networks.

石墨烯空心球的弹性缓冲效应助力高性能硅基锂离子电池

硅被认为是下一代锂离子电池极具潜力的负极材料.纳米硅的使用缓解了其在锂化时因体积变化引起的颗粒粉碎化.然而,团聚的硅颗粒间的相互挤压仍然会引起硅负极的迅速失效.为此,我们以弹性的石墨烯空心球为媒介在硅粒子之间引入机械缓冲空间,来灵活缓冲硅的体积变化,保持电极结构的稳定性.在锂化过程中,硅体积膨胀产生的应力通过压缩石墨烯空心球的内部空心得到了机械式的缓冲.除此之外,石墨烯空心球还减少了硅颗粒的局部团聚,有效地提高了整体电导率.基于这些优势,所设计的Si/GS电极在0.8 A g^(-1)的电流密度下循环200圈后性能仍维持在1200 mA hg^(-1)以上;在4 A g^(-1)的电流密度下,200次循环后仍可达到1025 mA h g^(-1).

High-throughput millimeter-wave wireless communications

Mobile communication is a fundamental element of information flow in modem society.The fifthgeneration mobile communication system(5G)has recently entered commercial use.Simultaneously,the evolution of 5G and the development of sixthgeneration mobile communication system(6G)are becoming hot topics of research in both academic and industrial circles.