A Hybrid Integrated and Low-Cost Multi-Chip Broadband Doherty Power Amplifier Module for 5G Massive MIMO Application

In this paper,a hybrid integrated broadband Doherty power amplifier(DPA)based on a multi-chip module(MCM),whose active devices are fabricated using the gallium nitride(GaN)process and whose passive circuits are fabricated using the gallium arsenide(GaAs)integrated passive device(IPD)process,is proposed for 5G massive multiple-input multiple-output(MIMO)application.An inverted DPA structure with a low-Q output network is proposed to achieve better bandwidth performance,and a single-driver architecture is adopted for a chip with high gain and small area.The proposed DPA has a bandwidth of 4.4-5.0 GHz that can achieve a saturation of more than 45.0 dBm.The gain compression from 37 dBm to saturation power is less than 4 dB,and the average power-added efficiency(PAE)is 36.3%with an 8.5 dB peak-to-average power ratio(PAPR)in 4.5-5.0 GHz.The measured adjacent channel power ratio(ACPR)is better than50 dBc after digital predistortion(DPD),exhibiting satisfactory linearity.

Homological properties of modules characterized by matrices

Some homological properties of R-modules were investigated by matrices over aring R. Given two cardinal numbers α, β and an α x β row-finite matrix A, it was proved thatExt_R^1(R^((α))/R^((β))A, M) = 0 if and only if M_α/r_(M_α)(R^((β))A) ≈ Hom_R(R^((β))A,M) ifand only if r_(M_β)l_(R^((β)))(A) = AM_α. Thus, the notion of (m,n)-injectivity was extended.Moreover, ( α, β) -flatness was characterized via annihilators of matrices, factorizations ofhomomorphisms as well as homological groups so that (m, n)-flat modules, f-projective modules andn-projective modules were consolidated under the notion of (α, β)-flat modules. Furthermore, acharacterization of left R-ML modules and some equivalent conditions for R^((β)) to be left R-MLwere presented. Consequently, the notions of coherent rings, (m, n)-coherent rings and π-coherentrings were consolidated under that of (α, β)-coherent rings.

A New Characterization on g-frames in Hilbert C^*-Modules

In this note, we establish a new characterization on g-frames in Hilbert C;-modules from the operator-theoretic point of view, with which we provide a correction to one result recently obtained by Yao(Yao X Y. Some properties of g-frames in Hilbert C;-modules（in Chinese）. Acta Math. Sinica, 2011, 54（1）: 1–8.).

Group Action on Fuzzy Modules

In this article, we introduce the notion of fuzzy G-module by defining the group action of G on a fuzzy set of a Z-module M. We establish the cases in which fuzzy submodules also become fuzzy G-submodules. Notions of a fuzzy prime submodule, fuzzy prime G-submodule, fuzzy semi prime submodule, fuzzy G-semi prime submodule, G-invariant fuzzy submodule and G-invariant fuzzy prime submodule of M are introduced and their properties are described. The homomorphic image and pre-image of fuzzy G-submodules, G-invariant fuzzy submodules and G-invariant fuzzy prime submodules of M are also established.

Penrose Transform on Induced <i>D_G/H</i>-Modules and Their Moduli Stacks in the Field Theory

We consider generalizations of the Radon-Schmid transform on coherent DG/H-Modules, with the intention of obtaining the equivalence between geometric objects (vector bundles) and algebraic objects (D-Modules) characterizing conformal classes in the space-time that determine a space moduli [1] on coherent sheaves for the securing solutions in field theory [2]. In a major context, elements of derived categories like D-branes and heterotic strings are considered, and using the geometric Langlands program, a moduli space is obtained of equivalence between certain geometrical pictures (non-conformal world sheets [3]) and physical stacks (derived sheaves), that establishes equivalence between certain theories of super symmetries of field of a Penrose transform that generalizes the implications given by the Langlands program. With it we obtain extensions of a cohomology of integrals for a major class of field equations to corresponding Hecke category.

Relatively Injective Modules with Respect to Torsion Theory

For a hereditary torsion theory τ, this paper mainly discuss properties of A-τ-injective modules, where A is a fixed left R-module. It is proved that if M is an A-τ-injective, B is a submodule of A, then 1） M is A/B-τ-injective; 2） M is B-τ-injective when B is τ-dense in A. Furthermore, we show that if A1,A2,... An, are relatively injective modules, then A1 A2 ... An is self-τ-injective if and only if A1 is self-τ-injective for each i.

Beyond the 100 Gbaud directly modulated laser for short reach applications

It is very attractive to apply a directly modulated laser(DML)-based intensity-modulation and direct-detection(IM/DD)system in future data centers and 5G fronthaul networks due to the advantages of low cost,low system complexity,and high energy efficiency,which perfectly match the application scenarios of the data centers and 5G fronthaul networks,in which a large number of high-speed optical interconnections are needed.However,as the data traffic in the data centers and 5G fronthaul networks continues to grow exponentially,the future requirements for data rates beyond 100 Gbaud are challenging the existing DML-based IM/DD system,and the main bottleneck is the modulation bandwidth of the DML.In this paper,the data rate demands and technical standards of the data centers and 5G fronthaul networks are reviewed in detail.With the modulation bandwidth requirements,the technical routes and achievements of recent DMLs are reviewed and discussed.In this way,the prospects,challenges,and future development of DMLs in the applications of future data centers and 5G fronthaul networks are comprehensively explored.

Automatic Classification of Superimposed Modulations for 5G MIMO Two-Way Cognitive Relay Networks

To promote reliable and secure communications in the cognitive radio network,the automatic modulation classification algorithms have been mainly proposed to estimate a single modulation.In this paper,we address the classification of superimposed modulations dedicated to 5G multipleinput multiple-output(MIMO)two-way cognitive relay network in realistic channels modeled with Nakagami-m distribution.Our purpose consists of classifying pairs of users modulations from superimposed signals.To achieve this goal,we apply the higher-order statistics in conjunction with the Multi-BoostAB classifier.We use several efficiency metrics including the true positive(TP)rate,false positive(FP)rate,precision,recall,F-Measure and receiver operating characteristic(ROC)area in order to evaluate the performance of the proposed algorithm in terms of correct superimposed modulations classification.Computer simulations prove that our proposal allows obtaining a good probability of classification for ten superimposed modulations at a low signal-to-noise ratio,including the worst case(i.e.,m=0.5),where the fading distribution follows a one-sided Gaussian distribution.We also carry out a comparative study between our proposal usingMultiBoostAB classifier with the decision tree(J48)classifier.Simulation results show that the performance of MultiBoostAB on the superimposed modulations classifications outperforms the one of J48 classifier.In addition,we study the impact of the symbols number,path loss exponent and relay position on the performance of the proposed automatic classification superimposed modulations in terms of probability of correct classification.

Design, Synthesis and Biological Evaluation of 2-Aroyl-3-aryl-6,7-dihydro-5H-furo[3,2-g]chromen Derivatives as a Novel Series of Estrogen Receptor Modulators

Based on the principles of the bioisosterism, combination of the active substructures of selective estrogen receptor modulators which are currently therapeutic agents available for the prevention and treatment of various estrogen dependent diseases, and structural optimization, a novel series of 2-aroyl-3-aryl-6,7-dihydro-5H-furo[3,2-g]- chromen derivatives was designed as potent selective estrogen receptor modulators via molecular docking. The target compounds have been synthesized, and characterized by 1R, proton NMR, ESI-MS, elemental analysis and evaluated for their antitumor activity against human osteosarcoma U2OS-EGFP-4FI2G cell line. Some target compounds showed good inhibition effects on U2OS-EGFP-4F12G cell line and the preliminary structure-activity relationships were discussed.

Functionally diverse ligands modulate different activation states of the formyl peptide receptor 2,a G protein-coupled receptor

OBJECTIVE To identify the mechanisms by which the formyl peptide receptor 2(FPR2)mediates both inflammatory and anti-inflammatory signaling in an agonist-dependent manner.METHODS Cells expressing FPR2 were incubated with weak agonists,Aβ42 and Ac2-26,before stimulation with a strong agonist,WKYMVm.Calcium mobilization,c AMP inhibition and MAP kinase activation were measured.Intramolecular FRET were determined using FPR2 constructs with an ECFP attached to the C-terminus and a Fl As H binding motif embedded in the first or third intracellular loop(IL1 or IL3,respectively).RESULTS Aβ42 did not induce significant Ca^(2+) mobilization,but positively modulated WKYMVm-induced Ca^(2+) mobilization and c AMP reduction in a dose-variable manner within a narrow range of ligand concentrations.Treating FPR2-expressing cells with Ac2-26,a peptide with anti-inflammatory activity,negatively modulated WKYMVm-induced Ca^(2+) mobilization and c AMP reduction.Intramolecular FRET assay showed that stimulation of the receptor constructs with Aβ42 brought the C-terminal domain closer to IL1 but away from IL3.An opposite conformational change was induced by Ac2-26.The FPR2 conformation induced by Aβ42 corresponded to enhanced ERK phosphorylation and attenuated p38 MAPK phosphorylation,whereas Ac2-26 induced FPR2 conformational change corresponding to elevated p38 MAPK phosphorylation and reduced ERK phosphorylation.CONCLUSION Aβ42 and Ac2-26 induce different conformational changes in FPR2.These findings provide a structural basis for FPR2 mediation of inflammatory vs anti-inflammatory functions and identify a type of receptor modulation that differs from the classic positive and negative allosteric modulation.

G protein-coupled receptor 37(GPR37) emerges as an important modulator of adenosinergic transmission in the striatum

G protein-coupled receptor 37 (GPR37), also known as parkin associated endothelin-like (Pael) receptor, is an orphan G protein- coupled receptor, which suffers a defective parking ubiquitination in autosomal recessive Parkinson’s disease promoting its endoplasmic reticulum aggregation and stress, neurotoxicity and neuronal death (Takahashi and Imai, 2003). Interestingly, we have demonstrated previously that GPR37 heteromerizes with adenosine A2A receptor (A2AR) in the striatum (Morato et al., 2017;Sokolina et al., 2017).

Intelligent Modulation Recognition of Communication Signal for Next-Generation 6G Networks

In recent years,the need for a fast,efficient and a reliable wireless network has increased dramatically.Numerous 5G networks have already been tested while a few are in the early stages of deployment.In noncooperative communication scenarios,the recognition of digital signal modulations assists people in identifying the communication targets and ensures an effective management over them.The recent advancements in both Machine Learning(ML)and Deep Learning(DL)models demand the development of effective modulation recognition models with self-learning capability.In this background,the current research article designs aDeep Learning enabled Intelligent Modulation Recognition of Communication Signal(DLIMR-CS)technique for next-generation networks.The aim of the proposed DLIMR-CS technique is to classify different kinds of digitally-modulated signals.In addition,the fractal feature extraction process is appliedwith the help of the Sevcik Fractal Dimension(SFD)approach.Then,the extracted features are fed into the Deep Variational Autoencoder(DVAE)model for the classification of the modulated signals.In order to improve the classification performance of the DVAE model,the Tunicate Swarm Algorithm(TSA)is used to finetune the hyperparameters involved in DVAE model.A wide range of simulations was conducted to establish the enhanced performance of the proposed DLIMR-CS model.The experimental outcomes confirmed the superior recognition rate of the DLIMR-CS model over recent state-of-the-art methods under different evaluation parameters.

GPSM2在肿瘤中作用机制的研究进展

G蛋白信号调节蛋白2(GPSM2)是一种G蛋白偶联受体信号通路的负性调节剂,在肝癌、胰腺癌、乳腺癌等中为促癌因子,在肺癌中为抑癌因子。在肿瘤细胞中,GPSM2不仅可以作用于细胞周期,影响有丝分裂,还间接作用于EGFR-AKT/ERK、PI3K/AKT、PBK/TOPK等多种信号通路,影响癌细胞增殖和迁移。GPSM2可作为多种肿瘤诊断、治疗和预后的潜在指标,有望成为肿瘤治疗新靶点。

Analysis on unit maximum capacity of orthogonal multiple watermarking for multimedia signals in B5G wireless communications

Beyond-5G(B5G)aims to meet the growing demands of mobile traffic and expand the communication space.Considering that intelligent applications to B5G wireless communications will involve security issues regarding user data and operational data,this paper analyzes the maximum capacity of the multi-watermarking method for multimedia signal hiding as a means of alleviating the information security problem of B5G.The multiwatermarking process employs spread transform dither modulation.During the watermarking procedure,Gram-Schmidt orthogonalization is used to obtain the multiple spreading vectors.Consequently,multiple watermarks can be simultaneously embedded into the same position of a multimedia signal.Moreover,the multiple watermarks can be extracted without affecting one another during the extraction process.We analyze the effect of the size of the spreading vector on the unit maximum capacity,and consequently derive the theoretical relationship between the size of the spreading vector and the unit maximum capacity.A number of experiments are conducted to determine the optimal parameter values for maximum robustness on the premise of high capacity and good imperceptibility.

肝癌组织中GPSM2、TGF-β1蛋白表达水平及临床意义

目的 探讨肝癌组织G蛋白信号调节蛋白(GPSM)2、转化生长因子1(TGF-β1)蛋白表达与临床病理参数及预后的关系。方法 选取原发性肝癌患者80例,取手术切除的肝癌组织和癌旁正常组织。采用免疫组织化学染色法检测GPSM2、TGF-β1在癌组织和癌旁正常组织中的表达差异,分析癌组织中GPSM2、TGF-β1表达水平与临床病理参数及预后的关系。结果 肝癌组织中GPSM2、TGF-β1高表达率分别为71.25%、82.50%,高于癌旁正常组织的18.75%、13.75%(P<0.05)。GPSM2在分化程度低的肝癌组织中高表达率较高(P<0.05),TGF-β1在分化程度低、有血管转移的肝癌组织中高表达率较高(P<0.05)。生存曲线显示,GPSM2、TGF-β1低表达患者的累积生存率(77.27%、85.71%)高于高表达患者(47.37%、48.48%),差异具有统计学意义(P<0.05)。结论 GPSM2、TGF-β1在肝癌组织中高表达率较高,其表达水平与分化程度密切相关,GPSM2、TGF-β1高表达患者预后较差。

Hilbert C^(*)-模中g-Riesz基的对偶性

本文研究Hilbert C^(*)-模中g-Riesz基的对偶性问题.利用算子理论方法,获得了Hilbert C^(*)-模中的给定序列是g-Riesz基且有唯一对偶g-框架的充要条件,g-Riesz基的对偶g-框架是g-Riesz基的充要条件,以及g-Riesz基成为无冗g-框架的充分条件,所得结果进一步展示了g-框架理论在Hilbert C^(*)-模与Hilbert空间中的差异性.

Gorenstein FP∞-Injective Modules and w-Noetherian Ring

We study some homological properties of Gorenstein FP∞-injective modules,and we prove(1)a ring R is not necessarily coherent if every Gorenstein FP∞-injective R-module is injective,and(2)a ring R is not necessarily coherent if every Gorenstein injective R-module is injective.In addition,we characterize w-Noetherian rings in terms of Gorenstein FP∞-injective modules,and we prove that a ring R is w-Noetherian if and only if every GV-torsion-free FP∞-injective R-module is Gorenstein FP∞-injective,if and only if any direct sum of GV-torsion-free FP∞-injective R-modules is Gorenstein FP∞-injective.

G-morphic模

利用模的自投射及生成核的性质给出了左R模为G-morphic模等价于其自同态环为左G-morphic环的条件,并利用此结论证明了G-morphic模有类似于G-morphic环的性质:在一定条件下G-morphic模的直积因子也为G-morphic模,从而在一定程度上反映了G-morphic模与G-morphic环的联系.

基于g-h坐标系SVPWM算法三电平PWM整流器的研究

介绍了三相三电平二极管中点钳位型PWM整流器电路拓扑。详细分析了空间矢量脉宽调制(SVPWM)的基本原理,针对传统的复杂SVPWM算法,分析了一种基于g-h坐标系的简化SVPWM算法。这种方法在矢量选取和作用时间计算方面进行了简化,避免了大量三角函数的运算,可以应用到三电平及多电平SVPWM算法中。最后在Matlab仿真环境中建立了三相三电平PWM整流器的电压定向控制系统(VOC)的仿真模型,对三电平g-h坐标系SVPWM算法进行了仿真研究,仿真结果验证了该算法的有效性。

G蛋白信号调节蛋白2在胰腺癌组织中的表达及临床意义

目的：探讨G蛋白信号调节蛋白2（G-protein signaling modulator 2,GPSM2）基因在胰腺癌组织中的表达及其临床意义。方法：选取54例胰腺癌患者临床石蜡样本制作组织芯片,利用免疫组化检测GPSM2在胰腺癌组织中的表达并分析GPSM2的表达与患者临床病理参数及预后的关系;另选取同期10例新鲜胰腺癌标本及配对的癌旁组织,采用实时RT-PCR法和蛋白质印迹法检测GPSM2 mRNA和蛋白的表达水平。结果：胰腺癌组织GPSM2 mRNA及蛋白的表达均明显高于配对的癌旁组织（P均〈0.05）。组织芯片检测结果显示,与配对的癌旁组织比较,胰腺癌组织中GPSM2表达明显上调（P〈0.05）,其高表达（40例）比例达74.1%。GPSM2的表达与患者的肿瘤T分期、TNM分期、分化程度相关：T分期越差（χ2=12.654,P〈0.01）,TNM分期越高（χ2=16.610,P〈0.01）,肿瘤分化程度越差（χ2=10.355,P〈0.01）,其GPSM2表达水平越高。生存分析表明,GPSM2高表达患者的中位生存期明显低于低表达患者（P〈0.05）。结论：胰腺癌组织GPSM2过表达,其表达与患者的肿瘤T分期、TNM分期、肿瘤分化程度相关,且与胰腺癌的预后有一定相关性。