An Intelligent Admission Control Scheme for Dynamic Slice Handover Policy in 5G Network Slicing

5G use cases,for example enhanced mobile broadband(eMBB),massive machine-type communications(mMTC),and an ultra-reliable low latency communication(URLLC),need a network architecture capable of sustaining stringent latency and bandwidth requirements;thus,it should be extremely flexible and dynamic.Slicing enables service providers to develop various network slice architectures.As users travel from one coverage region to another area,the callmust be routed to a slice thatmeets the same or different expectations.This research aims to develop and evaluate an algorithm to make handover decisions appearing in 5G sliced networks.Rules of thumb which indicates the accuracy regarding the training data classification schemes within machine learning should be considered for validation and selection of the appropriate machine learning strategies.Therefore,this study discusses the network model’s design and implementation of self-optimization Fuzzy Qlearning of the decision-making algorithm for slice handover.The algorithm’s performance is assessed by means of connection-level metrics considering the Quality of Service(QoS),specifically the probability of the new call to be blocked and the probability of a handoff call being dropped.Hence,within the network model,the call admission control(AC)method is modeled by leveraging supervised learning algorithm as prior knowledge of additional capacity.Moreover,to mitigate high complexity,the integration of fuzzy logic as well as Fuzzy Q-Learning is used to discretize state and the corresponding action spaces.The results generated from our proposal surpass the traditional methods without the use of supervised learning and fuzzy-Q learning.

基于SLICE模型的东台“三医”协同发展和治理实践分析

医疗、医保、医药协同发展和治理是实现卫生健康事业高质量发展和深化医药卫生体制改革的关键。剖析总结了江苏省东台市医疗、医保、医药协同发展和治理改革在战略设计(导航仪)、组织领导(引擎机)、资源统合(燃料箱)、协同工具(润滑剂)和评估反馈(晴雨表)全闭环方面的经验举措,提炼为“三医”协同发展和治理的SLICE模型,并提出在坚持以改革创新激发“三医”协同发展和治理活力的基础上,充分发挥各级党委、政府的主导作用,建立“三医”协同发展和治理跨部门议事协调机制,吸纳多元主体参与协同治理并强化协同治理措施的系统性,以确保“三医”协同发展和治理改革行稳致远。

Strengthening network slicing for Industrial Internet with deep reinforcement learning

Industrial Internet combines the industrial system with Internet connectivity to build a new manufacturing and service system covering the entire industry chain and value chain.Its highly heterogeneous network structure and diversified application requirements call for the applying of network slicing technology.Guaranteeing robust network slicing is essential for Industrial Internet,but it faces the challenge of complex slice topologies caused by the intricate interaction relationships among Network Functions(NFs)composing the slice.Existing works have not concerned the strengthening problem of industrial network slicing regarding its complex network properties.Towards this end,we aim to study this issue by intelligently selecting a subset of most valuable NFs with the minimum cost to satisfy the strengthening requirements.State-of-the-art AlphaGo series of algorithms and the advanced graph neural network technology are combined to build the solution.Simulation results demonstrate the superior performance of our scheme compared to the benchmark schemes.

Resource Allocation for Cognitive Network Slicing in PD-SCMA System Based on Two-Way Deep Reinforcement Learning

In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay mode.Secondary users(SUs)in the cognitive network are multiplexed by a new Power Domain Sparse Code Multiple Access(PD-SCMA)scheme,and the physical resources of the cognitive base station are virtualized into two types of slices:enhanced mobile broadband(eMBB)slice and ultrareliable low latency communication(URLLC)slice.We design the Double Deep Q Network(DDQN)network output the optimal codebook assignment scheme and simultaneously use the Deep Deterministic Policy Gradient(DDPG)network output the optimal power allocation scheme.The objective is to jointly optimize the spectral efficiency of the system and the Quality of Service(QoS)of SUs.Simulation results show that the proposed algorithm outperforms the CNDDQN algorithm and modified JEERA algorithm in terms of spectral efficiency and QoS satisfaction.Additionally,compared with the Power Domain Non-orthogonal Multiple Access(PD-NOMA)slices and the Sparse Code Multiple Access(SCMA)slices,the PD-SCMA slices can dramatically enhance spectral efficiency and increase the number of accessible users.

DNA Extraction from Formalin-fixed and Paraffin-embedded Tissues by Triton X-100 for Effective Amplification of EGFR Gene by Polymerase Chain Reaction

For first-line non-small-cell lung cancer（NSCLC） therapy,detecting mutation status of the epidermal growth factor receptor（EGFR） gene constitutes a prudent test to identify patients who are most likely to benefit from EGFR-tyrosine kinase inhibitor（TKI） therapy.Now,the material for detecting EGFR gene mutation status mainly comes from formalin-fixed and paraffin-embedded（FFPE） tissues.DNA extraction from FFPE and the amplification of EGFR gene by polymerase chain reaction（PCR） are two key steps for detecting EGFR gene mutation.We showed a simple method of DNA extraction from FFPE tissues for the effective amplification of EGFR gene.Extracting DNA from the FFPE tissues of NSCLC patients with 1% Triton X-100（pH=10.0） was performed by heating at 95 °C for 30 min.Meanwhile,a commercial kit was used to extract DNA from the same FFPE tissues of NSCLC patients for comparison.DNA extracted products were used as template for amplifying the exons 18,19,20 and 21 of EGFR by PCR for different amplified fragments.Results show that DNA fragment size extracted from FFPE tissues with 1% Triton X was about 250―500 base pairs（bp）.However,DNA fragment size extracted from FFPE tissues via commercial kit was about from several hundreds to several thousands bp.The DNA yield extracted from FFPE tissues with 1% Triton X was larger than that via commercial kit.For about 500 bp fragment,four exons of EGFR could not be amplified more efficiently from extracted DNA with 1% Triton X than with commercial kit.However,for about 200 bp fragment.This simple and non-laborious protocol could successfully be used to extract DNA from FFPE tissue for the amplification of EGFR gene by PCR,further screening of EGFR gene mutation and facilitating the molecular analysis of a large number of FFPE tissues from NSCLC patients.

User Scheduling and Slicing Resource Allocation in Industrial Internet of Things

Heterogeneous base station deployment enables to provide high capacity and wide area coverage.Network slicing makes it possible to allocate wireless resource for heterogeneous services on demand.These two promising technologies contribute to the unprecedented service in 5G.We establish a multiservice heterogeneous network model,which aims to raise the transmission rate under the delay constraints for active control terminals,and optimize the energy efficiency for passive network terminals.A policygradient-based deep reinforcement learning algorithm is proposed to make decisions on user association and power control in the continuous action space.Simulation results indicate the good convergence of the algorithm,and higher reward is obtained compared with other baselines.

Rapid diagnosis of disseminated Mycobacterium mucogenicum infection in formalin-fixed, paraffin-embedded specimen using nextgeneration sequencing: A case report

BACKGROUND Mycobacterium mucogenicum(M.mucogenicum)belongs to the group of rapidly growing Nontuberculous mycobacteria.This microorganism is associated with a wide spectrum of infectious diseases.Due to a low detection rate or the time required for conventional culture methodology,a rapid and broad-spectrum method is necessary to identify rare pathogens.CASE SUMMARY A 12-year-old immunocompetent girl presented with painful masses for five months.The first mass was found in the right upper quadrant of the abdomen,and was about 1 cm×1.5 cm in size,tough but pliable in texture,with an irregular margin and tenderness.An abscess gradually formed and ulcerated with suppuration of the mass.Three new masses appeared on the back one by one.Chest computed tomography showed patchy and streaky cloudy opacities in both lungs.Needle aspiration of the abscess was performed,but the smear and conventional culture were negative,and the pathological examination showed no pathogens.We then performed next-generation sequencing using a formalinfixed,paraffin-embedded specimen to identify the pathogen.A significantly high abundance of M.mucogenicum was detected.The patient’s abscesses gradually decreased in size,while inflammation in both lungs improved following 12-wk of treatment.No recurrence was observed four months after the end of the one-year treatment period.CONCLUSION Next-generation sequencing is a promising tool for the rapid and accurate diagnosis of rare pathogens,even when using a formalin-fixed,paraffin-embedded specimen.

Trefoil Factor 3 (TFF3) mRNA Expression Level in Follicular Thyroid Tumors Using Formalin-Fixed, Paraffin-Embedded (FFPE) Blocks

Background: Differential diagnosis of follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA) is often difficult since presence or absence of capsular/vascular invasion can not be determined by preoperative fine needle aspiration cytology, and may not be judged unanimously on permanent sections even among experienced pathologists. Determination of molecular-genetic factors such as trefoil factor 3 (TFF3) mRNA in the follicular thyroid tumors may be useful aid to improve the accuracy of diagnosis, though it is considered to be unstable and relatively low concentrated genetic substance. Purpose of our study is to investigate expression level of TFF3 mRNA of thyroid follicular tumors using formalin-fixed, paraffin-embedded (FFPE) tissue. Methods: Study population included FFPE sections from 19 FTC cases, 20 FTA cases, 11 adenomatous goiter (G) cases and 12 samples of normal thyroid tissue (N) adjacent to thyroid tumors. RNeasy FFPE kit was used for extraction of total RNA. Purification and concentration values were determined by spectrophotometer. Extracted RNA was used for cDNA synthesis in reverse transcription. Synthesized cDNA subsequently proceeded for relative quantification of TFF3 mRNA by RT-qPCR using TFF3 primers. Glyceroldehyde-3-phosphate dehydrogenase (GAPDH) and hypoxanthin phosphorobosyltransferase1 (HPRT1) were used as control genes. The mean and standard deviation of TFF3 mRNA expression level were analyzed by software Multiplate RQ. Results: Extraction by the FFPE kit yielded high concentration of RNA in all cases. Purification values were 1.8 in average. Concentration values were significantly higher in FTC and FTA relative to G and N tissues, possibly due to high density of thyrocytes in the samples. Relative quantification of TFF3 mRNA expression level showed broad ranges both in FTC and FTA, while the analyses in G and N tissues indicated narrow ranges. Conclusion: FFPE tissues from thyroid follicular tumors can be used for measurement of unstable and low concentrated genetic substances such as TFF3 mRNA. Its diagnostic value yet remains to be determined.

QUATERNIONIC SLICE REGULAR FUNCTIONS AND QUATERNIONIC LAPLACE TRANSFORMS

The functions studied in the paper are the quaternion-valued functions of a quaternionic variable.It is shown that the left slice regular functions and right slice regular functions are related by a particular involution,and that the intrinsic slice regular functions play a central role in the theory of slice regular functions.The relation between left slice regular functions,right slice regular functions and intrinsic slice regular functions is revealed.As an application,the classical Laplace transform is generalized naturally to quaternions in two different ways,which transform a quaternion-valued function of a real variable to a left or right slice regular function.The usual properties of the classical Laplace transforms are generalized to quaternionic Laplace transforms.

Opportunistic admission and resource allocation for slicing enhanced IoT networks

Network slicing is envisioned as one of the key techniques to meet the extremely diversified service requirements of the Internet of Things(IoT)as it provides an enhanced user experience and elastic resource configuration.In the context of slicing enhanced IoT networks,both the Service Provider(SP)and Infrastructure Provider(InP)face challenges of ensuring efficient slice construction and high profit in dynamic environments.These challenges arise from randomly generated and departed slice requests from end-users,uncertain resource availability,and multidimensional resource allocation.Admission and resource allocation for distinct demands of slice requests are the key issues in addressing these challenges and should be handled effectively in dynamic environments.To this end,we propose an Opportunistic Admission and Resource allocation(OAR)policy to deal with the issues of random slicing requests,uncertain resource availability,and heterogeneous multi-resources.The key idea of OAR is to allow the SP to decide whether to accept slice requests immediately or defer them according to the load and price of resources.To cope with the random slice requests and uncertain resource availability,we formulated this issue as a Markov Decision Process(MDP)to obtain the optimal admission policy,with the aim of maximizing the system reward.Furthermore,the buyer-seller game theory approach was adopted to realize the optimal resource allocation,while motivating each SP and InP to maximize their rewards.Our numerical results show that the proposed OAR policy can make reasonable decisions effectively and steadily,and outperforms the baseline schemes in terms of the system reward.

智能电网中基于二分图匹配的网络切片资源分配算法

为了解决智能电网中多类业务的服务质量需求难以同时得到满足的问题并兼顾电力终端和网络侧经济效用,提出了一种基于二分图匹配的网络切片资源分配算法。针对智能电网场景中的控制类和采集类业务,为电力终端分别制定相应的投标信息,并据此计算支付价格和效用矩阵;将网络切片与电力终端之间的资源分配建模为二分图匹配问题,根据不同业务的时延、传输速率或能耗需求,向终端分配不同的切片资源以最大化系统效用。仿真结果表明,相较于已有的双向拍卖算法和贪心算法,所提算法能够提高10%~20%的系统效用。

RedCap部署策略建议

RedCap作为轻量级5G技术,是蜂窝物联网的重要演进方向,它可有效兼顾行业对技术性能和部署成本的双重需求,有助于加速5G技术融入千行百业。分析了RedCap关键特性、基本通信功能要求、产业生态及应用场景等,提出RedCap部署策略及网络、业务规划建议,推动蜂窝物联网持续向端网协同方向发展和演进。

采用MSCT灌注成像检查评估周围型非小细胞肺癌分化程度的可行性分析

目的分析多层螺旋CT(MSCT)灌注成像检查评估周围型非小细胞肺癌(NSCLC)分化程度的可行性。方法选取本院2017年7月至2018年10月本院收治确诊的52例周围型NSCLC患者作为研究对象,比较不同分化级别患者的MSCT灌注成像参数;分析灌注参数与分化程度的相关性。结果高分化、中分化周围型NSCLC患者BF、BV、PS、MTT及PH数值均高于低分化周围型NSCLC,以高分化周围型NSCLC的BF、BV、PS、MTT及PH数值最高。各个灌注参数值,其中高分化、中分化周围型NSCLC的BF、PH与低分化周围型NSCLC比较差异显著(P<0.05),三者BV、PS及MTT数值比较,均为明显差异(P>0.05)。周围型NSCLC患者灌注参数BF、PH与其分化程度成负相关,且相关性显著(P<0.05)。结论MSCT灌注成像检查可有效反映周围型NSCLC的分化程度,其灌注参数中BF、PH对评估其分化程度有一定帮助,与周围型NSCLC分化程度具有一定相关性。

基于瓦片合并的影像快速切片技术研究

随着遥感影像质量提升和更新频率的加快,传统方式切片计算能力受限,为满足影像快速切片的需求,该文借鉴并行计算的思路,设计实现一套瓦片并行切片和基于瓦片合并的影像快速切片算法。从实验结果来看切片效率得到明显提升,有效解决单机切片效率低下的问题。

同时多层成像技术用于弥散张量成像评估脑胶质瘤

目的探讨同时多层成像(SMS)技术用于弥散张量成像(DTI)评估脑胶质瘤的价值。方法前瞻性对34例脑胶质瘤患者采集颅脑常规DTI及SMS-DTI,对比2种图像质量主观评分、信噪比(SNR)及对比度信噪比(CNR),以及基于2种图像所获全脑纤维束数及肿瘤相对各向异性分数(rFA)和平均扩散率(rMD)。结果34例中,23例为高级别、11例为低级别胶质瘤。SMS-DTI整体图像质量、显示肿瘤边缘清晰度和磁敏感伪影主观评分与常规DTI差异均无统计学意义(P均>0.05),而其SNR、CNR均低于常规DTI(P均<0.05);基于SMS-DTI所获不同病理分级脑胶质瘤患者全脑纤维束数及肿瘤rFA和rMD与常规DTI差异均无统计学意义(P均>0.05)。结论SMS技术用于DTI评估脑胶质瘤可在保证图像质量及定量分析结果准确性的前提下有效缩短采集时间。

烫漂预处理对苹果干燥过程中微观结构及质构品质的影响

为提高烫漂预处理后苹果片的热风干燥效率和品质,本研究系统评估了热水烫漂与真空蒸汽脉动烫漂两种预处理方法对苹果片的宏观干燥效果。研究结果表明,在真空度0.07 MPa、烫漂2次和烫漂时间3 min条件下真空蒸汽脉动烫漂预处理提升了苹果片的复水比和质构品质,同时缩短了干燥时间。通过石蜡切片、显微观测、图像处理等技术对两种预处理方法干燥的苹果片微观结构进行研究,对比分析在不同烫漂条件(热水烫漂:温度和时间;真空蒸汽脉动烫漂:真空度、次数和时间)下苹果片的细胞横截面面积、周长、当量直径、细胞圆度、壁面粗糙度因子和孔隙率的变化规律。结果显示,随着漂烫温度的升高、时间的延长和烫漂次数的增加,苹果片的细胞会产生使后续干燥过程中水分加速蒸发的变化,从而缩短干燥时间。此外,通过多项式拟合建立了微观结构参数与复水比之间的关系方程。研究结果可为揭示真空蒸汽脉动烫漂预处理对苹果微观结构和宏观品质影响的机理提供理论依据。

基于5G+V2X的融合组网车路协同系统

随着5G通信技术的发展,传统的基于PC5接口方式的车联网系统在时延和可靠性等方面,性能指标无法匹配车联网系统快速发展的要求。本文深入探讨了5G通信技术与V2X融合组网在车路协同系统中的应用前景,通过集成5G网络的高速率、低时延特性与V2X的广泛连接能力,提出了一种创新的融合组网架构,旨在构建更高效、安全的智慧交通生态。研究内容涵盖了系统架构设计、关键技术分析、应用场景示例、实验验证以及对未来的展望,为未来车路协同系统的部署与优化提供了全面的理论依据和技术指南。

基于LDC1101的电涡流传感器设计

传统的模拟式电涡流传感器存在容易受到干扰、电路设计复杂的问题而利用现场可编程门阵列(FPGA)或复杂可编程逻辑器件(CPLD)软件实现测量电路和输出信号的数字式电涡流传感器调试复杂的问题。针对以上问题,设计了基于LDC1101的数字化电涡流传感器,实现载波信号发生和测量信号解调于一体,并把测量结果通过SPI通信传输给控制器。每个传感器模块由1个LDC1101芯片、1个电涡流传感线圈和1个匹配电容组成。极大简化了电路设计以及调试难度。此传感器测量方法已用于无轴承永磁电机的悬浮控制中对转子磁钢的径向位置测量中。通过4只传感器安装在信号采集电路板上,差分测量然后计算出转子的x和y位置。试验结果表明,该方法分辨率高,可靠性好。

探讨单层动态匀场弥散加权成像在提高直肠癌图像质量的应用

目的:对单层动态匀场-弥散加权成像(iShim-DWI)和单次激发平面回波成像(SS-EPI)-DWI在直肠癌MR成像中的图像质量进行对比研究。方法:共纳入31例原发性直肠癌患者,对入组患者使用iShim-DWI(b=0、800、1600mm^(2)/s)和SS-EPI-DWI(b=0、1000mm^(2)/s)进行扫描。使用Mann-WhitneyU检验比较两者的伪影和图像质量评分。使用配对样本t检验比较两者的定量指标,包括臀大肌的标准差(SD)、病变组织和正常直肠壁的信号值(SI)、表观弥散系数(ADC)、信噪比(SNR)和对比度噪声比(CNR)。结果:iShim-DWI的图像质量比SS-EPI-DWI有显著提升(P<0.01)。在iShim-DWIb1600图像和ADC图中背景SD显著降低(P<0.05)。iShim-DWI中b800和b1600图像的SNR和CNR均高于SS-EPI-DWI中的b1000图像(P<0.01)。原发性直肠癌患者在iShim-DWI扫描模式下,其b800和b1600图像中病变组织的SI值均显著高于正常直肠组织(P<0.01)。结论:与SS-EPI-DWI相比,iShim-DWI不仅可以显著提高直肠癌的图像质量,降低图像噪声,还可以更加显著区分病变与正常直肠,其应用前景具有很大的临床意义。

面向SIMD指令集的SM4算法比特切片优化

SM4算法是中国自主设计的商用分组密码算法,其加解密计算性能成为影响信息系统数据机密性保障的重要因素之一.现有SM4算法优化主要面向硬件设计和软件查表等方向展开研究,分别存在依赖特定硬件环境、效率低下且易遭受侧信道攻击等问题.比特切片技术通过对输入数据重组实现了并行化高效分组密码处理,可以抵御针对缓存的侧信道攻击.然而现有切片分组密码研究对硬件平台相关性强、处理器架构支持单一,并且并行化处理流水启动较慢,面向小规模数据的加解密操作难以充分发挥单指令多数据(single instruction multiple data,SIMD)等先进指令集的优势.针对上述问题,首先提出了一种跨平台的通用切片分组密码算法模型,支持面向不同的处理器指令字长提供一致化的通用数据切片方法.在此基础上,提出了一种面向SIMD指令集的细粒度切片并行处理SM4优化算法,通过细粒度明文切片重组与线性处理优化有效缩短算法启动时间.实验结果表明,相比通用SM4算法,优化的SM4比特切片算法加密速率最高可达438.0 MBps,加密每字节所需的时钟周期最快高达7.0 CPB(cycle/B),加密性能平均提升80.4%~430.3%.