Potassium and calcium channels in different nerve cells act as therapeutic targets in neurological disorders

The central nervous system, information integration center of the body, is mainly composed of neurons and glial cells. The neuron is one of the most basic and important structural and functional units of the central nervous system, with sensory stimulation and excitation conduction functions. Astrocytes and microglia belong to the glial cell family, which is the main source of cytokines and represents the main defense system of the central nervous system. Nerve cells undergo neurotransmission or gliotransmission, which regulates neuronal activity via the ion channels, receptors, or transporters expressed on nerve cell membranes. Ion channels, composed of large transmembrane proteins, play crucial roles in maintaining nerve cell homeostasis. These channels are also important for control of the membrane potential and in the secretion of neurotransmitters. A variety of cellular functions and life activities, including functional regulation of the central nervous system, the generation and conduction of nerve excitation, the occurrence of receptor potential, heart pulsation, smooth muscle peristalsis, skeletal muscle contraction, and hormone secretion, are closely related to ion channels associated with passive transmembrane transport. Two types of ion channels in the central nervous system, potassium channels and calcium channels, are closely related to various neurological disorders, including Alzheimer's disease, Parkinson's disease, and epilepsy. Accordingly, various drugs that can affect these ion channels have been explored deeply to provide new directions for the treatment of these neurological disorders. In this review, we focus on the functions of potassium and calcium ion channels in different nerve cells and their involvement in neurological disorders such as Parkinson's disease, Alzheimer's disease, depression, epilepsy, autism, and rare disorders. We also describe several clinical drugs that target potassium or calcium channels in nerve cells and could be used to treat these disorders. We concluded that there are few clinical drugs that can improve the pathology these diseases by acting on potassium or calcium ions. Although a few novel ion-channelspecific modulators have been discovered, meaningful therapies have largely not yet been realized. The lack of target-specific drugs, their requirement to cross the blood–brain barrier, and their exact underlying mechanisms all need further attention. This review aims to explain the urgent problems that need research progress and provide comprehensive information aiming to arouse the research community's interest in the development of ion channel-targeting drugs and the identification of new therapeutic targets for that can increase the cure rate of nervous system diseases and reduce the occurrence of adverse reactions in other systems.

Engine Misfire Fault Detection Based on the Channel Attention Convolutional Model

To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precisely pinpointing misfire faults.In the experiment,we established a total of 11 distinct states,encompassing the engine’s normal state,single-cylinder misfire faults,and dual-cylinder misfire faults for different cylinders.Data collection was facilitated by a highly sensitive acceleration signal collector with a high sampling rate of 20,840Hz.The collected data were methodically divided into training and testing sets based on different experimental groups to ensure generalization and prevent overlap between the two sets.The results revealed that,with a vibration acceleration sequence of 1000 time steps(approximately 50 ms)as input,the SENET model achieved a misfire fault detection accuracy of 99.8%.For comparison,we also trained and tested several commonly used models,including Long Short-Term Memory(LSTM),Transformer,and Multi-Scale Residual Networks(MSRESNET),yielding accuracy rates of 84%,79%,and 95%,respectively.This underscores the superior accuracy of the SENET model in detecting engine misfire faults compared to other models.Furthermore,the F1 scores for each type of recognition in the SENET model surpassed 0.98,outperforming the baseline models.Our analysis indicated that the misclassified samples in the LSTM and Transformer models’predictions were primarily due to intra-class misidentifications between single-cylinder and dual-cylinder misfire scenarios.To delve deeper,we conducted a visual analysis of the features extracted by the LSTM and SENET models using T-distributed Stochastic Neighbor Embedding(T-SNE)technology.The findings revealed that,in the LSTMmodel,data points of the same type tended to cluster together with significant overlap.Conversely,in the SENET model,data points of various types were more widely and evenly dispersed,demonstrating its effectiveness in distinguishing between different fault types.

Energy Efficiency of a Solar Green Building Using Bio-Sourced Materials for Indoor Temperature and Humidity Optimization

A clean environment with low carbon emissions is the goal of research on the development of green and sustainable buildings that use bio-sourced materials in conjunction with solar energy to create more sustainable cities.This is particularly true in Africa,where there aren’t many studies on the topic.The current study suggests a 90 m^(2) model of a sustainable building in a dry climate that is movable to address the issue of housing in remote areas,ensures comfort in harsh weather conditions,uses solar renewable resources—which are plentiful in Africa—uses biosourced materials,and examines how these materials relate to temperature and humidity control while emitting minimal carbon emissions.In order to solve the topic under consideration,the work is split into two sections:numerical and experimental approaches.Using TRNSYS and Revit,the suggested prototype building is examined numerically to examine the impact of orientation,envelope composition made of bio-sourced materials,and carbon emissions.Through a hygrothermal investigation,experiments are conducted to evaluate this prototype’s effectiveness.Furthermore,an examination of the photovoltaic system’s production,consumption,and several scenarios used tomaximize battery life is included in the paper.Because the biosourcedmaterial achieves a thermal transmittance of 0.15(W.m^(-2).K^(-1)),the results demonstrate an intriguing finding in terms of comfort.This value satisfies the requirements of passive building,energy autonomy of the dwelling,and injection in-network with an annual value of 15,757 kWh.Additionally,compared to the literature,the heating needs ratio is 6.38(kWh/m^(2).an)and the cooling needs ratio is 49(kWh/m^(2).an),both of which are good values.According to international norms,the inside temperature doesn’t go above 26℃,and the humidity level is within a comfortable range.

Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

盆底超声检查和Green分型诊断产妇产后早期盆底结构及压力性尿失禁

目的:探究盆底超声检查和Green分型在产妇产后早期盆底结构及压力性尿失禁(SUI)诊断中的价值。方法:选取2021年3月-2023年3月本院就诊经产妇204例,根据产后早期(6~8周)SUI发生情况分为SUI组(82例)和非SUI组(122例)。检查产妇静息和Valsalva动作状态下膀胱颈距耻骨联合下缘的距离(BSD)、膀胱尿道后角(PUA)、膀胱颈移动度(BND)和尿道旋转角(UR),对比Green分型;采用受试者工作特征(ROC)曲线分析相关参数诊断SUI价值。结果:静息状态下,两组盆底超声参数无差异(P>0.05);SUI组Valsalva动作状态下的BSD、PUA、BND和UR值均大于非SUI组,Green分型Ι型占比(25.6%)低于非SUI组(59.8%)(均P<0.05)。ROC曲线分析,Green分型曲线下面积(AUC)0.579,对SUI诊断价值不佳(P=0.057),Valsalva动作状态下BSD(AUC=0.758)、PUA(AUC=0.743)、BND(AUC=0.769)和UR(AUC=0.705)对SUI诊断价值良好(均P<0.05)。结论:盆底超声检查和Green分型能有效评估经产妇早期盆底结构状况,前者可诊断SUI。

水禽细小病毒SYBR Green Ⅰ荧光定量PCR检测方法的建立与应用

为了建立水禽细小病毒(WPV)快速检测方法,根据序列比对结果在水禽细小病毒NS基因SF3保守区域内设计特异性引物,建立SYBR Green Ⅰ荧光定量PCR通用检测方法。该方法的扩增效率(E)为90.0%,相关系数(R~2)=0.99,标准曲线方程为y=-3.607x+38.77;除WPV出现S形扩增曲线外,新城疫病毒(NDV)、H9亚型禽流感病毒(H9 AIV)、鸭坦布苏病毒(DTMUV)、鸭肝炎病毒(DHAV)、鸭肠炎病毒(DEV)、鸭呼肠孤病毒(DRV)样品均未出现S形阳性扩增曲线;批内变异系数(CV)为0.15%~0.23%,批间变异系数为0.09%~0.28%。结果表明,SYBR Green Ⅰ荧光定量PCR检测方法重复性好、灵敏度高和特异性强。临床样品检测结果表明,SYBR Green Ⅰ荧光定量PCR与普通PCR的符合率达98.4%,灵敏度是普通PCR的1 000倍。SYBR Green Ⅰ荧光定量PCR检测方法不仅能定性检测WPV,还可以进行定量检测,可用于种鸭场、种鹅场的WPV净化检测,也可用于WPV临床大量样品的快速检测。

绿色星球环保频道探析——Green Planet Channel of Discovery之个案分析

一、绿色星球环保频道（Planet Green Channel of Discovery）初问世 2008年6月4日，美国著名的Discovery传媒集团将其麾下的家庭频道（Discovery Home Channel）全面更换为绿色星球环保频道（Planet Grin Channel），这是美国、乃至全世界第一个24小时不间断播出的以绿色环保节目为主题的电视频道。

猪流行性腹泻病毒SYBR Green I实时荧光定量PCR检测方法的建立

为了建立高效、灵敏的猪流行性腹泻病毒(PEDV)检测方法,本研究从GenBank数据库中获取PEDV N基因序列,扩增出PEDV N基因标准质粒,并在N基因的保守区域内设计了一对特异性荧光定量引物,成功建立了SYBR Green I实时荧光定量PCR检测方法。经过一系列试验表明,该检测方法线性关系良好,R^(2)值为0.99;特异性强,敏感性高,最低可检测至2.23 copies/μL,比普通PCR灵敏约100倍;重复性好,组内变异系数为0.25%~0.43%,组间变异系数为0.67%~0.97%;对于各地区96份临床样品检测出PEDV阳性率为25%。本研究建立的实时荧光定量PCR检测方法为PEDV的临床诊断、流行病学调查以及定量研究提供了有效的检测工具。

美洲鳗鲡腺瘤病毒(AEAdoV)普通PCR和SYBR Green I实时荧光定量PCR检测方法的建立及应用

为建立美洲鳗鲡腺瘤病毒(AEAdoV)的检测方法,根据AEAdoV福建株(AEAdoVFJ)的superfamily 3 helicases(S3H)序列,设计引物,建立了AEAdoV的普通PCR和qPCR检测方法;进一步评价检测方法的灵敏性、特异性及重复性,利用2种方法对美洲鳗鲡“出血性烂鳃”病料进行了检测,并对美洲鳗鲡体内不同组织的病毒含量进行分析。结果显示,普通PCR扩增的目的片段长度约300 bp,利用其构建的qPCR质粒标准品,其拷贝数与qPCR阈值循环数(C_(t))线性关系良好,线性范围广,标准曲线相关系数(R2)达到0.999,扩增效率为105.067%。建立的普通PCR法和qPCR的最低检测AEAdoV拷贝数分别为100个和10个。2种方法均可特异性检测AEAdoV,而对蛙虹彩病毒(RGV)、鳗鲡疱疹病毒(AngHV)、鲤疱疹病毒(KHV)、对虾白斑综合征病毒(WSSV)、日本鳗鲡内皮细胞坏死病毒(JEAdoV)和花鳗鲡腺瘤病毒(MEAdoV)均无扩增反应。qPCR法的组内和组间变异系数均小于2%,表明其重复性良好。临床应用结果显示,35份美洲鳗鲡“出血性烂鳃”病料,采用普通PCR法的AEAdoV检出率为82.8%,而qPCR法的AEAdoV检出率为97%。对美洲鳗鲡不同组织的病毒含量分析结果显示,心脏、肝脏、鳃、鳍的AEAdoV相对含量较高,而黏液、皮肤和脾脏的病毒含量相对较低。研究表明,建立的AEAdoV的灵敏度高、特异性强的普通PCR和qPCR检测方法,证实AEAdoV与美洲鳗鲡“出血性烂鳃”病密切相关,且在感染鳗鲡主要组织中都存在。实验结果对于研究AEAdoV的致病性,开展其流行情况和病原学情况分析具有重要意义。

约束Green函数与非线性地基梁模态分析

在生物和医学领域,微机电系统(MEMS)中的微梁结构在植入人体的使用时,由于体内的细胞环境类似于水凝胶,在这种环境下工作,设备和仪器的精度和稳定性很大程度上受到细胞弹性的影响.为了分析此类地基梁的动力学问题,本文建立了非线性基础上的梁振动模型,研究了任意位置弹簧和非线性弹簧基础上的梁模态.通过Laplace变换和线性叠加原理,得到了一种约束Green函数,利用数值计算验证方案的有效性,并研究了各种重要物理参数的影响,发现弹簧位置向跨中移动时,模态对称性被打破,弹簧刚度增加,模态阶数改变.

SYBR GreenⅠ染料-实时荧光定量聚合酶链式反应法检测发酵乳中的霉菌和酵母含量

目的建立一种应用SYBR GreenⅠ染料的实时荧光定量聚合酶链式反应法快速检测发酵乳中的霉菌和酵母菌。方法本研究针对霉菌与酵母菌的保守序列设计引物,确定最优反应体系与反应条件。通过熔解曲线以及非目标菌株的检测验证该方法的特异性;通过菌悬液的梯度稀释检测确定该方法的灵敏度;通过菌悬液与发酵乳样品混合后进行检测,确定该方法的检出限,并得到标准曲线。结果该方法能够特异性的检测发酵乳中的霉菌、酵母菌,无交叉反应。该方法检测霉菌、酵母菌的灵敏度均为10^(2) CFU/mL,并且当菌悬液与发酵乳样品混合后,并没有降低该方法的检出限。在10^(2)~10^(6) CFU/mL浓度范围内,菌液浓度的对数值与循环阈值(cyclethreshold,Ct)具有良好的线性关系,可以在市售样品的检测中通过Ct值计算样品中目标菌的含量,更快的判断发酵乳是否被霉菌、酵母菌污染。结论该方法可用于发酵乳中霉菌和酵母菌的快速检测,为发酵乳的食品安全提供了技术保障。

3型哺乳动物正呼肠孤病毒SYBR Green I荧光定量PCR方法的建立及应用

哺乳动物正呼肠孤病毒(MRV)是双链RNA病毒,可以感染自然宿主的哺乳动物和脊椎动物。为建立一种针对3型哺乳动物正呼肠孤病毒(MRV-3)的特异且快速的检测方法,本研究根据Genbank登录的MRV-3(OQ627746-OQ627755)S1基因保守区设计1对特异性引物,并从MRV-3中扩增S1基因,构建重组质粒p MD18-S1,经PCR和测序鉴定正确后作为质粒标准品,经反应体系及反应条件优化后首次初步建立了检测MRV-3的SYBR Green I荧光定量PCR(q PCR)方法。将质粒标准品10倍倍比稀释后作为模板经该q PCR扩增,建立标准曲线,结果显示,质粒标准品在1.3×10^(8)拷贝/μL~1.3×10^(3)拷贝/μL与各自的Ct值均呈良好的线性关系,斜率为-3.1706,R^(2)为0.9999,熔解曲线为单峰。以牛病毒性腹泻病毒(BVDV)、牛肠道病毒(BEV)、水牛匈爱病毒(Buf Hu V)、牛冠状病毒(BCo V)、牛细小病毒(BPV)和MRV-3的基因组DNA/c DNA为模板,利用本研究建立的q PCR方法检测,评估该方法的特异性;将质粒标准品10倍倍比稀释至1.3×10^(2)拷贝/μL~1.3×10^(8)拷贝/μL后作为模板,分别利用本研究建立的q PCR和常规PCR检测,比较两种方法的检测结果,评估本研究建立q PCR方法的敏感性;以1.3×10^(3)拷贝/μL~1.3×10^(7)拷贝/μL 5个不同浓度的质粒标准品为模板,利用该方法分别进行批内和批间的重复性试验,评估该方法的重复性。结果显示,该方法只能检测出MRV-3,其他相关病原的检测结果均为阴性;该q PCR对质粒标准品的检测限为1.3×10^(3)拷贝/μL,比常规PCR敏感性高10 000倍;批内和批间重复性试验的变异系数均小于或等于1.0%,表明该q PCR方法特异性强、敏感性高、重复性好。利用该方法检测220份牛粪便样品,结果显示MRV-3的检出率(3.64%,8/220)高于常规PCR的检出率(1.36%,3/220),两种检测方法的阳性符合率达100%,阴性符合率为97.75%,总符合率为97.78%。综上所述,本研究首次建立的检测MRV-3的SYBR Green I q PCR方法可以用于临床牛腹泻病原的检测,为MRV-3尤其是牛源MRV-3提供了一种快速灵敏的检测手段,也为MRV-3的后续研究奠定了基础。

三疣梭子蟹十足目虹彩病毒1 SYBR Green I荧光定量PCR检测方法的建立及初步应用

为建立十足目虹彩病毒1(decapod iridescent virus 1,DIV1)的SYBR GreenⅠ荧光定量PCR检测方法,根据DIV1的MCP和ATPase基因序列,设计并筛选出引物,以制备的DIV1阳性质粒标准品为模板构建标准曲线,建立DIV1的SYBR Green I qPCR方法,并对该方法进行临床初步应用。结果显示,建立的qPCR方法阈值循环数(cycle threshold value,Ct)与标准品拷贝数的对数线性关系良好,标准曲线相关系数(R^(2))为0.999;对DIV1阳性的虾蟹核酸样本能够进行特异性扩增,但对传染性脾肾坏死病毒(infectious spleen and kidney necrosis virus,ISKNV)和白斑综合征病毒(white spot syndrome virus,WSSV)阳性核酸样本均无扩增;最低检测限为9.77 copies/μL;Ct值的组内和组间变异系数均小于1%。运用该方法对70份疑似感染DIV1的虾蟹类样本进行DIV1检测,该方法阳性率为48.57%,与套式PCR检测方法的阳性率一致;利用建立的方法对DIV1阳性三疣梭子蟹的血淋巴、肝胰腺及心脏等组织进行定量检测分析,结果显示各组织中均存在DIV1,其中血淋巴中DIV1平均拷贝数最高。研究表明,建立的SYBR GreenⅠ荧光定量PCR方法特异性强、灵敏度高、重复性好,可用于对DIV1的快速、定量检测,对十足目虹彩病毒病的诊断和防控具有重要意义。

Piezo1 channel exaggerates ferroptosis of nucleus pulposus cells by mediating mechanical stress-induced iron influx

To date,several molecules have been found to facilitate iron influx,while the types of iron influx channels remain to be elucidated.Here,Piezo1 channel was identified as a key iron transporter in response to mechanical stress.Piezo1-mediated iron overload disturbed iron metabolism and exaggerated ferroptosis in nucleus pulposus cells(NPCs).Importantly,Piezo1-induced iron influx was independent of the transferrin receptor(TFRC),a well-recognized iron gatekeeper.Furthermore,pharmacological inactivation of Piezo1 profoundly reduced iron accumulation,alleviated mitochondrial ROS,and suppressed ferroptotic alterations in stimulation of mechanical stress.Moreover,conditional knockout of Piezo1(Col2a1-CreERT Piezo1^(flox/flox))attenuated the mechanical injury-induced intervertebral disc degeneration(IVDD).Notably,the protective effect of Piezo1 deficiency in IVDD was dampened in Piezo1/Gpx4 conditional double knockout(cDKO)mice(Col2a1-CreERT Piezo1^(flox/flox)/Gpx4^(flox/flox)).These findings suggest that Piezo1 is a potential determinant of iron influx,indicating that the Piezo1-iron-ferroptosis axis might shed light on the treatment of mechanical stress-induced diseases.

Reviewing electrochemical stability of ionic liquids-/deep eutectic solvents-based electrolytes in lithium-ion,lithium-metal and post-lithium-ion batteries for green and safe energy

Sustainable energy is the key issue for the environment protection,human activity and economic development.Ionic liquids(ILs)and deep eutectic solvents(DESs)are dogmatically regarded as green and sustainable electrolytes in lithium-ion,lithium-metal(e.g.,lithium-sulphur,lithium-oxygen)and post-lithium-ion(e.g.,sodium-ion,magnesium-ion,and aluminum-ion)batteries.High electrochemical stability of ILs/DESs is one of the prerequisites for green,sustainable and safe energy;while easy electrochemical decomposition of ILs/DESs would be contradictory to the concept of green chemistry by adding the cost,releasing volatile/hazardous by-products and hindering the recyclability.However,(1)are ILs/DESs-based electrolytes really electrochemically stable when they are not used in batteries?(2)are ILs/DESs-based electrolytes really electrochemically stable in real batteries?(3)how to design ILs/DESs-based electrolytes with high electrochemical stability for batteries to achieve sustainability and green development?Up to now,there is no summary on this topic,to the best of our knowledge.Here,we review the effect of chemical structure and non-structural factors on the electrochemical stability of ILs/DESs in simulated conditions.More importantly,electrochemical stability of ILs/DESs in real lithium-ion,lithium-metal and post-lithium-ion batteries is concluded and compared.Finally,the strategies to improve the electrochemical stability of ILs/DESs in lithium-ion,lithium-metal and post-lithium-ion batteries are proposed.This review would provide a guide to design ILs/DESs with high electrochemical stability for lithium-ion,lithium-metal and postlithium-ion batteries to achieve sustainable and green energy.

香辛料SYBR GREENⅠ染料实时聚合酶链式反应检测方法的建立及应用

目的:本研究致力于建立香辛料真实性成分的分子鉴定方法,为香辛料的掺假提供有效的鉴定和检测方法,在不同的使用条件下分别实现定性或半定量分析,为建立相关标准提供一定的基础技术支撑。方法:研究采用SYBR GREENⅠ染料实时聚合酶链式反应(polymerase chain reaction,PCR)方法,通过设计特异性引物成功建立了特异性检测八角、茴香、胡椒和花椒的分析技术。结果:该方法能够特异性检测出八角、茴香、胡椒、花椒,Ct值在标准品体积分数0.001%~10%范围内线性关系良好。针对八角标准品,检测限为1%;针对茴香、花椒、胡椒标准品,最检测限均为0.001%。利用该方法对5份实际样本进行检测,分别在样本1中未检测出八角、茴香、胡椒、花椒;样本2、3、5中检测出八角、茴香、胡椒;样本4中检测出八角、茴香、胡椒、花椒。结论:本实验建立的SYBR GREENⅠ染料实时PCR方法灵敏度高、重复性好,可应用于实际样品的检测。

Lithium-Ion Charged Polymer Channels Flattening Lithium Metal Anode

The concentration difference in the near-surface region of lithium metal is the main cause of lithium dendrite growth.Resolving this issue will be key to achieving high-performance lithium metal batteries(LMBs).Herein,we construct a lithium nitrate(LiNO_(3))-implanted electroactiveβphase polyvinylidene fluoride-co-hexafluoropropylene(PVDF-HFP)crystalline polymorph layer(PHL).The electronegatively charged polymer chains attain lithium ions on the surface to form lithium-ion charged channels.These channels act as reservoirs to sustainably release Li ions to recompense the ionic flux of electrolytes,decreasing the growth of lithium dendrites.The stretched molecular channels can also accelerate the transport of Li ions.The combined effects enable a high Coulombic efficiency of 97.0%for 250 cycles in lithium(Li)||copper(Cu)cell and a stable symmetric plating/stripping behavior over 2000 h at 3 mA cm^(-2)with ultrahigh Li utilization of 50%.Furthermore,the full cell coupled with PHL-Cu@Li anode and Li Fe PO_(4) cathode exhibits long-term cycle stability with high-capacity retention of 95.9%after 900 cycles.Impressively,the full cell paired with LiNi_(0.87)Co_(0.1)Mn_(0.03)O_(2)maintains a discharge capacity of 170.0 mAh g^(-1)with a capacity retention of 84.3%after 100 cycles even under harsh condition of ultralow N/P ratio of 0.83.This facile strategy will widen the potential application of LiNO_(3)in ester-based electrolyte for practical high-voltage LMBs.

The Channel Branches & Network Vessels on the Tianhui Lacquered Meridian Figurine——Taking the Heart-Regulated Channel as an Example

Along with the surge of unearthed medical literature and cultural relics in recent years,a network of channels in the system of medical conduit vessels(meridians) during the early Western Han dynasty has become much clearer gradually.In it,the increasing number of channel branches,network vessels and needle insertion holes(acupoints) is an important feature of the development of channel medicine during the Western Han dynasty.This is not only a reflection of the expanding requirements of the theoretical system of the main trunk channels and other vessels,but also an inevitable result of the continuous enrichment and accumulation of clinical experience.This article integrates the information about channel branches,network vessels,inscriptions,dots and further relics on the Tianhui(天回) Lacquered Meridian Figurine to compare the unearthed literature of the channel genre with the transmitted classical literature about acupuncture.The “Heart-Regulated Channel” in Medical Manuscripts on Bamboo Slips from Tianhui(《天回医简》) serves as an example to explain the occurrence,development and changes of the channel branches and network vessels in the early system of medical channels.

Deep learning for joint channel estimation and feedback in massive MIMO systems

The great potentials of massive Multiple-Input Multiple-Output(MIMO)in Frequency Division Duplex(FDD)mode can be fully exploited when the downlink Channel State Information(CSI)is available at base stations.However,the accurate CsI is difficult to obtain due to the large amount of feedback overhead caused by massive antennas.In this paper,we propose a deep learning based joint channel estimation and feedback framework,which comprehensively realizes the estimation,compression,and reconstruction of downlink channels in FDD massive MIMO systems.Two networks are constructed to perform estimation and feedback explicitly and implicitly.The explicit network adopts a multi-Signal-to-Noise-Ratios(SNRs)technique to obtain a single trained channel estimation subnet that works well with different SNRs and employs a deep residual network to reconstruct the channels,while the implicit network directly compresses pilots and sends them back to reduce network parameters.Quantization module is also designed to generate data-bearing bitstreams.Simulation results show that the two proposed networks exhibit excellent performance of reconstruction and are robust to different environments and quantization errors.

Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.