FPSblo:A Blockchain Network Transmission Model Utilizing Farthest Point Sampling

Peer-to-peer(P2P)overlay networks provide message transmission capabilities for blockchain systems.Improving data transmission efficiency in P2P networks can greatly enhance the performance of blockchain systems.However,traditional blockchain P2P networks face a common challenge where there is often a mismatch between the upper-layer traffic requirements and the underlying physical network topology.This mismatch results in redundant data transmission and inefficient routing,severely constraining the scalability of blockchain systems.To address these pressing issues,we propose FPSblo,an efficient transmission method for blockchain networks.Our inspiration for FPSblo stems from the Farthest Point Sampling(FPS)algorithm,a well-established technique widely utilized in point cloud image processing.In this work,we analogize blockchain nodes to points in a point cloud image and select a representative set of nodes to prioritize message forwarding so that messages reach the network edge quickly and are evenly distributed.Moreover,we compare our model with the Kadcast transmission model,which is a classic improvement model for blockchain P2P transmission networks,the experimental findings show that the FPSblo model reduces 34.8%of transmission redundancy and reduces the overload rate by 37.6%.By conducting experimental analysis,the FPS-BT model enhances the transmission capabilities of the P2P network in blockchain.

Unveiling three-dimensional sea surface signatures caused by internal solitary waves:insights from the surface water ocean topography mission

Internal solitary waves(ISW),characterized by large amplitude and long propagation distance,are widespread in global oceans.While remote sensing images have played an essential role in studying ISWs,they mainly exploit two-dimensional image information.However,with the launch of the surface water ocean topography(SWOT)satellite on December 16,2022,a unique opportunity has emerged to capture wide-swath three-dimensional ISW-induced sea surface information.In this study,we examine ISWs in the Andaman Sea using data from the Ka-band Radar Interferometer(KaRIN),a crucial sensor onboard SWOT.KaRIN not only provides backscattering satellite images but also employs synthetic aperture interferometry techniques to retrieve wide-swath two-dimensional sea surface height measurements.Our observations in the Andaman Sea revealed the presence of ISWs characterized by dark-bright strips and surface elevation solitons.The surface soliton has an amplitude of 0.32 m,resulting in an estimation of ISW amplitude of approximately 60 m.In contrast to traditional two-dimensional satellite images or nadir-looking altimetry data,the SWOT mission’s capability to capture threedimensional sea surface information represents a significant advancement.This breakthrough holds substantial promise for ISW studies,particularly in the context of ISW amplitude inversion.

Higher-Order Nonlinear Effects on Optical Soliton Propagation and Their Interactions

When pursuing femtosecond-scale ultrashort pulse optical communication, one cannot overlook higher-order nonlinear effects. Based on the fundamental theoretical model of the variable coefficient coupled high-order nonlinear Schr¨odinger equation, we analytically explore the evolution of optical solitons in the presence of highorder nonlinear effects. Moreover, the interactions between two nearby optical solitons and their transmission in a nonuniform fiber are investigated. The stability of optical soliton transmission and interactions are found to be destroyed to varying degrees due to higher-order nonlinear effects. The outcomes may offer some theoretical references for achieving ultra-high energy optical solitons in the future.

Deep learning in extracting tropical cyclone intensity and wind radius information from satellite infrared images—A review

热带气旋(TC)严重危害人类生命和财产安全,TC的实时监测一直是研究热点,随着空间和传感器技术的发展,卫星遥感已成为监测TC的主要手段.此外,深度学习具有卓越的数据挖掘能力,在地球科学中的表现优于基于物理或统计的算法,越来越多的深度学习算法被开发和应用于TC信息的提取,本文系统地回顾了深度学习在TC信息提取中的应用,并给出了深度学习模型在TC强度和风圈半径提取中的应用.此外,本文还展望了深度学习在TC信息提取中的应用前景.

苝二酰亚胺共价有机框架超级还原剂用于高效光催化芳基卤化物还原反应

自由基离子型分子光催化剂被证实是具有很强还原能力的可见光超级还原剂,它们在促进惰性的有机反应(例如将芳基卤化物还原为芳基自由基)方面具有突出的催化能力.然而,由于分子聚集严重地降低其催化活性,因而针对非均相超级还原剂的研究较少.本文提出了一种新的方法来解决上述问题,通过溶剂热反应将具有连续光诱导电子转移机制的苝二亚胺超级还原剂(PDI)异质化为二维给体-受体(D-A)共价有机框架(COFs).即以N,N'-双(3-戊基)-2,5,8,11-四(4-甲酰基苯基)苝二酰亚胺(TFPDI)与1,3,6,8-四(4-氨基苯基)芘\(Py-TA)或2,3,6,7-四(4-氨基基苯基)四硫富瓦烯(TTF-TA)为原料,通过溶剂热反应分别制备了两种高晶态二维D-A型COF结构:USTB-21和USTB-22,并用于芳基氯化物、芳基溴化物和芳基碘化物的光催化还原反应.X射线衍射和理论模拟结果表明,USTB-21和USTB-22具有二维共价键连接的层状结构,分别呈现AA和AB的堆积方式.在各自最佳反应条件下,COFs显示出与均相催化剂相媲美的可见光催化性能,可高效地还原一系列芳基氯化物、芳基溴化物和芳基碘化物.其中,USTB-22在可见光驱动不同的芳香卤化物还原时,3 h内的转化率高达99%.瞬态吸收光谱结果表明,相比于均相催化剂(N,N'-双(2,6-二异丙基苯基)苝二酰亚胺),自由基阴离子激发态寿命是150 ps,USTB-21和USTB-22具有更长的激发态寿命,分别为210和260 ps.顺磁共振波谱测试结果证明,自由基阴离子光催化剂异质化成晶态D-A型COFs能够有效地促进电荷分离效率和延长激发态寿命.上述结果说明,USTB-22具有良好的光催化性能主要是因为其激发态寿命较长以及电荷分离效率较好.理论模拟结果表明,所制备的材料具有D-A型的电子结构.对COF的模型片段进行理论计算,揭示了各步反应路径中吉布斯自由能的变化,从而进一步阐明了光催化机理.在催化反应过程中,芳基卤化物还原途径可分为两个阶段:第一阶段为双光子能量输入和光驱电子转移,包括光子捕获和(TTF-PDI•−)^(*)产生以及光驱动电子转移到4-溴苯乙酮底物;第二阶段为能量输出,用于还原4-溴苯乙酮底物生成苯乙酮.综上所述,本文通过溶剂热反应将具有连续光诱导电子转移机制的苝二亚胺超级还原剂异质化为二维D-A型COFs结构.该结构在芳基氯化物、芳基溴化物和芳基碘化物等的光催化还原反应中,可很好地促进电子从光催化剂转移到反应物,进而显著提高光催化反应的活性和选择性;本研究对于未来设计新型自由基离子型高效光催化剂提供了新的思路.

阿尔茨海默病患者体质指数与中脑边缘多巴胺系统及认知功能的相关性研究

目的:中脑边缘多巴胺系统在体重调节和认知功能中发挥着重要作用。研究发现阿尔茨海默病(Alzheimer's disease,AD)患者的体质指数(body mass index,BMI)和中脑多巴胺边缘系统易受AD病理的影响而发生变化。迄今为止,AD患者的BMI与中脑边缘多巴胺系统的关系尚不清楚。本文旨在探讨AD患者的BMI与中脑边缘多巴胺系统及认知功能的关系。方法:本研究使用的数据来自国际阿尔茨海默病神经影像计划数据库ADNI(Alzheimer's Disease Neuroimaging Initiative, ADNI),所有受试者于基线时进行了Aβ PET成像,同期完成脑核磁扫描及成套神经心理学测评。根据Aβ PET的标准化摄取值比(SUVR)将受试者分为Aβ阳性组(SUVR> 1.11)和阴性组(SUVR≤1.11)。以海马、杏仁核、伏隔核、尾状核和壳核作为中脑边缘多巴胺系统的感兴趣区进行分析。结果:共纳入1182例受试者,其中Aβ阳性608例,Aβ阴性574例。与Aβ阴性组相比,Aβ阳性组的海马、杏仁核、伏隔核及壳核的体积更小,BMI较低(P<0.05)。在Aβ阳性组中,BMI与海马、杏仁核、伏隔核、尾状核、壳核的体积及简易智能精神状态检查量表得分和记忆得分均呈正相关(P<0.05),而在Aβ阴性组中,BMI与感兴趣区体积、认知得分的相关性差异无统计学意义(P>0.05)。随访分析也表明在Aβ阳性组中,BMI与海马、杏仁核、伏隔核、壳核的体积及认知功能呈正相关。结论:BMI较低的AD患者中脑边缘多巴胺系统体积较小,认知功能较差。

A Multi-Constraint Path Optimization Scheme Based on Information Fusion in Software Defined Network

The existingmultipath routing in Software Defined Network (SDN) is relatively blind and inefficient, and there is alack of cooperation between the terminal and network sides, making it difficult to achieve dynamic adaptationof service requirements and network resources. To address these issues, we propose a multi-constraint pathoptimization scheme based on information fusion in SDN. The proposed scheme collects network topology andnetwork state information on the network side and computes disjoint paths between end hosts. It uses the FuzzyAnalytic Hierarchy Process (FAHP) to calculate the weight coefficients of multiple constrained parameters andconstructs a composite quality evaluation function for the paths to determine the priority of the disjoint paths. TheSDN controller extracts the service attributes by analyzing the packet header and selects the optimal path for flowrule forwarding. Furthermore, the service attributes are fed back to the path composite quality evaluation function,and the path priority is dynamically adjusted to achieve dynamic adaptation between service requirements andnetwork status. By continuously monitoring and analyzing the service attributes, the scheme can ensure optimalrouting decisions in response to varying network conditions and evolving service demands. The experimentalresults demonstrated that the proposed scheme can effectively improve average throughput and link utilizationwhile meeting the Quality of Service (QoS) requirements of various applications.

Synthesis, characteristics of hierarchical EU-1 zeolite for xylene isomerization probe reaction

Introduced a method of synthesizing hierarchical EU-1 zeolite with organosilanes as additive, and studied the influences of following different kinds of organosilanes on the synthesis of hierarchical EU-1 zeolite: γ-glycidoxy propyl trimethoxy silane(GPTMS), N-β-(aminoethyl)-γ-aminopropyl methyl dimethoxyl silane(APAEDMS),and N-(β-aminoethyl)-γ-aminopropyl dimethoxyl(ethyoxyl) silane(TMPED). The hierarchical EU-1 samples were characterized by XRD, SEM, N_2 adsorption, FT-IR and NH_3-TPD to analyze the crystallinity, morphology, surface area, pore size distribution and acidity. The results showed that hierarchical EU-1 zeolites were successfully synthesized; organosilanes have great influence on crystal morphology of EU-1 zeolites; the exterior surface area of hierarchical EU-1 zeolite, which synthesized with organosilanes(APAEDMS) adding into synthesis system, increased by 62.1% and mesopore volume increased by 129.1% compared with conventional EU-1 zeolites, thus can reduce the diffusional restriction markedly in catalytic reaction. The catalytic performance of hierarchical EU-1zeolites were evaluated in m-xylene isomerization on fixed bed reactor. The catalytic data showed that the isomerization activity PX/X of the hierarchical EU-1 zeolites reached around 24.09% in theoretical thermodynamic equilibrium from 23.83%, and the selectivity of C_8 aromatic hydrocarbon increased from 75.16% to 84.87%. The conversion of p-xylene increased from 16.30% to 18.41%.

Data-Based Optimal Tracking of Autonomous Nonlinear Switching Systems

In this paper,a data-based scheme is proposed to solve the optimal tracking problem of autonomous nonlinear switching systems.The system state is forced to track the reference signal by minimizing the performance function.First,the problem is transformed to solve the corresponding Bellman optimality equation in terms of the Q-function(also named as action value function).Then,an iterative algorithm based on adaptive dynamic programming(ADP)is developed to find the optimal solution which is totally based on sampled data.The linear-in-parameter(LIP)neural network is taken as the value function approximator.Considering the presence of approximation error at each iteration step,the generated approximated value function sequence is proved to be boundedness around the exact optimal solution under some verifiable assumptions.Moreover,the effect that the learning process will be terminated after a finite number of iterations is investigated in this paper.A sufficient condition for asymptotically stability of the tracking error is derived.Finally,the effectiveness of the algorithm is demonstrated with three simulation examples.

Preclinical and clinical applications of specific molecular imaging for HER2-positive breast cancer

Precision medicine and personalized therapy are receiving increased attention, and molecular-subtype classification has become crucial in planning therapeutic schedules in clinical practice for patients with breast cancer. Human epidermal growth factor receptor 2(HER2) is associated with high-grade breast tumors, high rates of lymph-node involvement, high risk of recurrence, and high resistance to general chemotherapy. Analysis of HER2 expression is highly important for doctors to identify patients who can benefit from trastuzumab therapy and monitor the response and efficacy of treatment. In recent years, significant efforts have been devoted to achieving specific and noninvasive HER2-positive breast cancer imaging in vivo. In this work, we reviewed existing literature on HER2 imaging in the past decade and summarized the studies from different points of view, such as imaging modalities and HER2-specific probes. We aimed to improve the understanding on the translational process in molecular imaging for HER2 breast cancer.

Value of metabolic parameters in distinguishing primary mediastinal lymphomas from thymic epithelial tumors

Objective:A high rate of unnecessary thymectomies has been reported.This study aimed to distinguish primary mediastinal lymphomas(PMLs)from thymic epithelial tumors(TETs)by evaluating volumetric and metabolic parameters with l8F-FDG PET/CT.Methods:A total of 136 patients who were pathologically diagnosed with TETs or PMLs were enrolled,and 18F-FDG PET/CT was performed before therapy.Volumetric parameters,including the mean SUV(SUVmean),metabolic tumor volume(MTV),total lesion glycolysis(TLG),and SUVmax,were determined and compared between the 2 subtypes.The diagnostic performance of these parameters was evaluated with receiver operating characteristic(ROC)curve analysis.Results:All parameters significantly differed between patients with PMLs and TETs.Patients with lymphomas were younger and had higher SUVmean,SUVmax,TLG,and MTV values than patients with TETs.The MTV and TLG values had similar diagnostic performance.ROC analysis indicated that the areas under the curves of the SUVmean and SUVmax values performed similarly(approximately 0.76)in differentiating patients with PMLs from TETs,and both values were better than the MTV and TLG values.When age was included with the SUVmax in differentiating TETs from PMLs,the AUC was 0.91,and the sensitivity and specificity increased to 80%and 93%,respectively.Conclusions:The SUVmax and volumetric parameters of 18F-FDG PET/CT can be used to distinguish patients with PMLs versus TETs,and thus may aid in preventing unnecessary thymectomies or other invasive operations.

Manganese toxicity-induced chlorosis in sugarcane seedlings involves inhibition of chlorophyll biosynthesis

Manganese(Mn)toxicity-induced leaf chlorosis limits crop production in acidic soils,but its underlying mechanisms remain unknown.The effects of excessive Mn on chlorophyll(Chl)biosynthesis in sugarcane(Saccharum officinarum L.)leaves were investigated.Under Mn treatment,Chl concentration decreased with Mn accumulation and chlorosis appeared in expanding leaves.Before that,levels of the initial Chl precursor 5-aminolevulinic acid(ALA)and its downstream intermediates decreased,whereas magnesium-protoporphyrin IX monomethyl ester(MgPME)accumulated.Overaccumulation of Mn in leaves downregulated the ALA biosynthetic gene GluTR(encoding glutamyl-tRNA reductase)and MgPME conversion gene MgPMEC(encoding MgPME cyclase),upregulated the ALA biosynthesis inhibitor FLU(encoding FLUORESCENT),but had no significant effect on the expression of other Chl biosynthetic genes.The above Mn-induced changes of Chl precursors and expression of corresponding genes commenced before the Chl decline and leaf chlorosis,and were reversed by ALA supplementation.Thus,excessive Mn-induced chlorosis in sugarcane is mediated by a Chl-biosynthesis disorder resulting from the inhibition of ALA synthesis and MgPME conversion.

Modification and sequential treatment of EU-1 zeolite in mild alkali and alkaline-acid conditions

EU-1 zeolites were sequentially treated with low-concentration sodium carbonate(Na_2CO_3) and hydrochloric acid(HCl) solutions.The obtained samples were characterized by X-ray diffraction(XRD),scanning electron microscopy(SEM),N_2 adsorption/desorption,temperature programmed desorption of NH_3(NH_3-TPD),solid state^(27)A1 nuclear magnetic resonance(^(27)A1 NMR),and the catalytic performances of the treated samples were tested in the xylene isomerization reaction.The results showed that the external surface area and mesoporous volume of the sample sequentially treated with 0.05 mol·L^(-1) Na_2CO_3 and 0.1 mol·L^(-1) HCl solutions reached73.9 m^2·g^(-1) and 0.162 cm^3·g^(-1),respectively.The catalytic performances of EU-1 zeolites were significantly improved,that the activity of the probe reaction increased from 23.03%to 23.61%and the selectivity increased from85.09%to 87.14%compared with those of parent sample.Furthermore,it was found that only amorphous silica and alumina species was dissolved during the post-treatment process,but the framework structure and the acidic properties of EU-1 zeolite remained intact.

Evaluation Model of Teaching Quality Based on Cloud Computing

In the teaching quality evaluation, due to the influence of various human factors, the teaching quality evaluation system is presented with some grey characteristics. Traditional evaluation methods cannot solve the problem effectively. Through gray relational analysis, the grey system of partial information known and unknown can be analyzed. It is difficult for the qualitative description language evaluation index to use traditional mathematical model for accurate representation. In this paper, cloud model is combined with grey relational analysis, and an evaluation method is proposed based on the cloudgrey relational analysis, in order to realize the mutual transformation between the qualitative information and quantitative numerical. Three university teachers’ information was collected by questionnaire survey, and the teaching quality was evaluated through the evaluation model based on grey relational analysis built in MATLAB. The results were compared with those of fuzzy comprehensive evaluation and the BP neural network evaluation. The results show that the teaching quality evaluation model based on cloud grey relational analysis has certain rationality and feasibility.

Expert Consensus on Nutritional Support for Children with Congenital Heart Disease(2023 Edition)

The second edition of the expert consensus on pediatric nutrition was formed based on a global update of pedia-tric nutrition guidelines or consensus worldwide,the management of congenital heart disease,and the results of multi-center clinical nutrition research for congenital heart disease following thefirst Chinese consensus edition of 2016.The consensus was also shaped by the results of three discussion sessions and two questionnaires con-ducted by the 13-member collaboration group.This process was informed by both clinical guidelines and expert consensus.The quality of literature,both in English and Chinese,and the level of recommendations were evaluated using the Grading of Recommendations Assessment,Development,and Evaluations(GRADE)system.

Decoding m^(6)A mRNA methylation by reader proteins in liver diseases

N6-methyladenosine(m^(6)A)is a dynamic and reversible epigenetic regulation.As the most prevalent internal post-transcriptional modification in eukaryotic RNA,it participates in the regulation of gene expression through various mechanisms,such as mRNA splicing,nuclear export,localization,translation efficiency,mRNA stability,and structural transformation.The involvement of m^(6)A in the regulation of gene expression depends on the specific recognition of m^(6)A-modified RNA by reader proteins.In the pathogenesis and treatment of liver disease,studies have found that the expression levels of key genes that promote or inhibit the development of liver disease are regulated by m^(6)A modification,in which abnormal expression of reader proteins determines the fate of these gene transcripts.In this review,we introduce m^(6)A readers,summarize the recognition and regulatory mechanisms of m^(6)A readers on mRNA,and focus on the biological functions and mechanisms of m^(6)A readers in liver cancer,viral hepatitis,non-alcoholic fatty liver disease(NAFLD),hepatic fibrosis(HF),acute liver injury(ALI),and other liver diseases.This information is expected to be of high value to researchers deciphering the links between m^(6)A readers and human liver diseases.

Circulating tumor cells: Biological features and survival mechanisms

Circulating tumor cells(CTCs)are neoplastic cells that are detached from primary tumors and enter circulation.Enumeration and characterization of CTCs are of significance in cancer diagnosis,prognosis,and treatment monitoring.CTC survival in the bloodstream is a limiting step for the development of metastases in distant organs.Recent technological advances,especially in single-cell molecular analyses have uncovered heterogeneous CTC survival mechanisms.Undergoing epithelial-to-mesenchymal transition(EMT),increasing stem cell-like properties,and forming cell clusters enable CTCs to adapt to the harsh microenvironment of the circulation.Expressing and releasing several immunosuppressive molecules help CTCs escape from anti-cancer immune mechanisms.This review article summarizes the biological characteristics of CTCs and focuses on the recent understanding of the mechanisms by which CTCs survive in circulation.Additionally,the clinical and therapeutic implications of CTCs are discussed.

Hydrothermal synthesis of polyimide-linked covalent organic frameworks towards ultrafast and stable cathodic sodium storage

Redox-active organic materials are capturing growing attention as cathode materials for sustainable alkaline metal ion batteries.However,the storage of Na+in most organic materials-based cathodes is plagued by low capacity and unsatisfying rate performance due to their low active site densities and limited exposed active sites.Herein,two polyimide-linked covalent organic frameworks(COFs),namely HATN-PD-COF and HATN-TAB-COF,were fabricated from hydrothermal synthesis with redoxactive triphenylene-2,3,6,7,10,11-hexacarboxylic acid and aromatic amines as starting materials.Powder X-ray diffraction and electron microscopy analysis indicate the high crystalline nature of these COFs with AA stacking configuration and orderly mesoporous tunnel.N_(2) sorption measurement discloses the permanent porosity of these two COFs with a Brunauer-EmmettTeller surface area of 1,065-1,200 m^(2)g^(-1)and a large pore size of 2.0-3.1 nm.Galvanostatic intermittent titration technique and density functional theory calculations reveal the facile Na+ion diffusion along the mesoporous tunnel of these COFs with a small energy barrier of 0.13-0.40 e V.In particular,the as-prepared COFs based-cathodes show ultrafast and stable Na+storage associated with their conjugated electronic structure,highly ordered mesoporous tunnel,robust structure,and redox-active C=N/C=O-rich framework as exemplified by the high reversible capacity of 210 m A h g^(-1)at 200 m A g^(-1),record-high rate performance(195 m A h g^(-1)at a high current density of 10,000 m A g^(-1))among organic electrodes and the capacity retention of nearly 91%at 10,000 m A g^(-1)after 7,000 cycles for HATN-PD-COF.

Fatigue test loading methodfor wagon body basedon measured load

Purpose–In this paper,the C80 special coal gondola car was taken as the subject,and the load test data of the car body at the center plate,side bearing and coupler measured on the dedicated line were broken down to generate the random load component spectrums of the car body under five working conditions,namely expansion,bouncing,rolling,torsion and pitching according to the typical motion attitude of the car body.Design/methodology/approach–On the basis of processing the measured load data,the random load component spectrums were equivalently converted into sinusoidal load component spectrums for bench test based on the principle of pseudo-damage equivalence of load.Relying on the fatigue and vibration test bench of the whole railway wagon,by taking each sinusoidal load component spectrum as the simulation target,the time waveform replication(TWR)iteration technology was adopted to create the drive signal of each loading actuator required for the fatigue test of car body on the bench,and the drive signal was corrected based on the equivalence principle of measured stress fatigue damage to obtain the fatigue test loads of car body under various typical working conditions.Findings–The fatigue test results on the test bench were substantially close to the measured test results on the line.According to the results,the relative error between the fatigue damage of the car body on the test bench and the measured damage on the line was within the range of
16.03%–27.14%.Originality/value–The bench test results basically reproduced the fatigue damage of the key parts of the car body on the line.

粗糙脉孢菌7种子囊型归类教学探究

遗传分析是本科遗传学教学的重要内容,四分子分析是真菌类遗传分析的独特方式,其中的粗糙脉孢菌顺序四分子分析不仅可以研究基因与着丝粒间的重组、基因间的重组,而且还可以精细研究同源染色体非姊妹染色单体之间的交换形式,是深入理解交换重组分子机制的重要遗传学研究材料。对此,教材中已有详尽的介绍。美中不足的是,中外教科书和相关专业期刊中缺乏对顺序四分子两基因连锁分析中7种基本子囊型归纳方法的具体介绍,令相关内容的学习留下疑惑。本文从顺序四分子两基因连锁遗传分析过程中涉及的3种四分子类型(PD、NPD和T)与两基因4种分离时期组合(ⅠⅠ,ⅡⅡ,ⅠⅡ,ⅡⅠ)的相互关系入手,设计表格,直观展现了二者的12种可能组合结果(3×4=12),并应用直观的对错符号(√、×),同时结合表后的3项分析,排除了其中的5种组合形式,最终归纳得到7种基本子囊型。本文提供了7种基本子囊型具体的归纳分析方法,解决了相关教学内容的论述不足问题,以期为真菌类顺序四分子遗传分析的教学提供帮助。