原子结构的k序与强子谱的相似性

原子结构的k序是原子能级结构的重要表示,k序性质可能对原子物理的教学有启发.本文在介绍k序性质的基础上,对k对称性与相似的强子谱的对称性进行了分析,指出k对称性破裂与强子谱对称性破裂有相似的起源.

原子能级的K序及对类碱离子基电子结构的应用

一、原子能级的 K 序与 H 序在原子和离子激发态能级次序及其特性的研究中,人们发现,对原子序数 Z≥11。

关于“k——序哈密尔顿图”一文的一点注记

本注记改正文［１］中一个引理的一点错误及引理证明中的失误。重新证明了若ｎ阶图Ｇ的任二不相邻顶点ｕ、ｖ有ｄ（ｕ）＋ｄ（ｖ）≥ｎ＋２ｋ－７，４≤ｋ≤ｎ，则对于Ｇ的任意不同的ｋ个顶点ｖ１，ｖ２，…，ｖｋ，有ｖ１（ｘ１）ｖ２（ｘ２）…ｖｋ－１（ｘｋ－１）ｖｋ型ｖ１—ｖｋ路（我们用ｖｉ（ｘｉ）ｖｉ＋１表示ｖｉｖｉ＋１或ｖｉｘｉｖｉ＋１。）或ｖｋｖ１（ｘ１）…（ｘｋ－２）ｖｋ－１型ｖｋ—ｖｋ－１路；若对任不相邻两顶点ｕ、ｖ有ｄ（ｕ）＋ｄ（ｖ）≥ｎ，则对于Ｇ中任三点ｖ１，ｖ２，ｖ３存在ｖ１（ｘ１）ｖ２（ｘ２）ｖ３型ｖ１—ｖ３路。最后对文［１］中的公开问题１提出自己的看法。

不一致决策表的k阶分配序约简

在不一致决策表中定义了k阶分配序约简,给出了k阶分配序一致集的判定定理。通过定义k阶分配序区分矩阵,给出了求k阶分配序约简的区分矩阵法。为了克服区分矩阵法时间复杂度过高的缺陷,通过定义属性的相对重要性,提出了一种求k阶分配序约简的启发式算法,分析得到该算法的时间复杂度是多项式的结论。实例验证了算法的有效性。

Novel K-best detection algorithms for MIMO system

Aiming at the optimum path excluding characteristics and the full constellation searching characteristics of the K-best detection algorithm, an improved-performance K-best detection algorithm and several reduced-complexity K-best detection algorithms are proposed. The improved-performance K-best detection algorithm deploys minimum mean square error （MMSE） filtering of a channel matrix before QR decomposition. This algorithm can decrease the probability of excluding the optimum path and achieve better performance. The reducedcomplexity K-best detection algorithms utilize a sphere decoding method to reduce searching constellation points. Simulation results show that the improved performance K-best detection algorithm obtains a 1 dB performance gain compared to the K- best detection algorithm based on sorted QR decomposition （SQRD）. Performance loss occurs when K = 4 in reduced complexity K-best detection algorithms. When K = 8, the reduced complexity K-best detection algorithms require less computational effort compared with traditional K-best detection algorithms and achieve the same performance.

Influential Node Ranking and Invulnerability of Air Traffic Cyber Physical System

To ensure flight safety,the complex network method is used to study the influence and invulnerability of air traffic cyber physical system(CPS)nodes.According to the rules of air traffic management,the logical coupling relationship between routes and sectors is analyzed,an air traffic CPS network model is constructed,and the indicators of node influence and invulnerability are established.The K-shell algorithm is improved to identify node influence,and the invulnerability is analyzed under random and selective attacks.Taking Airspace in Eastern China as an example,its influential nodes are sorted by degree,namely,K-shell,the improved K-shell(IKS)and betweenness centrality.The invulnerability of air traffic CPS under different attacks is analyzed.Results show that IKS can effectively identify the influential nodes in the air traffic CPS network,and IKS and betweenness centrality are the two key indicators that affect the invulnerability of air traffic CPS.

Learning taxis' cruising patterns with Ripley's K function

Taxi drivers' cruising patterns are learnt with GPS trajectory data collected in Shenzhen, China. By employing Ripley's K function, the impacts of land use and pick-up experience on taxis' cruising behavior are investigated concerning about both intensity of influence and radius of influence. The results indicate that, in general, taxi drivers tend to learn more from land use characteristics than from pick-up experience. The optimal radius of influence of land use points and previous pick-up points is 14.18 km and 9.93 km, respectively. The findings also show that the high-earning drivers or thorough drivers pay more attention to land use characteristics and tend to cruise in high-density area, while the low-earning drivers or focus drivers prefer to learn more from previous pick-up experience and select the area which is far away from the high-density area. These findings facilitate the development of measures of managing taxi's travel behavior by providing useful insights into taxis' cruising patterns. The results also provide useful advice for taxi drivers to make efficient cruising decision, which will contribute to the improvement of cruising efficiency and the reduction of negative effects.

干扰控制K均值序贯泛化二维地震信号去噪

K均值序贯泛化(SGK)去噪算法在字典更新阶段会引入噪声干扰。为了控制噪声干扰对字典原子的影响,构建一种干扰控制K均值序贯泛化(C-SGK)地震信号去噪算法。该算法在字典更新阶段通过判断信噪比值与设定阈值间的大小来决定是否更新原子。若信噪比值大于设定阈值,则顺序更新原子,反之则不更新原子。对人工合成和实际地震信号的去噪结果表明,本算法能够很好地控制噪声干扰,且与传统SGK算法比较发现,本文算法对地震信号的去噪效果更优。

THE 2-ERROR LINEAR COMPLEXITY OF 2~n-PERIODIC BINARY SEQUENCES WITH LINEAR COMPLEXITY 2~n-1

Linear complexity and k-error linear complexity of the stream cipher are two important standards to scale the randomicity of keystreams. For the 2n -periodicperiodic binary sequence with linear complexity 2n 1and k = 2,3,the number of sequences with given k-error linear complexity and the expected k-error linear complexity are provided. Moreover,the proportion of the sequences whose k-error linear complexity is bigger than the expected value is analyzed.

Biological Characteristics and Genome of Pardosa pseudoannulata

At the moment,little is found on the whole genomes of spiders in public databases.To this end,this study aimed to analyze the morphology,biological characteristics,and genome of Pardosa pseudoannulata,which was expected to add genome information of spiders.To be specific,Illumina sequencing was used to sequence the genome of this spider species,and K-mer(K=17)analysis to estimate the size,heterozygosity,and repetitiveness of the genome.More than 142.11 Gb high-quality reads were obtained,which were assembled into 3508.13 Mb contigs(N50=1035 bp)and 3542.56 Mb scaffolds(N50=1258 bp).Two peaks were found in the 17-mer distribution map.The genome of P.pseudoannulata was 4696.86 Mb,with the heterozygosity of 0.21%and 84.32%of repetitive sequences.This indicated that repetitive sequences were highly abundant in the genome of P.pseudoannulata and multi-generation selfing before genome sequencing can reduce the repetitiveness.In addition,NOVOheter can be used for genome assembly.This study layed a basis for the publication of spider genome data and provided a reference for the research on spider genomics.

Speech detection method based on a multi-window analysis

Aiming at the poor performance of speech signal detection at low signal-to-noise ratio(SNR),a method is proposed to detect active speech frames based on multi-window time-frequency(T-F)diagrams.First,the T-F diagram of the signal is calculated based on a multi-window T-F analysis,and a speech test statistic is constructed based on the characteristic difference between the signal and background noise.Second,the dynamic double-threshold processing is used for preliminary detection,and then the global double-threshold value is obtained using K-means clustering.Finally,the detection results are obtained by sequential decision.The experimental results show that the overall performance of the method is better than that of traditional methods under various SNR conditions and background noises.This method also has the advantages of low complexity,strong robustness,and adaptability to multi-national languages.

Research on natural language recognition algorithm based on sample entropy

Sample entropy can reflect the change of level of new information in signal sequence as well as the size of the new information. Based on the sample entropy as the features of speech classification, the paper firstly extract the sample entropy of mixed signal, mean and variance to calculate each signal sample entropy, finally uses the K mean clustering to recognize. The simulation results show that： the recognition rate can be increased to 89.2% based on sample entropy.

结直肠腺瘤,单原发及多原发结直肠癌中P53及K-ras基因的突变分析

目的探讨结直肠腺瘤、单原发结直肠癌、多原发结直肠癌中P53及K-ras基因的突变。方法收集25例正常结直肠组织、38例结直肠腺瘤、78例单原发结直肠癌、19例(同时性多原发癌7例,异时性多原发癌12例)多原发结直肠癌组织标本及患者临床病理资料,提取标本组织中基因组DNA,直接测序方法进行P53基因外显子5、6、7、8及K-ras基因密码子12、13序列分析,并对结直肠腺瘤及单原发结直肠癌的临床资料与其P53及K-ras基因突变进行多因素相关性分析。结果正常结直肠组织、结直肠腺瘤、单原发结直肠癌、多原发结直肠癌中P53基因的突变概率分别是0%(0/25)、44.8%(17/38)、43.6%(34/78)、42.1%(8/19),K-ras基因的突变概率分别为0%(0/25)、18.4%(7/38)、39.7%(31/78)、47.4%(9/19),正常结直肠组织中P53和K-ras基因突变概率与结直肠腺瘤、单原发结直肠癌、多原发结直肠癌中突变概率相比,差异均有统计学意义(P<0.05),结直肠腺瘤中K-ras基因突变概率与单原发结直肠癌、多原发结直肠癌中突变概率相比,差异均有统计学意义(P<0.05),结直肠腺瘤中P53基因突变概率高于K-ras基因(P<0.05)。P53及K-ras基因在单原发结直肠癌的Ⅰ、Ⅱ期及高分化类型中的突变概率与其在Ⅲ、Ⅳ期及中低分化类型中差异无统计学意义。患者的年龄、性别、家族史、肿瘤位置与结直肠腺瘤及单原发结直肠癌中P53及K-ras基因突变无相关性,肿瘤分期及肿瘤的分化程度亦不是单原发结直肠癌中P53及K-ras基因发生突变的危险因素。结论本研究再次证实在结直肠肿瘤的发生和发展过程中,P53及K-ras基因的突变起着重要的作用,并且在结直肠的肿瘤发生发展过程中P53基因的突变可能早于K-ras基因。

N-Spaces and mssc-Images of Metric Spaces

In this paper, we give some characterizations of N-spaces by mssc-images ofmetric spaces, and prove that a space X is an N-space if and only if X is a sequence-covering (sequentially quotient) mssc-image of a metric space, which answer a conjectureon N-spaces affirmatively.