On s-hamiltonian line graphs of claw-free graphs

For an integer $s\ge 0$, a graph $G$ is $s$-hamiltonian if for any vertex subset $S?V\left(G\right)$ with $\left|S\right|\le s$, $G?S$ is hamiltonian, and $G$ is $s$-hamiltonian connected if for any vertex subset $S?V\left(G\right)$ with $\left|S\right|\le s$, $G?S$ is hamiltonian connected. Thomassen in 1984 conjectured that every 4-connected line graph is hamiltonian (see Thomassen, 1986), and Ku?zel and Xiong in 2004 conjectured that every 4-connected line graph is hamiltonian connected (see Ryjá?ek and Vrána, 2011). In Broersma and Veldman (1987), Broersma and Veldman raised the characterization problem of $s$-hamiltonian line graphs. In Lai and Shao (2013), it is conjectured that for $s\ge 2$, a line graph $L\left(G\right)$ is $s$-hamiltonian if and only if $L\left(G\right)$ is $(s+2)$-connected. In this paper we prove the following.(i) For an integer $s\ge 2$, the line graph $L\left(G\right)$ of a claw-free graph $G$ is $s$-hamiltonian if and only if $L\left(G\right)$ is $(s+2)$-connected.(ii) The line graph $L\left(G\right)$ of a claw-free graph $G$ is 1-hamiltonian connected if and only if $L\left(G\right)$ is 4-connected.     

Strain induced strengthening of soft thermoplastic polyurethanes under cyclic deformation

We investigate the cyclic mechanical behavior in uniaxial tension of three different commercial thermoplastic polyurethane elastomers (TPU) often considered as a sustainable replacement for common filled elastomers. All TPU have similar hard segment contents and linear moduli but sensibly different large strain properties as shown by X-ray analysis. Despite these differences, we found a stiffening effect after conditioning in step cyclic loading which greatly differs from the common softening (also referred as Mullins effect) observed in chemically crosslinked filled rubbers. We propose that this self-reinforcement is related to the fragmentation of hard domains, naturally present in TPU, in smaller but more numerous sub-units that may act as new physical crosslinking points. The proposed stiffening mechanism is not dissimilar to the strain-induced crystallization observed in stretched natural rubber, but it presents a persistent nature. In particular, it may cause a local reinforcement where an inhomogeneous strain field is present, as is the case of a crack propagating in cyclic fatigue, providing a potential explanation for the well-known toughness and wear resistance of TPU.     

Association between the microbiomes of tonsil and saliva samples isolated from pediatric patients subjected to tonsillectomy for the treatment of tonsillar hyperplasia

Oral microbes have the capacity to spread throughout the gastrointestinal system and are strongly associated with multiple diseases. Given that tonsils are located between the oral cavity and the laryngopharynx at the gateway of the alimentary and respiratory tracts, tonsillar tissue may also be affected by microbiota from both the oral cavity (saliva) and the alimentary tract. Here, we analyzed the distribution and association of the microbial communities in the saliva and tonsils of Korean children subjected to tonsillectomy because of tonsil hyperplasia (n = 29). The microbiome profiles of saliva and tonsils were established via 16S rRNA gene sequencing. Based on the alpha diversity indices, the microbial communities of the two groups showed high similarities. According to Spearman’s ranking correlation analysis, the distribution of Treponema, the causative bacterium of periodontitis, in saliva and tonsils was found to have a significant positive correlation. Two representative microbes, Prevotella in saliva and Alloprevotella in tonsils, were negatively correlated, while Treponema 2 showed a strong positive correlation between saliva and tonsils. Taken together, strong similarities in the microbial communities of the tonsils and saliva are evident in terms of diversity and composition. The saliva microbiome is expected to significantly affect the tonsil microbiome. Furthermore, we suggest that our study creates an opportunity for tonsillar microbiome research to facilitate the development of novel microbiome-based therapeutic strategies.Subject terms: Comparative genomics, Metagenomics     

80.5 MeV/u碳离子诱发铜靶的放射性剩余产物测量

高能重带电粒子能直接穿透靶原子核外电子层,与原子核发生直接碰撞,发生散裂反应,产生一系列具有放射性的剩余产物核.重带电粒子诱发靶材放射性剩余核与辐射防护和人员安全有着密切联系,当前,大部分剩余核产额主要依靠蒙特卡罗粒子输运程序进行模拟计算,其准确程度亟需通过实验测量进行准确评估.本文利用能量为80.5 MeV/u的(12)^C⁶⁺粒子对薄铜靶开展了辐照实验与伽玛射线测量,结合伽玛谱学分析方法,得出了辐照产生的18种放射性剩余产物的初始活度和产生截面值,并与PHITS模拟结果进行对比.结果表明,PHITS模拟程序对放射性剩余核种类的估计具有较高可靠性,在其绝对产额方面,与实验测量仍具有较大偏差.     

Cobalt Based Nanoparticles Embedded Reduced Graphene Oxide Aerogel for Hydrogen Evolution Electrocatalyst

Efficient water electrolysis catalyst is highly demanded for the production of hydrogen as a sustainable energy fuel. It is reported that cobalt derived nanoparticle (CoS₂, CoP, CoS|P) decorated reduced graphene oxide (rGO) composite aerogel catalysts for highly active and reliable hydrogen evolution reaction electrocatalysts. 7 nm level cobalt derived nanoparticles are synthesized over graphene aerogel surfaces with excellent surface coverage and maximal expose of active sites. CoS|P/rGO hybrid aerogel composites show an excellent catalytic activity with overpotential of ≈169 mV at a current density of ≈10 mA cm^?2. Accordingly, efficient charge transfer is attained with Tafel slope of ≈52 mV dec^?1 and a charge transfer resistance (R_ct) of ≈12 Ω. This work suggests a viable route toward ultrasmall, uniform nanoparticles decorated graphene surfaces with well‐controlled chemical compositions, which can be generally useful for various applications commonly requiring large exposure of active surface area as well as robust interparticle charger transfer.     

基于无人机多光谱图像的土壤水分检测方法研究

以表层土壤为对象,探究土壤的多光谱反射率与土壤水分含量相关性,进行基于无人机多光谱图像的土壤水分含量预测模型方法的探究。选取中国农业大学通州实验站为研究区域,实地采集试验田的土壤样本100组,按照一定梯度配制土壤含水量,配成的土壤含水率为10%~50%之间,土壤含量的真实值采用土壤烘干法进行测定。多光谱相机灵巧便捷,可搭载在无人机上对土壤进行监测。将RedEdged-M型多光谱相机搭载在Phantom 3型无人机上,选择阳光充足的采集环境,实时采集土壤样本的多光谱图像,建立土壤多光谱信息与水分含量之间的模型。利用处理光谱数据的ENVI5.3软件提取土壤样本多光谱信息,以多光谱相机自带的标准白板反射率为100%,计算出土壤样本在蓝、绿、红、红边、近红外五个波段的光谱反射率。采用BP神经网络算法、支持向量机算法、偏最小二乘算法分别建立基于无人机多光谱图像的土壤水分含量的预测模型。以80组土壤样本数据作为训练集,建立基于多光谱图像的土壤水分含量预测模型。采用莱文贝格-马夸特算法对BPNN进行改进,提高了其训练速度,当网络结构为5-10-1时,训练效果最好,本文选择该网络结构;SVM采取高斯核函数,当参数为0.56时,模型效果最好。本研究采用归一化均方根误差(NRMSE)和决策系数(R 2)对三种土壤水分含量的预测模型进行定量对比。以20组土壤样本数据作为测试集,结果可知,基于BP神经网络土壤水分含量预测模型的NRMSE为0.268,R 2为0.872;基于支持向量机的土壤水分含量预测模型的NRMSE为0.298,R 2为0.821;基于偏最小二乘土壤水分含量预测模型的NRMSE为0.316,R 2为0.789。对三种模型分析可知,基于BPNN的土壤水分含量预测模型效果均较好。结果可知,土壤的光谱反射率与含水率间存在较密切的相关性,将多光谱相机搭载在无人机上可以对土壤水分含量进行有效的实时监测,对监测土壤墒情提供技术支持和理论支撑。     

镧系金属一氢化物有效芯势研究

采用Cundari和Stevens等推导的有效芯势对镧系金属一氢化物进行了理论计算，以探讨镧系金属元素与氢的相互作用。结果表明所有镧系金属一氢化物基态时理论上是稳定的，最稳定的是SmH,最不稳定的是DyH;键长计算结果显示，基态时镧系金属一招兵买马花物有独立王国 收缩现象发生；红外振动频率理论计算值与实验结果一致；成键轨道中，金属原子轨道的贡献主要是s轨道和d轨道：从CeH至ErH(GdH)例外）随着外层电子的增加s轨道成分逐渐增大d轨道成分逐渐减小；从TmH和LuH（包括GdH)，成键轨道中金属原子轨道的贡献主要是d轨道，约为90％；约大多数镧系金属一氧化物的成键轨道中金属原子轨道f成分小于1％。     

微波消解-氢化物发生-原子荧光光谱法测定7种中草药中砷

利用原子荧光光谱法测定7种驱虫类中草药中的砷.实验采用微波消解样品,以盐酸为测定介质,硫脲-抗坏血酸为预还原剂,硼氢化钾为氢化剂,用氢化物发生-原子荧光光谱法测定砷含量.砷含量在10-100ng/mL浓度范围内线性关系好(r2=0.9924).回收率为93.83%-110.94%之间.方法简便、快速、灵敏、准确,可用于中草药中砷的测定.