Skeleton-Based Volumetric Parameterizations for Lattice Structures

Lattice structures with excellent physical properties have attracted great research interest.In this paper,a novel volume parametric modeling method based on the skeleton model is proposed for the construction of threedimensional lattice structures.The skeleton model is divided into three types of nodes.And the corresponding algorithms are utilized to construct diverse types of volume parametric nodes.The unit-cell is assembled with distinct nodes according to the geometric features.The final lattice structure is created by the periodic arrangement of unit-cells.Several different types of volume parametric lattice structures are constructed to prove the stability and applicability of the proposed method.The quality is assessed in terms of the value of the Jacobian matrix.Moreover,the volume parametric lattice structures are tested with the isogeometric analysis to verify the feasibility of integration of modeling and simulation.

Research on Link Duration for Mobile Multihop Communication Networks

Mobile multihop communication network is an important branch of modern mobile communication system, and is an important technical support for ubiquitous communication. The random movement of the nodes makes the networking be more flexible, but the frequently changing topology will decrease the link duration between nodes significantly, which will increase the packets loss probability and affect the network communication performance. Aiming at the problem of declining link duration caused by nomadic characteristics in mobile multihop communication network, four link duration models for possible moving states are established based on different features in real networking process in this paper, which will provide reliable criterion for the optimal routing selection. Model analysis and simulation results show that the reliable route established by the proposed model will effectively extend the link duration, and can enhance the global stability of the mobile multihop information transmission, so as to provide new option to transmission reliability improvement for the mobile communication network.

Effects of external stimuli on the pacemaker function of the sinoatrial node in sodium channel gene mutations models

Loss of function and gain of function mutations of the sodium channel were investigated using an intact two-dimensional rabbit sinoatrial node (SAN) and atrial cell model. The effects of three external stimuli (acetylcholine secretion by the vagal nerve, acid-base concentration, and tissue temperature) on cardiac pacemaker function and conduction were studied. Our results show that these two groups of mutations have different effects on pacemaker function and conduction. Furthermore, we found that the negative effects of these mutations could be altered by external stimuli. The bradycardic effects of mutations were magnified by an increase in acetylcholine level. Changes in acid-base concentration and tissue temperature increased the ability of the SAN to recover its pacemaker function. The results of this study increase our understanding of sodium channel disorders, and help to advance research on the treatment of these conditions.

Species-or genus-dependent immunostimulatory effects of gut-derived potential probiotics

The immune regulatory effects of probiotics have been widely recognized to be strain-specific.However,it is unknown if there is a species-or genus-dependent manner.In this study,we use an in vitro mesenteric lymph node(MLN)model to systematically evaluate the immunostimulatory effects of gut-derived potential probiotics.The results exhibit an obvious species or genus consensus immune response pattern.RNA-seq shows that T cell-dependent B cell activation and antibody responses may be inherent to this model.Of the five tested genera,Akkermansia spp.and Clostridium butyrium directly activate the immune response in vitro,as indicated by the secretion of interleukin-10.Bifidobacterium spp.and Bacteroides spp.activate immune response with the help of stimuli(anti-CD3 and anti-CD28 antibodies).Lactobacillus spp.blunt the immune response with or without stimuli.Further investigations show that the cell surface protein of A.muciniphila AH39,which may serve as a T cell receptor cognate antigen,might evoke an in vitro immune activation.In vivo,oral administration of A.muciniphila AH39 influences the proportion of T regulatory cells(Tregs)in MLNs and the spleen under homeostasis in both specific pathogen-free and germ-free mice.All these findings indicate the distinct effects of different genera or species of potential gut-derived probiotics on intestinal and systemic immunity.

Urban traffic congestion propagation and bottleneck identification

Bottlenecks in urban traffic network are sticking points in restricting network collectivity traffic efficiency. To identify network bottlenecks effectively is a foundational work for improving network traffic condition and preventing traffic congestion. In this paper, a congestion propagation model of urban network traffic is proposed based on the cell transmission model （CTM）. The proposed model includes a link model, which describes flow propagation on links, and a node model, which represents link-to-link flow propagation. A new method of estimating average journey velocity （AJV） of both link and network is developed to identify network congestion bottlenecks. A numerical example is studied in Sioux Falls urban traffic network. The proposed model is employed in simulating network traffic propagation and congestion bottleneck identification under different traffic demands. The simulation results show that continual increase of traffic demand is an immediate factor in network congestion bottleneck emergence and increase as well as reducing network collectivity capability. Whether a particular link will become a bottleneck is mainly determined by its position in network, its traffic flow （attributed to different OD pairs） component, and network traffic demand.

Latent Co-interests' Relationship Prediction

With the development of the social media and Internet, discovering latent information from massive information is becoming particularly relevant to improving user experience. Research efforts based on preferences and relationships between users have attracted more and more attention. Predictive problems, such as inferring friend relationship and co-author relationship between users have been explored. However, many such methods are based on analyzing either node features or the network structures separately, few have tried to tackle both of them at the same time. In this paper, in order to discover latent co-interests＇ relationship, we not only consider users＇ attributes but network information as well. In addition, we propose an Interest-based Factor Graph Model （I-FGM） to incorporate these factors. Experiments on two data sets （bookmarking and music network） demonstrate that this predictive method can achieve better results than the other three methods （ANN, NB, and SVM）.