To gain insight into the function of AOB and MOB during different social interaction and in different vole species,the behaviors and neural activation of the olfactory bulbs in social interactions of mandarin voles Mi...To gain insight into the function of AOB and MOB during different social interaction and in different vole species,the behaviors and neural activation of the olfactory bulbs in social interactions of mandarin voles Microtus mandarinus and reed voles Microtus fortis were compared in the present research.Mandarin voles spent significantly more time attacking and sniffing their opponents and sniffing sawdust than reed voles.During same sex encounters,mandarin voles attacked their opponents for a significantly longer time and sniffed its opponent for shorter time compared with male-female interactions.However,no significant behavioral differences were found during encounters of two individual reed voles,regardless of gender composition of the pair.Using c-Fos as an indicator of neural activation,we observed that neural activation was significantly higher in almost all sub-regions of the main olfactory bulb(MOB)and the accessory olfactory bulb(AOB)of mandarin voles compared with reed voles.Numbers of c-Fos-ir neurons in almost all sub-regions of the AOB and the MOB during male-female interactions were also higher than those in interactions of the same sex.Anterior-posterior ratios of Fos-ir neurons in the AOBM(AOBMR)and the AOBG(AOBGR)in male-female interaction were significantly higher than those in interaction of the same sex.The AOBMR of male mandarin voles and reed voles were larger than those of females in male-female interactions.Behavioral patterns are consistent with cellular activity patterns.Consistent level of neural activation in MOB and AOB suggests important roles of both the main olfactory bulb and the accessory olfactory bulb in social interaction in two species.展开更多
To discover and identify the influential nodes in any complex network has been an important issue.It is a significant factor in order to control over the network.Through control on a network,any information can be spr...To discover and identify the influential nodes in any complex network has been an important issue.It is a significant factor in order to control over the network.Through control on a network,any information can be spread and stopped in a short span of time.Both targets can be achieved,since network of information can be extended and as well destroyed.So,information spread and community formation have become one of the most crucial issues in the world of SNA(Social Network Analysis).In this work,the complex network of twitter social network has been formalized and results are analyzed.For this purpose,different network metrics have been utilized.Visualization of the network is provided in its original form and then filter out(different percentages)from the network to eliminate the less impacting nodes and edges for better analysis.This network is analyzed according to different centrality measures,like edge-betweenness,betweenness centrality,closeness centrality and eigenvector centrality.Influential nodes are detected and their impact is observed on the network.The communities are analyzed in terms of network coverage considering theMinimum Spanning Tree,shortest path distribution and network diameter.It is found that these are the very effective ways to find influential and central nodes from such big social networks like Facebook,Instagram,Twitter,LinkedIn,etc.展开更多
基金supported by National Natural Science Foundation of China(No.30670273No.30200026)Ministry of Education Key Project of Peoples Republic of China(20060718)
文摘To gain insight into the function of AOB and MOB during different social interaction and in different vole species,the behaviors and neural activation of the olfactory bulbs in social interactions of mandarin voles Microtus mandarinus and reed voles Microtus fortis were compared in the present research.Mandarin voles spent significantly more time attacking and sniffing their opponents and sniffing sawdust than reed voles.During same sex encounters,mandarin voles attacked their opponents for a significantly longer time and sniffed its opponent for shorter time compared with male-female interactions.However,no significant behavioral differences were found during encounters of two individual reed voles,regardless of gender composition of the pair.Using c-Fos as an indicator of neural activation,we observed that neural activation was significantly higher in almost all sub-regions of the main olfactory bulb(MOB)and the accessory olfactory bulb(AOB)of mandarin voles compared with reed voles.Numbers of c-Fos-ir neurons in almost all sub-regions of the AOB and the MOB during male-female interactions were also higher than those in interactions of the same sex.Anterior-posterior ratios of Fos-ir neurons in the AOBM(AOBMR)and the AOBG(AOBGR)in male-female interaction were significantly higher than those in interaction of the same sex.The AOBMR of male mandarin voles and reed voles were larger than those of females in male-female interactions.Behavioral patterns are consistent with cellular activity patterns.Consistent level of neural activation in MOB and AOB suggests important roles of both the main olfactory bulb and the accessory olfactory bulb in social interaction in two species.
文摘To discover and identify the influential nodes in any complex network has been an important issue.It is a significant factor in order to control over the network.Through control on a network,any information can be spread and stopped in a short span of time.Both targets can be achieved,since network of information can be extended and as well destroyed.So,information spread and community formation have become one of the most crucial issues in the world of SNA(Social Network Analysis).In this work,the complex network of twitter social network has been formalized and results are analyzed.For this purpose,different network metrics have been utilized.Visualization of the network is provided in its original form and then filter out(different percentages)from the network to eliminate the less impacting nodes and edges for better analysis.This network is analyzed according to different centrality measures,like edge-betweenness,betweenness centrality,closeness centrality and eigenvector centrality.Influential nodes are detected and their impact is observed on the network.The communities are analyzed in terms of network coverage considering theMinimum Spanning Tree,shortest path distribution and network diameter.It is found that these are the very effective ways to find influential and central nodes from such big social networks like Facebook,Instagram,Twitter,LinkedIn,etc.
