The alien red turpentine beetle （RTB）, Dendroctonus valens LeConte, is one of the most economically destructive forest pests in China, having killed more than 6 million pines in recent years. There is a need to unde...The alien red turpentine beetle （RTB）, Dendroctonus valens LeConte, is one of the most economically destructive forest pests in China, having killed more than 6 million pines in recent years. There is a need to understand the basic biology and ecology of the beetle in order to develop an effective monitoring and management strategy. In this study, the effects of hillside exposure （south- and north-facing）, host-tree locations according to relief （valley, mid-slope, and ridge-top） and tree diameters on RTB colonization were investigated in one valley （3 sites）. The results showed that （i） RTB clearly preferred colonizing pines growing on south-facing hillsides, especially in the valley; （ii） RTB preferred to colonize the pines growing at the valley rather than pines growing at mid-slope or on ridge-top; （iii） RTB preferred to colonize trees with large diameter over small and medium-sized pines; （iv） the attack density of RTBs （measured by pitch tubes/pine） was obviously higher on larger trees standing in the valley than other trees standing at other places. We conclude from RTB colonization patterns, that RTB prefers to attack large trees in the valley, which may be useful in developing a pest-management strategy.展开更多
Independent component analysis （ICA） is a widely used method for blind source separation （BSS）. The mature ICA model has a restriction that the number of the sources must equal to that of the sensors used to colle...Independent component analysis （ICA） is a widely used method for blind source separation （BSS）. The mature ICA model has a restriction that the number of the sources must equal to that of the sensors used to collect data, which is hard to meet in most practical cases. In this paper, an overdetermined ICA method is proposed and successfully used in the analysis of human colonic pressure signals. Using principal component analysis （PCA）, the method estimates the number of the sources firstly and reduces the dimensions of the observed signals to the same with that of the sources; and then, Fast- ICA is used to estimate all the sources. From 26 groups of colonic pressure recordings, several colonic motor patterns are extracted, which riot only prove the effectiveness of this method, but also greatly facilitate further medical researches.展开更多
基金This study was funded by the National Natural Science Foundation of China （Project 30525009 and 30621003） and Beijing Science and Technology Commission （D0705002040391）. Workers at Chakou Forest Farm, Gujiao, Shanxi Province, provided technical assistance in the field. We thank Emily Wheeler for editorial assistance.
文摘The alien red turpentine beetle （RTB）, Dendroctonus valens LeConte, is one of the most economically destructive forest pests in China, having killed more than 6 million pines in recent years. There is a need to understand the basic biology and ecology of the beetle in order to develop an effective monitoring and management strategy. In this study, the effects of hillside exposure （south- and north-facing）, host-tree locations according to relief （valley, mid-slope, and ridge-top） and tree diameters on RTB colonization were investigated in one valley （3 sites）. The results showed that （i） RTB clearly preferred colonizing pines growing on south-facing hillsides, especially in the valley; （ii） RTB preferred to colonize the pines growing at the valley rather than pines growing at mid-slope or on ridge-top; （iii） RTB preferred to colonize trees with large diameter over small and medium-sized pines; （iv） the attack density of RTBs （measured by pitch tubes/pine） was obviously higher on larger trees standing in the valley than other trees standing at other places. We conclude from RTB colonization patterns, that RTB prefers to attack large trees in the valley, which may be useful in developing a pest-management strategy.
基金supported by National Natural Science Foundation(No.60875061)
文摘Independent component analysis （ICA） is a widely used method for blind source separation （BSS）. The mature ICA model has a restriction that the number of the sources must equal to that of the sensors used to collect data, which is hard to meet in most practical cases. In this paper, an overdetermined ICA method is proposed and successfully used in the analysis of human colonic pressure signals. Using principal component analysis （PCA）, the method estimates the number of the sources firstly and reduces the dimensions of the observed signals to the same with that of the sources; and then, Fast- ICA is used to estimate all the sources. From 26 groups of colonic pressure recordings, several colonic motor patterns are extracted, which riot only prove the effectiveness of this method, but also greatly facilitate further medical researches.
