Abundant well-preserved large articulated sponge fossils and isolated spicules have been reported from the Early Cambrian Hetang Formation, southern Anhui Province. This unique epifaunal fossil assemblage dominated by...Abundant well-preserved large articulated sponge fossils and isolated spicules have been reported from the Early Cambrian Hetang Formation, southern Anhui Province. This unique epifaunal fossil assemblage dominated by articulated sponge fossils is called the Xidi Sponge Fauna. The sponge fauna lived in a quiet oxygenic environment be- low the storm wave base. Bloom of phytoplankton and rapid sedimentation rate resulted in the deposition of the black shales. Sufficient food supply, lack of other competitors, abundant ecological niches, and demand for oxygen during early Cambrian were in favor of the diversification and evo- lution of large sponges in the Early Cambrian.展开更多
The Sphinx is an enigmatic monster in Greek my-thology that had the body of a lion, wings of a bird, and head and bust of a woman. As the myth goes, the Sphinx guarded the gate to Thebes and would kill anyone unableto...The Sphinx is an enigmatic monster in Greek my-thology that had the body of a lion, wings of a bird, and head and bust of a woman. As the myth goes, the Sphinx guarded the gate to Thebes and would kill anyone unableto answer her riddle. The Sphinx riddle was eventuallycorrectly solved by Oedipus who later became the king of Thebes.展开更多
Gene selection (feature selection) is generally pertormed in gene space(feature space), where a very serious curse of dimensionality problem always existsbecause the number of genes is much larger than the number of s...Gene selection (feature selection) is generally pertormed in gene space(feature space), where a very serious curse of dimensionality problem always existsbecause the number of genes is much larger than the number of samples in gene space(G-space). This results in difficulty in modeling the data set in this space and the lowconfidence of the result of gene selection. How to find a gene subset in this case is achallenging subject. In this paper, the above G-space is transformed into its dual space,referred to as class space (C-space) such that the number of dimensions is the verynumber of classes of the samples in G-space and the number of samples in C-space isthe number of genes in G-space. it is obvious that the curse of dimensionality in C-spacedoes not exist. A new gene selection method which is based on the principle of separatingdifferent classes as far as possible is presented with the help of Principal ComponentAnalysis (PCA). The experimental results on gene selection for real data set areevaluated with Fisher criterion, weighted Fisher criterion as well as leave-one-out crossvalidation, showing that the method presented here is effective and efficient.展开更多
This paper presents a coupled neural network, called output-threshold coupled neural network (OTCNN), which can mimic the autowaves in the present pulsed coupled neural networks (PCNNs), by the construction of mutual ...This paper presents a coupled neural network, called output-threshold coupled neural network (OTCNN), which can mimic the autowaves in the present pulsed coupled neural networks (PCNNs), by the construction of mutual coupling between neuron outputs and the threshold of a neuron. Based on its autowaves, this paper presents a method for finding the shortest path in shortest time with OTCNNs. The method presented here features much fewer neurons needed, simplicity of the structure of the neurons and the networks, and large scale of parallel computation. It is shown that OTCNN is very effective in finding the shortest paths from a single start node to multiple destination nodes for asymmetric weighted graph, with a number of iterations proportional only to the length of the shortest paths, but independent of the complexity of the graph and the total number of existing paths in the graph. Finally, examples for finding the shortest path are presented.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.50278041)supported by the Key Invite Public Bidding Project for Social Development of Jiangsu Province(Grant No.BS2002049)+1 种基金the Key Laboratory Foundation of Environmental Engineering of Jiangsu Province(Grant No.KF040002)funded by the US National Science Foundation(USA,NSF,Grant No.BES-0201849).
文摘Abundant well-preserved large articulated sponge fossils and isolated spicules have been reported from the Early Cambrian Hetang Formation, southern Anhui Province. This unique epifaunal fossil assemblage dominated by articulated sponge fossils is called the Xidi Sponge Fauna. The sponge fauna lived in a quiet oxygenic environment be- low the storm wave base. Bloom of phytoplankton and rapid sedimentation rate resulted in the deposition of the black shales. Sufficient food supply, lack of other competitors, abundant ecological niches, and demand for oxygen during early Cambrian were in favor of the diversification and evo- lution of large sponges in the Early Cambrian.
文摘The Sphinx is an enigmatic monster in Greek my-thology that had the body of a lion, wings of a bird, and head and bust of a woman. As the myth goes, the Sphinx guarded the gate to Thebes and would kill anyone unableto answer her riddle. The Sphinx riddle was eventuallycorrectly solved by Oedipus who later became the king of Thebes.
文摘Gene selection (feature selection) is generally pertormed in gene space(feature space), where a very serious curse of dimensionality problem always existsbecause the number of genes is much larger than the number of samples in gene space(G-space). This results in difficulty in modeling the data set in this space and the lowconfidence of the result of gene selection. How to find a gene subset in this case is achallenging subject. In this paper, the above G-space is transformed into its dual space,referred to as class space (C-space) such that the number of dimensions is the verynumber of classes of the samples in G-space and the number of samples in C-space isthe number of genes in G-space. it is obvious that the curse of dimensionality in C-spacedoes not exist. A new gene selection method which is based on the principle of separatingdifferent classes as far as possible is presented with the help of Principal ComponentAnalysis (PCA). The experimental results on gene selection for real data set areevaluated with Fisher criterion, weighted Fisher criterion as well as leave-one-out crossvalidation, showing that the method presented here is effective and efficient.
文摘This paper presents a coupled neural network, called output-threshold coupled neural network (OTCNN), which can mimic the autowaves in the present pulsed coupled neural networks (PCNNs), by the construction of mutual coupling between neuron outputs and the threshold of a neuron. Based on its autowaves, this paper presents a method for finding the shortest path in shortest time with OTCNNs. The method presented here features much fewer neurons needed, simplicity of the structure of the neurons and the networks, and large scale of parallel computation. It is shown that OTCNN is very effective in finding the shortest paths from a single start node to multiple destination nodes for asymmetric weighted graph, with a number of iterations proportional only to the length of the shortest paths, but independent of the complexity of the graph and the total number of existing paths in the graph. Finally, examples for finding the shortest path are presented.
