Objective: To evaluate the clinical and radiological factors that affect therecurrence of the meningioma patient so as to effectively prevent and cure recurrence of meningiomapatients more earlier. Methods: The clinic...Objective: To evaluate the clinical and radiological factors that affect therecurrence of the meningioma patient so as to effectively prevent and cure recurrence of meningiomapatients more earlier. Methods: The clinical features and radiological aspects in 145 cases ofmeningiomas undergoing operation during 1993-1997 were retrospectively studied. The data of only 83cases of all 145 cases were available. The factors were evaluated with univariate and multivariateanalysis. Results: With univariate analysis, 7 factors showed highly significance to recurrence ofmeningiomas: tumor size, tumor location, tumor shape, edema, extent of resection, pathologicalgrade, CT enhancement. With multivariate analysis, 4 factors showed significant danger to recurrenceof meningiomas: pathological grade, extent of resection, tumor shape and CT enhancement.Conclusion: The main factors that affect the recurrence of meningioma patients are pathologicalgrade, extent of resection, tumor shape and CT enhancement.展开更多
The archaeological site of the Sanxingdui may date back as far as 5,000 years ago. The typical profiles of Palaeo-Stagnic-Anthrosols near the ancient site were selected, which aimed to identify diagnostic horizons emp...The archaeological site of the Sanxingdui may date back as far as 5,000 years ago. The typical profiles of Palaeo-Stagnic-Anthrosols near the ancient site were selected, which aimed to identify diagnostic horizons employing methodology of soil taxonomic classification and to reveal the micromorphological properties of the paleosols. Under long-term anthropogenic mellowing, the discernible differentiation between anthrostagnic epipedon and its subhorizons as well as hydragric horizon and its subhorizons occurred in Paleo-Stagnie-Anthrosols at the archaeological site of the Sanxingdui. The mieromorphological properties diversified among each specific diagnostic subhorizon, e.g., the developed microstructure in cultivated subhorizon within anthrostagnic epipedon, closely arranged particles and considerable micropores beneficial to both of water conservation and filtration in plow subhorizon within anthrostagnic epipedon, and automorphic optical-orientation clays and calcareous corrosion in hydragric horizons. The findings above of micromorphological features related with diagnostic horizons are significant for soil taxonomic classification.展开更多
Fertile topsoil was added onto the surface of barren slope land in Three Gorges Reservoir region of China in an anthropogenic process known as the foreign soil reconstruction project. The main goal of this paper was t...Fertile topsoil was added onto the surface of barren slope land in Three Gorges Reservoir region of China in an anthropogenic process known as the foreign soil reconstruction project. The main goal of this paper was to reveal the influence of anthropogenic activities on pedogenic processes and soil classifications. Chemical weathering indices and comparative analysis were applied to discuss changes in geochemical compositions and weathering features of purplish soils(Cambisols) before and after the project. Results showed that:(1) The foreign soil reconstruction project slightly altered the major element composition of topsoil and improved the soil structure. Although the distributions of major elements in the original topsoil, original subsoil, foreign topsoil and newly constructed topsoil were all similar to that in upper continental crust, newly constructed topsoil was the most similar soil.(2) The chemical index of alteration was more sensitive than the weathering index of Parker at indicating chemical weathering status of purplish soil. The chemical weathering status of newly constructed topsoil was higher than that of the original topsoil and lower than that of foreign topsoil.(3) Anthropogenic activities may provide a promising new thought for the anthropogenic soil classification system. The scope and subgroups of Anthrosols should be extended and strengthened. Or there may be a need to combine Anthrosols and Technosols orders to create a new soil order. The results may be used for optimizing soil mellowing engineering activities and enriching the soil classification system.展开更多
Urticaceae Juss.is a large cosmopolitan family and taxonomically difficult group,partly because it encompasses a broad range of morphological diversity and many of the diagnostic characters（e.g.flower,achene.stipule,...Urticaceae Juss.is a large cosmopolitan family and taxonomically difficult group,partly because it encompasses a broad range of morphological diversity and many of the diagnostic characters（e.g.flower,achene.stipule,bract）require a microscope for accurate determination.Meanwhile,most Uriiceae species have stinging hairs which make them more difficult to collect and identify.As a result,the infra-familial classification of Urticaceae has been controversial for more than a century.A research group led by Prof.展开更多
In some image classification tasks, similarities among different categories are different and the samples are usually misclassified as highly similar categories. To distinguish highly similar categories, more specific...In some image classification tasks, similarities among different categories are different and the samples are usually misclassified as highly similar categories. To distinguish highly similar categories, more specific features are required so that the classifier can improve the classification performance. In this paper, we propose a novel two-level hierarchical feature learning framework based on the deep convolutional neural network(CNN), which is simple and effective. First, the deep feature extractors of different levels are trained using the transfer learning method that fine-tunes the pre-trained deep CNN model toward the new target dataset. Second, the general feature extracted from all the categories and the specific feature extracted from highly similar categories are fused into a feature vector. Then the final feature representation is fed into a linear classifier. Finally, experiments using the Caltech-256, Oxford Flower-102, and Tasmania Coral Point Count(CPC) datasets demonstrate that the expression ability of the deep features resulting from two-level hierarchical feature learning is powerful. Our proposed method effectively increases the classification accuracy in comparison with flat multiple classification methods.展开更多
The explosive growth ofmalware variants poses a major threat to information security. Traditional anti-virus systems based on signatures fail to classify unknown malware into their corresponding families and to detect...The explosive growth ofmalware variants poses a major threat to information security. Traditional anti-virus systems based on signatures fail to classify unknown malware into their corresponding families and to detect new kinds of malware pro- grams. Therefore, we propose a machine learning based malware analysis system, which is composed of three modules： data processing, decision making, and new malware detection. The data processing module deals with gray-scale images, Opcode n-gram, and import fimctions, which are employed to extract the features of the malware. The decision-making module uses the features to classify the malware and to identify suspicious malware. Finally, the detection module uses the shared nearest neighbor （SNN） clustering algorithm to discover new malware families. Our approach is evaluated on more than 20 000 malware instances, which were collected by Kingsoft, ESET NOD32, and Anubis. The results show that our system can effectively classify the un- known malware with a best accuracy of 98.9%, and successfully detects 86.7% of the new malware.展开更多
In this paper, firstly, target candidate regions are extracted by combining maximum symmetric surround saliency detection algorithm with a cellular automata dynamic evolution model. Secondly, an eigenvector independen...In this paper, firstly, target candidate regions are extracted by combining maximum symmetric surround saliency detection algorithm with a cellular automata dynamic evolution model. Secondly, an eigenvector independent of the ship target size is constructed by combining the shape feature with ship histogram of oriented gradient(S-HOG) feature, and the target can be recognized by Ada Boost classifier. As demonstrated in our experiments, the proposed method with the detection accuracy of over 96% outperforms the state-of-the-art method. efficiency switch and modulation.展开更多
The rarefied effect of gas flow in microchannel is significant and cannot be well described by traditional hydrodynamic models. It has been known that discrete Boltzmann model(DBM) has the potential to investigate flo...The rarefied effect of gas flow in microchannel is significant and cannot be well described by traditional hydrodynamic models. It has been known that discrete Boltzmann model(DBM) has the potential to investigate flows in a relatively wider range of Knudsen number because of its intrinsic kinetic nature inherited from Boltzmann equation.It is crucial to have a proper kinetic boundary condition for DBM to capture the velocity slip and the flow characteristics in the Knudsen layer. In this paper, we present a DBM combined with Maxwell-type boundary condition model for slip flow. The tangential momentum accommodation coefficient is introduced to implement a gas-surface interaction model.Both the velocity slip and the Knudsen layer under various Knudsen numbers and accommodation coefficients can be well described. Two kinds of slip flows, including Couette flow and Poiseuille flow, are simulated to verify the model.To dynamically compare results from different models, the relation between the definition of Knudsen number in hard sphere model and that in BGK model is clarified.展开更多
文摘Objective: To evaluate the clinical and radiological factors that affect therecurrence of the meningioma patient so as to effectively prevent and cure recurrence of meningiomapatients more earlier. Methods: The clinical features and radiological aspects in 145 cases ofmeningiomas undergoing operation during 1993-1997 were retrospectively studied. The data of only 83cases of all 145 cases were available. The factors were evaluated with univariate and multivariateanalysis. Results: With univariate analysis, 7 factors showed highly significance to recurrence ofmeningiomas: tumor size, tumor location, tumor shape, edema, extent of resection, pathologicalgrade, CT enhancement. With multivariate analysis, 4 factors showed significant danger to recurrenceof meningiomas: pathological grade, extent of resection, tumor shape and CT enhancement.Conclusion: The main factors that affect the recurrence of meningioma patients are pathologicalgrade, extent of resection, tumor shape and CT enhancement.
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No KZCX2-YW-409)
文摘The archaeological site of the Sanxingdui may date back as far as 5,000 years ago. The typical profiles of Palaeo-Stagnic-Anthrosols near the ancient site were selected, which aimed to identify diagnostic horizons employing methodology of soil taxonomic classification and to reveal the micromorphological properties of the paleosols. Under long-term anthropogenic mellowing, the discernible differentiation between anthrostagnic epipedon and its subhorizons as well as hydragric horizon and its subhorizons occurred in Paleo-Stagnie-Anthrosols at the archaeological site of the Sanxingdui. The mieromorphological properties diversified among each specific diagnostic subhorizon, e.g., the developed microstructure in cultivated subhorizon within anthrostagnic epipedon, closely arranged particles and considerable micropores beneficial to both of water conservation and filtration in plow subhorizon within anthrostagnic epipedon, and automorphic optical-orientation clays and calcareous corrosion in hydragric horizons. The findings above of micromorphological features related with diagnostic horizons are significant for soil taxonomic classification.
基金the National Key Technology Research and Development Program of the Ministry of Science and Technology of China (Grant No. 2012BAD05B06)
文摘Fertile topsoil was added onto the surface of barren slope land in Three Gorges Reservoir region of China in an anthropogenic process known as the foreign soil reconstruction project. The main goal of this paper was to reveal the influence of anthropogenic activities on pedogenic processes and soil classifications. Chemical weathering indices and comparative analysis were applied to discuss changes in geochemical compositions and weathering features of purplish soils(Cambisols) before and after the project. Results showed that:(1) The foreign soil reconstruction project slightly altered the major element composition of topsoil and improved the soil structure. Although the distributions of major elements in the original topsoil, original subsoil, foreign topsoil and newly constructed topsoil were all similar to that in upper continental crust, newly constructed topsoil was the most similar soil.(2) The chemical index of alteration was more sensitive than the weathering index of Parker at indicating chemical weathering status of purplish soil. The chemical weathering status of newly constructed topsoil was higher than that of the original topsoil and lower than that of foreign topsoil.(3) Anthropogenic activities may provide a promising new thought for the anthropogenic soil classification system. The scope and subgroups of Anthrosols should be extended and strengthened. Or there may be a need to combine Anthrosols and Technosols orders to create a new soil order. The results may be used for optimizing soil mellowing engineering activities and enriching the soil classification system.
文摘Urticaceae Juss.is a large cosmopolitan family and taxonomically difficult group,partly because it encompasses a broad range of morphological diversity and many of the diagnostic characters（e.g.flower,achene.stipule,bract）require a microscope for accurate determination.Meanwhile,most Uriiceae species have stinging hairs which make them more difficult to collect and identify.As a result,the infra-familial classification of Urticaceae has been controversial for more than a century.A research group led by Prof.
基金Project supported by the National Natural Science Foundation of China(No.61379074)the Zhejiang Provincial Natural Science Foundation of China(Nos.LZ12F02003 and LY15F020035)
文摘In some image classification tasks, similarities among different categories are different and the samples are usually misclassified as highly similar categories. To distinguish highly similar categories, more specific features are required so that the classifier can improve the classification performance. In this paper, we propose a novel two-level hierarchical feature learning framework based on the deep convolutional neural network(CNN), which is simple and effective. First, the deep feature extractors of different levels are trained using the transfer learning method that fine-tunes the pre-trained deep CNN model toward the new target dataset. Second, the general feature extracted from all the categories and the specific feature extracted from highly similar categories are fused into a feature vector. Then the final feature representation is fed into a linear classifier. Finally, experiments using the Caltech-256, Oxford Flower-102, and Tasmania Coral Point Count(CPC) datasets demonstrate that the expression ability of the deep features resulting from two-level hierarchical feature learning is powerful. Our proposed method effectively increases the classification accuracy in comparison with flat multiple classification methods.
基金Project supported by the Natiooal Natural Science Foundation of China （No. 61303264） and the National Basic Research Program （973） of China （Nos. 2012CB315906 and 0800065111001）
文摘The explosive growth ofmalware variants poses a major threat to information security. Traditional anti-virus systems based on signatures fail to classify unknown malware into their corresponding families and to detect new kinds of malware pro- grams. Therefore, we propose a machine learning based malware analysis system, which is composed of three modules： data processing, decision making, and new malware detection. The data processing module deals with gray-scale images, Opcode n-gram, and import fimctions, which are employed to extract the features of the malware. The decision-making module uses the features to classify the malware and to identify suspicious malware. Finally, the detection module uses the shared nearest neighbor （SNN） clustering algorithm to discover new malware families. Our approach is evaluated on more than 20 000 malware instances, which were collected by Kingsoft, ESET NOD32, and Anubis. The results show that our system can effectively classify the un- known malware with a best accuracy of 98.9%, and successfully detects 86.7% of the new malware.
基金supported by the National Natural Science Foundation of China(No.61401425)
文摘In this paper, firstly, target candidate regions are extracted by combining maximum symmetric surround saliency detection algorithm with a cellular automata dynamic evolution model. Secondly, an eigenvector independent of the ship target size is constructed by combining the shape feature with ship histogram of oriented gradient(S-HOG) feature, and the target can be recognized by Ada Boost classifier. As demonstrated in our experiments, the proposed method with the detection accuracy of over 96% outperforms the state-of-the-art method. efficiency switch and modulation.
基金Support of National Natural Science Foundation of China under Grant Nos.11475028,11772064,and 11502117Science Challenge Project under Grant Nos.JCKY2016212A501 and TZ2016002
文摘The rarefied effect of gas flow in microchannel is significant and cannot be well described by traditional hydrodynamic models. It has been known that discrete Boltzmann model(DBM) has the potential to investigate flows in a relatively wider range of Knudsen number because of its intrinsic kinetic nature inherited from Boltzmann equation.It is crucial to have a proper kinetic boundary condition for DBM to capture the velocity slip and the flow characteristics in the Knudsen layer. In this paper, we present a DBM combined with Maxwell-type boundary condition model for slip flow. The tangential momentum accommodation coefficient is introduced to implement a gas-surface interaction model.Both the velocity slip and the Knudsen layer under various Knudsen numbers and accommodation coefficients can be well described. Two kinds of slip flows, including Couette flow and Poiseuille flow, are simulated to verify the model.To dynamically compare results from different models, the relation between the definition of Knudsen number in hard sphere model and that in BGK model is clarified.
