This work investigated the aging effects on the rheological properties of high viscosity modified asphalt(HVMA).First,the high-and low-temperature rheological properties were measured by a dynamic shear rheometer and ...This work investigated the aging effects on the rheological properties of high viscosity modified asphalt(HVMA).First,the high-and low-temperature rheological properties were measured by a dynamic shear rheometer and a bending beam rheometer,respectively.The aging mechanism was then tested using an Fourier transform infrared spectroscopy and a scanning electron microscope.Besides,a study was performed to compare the aging effects on the rheological properties of HVMA,crumb rubber modified asphalt(CRMA),and neat asphalt(SK-90).The experimental results showed that the effects of the long-term aging on HVMA exceeded those of short-term aging.The complex shear modulus of the HVMA was improved by the aging in the whole frequency range.The complex shear modulus of the HVMA after the long-term aging was larger than after the short-term aging.Thus,the aging improved the high-temperature viscoelastic performance of HVMA.With a decrease in temperature from-12℃to-24℃,the low-temperature viscoelastic performance of HVMA decreased since its stiffness modulus and low continuous grading temperature increase.Both of the short-and long-term aging of HVMA were caused by an oxidation reaction,while modifier swelling also happened after long-term aging.Compared to CRMA and SK-90,aging had a limited influence on the high-and low-temperature rheological properties of HVMA.展开更多
Cell segmentation and counting play a very important role in the medical field.The diagnosis of many diseases relies heavily on the kind and number of cells in the blood.convolution neural network achieves encouraging...Cell segmentation and counting play a very important role in the medical field.The diagnosis of many diseases relies heavily on the kind and number of cells in the blood.convolution neural network achieves encouraging results on image segmentation.However,this data-driven method requires a large number of annotations and can be a time-consuming and expensive process,prone to human error.In this paper,we present a novel frame to segment and count cells without too many manually annotated cell images.Before training.we generated the cell image labels on single-kind cell images using traditional algorithms.These images were then used to form the train set with the label.Different train sets composed of different kinds of cell images are presented to the segmentation model to update its parameters.Finally,the pretrained U-Net model is transferred to segment the mixed cell images using a small dataset of manually labeled mixed cell images.To better evaluate the efectiveness of the proposed method,we design and train a new automatic cell segmentation and count framework.The test results and analyses show that the segmentation and count performance of the framework trained by the proposed method equal the model trained by large amounts of annotated mixed cell images.展开更多
基金supported by the National Key R&D Program of China(Grant No.2018YFB1600200)the Fok YingTong Education Foundation(Grant No.161072)+1 种基金the Youth Top-notch Talent Support Program of Shaanxi Provincethe Fundamental Research Funds for the Central Universities(Grant No.300102219317)。
文摘This work investigated the aging effects on the rheological properties of high viscosity modified asphalt(HVMA).First,the high-and low-temperature rheological properties were measured by a dynamic shear rheometer and a bending beam rheometer,respectively.The aging mechanism was then tested using an Fourier transform infrared spectroscopy and a scanning electron microscope.Besides,a study was performed to compare the aging effects on the rheological properties of HVMA,crumb rubber modified asphalt(CRMA),and neat asphalt(SK-90).The experimental results showed that the effects of the long-term aging on HVMA exceeded those of short-term aging.The complex shear modulus of the HVMA was improved by the aging in the whole frequency range.The complex shear modulus of the HVMA after the long-term aging was larger than after the short-term aging.Thus,the aging improved the high-temperature viscoelastic performance of HVMA.With a decrease in temperature from-12℃to-24℃,the low-temperature viscoelastic performance of HVMA decreased since its stiffness modulus and low continuous grading temperature increase.Both of the short-and long-term aging of HVMA were caused by an oxidation reaction,while modifier swelling also happened after long-term aging.Compared to CRMA and SK-90,aging had a limited influence on the high-and low-temperature rheological properties of HVMA.
基金support from the National Key R&D Program of China(No.2019YFB1309700)the Bejing Nova Program of Science and Technology under Grant No.Z19100001119003.
文摘Cell segmentation and counting play a very important role in the medical field.The diagnosis of many diseases relies heavily on the kind and number of cells in the blood.convolution neural network achieves encouraging results on image segmentation.However,this data-driven method requires a large number of annotations and can be a time-consuming and expensive process,prone to human error.In this paper,we present a novel frame to segment and count cells without too many manually annotated cell images.Before training.we generated the cell image labels on single-kind cell images using traditional algorithms.These images were then used to form the train set with the label.Different train sets composed of different kinds of cell images are presented to the segmentation model to update its parameters.Finally,the pretrained U-Net model is transferred to segment the mixed cell images using a small dataset of manually labeled mixed cell images.To better evaluate the efectiveness of the proposed method,we design and train a new automatic cell segmentation and count framework.The test results and analyses show that the segmentation and count performance of the framework trained by the proposed method equal the model trained by large amounts of annotated mixed cell images.
