Three-dimensional(3D)printing technology is increasingly used in experimental research of geotechnical engineering.Compared to other materials,3D layer-by-layer printing specimens are extremely similar to the inherent...Three-dimensional(3D)printing technology is increasingly used in experimental research of geotechnical engineering.Compared to other materials,3D layer-by-layer printing specimens are extremely similar to the inherent properties of natural layered rock masses.In this paper,soft-hard interbedded rock masses with different dip angles were prepared based on 3D printing(3DP)sand core technology.Uniaxial compression creep tests were conducted to investigate its anisotropic creep behavior based on digital imaging correlation(DIC)technology.The results show that the anisotropic creep behavior of the 3DP soft-hard interbedded rock mass is mainly affected by the dip angles of the weak interlayer when the stress is at low levels.As the stress level increases,the effect of creep stress on its creep anisotropy increases significantly,and the dip angle is no longer the main factor.The minimum value of the long-term strength and creep failure strength always appears in the weak interlayer within 30°–60°,which explains why the failure of the layered rock mass is controlled by the weak interlayer and generally emerges at 45°.The tests results are verified by comparing with theoretical and other published studies.The feasibility of the 3DP soft-hard interbedded rock mass provides broad prospects and application values for 3DP technology in future experimental research.展开更多
Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient manner.Identifying different types of brain tumors,including gliomas,meningiomas,p...Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient manner.Identifying different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI images.Current approaches predominantly rely on traditional machine learning and basic deep learning methods for image classification.These methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI images.Utilizing the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor classification.Our approach highlights a major advancement in employing sophisticated machine learning techniques within Computer Science and Engineering,showcasing a highly accurate framework with significant potential for healthcare technologies.The model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification report.This successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current methods.The integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider application.This research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.展开更多
In order to store and manage a large amount of ground and indoor image data with high resolution, an integrated data management system needs to be developed. Possible strategies for this purpose were discussed togethe...In order to store and manage a large amount of ground and indoor image data with high resolution, an integrated data management system needs to be developed. Possible strategies for this purpose were discussed together with initial test on the newly defined 3D maps. The features of such 3D maps, data organization, key techniques used for the map storage, such as image compression based on wavelet transformation, quadtree index, update and retrieval, were analyzed, with the goals of bringing some profits to the storage and management of the digital data in the visual construction of digital mine, digital city and digital community.展开更多
With the pretreatment of pyrolysis, the uniform, smooth, dense and crack free Gd2O3∶Eu3+ films were obtained by sol-gel process without shielding atmosphere. Atomic force microscopy （AFM）, X-ray diffraction （XRD）...With the pretreatment of pyrolysis, the uniform, smooth, dense and crack free Gd2O3∶Eu3+ films were obtained by sol-gel process without shielding atmosphere. Atomic force microscopy （AFM）, X-ray diffraction （XRD）, Ellipsometry, transmission, photoluminescence and X-ray excited emission were applied to study to the surface morphology, structure, thickness and optical properties of the films. The results show that the films are made up of grains with cubic structure in average size about 22 nm. With 21 times reproducible spin coating and pyrolysis treatment, the thickness of the film could reach to 792 nm and the transmittance of the film in visible region is above 90%. Two peaks at 223 and 250 nm are found in excitation spectra, which correspond to host lattice （HL） excitation and charge transfer （CT） excitation, respectively. Meanwhile, the main peak relates to HL excitation which is contrary to that of Gd2O3∶Eu3+ powder. This phenomenon will be beneficial to radioluminescence. The emission spectra show that the main peak located at 611 nm could be excited either by UV or X-ray, which correspond to （（）7F2→（）5D0） transition in Eu3+ ions. The luminescence intensity at 10 ms is only 10-4 time of that at 10 μs, which means that the afterglow in Gd2O3∶Eu3+ films is insignificant for X-ray imaging.展开更多
合成一种非线性光学(NLO)有机材料查尔酮:1-(芘-1-基)-3-(噻吩-3-基)丙烯酮,通过1 H NMR、IR、HR-MS表征了其结构。采用4f相位相干成像技术测定了它的三阶NLO性质,相关参数为:脉宽4ns,激光波长为450nm,非线性吸收系数(β)=7.3×10-1...合成一种非线性光学(NLO)有机材料查尔酮:1-(芘-1-基)-3-(噻吩-3-基)丙烯酮,通过1 H NMR、IR、HR-MS表征了其结构。采用4f相位相干成像技术测定了它的三阶NLO性质,相关参数为:脉宽4ns,激光波长为450nm,非线性吸收系数(β)=7.3×10-10 m/W,非线性折射率(n2)=-3.6×10-17 m2/W,三阶非线性极化率(χ(3))=4.12×10-11 esu;并测定了紫外光谱、荧光光谱和DSC曲线。采用密度泛函方法计算了它的轨道能量和极化率,结果表明电子转移可在分子内部进行,显示出良好的NLO活性。展开更多
基金the support of the National Natural Science Foundation of China(Grant Nos.42207199,52179113,42272333)Zhejiang Postdoctoral Scientific Research Project(Grant Nos.ZJ2022155,ZJ2022156)。
文摘Three-dimensional(3D)printing technology is increasingly used in experimental research of geotechnical engineering.Compared to other materials,3D layer-by-layer printing specimens are extremely similar to the inherent properties of natural layered rock masses.In this paper,soft-hard interbedded rock masses with different dip angles were prepared based on 3D printing(3DP)sand core technology.Uniaxial compression creep tests were conducted to investigate its anisotropic creep behavior based on digital imaging correlation(DIC)technology.The results show that the anisotropic creep behavior of the 3DP soft-hard interbedded rock mass is mainly affected by the dip angles of the weak interlayer when the stress is at low levels.As the stress level increases,the effect of creep stress on its creep anisotropy increases significantly,and the dip angle is no longer the main factor.The minimum value of the long-term strength and creep failure strength always appears in the weak interlayer within 30°–60°,which explains why the failure of the layered rock mass is controlled by the weak interlayer and generally emerges at 45°.The tests results are verified by comparing with theoretical and other published studies.The feasibility of the 3DP soft-hard interbedded rock mass provides broad prospects and application values for 3DP technology in future experimental research.
基金supported by the Researchers Supporting Program at King Saud University.Researchers Supporting Project number(RSPD2024R867),King Saud University,Riyadh,Saudi Arabia.
文摘Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient manner.Identifying different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI images.Current approaches predominantly rely on traditional machine learning and basic deep learning methods for image classification.These methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI images.Utilizing the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor classification.Our approach highlights a major advancement in employing sophisticated machine learning techniques within Computer Science and Engineering,showcasing a highly accurate framework with significant potential for healthcare technologies.The model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification report.This successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current methods.The integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider application.This research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.
文摘In order to store and manage a large amount of ground and indoor image data with high resolution, an integrated data management system needs to be developed. Possible strategies for this purpose were discussed together with initial test on the newly defined 3D maps. The features of such 3D maps, data organization, key techniques used for the map storage, such as image compression based on wavelet transformation, quadtree index, update and retrieval, were analyzed, with the goals of bringing some profits to the storage and management of the digital data in the visual construction of digital mine, digital city and digital community.
文摘With the pretreatment of pyrolysis, the uniform, smooth, dense and crack free Gd2O3∶Eu3+ films were obtained by sol-gel process without shielding atmosphere. Atomic force microscopy （AFM）, X-ray diffraction （XRD）, Ellipsometry, transmission, photoluminescence and X-ray excited emission were applied to study to the surface morphology, structure, thickness and optical properties of the films. The results show that the films are made up of grains with cubic structure in average size about 22 nm. With 21 times reproducible spin coating and pyrolysis treatment, the thickness of the film could reach to 792 nm and the transmittance of the film in visible region is above 90%. Two peaks at 223 and 250 nm are found in excitation spectra, which correspond to host lattice （HL） excitation and charge transfer （CT） excitation, respectively. Meanwhile, the main peak relates to HL excitation which is contrary to that of Gd2O3∶Eu3+ powder. This phenomenon will be beneficial to radioluminescence. The emission spectra show that the main peak located at 611 nm could be excited either by UV or X-ray, which correspond to （（）7F2→（）5D0） transition in Eu3+ ions. The luminescence intensity at 10 ms is only 10-4 time of that at 10 μs, which means that the afterglow in Gd2O3∶Eu3+ films is insignificant for X-ray imaging.
