Nodal-line semimetals have become a research hot-spot due to their novel properties and great potential application in spin electronics. It is more challenging to find 2D nodal-line semimetals that can resist the spin...Nodal-line semimetals have become a research hot-spot due to their novel properties and great potential application in spin electronics. It is more challenging to find 2D nodal-line semimetals that can resist the spin–orbit coupling(SOC)effect. Here, we predict that 2D tetragonal Zn B is a nodal-line semimetal with great transport properties. There are two crossing bands centered on the S point at the Fermi surface without SOC, which are mainly composed of the pxy orbitals of Zn and B atoms and the pz orbitals of the B atom. Therefore, the system presents a nodal line centered on the S point in its Brillouin zone(BZ). And the nodal line is protected by the horizontal mirror symmetry M_(z). We further examine the robustness of a nodal line under biaxial strain by applying up to-4% in-plane compressive strain and 5% tensile strain on the Zn B monolayer, respectively. The transmission along the a direction is significantly stronger than that along the b direction in the conductive channel. The current in the a direction is as high as 26.63 μA at 0.8 V, and that in the b direction reaches 8.68 μA at 0.8 V. It is interesting that the transport characteristics of Zn B show the negative differential resistance(NDR) effect after 0.8 V along the a(b) direction. The results provide an ideal platform for research of fundamental physics of 2D nodal-line fermions and nanoscale spintronics, as well as the design of new quantum devices.展开更多
Diabetic retinopathy is a critical eye condition that,if not treated,can lead to vision loss.Traditional methods of diagnosing and treating the disease are time-consuming and expensive.However,machine learning and dee...Diabetic retinopathy is a critical eye condition that,if not treated,can lead to vision loss.Traditional methods of diagnosing and treating the disease are time-consuming and expensive.However,machine learning and deep transfer learning(DTL)techniques have shown promise in medical applications,including detecting,classifying,and segmenting diabetic retinopathy.These advanced techniques offer higher accuracy and performance.ComputerAided Diagnosis(CAD)is crucial in speeding up classification and providing accurate disease diagnoses.Overall,these technological advancements hold great potential for improving the management of diabetic retinopathy.The study’s objective was to differentiate between different classes of diabetes and verify the model’s capability to distinguish between these classes.The robustness of the model was evaluated using other metrics such as accuracy(ACC),precision(PRE),recall(REC),and area under the curve(AUC).In this particular study,the researchers utilized data cleansing techniques,transfer learning(TL),and convolutional neural network(CNN)methods to effectively identify and categorize the various diseases associated with diabetic retinopathy(DR).They employed the VGG-16CNN model,incorporating intelligent parameters that enhanced its robustness.The outcomes surpassed the results obtained by the auto enhancement(AE)filter,which had an ACC of over 98%.The manuscript provides visual aids such as graphs,tables,and techniques and frameworks to enhance understanding.This study highlights the significance of optimized deep TL in improving the metrics of the classification of the four separate classes of DR.The manuscript emphasizes the importance of using the VGG16CNN classification technique in this context.展开更多
A novel mesa ultra-thin base AlGaAs/GaAs HBT is designed and fabricated with wet chemical selective etch technique and monitor electrode technique. It has a particular and obvious voltage-controlled NDR whose PVCR is ...A novel mesa ultra-thin base AlGaAs/GaAs HBT is designed and fabricated with wet chemical selective etch technique and monitor electrode technique. It has a particular and obvious voltage-controlled NDR whose PVCR is larger than 120. By use of device simulation,the cause of NDR is that increasing collector voltage makes the ultrathin base reach through and the device transforms from a bipolar state to a bulk barrier state. In addition, the simulated cutoff frequency is about 60-80GHz.展开更多
基金Project supported by the Natural Science Foundation of Shandong Province, China (Grant No. ZR2019MA041)Taishan Scholar Project of Shandong Province, China (Grant No. ts20190939)the National Natural Science Foundation of China (Grant No. 62071200)。
文摘Nodal-line semimetals have become a research hot-spot due to their novel properties and great potential application in spin electronics. It is more challenging to find 2D nodal-line semimetals that can resist the spin–orbit coupling(SOC)effect. Here, we predict that 2D tetragonal Zn B is a nodal-line semimetal with great transport properties. There are two crossing bands centered on the S point at the Fermi surface without SOC, which are mainly composed of the pxy orbitals of Zn and B atoms and the pz orbitals of the B atom. Therefore, the system presents a nodal line centered on the S point in its Brillouin zone(BZ). And the nodal line is protected by the horizontal mirror symmetry M_(z). We further examine the robustness of a nodal line under biaxial strain by applying up to-4% in-plane compressive strain and 5% tensile strain on the Zn B monolayer, respectively. The transmission along the a direction is significantly stronger than that along the b direction in the conductive channel. The current in the a direction is as high as 26.63 μA at 0.8 V, and that in the b direction reaches 8.68 μA at 0.8 V. It is interesting that the transport characteristics of Zn B show the negative differential resistance(NDR) effect after 0.8 V along the a(b) direction. The results provide an ideal platform for research of fundamental physics of 2D nodal-line fermions and nanoscale spintronics, as well as the design of new quantum devices.
文摘Diabetic retinopathy is a critical eye condition that,if not treated,can lead to vision loss.Traditional methods of diagnosing and treating the disease are time-consuming and expensive.However,machine learning and deep transfer learning(DTL)techniques have shown promise in medical applications,including detecting,classifying,and segmenting diabetic retinopathy.These advanced techniques offer higher accuracy and performance.ComputerAided Diagnosis(CAD)is crucial in speeding up classification and providing accurate disease diagnoses.Overall,these technological advancements hold great potential for improving the management of diabetic retinopathy.The study’s objective was to differentiate between different classes of diabetes and verify the model’s capability to distinguish between these classes.The robustness of the model was evaluated using other metrics such as accuracy(ACC),precision(PRE),recall(REC),and area under the curve(AUC).In this particular study,the researchers utilized data cleansing techniques,transfer learning(TL),and convolutional neural network(CNN)methods to effectively identify and categorize the various diseases associated with diabetic retinopathy(DR).They employed the VGG-16CNN model,incorporating intelligent parameters that enhanced its robustness.The outcomes surpassed the results obtained by the auto enhancement(AE)filter,which had an ACC of over 98%.The manuscript provides visual aids such as graphs,tables,and techniques and frameworks to enhance understanding.This study highlights the significance of optimized deep TL in improving the metrics of the classification of the four separate classes of DR.The manuscript emphasizes the importance of using the VGG16CNN classification technique in this context.
文摘A novel mesa ultra-thin base AlGaAs/GaAs HBT is designed and fabricated with wet chemical selective etch technique and monitor electrode technique. It has a particular and obvious voltage-controlled NDR whose PVCR is larger than 120. By use of device simulation,the cause of NDR is that increasing collector voltage makes the ultrathin base reach through and the device transforms from a bipolar state to a bulk barrier state. In addition, the simulated cutoff frequency is about 60-80GHz.
