Search

This investigation explores the structural and electronic properties of low-temperature-grown (InAs)4(GaAs)3/Be-doped InAlAs and InGaAs/Be-doped InAlAs multiple quantum wells (MQWs), utilizing migration-enhanced epitaxy (MEE) and conventional molecular beam epitaxy (MBE) growth mode. Through comprehensive characterization methods including transmission electron microscopy (TEM), Raman spectroscopy, atomic force microscopy (AFM), pump–probe transient reflectivity, and Hall effect measurements, the study reveals significant distinctions between the two types of MQWs. The (InAs)4(GaAs)3/Be-doped InAlAs MQWs grown via the MEE mode exhibit enhanced periodicity and interface quality over the InGaAs/Be-InAlAs MQWs grown through the conventional molecule beam epitaxy (MBE) mode, as evidenced by TEM. The AFM results indicate lower surface roughness for the (InAs)4(GaAs)3/Be-doped InAlAs MQWs by using the MEE mode. Raman spectroscopy reveals weaker disorder-activated modes in the (InAs)4(GaAs)3/Be-doped InAlAs MQWs by using the MEE mode. This originates from utilizing the (InAs)4(GaAs)3 short period superlattices rather than InGaAs, which suppresses the arbitrary distribution of Ga and In atoms during the InGaAs growth. Furthermore, pump–probe transient reflectivity measurements show shorter carrier lifetimes in the (InAs)4(GaAs)3/Be-doped InAlAs MQWs, attributed to a higher density of antisite defects. It is noteworthy that room temperature Hall measurements imply that the mobility of (InAs)4(GaAs)3/Be-doped InAlAs MQWs grown at a low temperature of 250 °C via the MEE mode is superior to that of InGaAs/Be-doped InAlAs MQWs grown in the conventional MBE growth mode, reaching 2230 cm2/V.s. The reason for the higher mobility of (InAs)4(GaAs)3/Be-doped InAlAs MQWs is that this short-period superlattice structure can effectively suppress alloy scattering caused by the arbitrary distribution of In and Ga atoms during the growth process of the InGaAs ternary alloy. These results exhibit the promise of the MEE growth approach for growing high-performance MQWs for advanced optoelectronic applications, notably for high-speed optoelectronic devices like THz photoconductive antennas. [ABSTRACT FROM AUTHOR]

Objective. Diabetic retinopathy (DR) grading plays an important role in clinical diagnosis. However, automatic grading of DR is challenging due to the presence of intra-class variation and small lesions. On the one hand, deep features learned by convolutional neural networks often lose valid information about these small lesions. On the other hand, the great variability of lesion features, including differences in type and quantity, can exhibit considerable divergence even among fundus images of the same grade. To address these issues, we propose a novel multi-scale multi-attention network (MMNet). Approach. Firstly, to focus on different lesion features of fundus images, we propose a lesion attention module, which aims to encode multiple different lesion attention feature maps by combining channel attention and spatial attention, thus extracting global feature information and preserving diverse lesion features. Secondly, we propose a multi-scale feature fusion module to learn more feature information for small lesion regions, which combines complementary relationships between different convolutional layers to capture more detailed feature information. Furthermore, we introduce a Cross-layer Consistency Constraint Loss to overcome semantic differences between multi-scale features. Main results. The proposed MMNet obtains a high accuracy of 86.4% and a high kappa score of 88.4% for multi-class DR grading tasks on the EyePACS dataset, while 98.6% AUC, 95.3% accuracy, 92.7% recall, 95.0% precision, and 93.3% F1-score for referral and non-referral classification on the Messidor-1 dataset. Extensive experiments on two challenging benchmarks demonstrate that our MMNet achieves significant improvements and outperforms other state-of-the-art DR grading methods. Significance. MMNet has improved the diagnostic efficiency and accuracy of diabetes retinopathy and promoted the application of computer-aided medical diagnosis in DR screening. [ABSTRACT FROM AUTHOR]

In view of the problem of insufficient storage capacity of the original landfill site, it is a very economical and effective way to use the horizontal, longitudinal and composite extension of garbage dam with geotextile reinforced earth dam. In this paper, the types of garbage dam, dam extension technology, dam reinforcement method and stability of garbage dam are introduced and discusses the types and advantages and disadvantages of dam retaining, the construction technology of dam retaining, the stability analysis and influencing factors of garbage dam retaining and the safety monitoring of dam body.