Breakdown Characteristics of Varistor Ceramics

Breakdown characteristics are of great importance for varistor ceramics, which largely depend on Schottky barriers at grain boundaries. In order to enhance breakdown performance for meeting the requirement of device miniaturization, different doping methods are introduced to not only restrict grain size from additional phase but also manipulate defect structure of Schottky barrier at grain boundaries from substitution. Distribution of barriers is another key point affecting breakdown characteristics in varistor ceramics. Dimensional effect, which is detected in not only ZnO ceramics but also CaCu3Ti4O12 ceramics, is practically and theoretically found to be closely correlated with uniformity of grains. As a result, breakdown characteristics of varistors are dominated by combination effect of single barrier performance and spatial barrier distribution. In this chapter, enhanced breakdown field in CaxSr1−xCu3Ti4O12 ceramics, in situ synthesized CaCu3Ti4O12-CuAl2O4 ceramics, and CaCu3Ti4O12-Y2/3Cu3Ti4O12 composite ceramics are investigated from the aspect of Schottky barriers at grain boundaries. In addition, dimensional effect is found in both ZnO and CaCu3Ti4O12 ceramics, which are investigated from grain size distribution through theoretical and experimental analysis

Object Detection in 3D Point Clouds via Local Correlation-Aware Point Embedding

We present an improved approach for 3D object detection in point clouds data based on the Frustum PointNet (F-PointNet). Compared to the original F-PointNet, our newly proposed method considers the point neighborhood when computing point features. The newly introduced local neighborhood embedding operation mimics the convolutional operations in 2D neural networks. Thus features of each point are not only computed with the features of its own or of the whole point cloud, but also computed especially with respect to the features of its neighbors. Experiments show that our proposed method achieves better performance than the F-Pointnet baseline on 3D object detection tasks

Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis

In the last few years, deep learning classifiers have shown promising results in image-based medical diagnosis. However, interpreting the outputs of these models remains a challenge. In cancer diagnosis, interpretability can be achieved by localizing the region of the input image responsible for the output, i.e. the location of a lesion. Alternatively, segmentation or detection models can be trained with pixel-wise annotations indicating the locations of malignant lesions. Unfortunately, acquiring such labels is labor-intensive and requires medical expertise. To overcome this difficulty, weakly-supervised localization can be utilized. These methods allow neural network classifiers to output saliency maps highlighting the regions of the input most relevant to the classification task (e.g. malignant lesions in mammograms) using only image-level labels (e.g. whether the patient has cancer or not) during training. When applied to high-resolution images, existing methods produce low-resolution saliency maps. This is problematic in applications in which suspicious lesions are small in relation to the image size. In this work, we introduce a novel neural network architecture to perform weakly-supervised segmentation of high-resolution images. The proposed model selects regions of interest via coarse-level localization, and then performs fine-grained segmentation of those regions. We apply this model to breast cancer diagnosis with screening mammography, and validate it on a large clinically-realistic dataset. Measured by Dice similarity score, our approach outperforms existing methods by a large margin in terms of localization performance of benign and malignant lesions, relatively improving the performance by 39.6% and 20.0%, respectively. Code and the weights of some of the models are available at https://github.com/nyukat/GLAMComment: The last two authors contributed equally. Accepted to Medical Imaging with Deep Learning (MIDL) 202

Ecological stoichiometry and homeostasis characteristics of plant-litter-soil system with vegetation restoration of the karst desertification control

It is of great significance to clarify the ecologically chemical stoichiometric characteristics of plant-litter-soil in vegetation restoration process for elucidating the nutrient cycling law and soil nutrient management of karst ecosystem. The carbon (C), nitrogen (N) and phosphorus (P) contents of leaves, litter and soil and their stoichiometry were determined in loquat (Eribotrya japonica) plantations in a karst plateau canyon after 3, 6, 10 and 15 years of restoration. The homeostasis characteristics of leaf N, P, and N:P with the change in soil nutrients during restoration were revealed. The results showed that leaf C, N, and P contents initially increased and then decreased with increasing years of restoration at the same sampling time. The contents of nutrients in soil and litter varied with increasing restoration years, with the highest values mostly appearing in May and July. This could be due to greater moisture in May and July, which helps with nutrient absorption and transformation. The leaf N:P ratio of loquat with different restoration years was 35.76-47.39, with an average of 40.06. Therefore, loquat leaves may experience P limitation in the growth process. The relationships between N, P and N:P in leaves and soil indexes could be simulated by a homeostasis model. Except for the weak sensitivity of loquat leaf N in 10 years, the other indexes and treatments had a certain homeostasis. Plants maintain homeostasis by regulating physiological responses in vivo in response to soil nutrient changes, indicating that loquat has good adaptability in karst desertification environments, but attention should focus on the management of soil P in the field as part of the vegetation restoration process. Therefore, in future research, we should combine the soil water and fertilizer conditions of different growing seasons in karst rocky desertification areas and provide scientific field management to ensure that the results of rocky desertification management can play a role in rural revitalization

Power loss transition of stable ZnO varistor ceramics: Role of oxygen adsorption on the stability of interface states at the grain boundary

Highly stable ZnO varistor ceramics with steadily decreasing power loss have been put into applications in electrical and electronic systems for overvoltage protections, even with the absence of general understandings on their aging behaviors. In this paper, we investigated their aging nature via conducting comparative direct current (DC) aging experiments both in air and in nitrogen, during which variations of electrical properties and interface properties were measured and analyzed. Notably, continuously increasing power loss with severe electrical degradation was observed for the sample aged in nitrogen. The power loss transition was discovered to be closely related to the consumption of oxygen adsorption at the grain boundary (GB), which could, however, remain constant for the sample aged in air. The interface density of states (DOS) Ni, which is crucial for pinning the potential barrier, was proved to decrease in nitrogen, but keep stable in air. Therefore, it is concluded that the oxygen adsorption at the GB is significant for the stability of interface states, which further correlates to the long-term stability of modern stable ZnO varistor ceramics

Analysis of Flavor and Nutritional Quality of Fresh Sea Buckthorn Juice and Pulp

Identification of odor compounds in fresh sea buckthorn juice (FSBJ) and pulp (SBP) was performed by gas chromatography-mass spectrometry-olfactometry (GC-MS-O). A total of 39 and 36 odor compounds were identified in FSBJ and SBP, respectively. Further findings revealed that ethyl hexanoate, ethyl 2-methylbutyrate, ethyl 3-methylbutyrate, and 3-methylbutyl 3-methylbutanoate had high flavor dilution (FD) factors and were identified as the key odor compounds in FSBJ. In addition, the contents of ester compounds contributing to the fruity odor were significantly reduced in SBP after pasteurization. Sensory evaluation and electronic tongue analysis revealed that the sweetness and overall taste of SBP were superior to those of FSBJ. The contents of vitamin C and total flavonoids were significantly lower in SBP than in FSBJ, indicating that pasteurization reduces the nutritional quality of FSBJ. The results of the study can provide theoretical references for the flavor and nutritional quality optimization of sea buckthorn products