Numerical analysis and thermal fatigue life prediction of solder layer in a SiC-IGBT power module

Limited by the mechanical properties of materials, silicon (Si) carbide insulated gate bipolar transistor (IGBT) can no longer meet the requirements of high power and high frequency electronic devices. Silicon carbide (SiC) IGBT, represented by SiC MOSFET, combines the excellent performance of SiC materials and IGBT devices, and becomes an ideal device for high-frequency and high-temperature electronic devices. Even so, the thermal fatigue failure of SiC IGBT, which directly determines its application and promotion, is a problem worthy of attention. In this study, the thermal fatigue behavior of SiC-IGBT under cyclic temperature cycles was investigated by finite element method. The finite element thermomechanical model was established, and stress-strain distribution and creep characteristics of the SnAgCu solder layer were obtained. The thermal fatigue life of the solder was predicted by the creep, shear strain and energy model respectively, and the failure position and factor of failure were discussed

Studies on the soybean aphid, Aphid glycines Matsumura

The soybean aphid is widely distributed among all major soybean growing regions in China. It causes severe damage in Jilin, Liaoning, and Helongjiang Provinces, and part of the inner Mongolian autonomous region, and those areas are often called aphid-stricken areas. Its hosts include wild soybean (Glycine benth forma lanceolate Makino), buckthorn (Rhamnus davuricus) as well as soybean. Results of field investigation and inoculation experiments confirmed that the widely distributed buckthorn in the Northern Provinces is the over-wintering host for soybean aphids. According to the life cycle of aphids and their characteristic damage to soybeans, three different periods of impact can be recognized: 1) starting from seedling stage to blooming stage (mid-July), the aphid population reaches its peak point. About 50-70% of the whole aphid population colonizes on the tender leaves and twigs on top of the soy plants. The soybean damage caused during this period has the worst impact on the plants. 2) During the third ten days of July when the soybean plants cease to grow, aphids then migrate from the top leaves and twigs to the middle or lower ones and feed on the underside of the leaves. At the same time, the young nymphs appear. The aphid population grows slowly, and their damage to soybean plants is at a low tide. 3) From late August -- the late pod bearing period -- to early September -- the yellow maturing period -- aphids start their late multiplying stage. In late Fall, aphids migrate back to buckthorn, their overwintering host, and oviposit overwintering eggs after mating. During Fall, the male aphids and the ovipositional female aphids are living on different hosts. Gynoparae live on buckthorn, and the male aphids live on soybean. Aphids reproduce 15 generations a year on soybean. After analyzing the life cycle of aphids, their growth pattern in the field, as well as the meteorological data in recent years, we came to preliminary results about the growth and decline pattern of aphids and their affecting factors: 1) the more the overwintering eggs and aphids numbers were at the seedling stage, the more severe their impact on seedlings; 2) Average temperatures between 22-25 °C and relative humidity below 78% from late June to early July greatly favored the growth and reproduction of aphids. Even if the original aphid population is small, severe aphid epidemics still could occur during the blooming period in July because aphids reproduced very quickly under those favorable weather conditions; 3) As the growth points ceased growing in late July and the nutrient condition deteriorated, the aphid population declined. In summary, we may make long- or short-term predictions of aphid epidemics based on the number of overwintering eggs, meteorological data, and current and past aphid information. Based on the results of several years’ laboratory and field experiments, the following aphid control measures achieved very good results: 0.5% lindane (benzene hexachloride, or BHC), 1 to 300-400 diluted 6% BHC wettable powder, 1 to 15000 diluted E605 (parathion), 1 to 100 diluted tobacco leaf solution, and seed coating with 20% BHC. Among these methods, 0.5% BHC powder and seed coating with 0.7% of 20% BHC have been widely used in agricultural practice.Originating text in Chinese.Citation: Wang, Cheng Lun, Xiang, Liang Ying, Zhang, Guang Xue, Zhu, Hong Fu. (1962). Studies on the soybean aphid, Aphid glycines Matsumura. Acta Entomologica Sinica, 11, 31-44

Molecular Dynamic Simulation to Explore the Molecular Basis of Btk-PH Domain Interaction with Ins(1,3,4,5)P4

Bruton’s tyrosine kinase contains a pleckstrin homology domain, and it specifically binds inositol 1,3,4,5-tetrakisphosphate (Ins(1,3,4,5)P4), which is involved in the maturation of B cells. In this paper, we studied 12 systems including the wild type and 11 mutants, K12R, S14F, K19E, R28C/H, E41K, L11P, F25S, Y40N, and K12R-R28C/H, to investigate any change in the ligand binding site of each mutant. Molecular dynamics simulations combined with the method of molecular mechanics/Poisson-Boltzmann solvent-accessible surface area have been applied to the twelve systems, and reasonable mutant structures and their binding free energies have been obtained as criteria in the final classification. As a result, five structures, K12R, K19E, R28C/H, and E41K mutants, were classified as “functional mutations,” whereas L11P, S14F, F25S, and Y40N were grouped into “folding mutations.” This rigorous study of the binding affinity of each of the mutants and their classification provides some new insights into the biological function of the Btk-PH domain and related mutation-causing diseases

tert-Butyl 3-amino-2-methyl-6,7-dihydro-2H-pyrazolo[4,3-c]pyridine-5(4H)-carboxyl­ate

In the mol­ecule of the title compound, C12H20N4O2, the dihydro­piperidine ring assumes a half-chair conformation. In the crystal, cllassical N—H⋯O and N—H⋯N inter­molecular hydrogen bonds link mol­ecules into double chains along the a axis

Improve Deep Forest with Learnable Layerwise Augmentation Policy Schedule

As a modern ensemble technique, Deep Forest (DF) employs a cascading structure to construct deep models, providing stronger representational power compared to traditional decision forests. However, its greedy multi-layer learning procedure is prone to overfitting, limiting model effectiveness and generalizability. This paper presents an optimized Deep Forest, featuring learnable, layerwise data augmentation policy schedules. Specifically, We introduce the Cut Mix for Tabular data (CMT) augmentation technique to mitigate overfitting and develop a population-based search algorithm to tailor augmentation intensity for each layer. Additionally, we propose to incorporate outputs from intermediate layers into a checkpoint ensemble for more stable performance. Experimental results show that our method sets new state-of-the-art (SOTA) benchmarks in various tabular classification tasks, outperforming shallow tree ensembles, deep forests, deep neural network, and AutoML competitors. The learned policies also transfer effectively to Deep Forest variants, underscoring its potential for enhancing non-differentiable deep learning modules in tabular signal processing

Cross-Modality Paired-Images Generation for RGB-Infrared Person Re-Identification

RGB-Infrared (IR) person re-identification is very challenging due to the large cross-modality variations between RGB and IR images. The key solution is to learn aligned features to the bridge RGB and IR modalities. However, due to the lack of correspondence labels between every pair of RGB and IR images, most methods try to alleviate the variations with set-level alignment by reducing the distance between the entire RGB and IR sets. However, this set-level alignment may lead to misalignment of some instances, which limits the performance for RGB-IR Re-ID. Different from existing methods, in this paper, we propose to generate cross-modality paired-images and perform both global set-level and fine-grained instance-level alignments. Our proposed method enjoys several merits. First, our method can perform set-level alignment by disentangling modality-specific and modality-invariant features. Compared with conventional methods, ours can explicitly remove the modality-specific features and the modality variation can be better reduced. Second, given cross-modality unpaired-images of a person, our method can generate cross-modality paired images from exchanged images. With them, we can directly perform instance-level alignment by minimizing distances of every pair of images. Extensive experimental results on two standard benchmarks demonstrate that the proposed model favourably against state-of-the-art methods. Especially, on SYSU-MM01 dataset, our model can achieve a gain of 9.2% and 7.7% in terms of Rank-1 and mAP. Code is available at https://github.com/wangguanan/JSIA-ReID.Comment: accepted by AAAI'2