学情调查和数据驱动专业基础课教学探索

文章以“数字电子技术基础”课程为对象,设计了基于教学数据和问卷调查的教学框架。通过学生情况调查和雨课堂教学数据掌握学习状态和学习能力,针对性设计了个性化作业布置、拓展延伸、疫情线上自学跟学双通道等特色教学方式。结课问卷表明教学设计得到了良好评价和认可。     

Soluble polyimide as liquid crystal perpendicular alignment layer

Journal of Materials Science - Three polyimides (PIs) were prepared from a diamine containing biphenyl ester group as a side chain and a corresponding dianhydride chosen from...     

Mutual information maximizing GAN inversion for real face with identity preservation

Recent generative adversarial networks (GANs) have yielded remarkable performance in face image synthesis. GAN inversion embeds an image into the latent space of a pretrained generator, enabling it to be used for real face manipulation. However, current inversion approaches for real faces suffer the dilemma of initialization collapse and identity loss. In this paper, we propose a hierarchical GAN inversion for real faces with identity preservation based on mutual information maximization. We first use a facial domain guaranteed initialization to avoid the initialization collapse. Furthermore, we prove that maximizing the mutual information between inverted faces and their identities is equivalent to minimizing the distance between identity features from inverted and original faces. Optimization for real face inversion with identity preservation is implemented on this mutual information-maximizing constraint. Extensive experimental results show that our approach outperforms state-of-the-art solutions for inverting and editing real faces, particularly in terms of face identity preservation.     

Collaborative Distribution Alignment for 2D image-based 3D shape retrieval

Retrieving 3D shapes with 2D images has become a popular research area nowadays, and a great deal of work has been devoted to reducing the discrepancy between 3D shapes and 2D images to improve retrieval performance. However, most approaches ignore the semantic information and decision boundaries of the two domains, and cannot achieve both domain alignment and category alignment in one module. In this paper, a novel Collaborative Distribution Alignment (CDA) model is developed to address the above existing challenges. Specifically, we first adopt a dual-stream CNN, following a similarity guided constraint module, to generate discriminative embeddings for input 2D images and 3D shapes (described as multiple views). Subsequently, we explicitly introduce a joint domain-class alignment module to dynamically learn a class-discriminative and domain-agnostic feature space, which can narrow the distance between 2D image and 3D shape instances of the same underlying category, while pushing apart the instances from different categories. Furthermore, we apply a decision boundary refinement module to avoid generating class-ambiguity embeddings by dynamically adjusting inconsistencies between two discriminators. Extensive experiments and evaluations on two challenging benchmarks, MI3DOR and MI3DOR-2, demonstrate the superiority of the proposed CDA method for 2D image-based 3D shape retrieval task.     

Multi-scale and multi-patch transformer for sandstorm image enhancement

Sandstorm is a meteorological phenomenon common in arid and semi-arid regions. A sandstorm can carry large volumes of sand unexpectedly, which leads to severe color deviations and significantly degraded visibility when an image is taken in such a scenario. However, existing image enhancement methods cannot enhance sandstorm images well due to the challenging degradations and the scarcity of sandstorm training data. In this paper, we propose a Transformer with rotary position embedding to perform sandstorm image enhancement via building multi-scale and multi-patch dependencies. Our key insights in this work are 1) a multi-scale Transformer can globally eliminate the color deviations of sandstorm images via aggregating global information, 2) a multi-patch Transformer can recover local details well via learning the spatial variant degradations, and 3) a U-shape Transformer with rotary position embedding as the core unit of multi-scale and multi-patch Transformer can effectively build the long-range dependencies. We also contribute a real-world Sandstorm Image Enhancement (SIE) dataset including 1,400 sandstorm images with different degrees of degradations and various scenes. Experiments performed on synthetic images and real-world sandstorm images demonstrate that our proposed method not only obtains visually pleasing results but also outperforms state-of-the-art methods qualitatively and quantitatively.     

Structural regulation and polishing performance of dendritic mesoporous silica (D-mSiO2) supported with samarium-doped cerium oxide composites

Ceria (CeO₂) particles are prevalent polishing abrasive materials. Trivalent lanthanide ions are the popular category of dopants for enriched surface defects and thus improved physicochemical properties, since they are highly compatible with CeO₂ lattices. Herein, a series of dendritic-like mesoporous silica (D-mSiO₂)-supported samarium (Sm)-doped CeO₂ nanocrystals were synthesized via a facile chemical precipitation method. The relation of the structural characteristics and chemical mechanical polishing (CMP) performances were investigated to explore the effect of Sm-doping amounts on the D-mSiO₂/Sm_xCe_1?xO_2?δ (x = 0–1) composite abrasives. The involved low-modulus D-mSiO₂ cores aimed to eliminate surface scratch and damage, resulting from the optimized contact behavior between abrasives and surfaces. The trivalent cerium (Ce³⁺) and oxygen vacancy (V_O) at CeO₂ surfaces were expected to be reactive sites for the material removal process over SiO₂ films. The optimal oxide-CMP performances in terms of removal efficiency and surface quality were achieved by the 40% Sm-doped composite abrasives. It might be attributed to the high Ce³⁺ and V_O concentrations and the enhancement of tribochemical reactivity between CeO₂SiO₂ interfaces. Furthermore, the relationship between the surface chemistry, polishing performance as well as the actual role in oxide-CMP of the D-mSiO₂/Sm_xCe_1?xO_2?δ abrasives were also discussed.     

Facile synthesis of Ti3C2 MXene-modified Bi2.15WO6 nanosheets with enhanced reactivity for photocatalytic reduction of Cr(VI)

Through a facile hydrothermal method, we have successfully prepared Ti₃C₂/Bi_2.15WO₆ (TC/BWO) composite, and systematically investigated their reactivity for the photocatalytic reduction of Cr(VI) under visible light. X-ray diffraction and Raman analysis confirm the formation of heterostructure between Bi_2.15WO₆ and Ti₃C₂. The resultant 7TC/BWO composite exhibits enhanced photoactivity toward Cr(VI) reduction. After 120 min irradiation, the conversion of Cr(VI) reaches 92.5% with the quasi-first-order kinetic constant of k = 0.0145 min^?1, which is higher than that of pure BWO (30% and k = 0.0005 min^?1). The electrochemical and photoluminescent characterization confirm that the introduction of Ti₃C₂ is conducive to the separation of carriers, thus significantly improves the photocatalytic performance of TC/BWO. Furthermore, the radical capture experiments verify that the electrons are important for enhancing reduction of Cr(VI) to Cr(III). As a result, this research provides a comprehensive understanding of the reduction of Cr(VI) by TC/BWO composite under visible light.     

Dielectric performance and conductive mechanism of KNN-based ceramics prepared via sol–gel core–shell process

Journal of Materials Science: Materials in Electronics - 0.95(Li0.02Na0.50K0.48)(Nb0.95Sb0.05)O3–0.05AgTaO3@BaZrO3 (LNKNbSAT@BZ) lead-free ceramics were prepared via a sol–gel...     

Highly enhanced energy storage properties of H2O2-hydroxylated rare earth ferrites (LaFeO3 and GdFeO3) nanofillers in poly(vinylidene fluoride)-based nanocomposite films

Journal of Materials Science: Materials in Electronics - Pure PVDF has higher breakdown strength but low dielectric and ferroelectric properties. Thus, we synthesized the LaFeO3 and GdFeO3...