EPCFormer: Expression Prompt Collaboration Transformer for Universal Referring Video Object Segmentation

Audio-guided Video Object Segmentation (A-VOS) and Referring Video Object Segmentation (R-VOS) are two highly-related tasks, which both aim to segment specific objects from video sequences according to user-provided expression prompts. However, due to the challenges in modeling representations for different modalities, contemporary methods struggle to strike a balance between interaction flexibility and high-precision localization and segmentation. In this paper, we address this problem from two perspectives: the alignment representation of audio and text and the deep interaction among audio, text, and visual features. First, we propose a universal architecture, the Expression Prompt Collaboration Transformer, herein EPCFormer. Next, we propose an Expression Alignment (EA) mechanism for audio and text expressions. By introducing contrastive learning for audio and text expressions, the proposed EPCFormer realizes comprehension of the semantic equivalence between audio and text expressions denoting the same objects. Then, to facilitate deep interactions among audio, text, and video features, we introduce an Expression-Visual Attention (EVA) mechanism. The knowledge of video object segmentation in terms of the expression prompts can seamlessly transfer between the two tasks by deeply exploring complementary cues between text and audio. Experiments on well-recognized benchmarks demonstrate that our universal EPCFormer attains state-of-the-art results on both tasks. The source code of EPCFormer will be made publicly available at https://github.com/lab206/EPCFormer.Comment: The source code will be made publicly available at https://github.com/lab206/EPCForme

SSD-MonoDETR: Supervised Scale-aware Deformable Transformer for Monocular 3D Object Detection

Transformer-based methods have demonstrated superior performance for monocular 3D object detection recently, which aims at predicting 3D attributes from a single 2D image. Most existing transformer-based methods leverage both visual and depth representations to explore valuable query points on objects, and the quality of the learned query points has a great impact on detection accuracy. Unfortunately, existing unsupervised attention mechanisms in transformers are prone to generate low-quality query features due to inaccurate receptive fields, especially on hard objects. To tackle this problem, this paper proposes a novel Supervised Scale-aware Deformable Attention (SSDA) for monocular 3D object detection. Specifically, SSDA presets several masks with different scales and utilizes depth and visual features to adaptively learn a scale-aware filter for object query augmentation. Imposing the scale awareness, SSDA could well predict the accurate receptive field of an object query to support robust query feature generation. Aside from this, SSDA is assigned with a Weighted Scale Matching (WSM) loss to supervise scale prediction, which presents more confident results as compared to the unsupervised attention mechanisms. Extensive experiments on the KITTI benchmark demonstrate that SSDA significantly improves the detection accuracy, especially on moderate and hard objects, yielding state-of-the-art performance as compared to the existing approaches. Our code will be made publicly available at https://github.com/mikasa3lili/SSD-MonoDETR.Comment: Code will be made publicly available at https://github.com/mikasa3lili/SSD-MonoDET

Interface-engineered ferroelectricity of epitaxial Hf\u3csub\u3e0.5\u3c/sub\u3eZr\u3csub\u3e0.5\u3c/sub\u3eO\u3csub\u3e2\u3c/sub\u3e thin films

Ferroelectric hafnia-based thin films have attracted intense attention due to their compatibility with complementary metal-oxide-semiconductor technology. However, the ferroelectric orthorhombic phase is thermodynamically metastable. Various efforts have been made to stabilize the ferroelectric orthorhombic phase of hafnia-based films such as controlling the growth kinetics and mechanical confinement. Here, we demonstrate a key interface engineering strategy to stabilize and enhance the ferroelectric orthorhombic phase of the Hf0.5Zr0.5O2 thin film by deliberately controlling the termination of the bottom La0.67Sr0.33MnO3 layer. We find that the Hf0.5Zr0.5O2 films on the MnO2-terminated La0.67Sr0.33MnO3 have more ferroelectric orthorhombic phase than those on the LaSrO-terminated La0.67Sr0.33MnO3, while with no wake-up effect. Even though the Hf0.5Zr0.5O2 thickness is as thin as 1.5nm, the clear ferroelectric orthorhombic (111) orientation is observed on the MnO2 termination. Our transmission electron microscopy characterization and theoretical modelling reveal that reconstruction at the Hf0.5Zr0.5O2/ La0.67Sr0.33MnO3 interface and hole doping of the Hf0.5Zr0.5O2 layer resulting from theMnO2 interface termination are responsible for the stabilization of the metastable ferroelectric phase of Hf0.5Zr0.5O2. We anticipate that these results will inspire further studies of interface-engineered hafnia-based systems

Hepatoprotective Effects of Rosmarinic Acid on Ovalbumin-Induced Intestinal Food Allergy Mouse Model

Rosmarinic acid (RA) has been proven to exert antianaphylaxis in atopic dermatitis, asthma, and allergic rhinitis. The aim of this study was to determine the hepatoprotective effects of RA on ovalbumin (OVA) challenge-induced intestinal allergy. The results exhibited that RA could relieve anaphylactic symptoms, decrease diarrhea, and prevent hypothermia in allergic mice. Moreover, the elevation of OVA specific IgE (OVA-sIgE), histamine, and mouse mast cell proteinases (mMCP-1) in the serum of OVA challenged mice were remarkably inhibited by RA. OVA challenge resulted in notable increases in serum alanine aminotransferase (ALT), aspartate aminotransferase (AST) activities, liver malondialdehyde (MDA) and nitic oxide (NO) levels, and a remarkable decrease in liver superoxide dismutase (SOD) activity and glutathione (GSH) level. RA treatments succeeded in improving these biochemical parameters and promote the redox homeostasis. Cytokine expression evaluation showed that RA effectively enhanced the expression of anti-inflammatory cytokines (IL-10 and FOXP-3) in the liver of OVA-challenged mice. Meanwhile, the elevation of pro-inflammatory cytokines (TNF-α, IL-4, IL-6, mMCP-1, and iNOS) were remarkably inhibited by RA. These findings suggest that RA possesses hepatoprotective effects on OVA challenge-induced liver injury. The anti-oxidative and anti-inflammatory activities of RA potentially play vital roles in this process

Thermal decomposition characteristics and thermal safety performance evaluation of HAN-based propellant under different external environmental stimulations

This research aims to investigate thermal characteristics and assess thermal hazards of hydroxylamine nitrate (HAN)-based liquid propellant using a combination of accelerating rate calorimeter and high-pressure differential scanning calorimetry. Adiabatic experiments revealed that the exothermic reaction initiated at 115.7 °C and a rise sharply was at 128.4 °C with a maximum self-heating rate of 164.3 °C/min and the exothermic event was accompanied by a pressure rise of 3.7 bar in 0.03s. The corrected values of adiabatic temperature rise and time to maximum rate were 605.6 °C and 1.46 min, which confirms the vulnerability of the propellant to undergo a catastrophic explosion. To prevent thermal loss prevention accidents, time to maximum rate was obtained as 24 h under 111.3 °C. The apparent activation energy calculated decreased greatly with the increase of storage temperature from 25 °C to 45 °C, and so did the thermal explosion temperature (Tb) and self-accelerating decomposition temperature (TSADT). Additionally, the linear relationship between Ea and T was E = 991.7–2.7904T. The reliability of TSADT prediction was validated through slow cook-off test. Furthermore, the propellant exhibited more violent thermal decomposition under high pressure, resulting in a higher peak power. The thermokinetic parameters related to this phenomenon were identified, specifically at pressure of 4.0 MPa

Interface-engineered ferroelectricity of epitaxial Hf0.5Zr0.5O2 thin films

Ferroelectric hafnia-based thin films are promising for applications in memories and neuromorphic devices due to their robust ferroelectricity at reduced dimensions. Here, the authors demonstrate stabilization of the metastable orthorhombic phase in Hf0.5 Zr0.5O2 films by interface engineering with a hole doping mechanism