Abstract Herein, novel conductive composite hydrogels are developed with high stretchability, ultra‐softness, excellent conductivity, and good self‐healing ability. The formed in the water/glycerol binary solvent system, which polyaniline nanoparticles (PANI‐NPs) incorporated into poly(poly(ethylene glycol) methacrylate‐co‐acrylic acid) (P(PEG‐co‐AA)) scaffolds via dynamically electrostatic interactions hydrogen bonds. PANI‐NPs serve as fillers to assign conductivity hydrogel, while enhanced...

The dominant graph neural networks (GNNs) over-rely on the links, several serious performance problems with which have been witnessed already, e.g., suspended animation problem and over-smoothing problem. What's more, inherently inter-connected nature precludes parallelization within graph, becomes critical for large-sized as memory constraints limit batching across nodes. In this paper, we will introduce a new network, namely GRAPH-BERT (Graph based BERT), solely attention mechanism without...

Histopathological image classification (HIC) and content-based histopathological retrieval (CBHIR) are two promising applications for the whole slide (WSI) analysis. HIC can efficiently predict type of lesion involved in a image. In general, aid pathologists locating high-risk cancer regions from WSI by providing cancerous probability map WSI. contrast, CBHIR was developed to allow searches with similar content region interest (ROI) database consisting historical cases. Sets cases accessible...

Multispectral remote sensing images are often contaminated by haze, which causes low image quality. In this paper, a novel dehazing method based on deep convolutional neural network (CNN) with the residual structure is proposed for multispectral images. First, multiple CNN individuals connected in parallel and each individual used to learn regression from hazy clear image. Then, outputs of fused weight maps produce final result. designed network, individuals, mining multiscale haze features...

To meet various practical requirements and enhance human experience, hydrogels possessing multifunctionality are of great significance for flexible wearable sensors. Herein, a novel strategy has been developed to fabricate nanocomposite with combination excellent stretchability, rapid recoverability, self-healing, outstanding adhesiveness. The PAAc/SiO2-g-PAAm were facilely prepared through the polymerization acrylic acid (AAc) using SiO2-g-polyacrylamide core–shell hybrid nanoparticles...

Fine-grained visual categorization (FGVC) is an important and challenging problem due to large intra-class differences small inter-class caused by deformation, illumination, angles, etc. Although major advances have been achieved in natural images the past few years release of popular datasets such as CUB-200-2011, Stanford Cars Aircraft datasets, fine-grained ship classification remote sensing has rarely studied because relative scarcity publicly available datasets. In this paper, we...

Extractive summarization is a crucial task in natural language processing that aims to condense long documents into shorter versions by directly extracting sentences. The recent introduction of large models has attracted significant interest the NLP community due its remarkable performance on wide range downstream tasks. This paper first presents thorough evaluation ChatGPT’s extractive and compares it with traditional fine-tuning methods various benchmark datasets. Our experimental analysis...

Herein, we propose a facile strategy to fabricate high-performance hydrogels combining strain-stiffening mechanical behavior with self-healing ability and low hysteresis, which feature unique structure two mechanically distinct polymeric networks. The stereocomplex micelles sc–PEG-PLA are first obtained from the mixtures of poly(ethylene glycol)-b-poly(l-lactide) (PEG–PLLA) glycol)-b-poly(d-lactide) (PEG–PDLA), then PAA/sc–PEG-PLA fabricated one-pot free radical polymerization process...

Automatic ship detection in optical remote sensing images has attracted wide attention for its broad applications. Major challenges this task include the interference of cloud, wave, wake, and high computational expenses. We propose a fast robust algorithm to solve these issues. The framework is designed based on deep convolutional neural networks (CNNs), which provide accurate locations targets an efficient way. First, CNN extract features. Then, region proposal network (RPN) applied...

Inshore ship detection is a popular research domain for optical remote sensing image understanding with many applications in harbor management. However, recent approaches on inshore depend heavily hand-crafted features, which need complicated procedure. In this paper, we propose new method to achieve based Mask R-CNN. We introduce Soft-Non-Maximum Suppression (Soft-NMS) into our framework improve the robustness nearby ships. Both battleships and merchantships can be detected framework....

Text classification is a fundamental problem in natural language processing. Recent studies applied graph neural network (GNN) techniques to capture global word co-occurrence corpus. However, previous works are not scalable large-sized corpus and ignore the heterogeneity of text graph. To address these problems, we introduce novel Transformer based heterogeneous network, namely Graph (TG-Transformer). Our model learns effective node representations by capturing structure from We propose...

Herein, a novel strategy has been developed for the preparation of high-performance conductive elastomers featuring long functional polymer cross-linkers. The macromolecular cross-linkers containing multi boronic ester bonds in backbone were designed via thiol/acrylate reactions between poly(ethylene glycol) diacrylate (PEGDA) and dithiol-containing (BDB). obtained PEG–BDB was copolymerized with n-butyl acrylate (n-BA) to provide PBA/PEG–BDB elastomers. resultant exhibit combined desirable...

Ionic liquid (IL)-based conductive elastomers have recently emerged as promising stretchable electrodes for applications in flexible electronic devices because of the interesting features ILs. However, conventional IL-based suffer from low mechanical properties, instability ambient environment, and lack self-healability. Herein, highly stretchable, stable, self-healable PnBA/SiO2/PVI (Cu2+, [EMIM]+[BF4]−) were designed facilely fabricated by one-pot Pickering emulsion polymerization. The is...

Existing text summarization systems have made significant progress in recent years, but typically generate summaries a single step. The one-shot setting is sometimes inadequate, however, as the generated summary may contain hallucinations or overlook important details related to reader's interests. In this paper, we address limitation by proposing SummIt, an iterative framework based on large language models like ChatGPT. Our enables model refine iteratively through self-evaluation and...

In contrast to natural objects, aerial targets are usually non-axis aligned with arbitrary orientations. However, mainstream weakly supervised object detection (WSOD) methods can only predict horizontal bounding boxes (HBBs) from existing proposals generated by offline algorithms. To oriented (OBBs) for while testing images end-to-end without proposals, WSODet is designed leveraging on layerwise relevance propagation (LRP) and point set representation (RepPoints). be specific, based the WSOD...

In the field of pathology, whole slide image (WSI) has become major carrier visual and diagnostic information. Content-based retrieval among WSIs can aid diagnosis an unknown pathological by finding its similar regions in with However, huge size complex content WSI pose several challenges for retrieval. this paper, we propose unsupervised, accurate, fast method a breast histopathological image. Specifically, presents local statistical feature nuclei morphology distribution nuclei, employs...

This paper presents a novel vision-based method to solve the 6-degree-of-freedom pose estimation problem of textureless space objects from single monocular image. Our approach follows coarse-to-fine procedure, utilizing only shape and contour information input To achieve invariance initialization, we select series projection images that are similar image establish many-to-one 2D-3D correspondences by feature matching. Intensive attention is focused on outlier rejection introduce an...

Multispectral remote sensing images are often degraded by clouds, resulting in the reduced efficiency and accuracy of image interpretation. Thin cloud removal is one most important significant tasks for optical multispectral images. In this article, we propose a novel thin method images, which combination traditional methods deep learning methods. First, adopt U-Net to estimate reference thickness map cloudy image. Then, convolutional neural network named Slope-Net designed coefficient each...