By rational <italic>in situ</italic> crystallization, HKUST-1 embedded in a chitosan film exhibits reduced cytotoxicity and restricted copper release, inducing enhanced infectious wound therapy.

Language Models (LMs) have demonstrated impressive molecule understanding ability on various 1D text-related tasks. However, they inherently lack 2D graph perception — a critical of human professionals in comprehending molecules’ topological structures. To bridge this gap, we propose MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter. MolCA enables an LM (i.e., Galactica) to understand both text- graph-based molecular contents via the cross-modal...

Triple oxygen isotope ratios

By adjusting the methanol/water ratio to control phases and morphologies, ZIFs showed enhanced performance for heavy metal adsorption.

We propose R-Map (Reposting Map), a visual analytical approach with map metaphor to support interactive exploration and analysis of the information reposting process in social media. A single original media post can cause large cascades repostings (i.e., retweets) on online networks, involving thousands, even millions people different opinions. Such behaviors form tree, which node represents message link relation. In R-Map, tree structure be spatialized highlighted key players tiled nodes....

Leading graph contrastive learning (GCL) methods perform augmentations in two fashions: (1) randomly corrupting the anchor graph, which could cause loss of semantic information, or (2) using domain knowledge to maintain salient features, undermines generalization other domains. Taking an invariance look at GCL, we argue that a high-performing augmentation should preserve semantics graphs regarding instance-discrimination. To this end, relate GCL with invariant rationale discovery, and...

Language Models (LMs) have greatly influenced diverse domains. However, their inherent limitation in comprehending 3D molecular structures has considerably constrained potential the biomolecular domain. To bridge this gap, we focus on molecule-text interpretation, and propose 3D-MoLM: 3D-Molecular Modeling. Specifically, 3D-MoLM enables an LM to interpret analyze molecules by equipping with a encoder. This integration is achieved projector, bridging encoder's representation space LM's input...

Sequential recommendation aims to predict users' next interaction with items based on their past engagement sequence. Recently, the advent of Large Language Models (LLMs) has sparked interest in leveraging them for sequential recommendation, viewing it as language modeling. Previous studies represent within LLMs' input prompts either ID indices or textual metadata. However, these approaches often fail encapsulate comprehensive world knowledge exhibit sufficient behavioral understanding. To...

Molecular Relational Learning (MRL), aiming to understand interactions between molecular pairs, plays a pivotal role in advancing biochemical research. Recently, the adoption of large language models (LLMs), known for their vast knowledge repositories and advanced logical inference capabilities, has emerged as promising way efficient effective MRL. Despite potential, these methods predominantly rely on textual data, thus not fully harnessing wealth structural information inherent graphs....

In this paper, a new scheme of combining cooperative diversity with network coding is proposed for wireless uplink multi-source multi-relay networks. The existing network-coded always conducts operation at relays in moderate-to-high signal-to-noise ratio region. Distinct from it, the determines either direct mode or according to channel qualities broadcast phase. Compared scheme, achieves performance gain terms both order and system ergodic capacity without extra bandwidth resource...

In this study, an innovative Ag/ZnO/BC nanofilms composite material was synthesized by loading zinc oxide and silver on biochar using a combination of hydrothermal calcination methods oxide, as raw materials. Subsequent characterization analysis confirmed the successful synthesis photocatalysts, Ag/ZnO nanocomposite particles were effectively loaded (BC). The exhibited robust photocatalytic removal under visible light irradiation simulated wastewater conditions with ammonia nitrogen...

Scientific literature understanding is crucial for extracting targeted information and garnering insights, thereby significantly advancing scientific discovery. Despite the remarkable success of Large Language Models (LLMs), they face challenges in understanding, primarily due to (1) a lack knowledge (2) unfamiliarity with specialized tasks. To develop an LLM we propose hybrid strategy that integrates continual pre-training (CPT) supervised fine-tuning (SFT), simultaneously infuse domain...

Visual localization, which estimates a camera's pose within known scene, is long-standing challenge in vision and robotics. Recent end-to-end methods that directly regress camera poses from query images have gained attention for fast inference. However, existing often struggle to generalize unseen views. In this work, we aim unleash the power of data synthesis promote generalizability regression. Specifically, lift real 2D into 3D Gaussian Splats with varying appearance deblurring abilities,...

Many companies and organizations have started to use some form of AIenabled auto mated tools assist in their hiring process, e.g. screening resumes, interviewing candi dates, performance evaluation. While those AI greatly improved human re source operations efficiency provided conveniences job seekers as well, there are increasing concerns on unfair treatment candidates, caused by underlying bias systems. Laws around equal opportunity fairness, like GDPR, CCPA, introduced or under...

Nighttime semantic segmentation plays a crucial role in practical applications, such as autonomous driving, where it frequently encounters difficulties caused by inadequate illumination conditions and the absence of well-annotated datasets. Moreover, models trained on daytime datasets often face generalizing effectively to nighttime conditions. Unsupervised domain adaptation (UDA) has shown potential address challenges achieved remarkable results for segmentation. However, existing methods...

Abstract Danmu (Danmaku) is a unique social media service in online videos, especially popular Japan and China, for viewers to write comments while watching videos. The danmu are overlaid on the video screen synchronized associated time, indicating viewers' thoughts of clip. This paper introduces an interactive visualization system analyze viewer behaviors collection videos enable detailed exploration one demand. identified by comparing time post danmu. supports analyzing content against...

Multiclass contour visualization is often used to interpret complex data attributes in such fields as weather forecasting, computational fluid dynamics, and artificial intelligence. However, effective accurate representations of underlying patterns correlations can be challenging multiclass visualization, primarily due the inevitable visual cluttering occlusions when number classes significant. To address this issue, design must carefully choose parameters make more comprehensible. With goal...