Abstract The design and fabrication of flexible, porous, conductive electrodes with customizable functions become the prime challenge in development new‐generation wearable electronics, especially for rechargeable batteries. Here, NiCo bialloy particulate catalyst‐loaded self‐supporting carbon foam framework (NiCo@SCF) as a flexible electrode has been fabricated through one facile adsorption‐pyrolysis method using commercial melamine foam. Compared Pt/C Ir/C benchmark catalysts, NiCo@SCF...

Tax risk behavior causes serious loss of fiscal revenue, damages the country's public infrastructure, and disturbs market economic order fair competition. In recent years, tax detection, driven by information technology such as data mining artificial intelligence, has received extensive attention. To promote high-quality development detection methods, this paper provides first comprehensive overview summary existing methods worldwide. More specifically, it discusses negative impacts...

The oblique water entry of a hollow cylinder at various angles is numerically studied. formation characteristics the internal and external cavities, curling splash, underwater rotation are revealed analyzed. Our results show that asymmetric left- right-attached cavities form near both inner outer walls cylinder. There different patterns for cavity between left right sides. mainly formed by shrinkage after closure, whereas flow separation small water-entry angles. An inclined concavity forms...

With the further improvement of educational requirements, English teaching content innovation and method optimization are becoming more important. In this paper, we constructed AI-CIM model AI-MOM based on AI technology. Specifically, RNN, which can realize function generating innovative existing materials. We Teaching Method Optimization Model TCN, providing suggestions to teachers students’ loading performance. validate effectiveness through empirical analysis. The results show that...

The graph with complex annotations is the most potent data type, whose constantly evolving motivates further exploration of unsupervised dynamic representation. One representative paradigms contrastive learning. It constructs self-supervised signals by maximizing mutual information between statistic graph's augmentation views. However, semantics and labels may change within process, causing a significant performance drop in downstream tasks. This drawback becomes greatly magnified on graphs....

Recent years have witnessed rapid advances in graph representation learning, with the continuous embedding approach emerging as dominant paradigm. However, such methods encounter issues regarding parameter efficiency, interpretability, and robustness. Thus, Quantized Graph Representation (QGR) learning has recently gained increasing interest, which represents structure discrete codes instead of conventional embeddings. Given its analogous form to natural language, QGR also possesses...

The development and evaluation of graph neural networks (GNNs) generally follow the independent identically distributed (i.i.d.) assumption. Yet this assumption is often untenable in practice due to uncontrollable data generation mechanism. In particular, when distribution shows a significant shift, most GNNs would fail produce reliable predictions may even make decisions randomly. One promising solutions improve model generalization pick out causal invariant parts input graph. Nonetheless,...

The neutrophil percentage-to-albumin ratio (NPAR) is connected with all-cause mortality and stroke-related pneumonia. purpose of this study was to assess the diagnostic efficacy NPAR in predicting functional outcomes at 90 days after endovascular thrombectomy (EVT). We retrospective analyzed consecutive patients who underwent EVT Nanjing First Hospital from October 2019 June 2024. defined as percentage neutrophils divided by albumin levels. An unfavorable outcome indicated a modified Rankin...

In order to reduce the current ripple and improve power density of system, multiple structure design is generally adopted by traditional bidirectional DC/DC converter. However, fixed multiplicity can’t make converter always output smallest under different duty ratios. Through this research, it found that related cycle parallel multiplicity, then a variable proposed. Firstly, relationship between deduced, basic topology determined; Secondly, average value model AC small signal system are...

Natural hazards, such as wildfires, pose a significant threat to communities worldwide. Realtime forecasting of travel demand during wildfire evacuations is crucial for emergency managers and transportation planners make timely better-informed decisions. However, few studies focus on accurate in large-scale evacuations. To tackle this research gap, the study develops new methodological framework modeling highly granular spatiotemporal trip generation by using (a) GPS data generated mobile...

Enhancing the hydrophilicity and UV protective property of poly(ethylene terephthalate) (PET) fabric are two significant ways to upgrade its quality enlarge applicable area. Biobased finishes greatly welcomed for fabrication sustainable textiles; however, their application on PET is still challenging compared with case natural fabric. This study presents a strategy that immobilizes epigallocatechin gallate (EGCG) onto using citric acid (CA) durably hydrophilic UV-proof properties negligible...

Real-time forecasting of travel demand during wildfire evacuations is crucial for emergency managers and transportation planners to make timely better-informed decisions. However, few studies focus on accurate in large-scale evacuations. Therefore, this study develops tests a new methodological framework modeling trip generation by using (a) GPS data generated mobile devices (b) state-of-the-art AI technologies. The proposed methodology aims at evacuation trips other types trips. Based the...

The Plackett--Luce model is a popular approach for ranking data analysis, where utility vector employed to determine the probability of each outcome based on Luce's choice axiom. In this paper, we investigate asymptotic theory estimation by maximizing different types likelihood, such as full-, marginal-, and quasi-likelihood. We provide rank-matching interpretation estimating equations these estimators analyze their behavior number items being compared tends infinity. particular, establish...

A new 3D mesoscale computational approach to simulate the mechanical behavior of soil–rock mixtures (SRMs) with consideration grain-crushing process is proposed in this study. The adopts a random SRM mesostructure generation algorithm create structure. Based on generated mesostructure, whole simulation area divided into discrete cubic numbers, and transformed material distribution matrix as an input for approach. achieved by coupling calculation Matlab COMSOL. Theimulations are presented...

In order to better serve humans and improve the adaptability of quadruped robots in complex environments, a stable adaptive stair climbing algorithm based on vision is proposed. The terrain geometry stairs can be captured depth camera. Capture Point (CP) control Linear Inverted Pendulum Model (LIPM) realizes centroid stability reachable domain landing point desired are found camera vision. Finally, special leg structure adopted reduce phenomenon sliding collision, posture adjustment used...

Practical natural language processing (NLP) tasks are commonly long-tailed with noisy labels. Those problems challenge the generalization and robustness of complex models such as Deep Neural Networks (DNNs). Some used resampling techniques, oversampling or undersampling, could easily lead to overfitting. It is growing popular learn data weights leveraging a small amount metadata. Besides, recent studies have shown advantages self-supervised pre-training, particularly under-represented data....

Pairwise comparison models have been widely used for utility evaluation and ranking across various fields. The increasing scale of problems today underscores the need to understand statistical inference in these when number subjects diverges, a topic currently lacking literature except few special instances. To partially address this gap, paper establishes near-optimal asymptotic normality result maximum likelihood estimator broad class pairwise models, as well non-asymptotic convergence...