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Electron scattering by Friedel oscillations in carbon nanotubes

Nano research 2022年第2期15卷 889-897页

作者： Takumi Inaba Takahiro Morimoto Satoshi Yamazaki Toshiya Okazaki CNT-Application Research Center National Institute of Advanced Industrial Science and TechnologyTsukuba 305-8565Japan Research Association of High-Throughput Design and Development for Advanced Functional Materials Tsukuba 305-8565Japan

Multi-walled carbon nanotube networks were confirmed to exhibit a linear decrease in resistivity with increasing temperature from 100 to above 400 *** linearity was explained using a defect scattering model that involved Friedel oscillations(that is,electron-electron interactions).The applicability of this model,which was originally proposed for graphene,to carbon nanotubes was assessed based on a comparison of various experimental *** in the slopes of the resistivity-temperature plots following the introduction of defects,as well as an effect of charge concentration on the slope were key predictions of this *** results obtained from few-walled carbon nanotube networks are also *** the literature,linear resistivity-temperature plots were obtained from other graphene derivatives,indicating that the linearity originates from the hexagonal symmetry of these *** present work also indicated a relationship between the appearance of linearity and negative magnetoresistance above 100 *** on a mechanism incorporating scattering in association with Friedel oscillations and conventional electron conduction models,the universality of resistivity-temperature plots obtained from carbon nanotube networks is introduced.

关键词： carbon nanotube electron transport electron-electron interaction Friedel oscillations magnetoresistance

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Emergency Vehicle Priority Strategy Based on the Cellular Automata Model 6

Emergency Vehicle Priority Strategy Based on the Cellular Au...

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6th International Conference on Communications, Information System and Computer Engineering, CISCE 2024

作者： Zhou, Yujuan Wen, Jiayan School of Automation Guangxi University of Science and Technology The Research Center for Intelligent Cooperation and Cross-application Liuzhou China Guangxi University of Science and Technology Guangxi Key Laboratory of Automobile Components and Vehicle Technology Liuzhou China

ISBN: (纸本)9798350353174

To address the issue of emergency vehicle delays in congested urban areas, this paper proposes a novel priority strategy for emergency vehicles based on the V2X environment. Implemented within a newly developed dual-lane cellular automaton model featuring emergency vehicles, this strategy leverages real-time information acquisition to allow civilian vehicles to change lanes immediately when conditions permit, significantly reducing travel time for emergency vehicles and minimizing the impact on social vehicles traffic speed. Simulation results confirm that this strategy substantially enhances the efficiency of emergency vehicle operations in urban areas, demonstrating significant practicality and potential for application. Moreover, the implementation of this strategy contributes valuable theoretical and practical insights to the field of intelligent transportation systems, paving the way for future advancements in urban traffic management and emergency response optimization. © 2024 IEEE.

关键词： Emergency vehicles

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Enhancing Reranking for Recommendation with LLMs through User Preference Retrieval 31

Enhancing Reranking for Recommendation with LLMs through Use...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Zhang, Haobo Zhu, Qiannan Dou, Zhicheng Gaoling School of Artificial Intelligence Renmin University of China China School of Artificial Intelligence Beijing Normal University China Engineering Research Center of Intelligent Technology and Educational Application MOE China

ISBN: (纸本)9798891761964

Recently, large language models (LLMs) have shown the potential to enhance recommendations due to their sufficient knowledge and remarkable summarization ability. However, the existing LLM-powered recommendation may create redundant output, which generates irrelevant information about the user's preferences on candidate items from user behavior sequences. To address the issues, we propose a framework UR4Rec that enhances reranking for recommendation with large language models through user preference retrieval. Specifically, UR4Rec develops a small transformer-based user preference retriever towards candidate items to build the bridge between LLMs and recommendation, which focuses on producing the essential knowledge through LLMs from user behavior sequences to enhance reranking for recommendation. Our experimental results on three real-world public datasets demonstrate the superiority of UR4Rec over existing baseline models. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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research on Tibetan Speech Recognition Based on CNN-DFSMN-CTC 2

Research on Tibetan Speech Recognition Based on CNN-DFSMN-CT...

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2nd Asia Conference on Electrical, Power and Computer Engineering, EPCE 2023

作者： Gan, Zhenye Kong, Zhenxing Zhang, Min Northwest Normal University Engineering Research Center of Gansu Province for Intelligent Information Technology and Application College of Physics and Electronic Engineering LanZhou China

ISBN: (纸本)9798350310818

In this paper, we present an improved acoustic model CNN-DFSMN, and it uses CNN to study local frequency domain and time domain features, and introduces skip connections between memory blocks in adjacent layers, thus alleviating the problem of gradient disappearance when building very deep structures. In recent years, the acoustic model based on Connected Temporal Classification (CTC) has achieved good performance in speech recognition. Generally, lstm-type networks are used as acoustic models in CTC. However, LSTM calculation cost is high and sometimes it is hard to train CTC criteria. This paper, Be inspired by DFSMN's work, we replace LSTM with DFSMN in the acoustic modeling based on CCT, then combine convolution neural network (CNN) with this architecture to train an acoustic model based on CNN-DFSMN-CTC, match the acoustic model with the 3-gram language model, and combine dictionary and acoustic feature vector to identify and decode the recognition text. This further improves the performance of Tibetan speech recognition. The last experiment results show that the WER of DFSMN-CTC based methods is 2.34% and 0.94% higher than that of CNN-CTC based and LSTM-CTC based methods under the same test set. The recognition rate based on CNN-DFSMN-CTC is 3.52% and 2.23% higher than that based on DFSMN and DFSMN-CTC. © 2023 IEEE.

关键词： Speech recognition

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TLRNet: Tibetan Lip Reading Based on ResNet and BiGRU 2

TLRNet: Tibetan Lip Reading Based on ResNet and BiGRU

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2nd Asia Conference on Electrical, Power and Computer Engineering, EPCE 2023

作者： Gan, Zhenye Ding, Xu Yu, Xinke Kong, Zhenxing Northwest Normal University Engineering Research Center of Gansu Province for Intelligent Information Technology and Application College of Physics and Electronic Engineering Lanzhou China

ISBN: (纸本)9798350310818

Lip reading, also known as visual speech recognition, is a way of human-computer interaction based on visual information. At present, the research on lip reading mainly focuses on English and Mandarin Chinese, and there are relatively few studies on Tibetan, a low-resource minority language. Therefore, the present study proposes a specific deep learning model named the TLRNet for word-level visual speech recognition for Tibetan. The model comprises the ResNet-18 architecture, which is a residual neural network, and the BiGRU layer, a bi-directional gated recurrent unit. We train and evaluate it on the TLRW-50 dataset, which consists of fifty common Tibetan words. Our proposed model achieves Top-1 and Top-5 classification accuracies of 41.82% and 59.37%, respectively, demonstrating its potential effectiveness in recognizing Tibetan spoken words based on visual cues. © 2023 IEEE.

关键词： Human computer interaction

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Tibetan Speech Recognition Based on Multipath Convolutional Neural Network 2

Tibetan Speech Recognition Based on Multipath Convolutional ...

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2nd Asia Conference on Electrical, Power and Computer Engineering, EPCE 2023

作者： Gan, Zhenye Li, Tingting Guo, Hanwen Northwest Normal University Engineering Research Center of Gansu Province for Intelligent Information Technology and Application School of Physics and Electronic Engineering Lanzhou China

ISBN: (纸本)9798350310818

In recent years, end-to-end automatic speech recognition (ASR) has been widely used. Many researchers have studied and improved convolutional neural networks (CNNs), but most of them are improved from the depth direction, ignoring some detailed features in the width direction. Therefore, this paper proposes a MCNN-CTC based method for Tibetan speech recognition. The multipath convolutional neural network (MCNN) acquires more detailed features by increasing the width of the network. In order to study the effect of the depth and width of the model on speech recognition rate, this paper studies MCNN-CTC with DCNN-CTC as the baseline model. The results show that compared with DCNN-CTC, the relative error rate of MCNN-CTC decreases by 7.72% when syllables are used as modeling units. When the word was used as the modeling unit, the relative error rate decreased by 7.79%, which verified the validity of the model. © 2023 IEEE.

关键词： Speech recognition

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An improved Tibetan speaker recognition method based on ResNet 2

An improved Tibetan speaker recognition method based on ResN...

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2nd Asia Conference on Electrical, Power and Computer Engineering, EPCE 2023

作者： Gan, Zhenye Li, Jincheng Qu, Ziqian Yu, Yue Northwest Normal University Engineering Research Center of Gansu Province for Intelligent Information Technology and Application College of Physics and Electronic Engineering LanZhou China

ISBN: (纸本)9798350310818

In the past decade, there have been relatively few studies on speaker recognition based on minority languages, especially Tibetan, and most of them use traditional recognition methods. Starting from the Tibetan level, this paper adopts the mainstream neural network learning, and proposes a new Fast ResNet-101 structure by improving the residual network (ResNet) module structure, thus constructing a complete Tibetan speaker recognition system. The improved model is compared and evaluated by two metric learning loss functions, prototype and angle prototype. By introducing Fast ResNet-34 and Fast ResNet-50 models as baselines, the experimental comparison shows that the Fast ResNet-101 model with deeper network structure has the best performance, and the model recognition effect after Angular Prototype metric loss function processing is better. The recognition error rate can reach 3.72 %. © 2023 IEEE.

关键词： Speech recognition

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SPA-Tracker: Spectral Prompt Adaptation for Hyperspectral Object Tracking 14

SPA-Tracker: Spectral Prompt Adaptation for Hyperspectral Ob...

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14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2024

作者： Wan, Huang Xie, Shaoxiong Luo, Tian Ma, Siqi Zhao, Lin Li, Wen Hu, Wenjing Hunan Institute of Science and Technology School of Information Science and Engineering Yueyang414006 China Hunan Institute of Science and Technology Hunan Engineering Technology Research Center for 3D Reconstruction and Intelligent Application Yueyang China

ISBN: (纸本)9798331513139

Hyperspectral object tracking (HOT) is a crucial research area in computer vision and remote sensing. Unlike RGB-based trackers, HOT can more accurately capture the intrinsic material characteristics of objects. However, the limited number of training samples in hyperspectral datasets presents challenges for developing robust hyperspectral trackers. To tackle this issue, prompt learning is utilized to enhance spectral information in the input space while leveraging prior knowledge from foundational trackers. In this paper, we introduce a novel Spectral Prompt Adaptation Tracker (SPA-Tracker) that learns valuable prompts from hyperspectral images and adapts prompt information with hyperspectral, even when labeled training data is scarce. Compared to the baseline, SPA-Tracker includes two distinct modules: 1) A Spectral Information Prompt (SIP) module that extracts useful spectral information to enrich the input;and 2) An efficient Embedded Adapter (EA) module that facilitates learning interactions between RGB and hyperspectral features, thereby minimizing reliance on pre-trained RGB trackers. Extensive experiments demonstrate that our method achieves outstanding performance on HOT tasks. © 2024 IEEE.

关键词： Object tracking

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Bioinformatic Resources for Exploring Human-virus Protein-protein Interactions Based on Binding Modes

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Genomics, Proteomics & Bioinformatics 2024年第5期22卷 45-59页

作者： Huimin Chen Jiaxin Liu Gege Tang Gefei Hao Guangfu Yang State Key Laboratory of Green Pesticide International Joint Research Center for Intelligent Biosensor Technology and HealthCentral China Normal UniversityWuhan 430079China State Key Laboratory of Green Pesticide Key Laboratory of Green Pesticide and Agricultural BioengineeringMinistry of EducationCenter for Research and Development of Fine ChemicalsGuizhou UniversityGuiyang 550025China

Historically,there have been many outbreaks of viral diseases that have continued to claim millions of *** on human-virus protein-protein interactions(PPIs)is vital to understanding the principles of human-virus relationships,providing an essential foundation for developing virus control strategies to combat *** rapidly accumulating data on human-virus PPIs offer unprecedented opportunities for bioinformatics research around human-virus ***,available detailed analyses and summaries to help use these resources systematically and efficiently are ***,we comprehensively review the bioinformatic resources used in human-virus PPI research,and discuss and compare their functions,performance,and *** review aims to provide researchers with a bioinformatic toolbox that will hopefully better facilitate the exploration of human-virus PPIs based on binding modes.

关键词： Artificial intelligence Bioinformatic resource Protein-protein docking Protein-protein interaction Viral pandemic

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Inter-organelle communication dynamically orchestrates juvenile hormone biosynthesis and female reproduction

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National Science Review 2025年第3期12卷 71-87页

作者： Shiming Zhu Fangfang Liu Xiaoyi Chen Sishi Xia Yingting Wu Wei Tang Chonghua Ren Jian Wang Sheng Li Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology Guangzhou Key Laboratory of Insect Development Regulation and Application Research Institute of Insect Science and Technology School of Life Sciences South China Normal University Guangmeiyuan R&D Center Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology South China Normal University Department of Entomology University of Maryland College Park

Inter-organelle communication coordinates cellular homeostasis and function. Juvenile hormone（ JH） is produced in the corpora allata（CA） and acts as a gonadotrophic hormone in most insects. Using transcriptomic, biochemical, molecular, and genetic analyses, here we investigated the underlying mechanism of how inter-organelle communication dynamically orchestrates JH biosynthesis and female reproduction in the American cockroach, Periplaneta americana. The extracellular stimuli insulin and allatostatin act through their membrane receptors and antagonistically regulate Ry R-mediated Ca2+release from the endoplasmic reticulum in CA cells. Ca2+-activated Ca MKII stimulates energy metabolism in the mitochondria partially via SLC25A6, and induces the expression of JH biosynthetic genes HMGR, Jhamt,and Cyp15a1 through activating transcription factor CREB, which recruits CBP for histone acetylation in the nucleus. Additionally, mitochondria interact with CREB-CBP through mitonuclear communication to regulate JH biosynthesis. From the perspective of inter-organelle communication, this comprehensive study significantly advanced our understanding of hormone biosynthesis and reproductive biology in insects.

关键词： membrane receptor endoplasmic reticulum calcium signaling mitochondrial activity transcriptional regulation epigenetic regulation

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