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Gold nanoparticles decorated on MOF derived Cu5Zn8 hollow porous carbon nanocubes for magnetic resonance imaging guided tumor microenvironment-mediated synergistic chemodynamic and photothermal therapy

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Biomaterials Advances 2024年 158卷

作者： Thirumurugan, Senthilkumar Dash, Pranjyan Sakthivel, Rajalakshmi Lin, Yu-Chien Sun, Ying-Sui Lin, Ching-Po Wang, An-Ni Liu, Xinke Dhawan, Udesh Chung, Ren-Jei Taipei10608 Taiwan School of Dental Technology College of Oral Medicine Taipei Medical University Taipei11031 Taiwan Institute of Neuroscience National Yang-Ming University Taipei11221 Taiwan Scrona AG Zürich8045 Switzerland College of Materials Science and Engineering Chinese Engineering and Research Institute of Microelectronics Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Centre for the Cellular Microenvironment Division of Biomedical Engineering James Watt School of Engineering Mazumdar-Shaw Advanced Research Centre University of Glasgow GlasgowG116EW United Kingdom Taipei10608 Taiwan

Combining chemodynamic therapy (CDT) with photothermal therapy (PTT) has developed as a promising approach for cancer treatment, as it enhances therapeutic efficiency through redox reactions and external laser induction. In this study, we designed metal organic framework (MOF) -derived Cu5Zn8/HPCNC through a carbonization process and decorated them with gold nanoparticles (Au@Cu5Zn8/HPCNC). The resulting nanoparticles were employed as a photothermal agent and Fenton catalyst. The Fenton reaction facilitated the conversation of Cu2+ to Cu+ through reaction with local H2O2, generating reactive hydroxyl radicals (·OH) with potent cytotoxic effects. To enhance the Fenton-like reaction and achieve combined therapy, laser irradiation of the Au@Cu5Zn8/HPCNC induced efficient photothermal therapy by generating localized heat. With a significantly increased absorption of Au@Cu5Zn8/HPCNC at 808 nm, the photothermal efficiency was determined to be 57.45 %. Additionally, Au@Cu5Zn8/HPCNC demonstrated potential as a contrast agent for magnetic resonance imaging (MRI) of cancers. Furthermore, the synergistic combination of PTT and CDT significantly inhibited tumor growth. This integrated approach of PTT and CDT holds great promise for cancer therapy, offering enhanced CDT and modulation of the tumor microenvironment (TME), and opening new avenues in the fight against cancer. © 2024 Elsevier B.V.

关键词： Magnetic resonance imaging

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Si-rich Silicon Nitride for Nonlinear Signal Processing Applications

Si-rich Silicon Nitride for Nonlinear Signal Processing Appl...

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Smart Photonic and Optoelectronic Integrated Circuits 2024

作者： Gardes, Frederic Vitali, Valerio Bucio, Thalía Domínguez Liu, Hao González, José Manuel Luque Jurado-Romero, Francisco Ortega-Moñux, Alejandro Churchill, Glenn Gates, James C. Hillier, James Kalfagiannis, Nikolaos Melati, Daniele Cristiani, Ilaria Schmid, Jens H. Cheben, Pavel Wangüemert-Pérez, J. Gonzalo Molina-Fernández, Íñigo Lacava, Cosimo Petropoulos, Periklis Optoelectronics Research Centre University of Southampton SouthamptonSO17 1BJ United Kingdom Electrical Computer and Biomedical Engineering Department University of Pavia Pavia27100 Italy Universidad de Málaga CEI Andalucía TECH E.T.S.I. Telecomunicación Málaga29010 Spain School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom Centre de Nanosciences et de Nanotechnologies Université Paris-Saclay CNRS Palaiseau91120 France Advanced Electronics and Photonics Research Center National Research Council Canada 1200 Montreal Road OttawaONK1A 0R6 Canada

ISBN: (纸本)9781510670402

We report the demonstration of an integrated silicon-rich silicon nitride wavelength converter based on the Bragg scattering intermodal four-wave mixing process. This broadband wavelength converter incorporates on-chip mode conversion, multiplexing and de-multiplexing functionalities. The system allows for broadband signal conversion with a 3dB bandwidth exceeding 70 nm. © 2024 SPIE.

关键词： Four wave mixing

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arXiv

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arXiv 2024年

作者： Ren, Yingying Li, Qiuli Guo, Yangyang Pedrycz, Witold Xing, Lining Liu, Anfeng Song, Yanjie School of Computer Electronics and Information Guangxi University Nanning China Guangxi Key Laboratory of Multimedia Communications and Network Technology China Key Laboratory of Parallel Distributed and Intelligent Computing Guangxi University China School of Systems Science Beijing Jiaotong University Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Systems Research Institute Polish Academy of Sciences Poland Faculty of Engineering and Natural Sciences Department of Computer Engineering Sariyer Istanbul Turkey School of Electronic Engineering Xidian University Xian China School of Electronic Engineering Central South University Changsha China National Engineering Research Center of Maritime Navigation System Dalian Maritime University Dalian China

With the rapid development of the satellite industry, the information transmission network based on communication satellites has gradually become a major and important part of the future satellite ground integration network. However, the low transmission efficiency of the satellite data relay back mission has become a problem that is currently constraining the construction of the system and needs to be solved urgently. Effectively planning the task of satellite ground networking by reasonably scheduling resources is crucial for the efficient transmission of task data. In this paper, we hope to provide a task execution scheme that maximizes the profit of the networking task for satellite ground network planning considering feeding mode (SGNPFM). To solve the SGNPFM problem, a mixed-integer planning model with the objective of maximizing the gain of the link-building task is constructed, which considers various constraints of the satellite in the feed-switching mode. Based on the problem characteristics, we propose a distance similarity-based genetic optimization algorithm (DSGA), which considers the state characteristics between the tasks and introduces a weighted Euclidean distance method to determine the similarity between the tasks. To obtain more high-quality solutions, different similarity evaluation methods are designed to assist the algorithm in intelligently screening individuals. The DSGAalso uses an adaptive crossover strategy based on similarity mechanism, which guides the algorithm to achieve efficient population search. In addition, a task scheduling algorithm considering the feed-switching mode is designed for decoding the algorithm to generate a highquality scheme. The results of simulation experiments show that the DSGA can effectively solve the SGNPFM problem. Compared to other algorithms, the proposed algorithm not only obtains higher quality planning schemes but also has faster algorithm convergence speed. The proposed algorithm improves data trans

关键词： Profitability

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Radiomics-Based Reliable Predictions of Side Effects After Radiotherapy for Prostate Cancer

Radiomics-Based Reliable Predictions of Side Effects After R...

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IEEE International Symposium on Biomedical Imaging

作者： Giulio Del Corso Eva Pachetti Rossana Buongiorno Ana Carolina Rodrigues Danila Germanese M. Antonietta Pascali José Almeida Nuno Rodrigues Manolis Tsiknakis Nickolas Papanikolaou Daniele Regge Kostas Marias ProCAncer-I Consortium Sara Colantonio National Research Council of Italy Institute of Information Science and Technologies Pisa Italy Department of Information Engineering University of Pisa Pisa Italy Champalimaud Foundation Centre for the Unknown Lisbon Portugal Foundation for Research and Technology Hellas Institute of Computer Science Heraklion Greece Department of Radiology Candiolo Cancer Institute Candiolo Italy

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

This work offers insight into the effectiveness of probabilistic models, specifically those based on ensemble approximations, in predicting adverse side effects following radiotherapy for prostate cancer. We trained a random forest model on radiomic features from 134 T2-weighted Magnetic Resonance (MRI) images of the prostate gland to identify patients experiencing acute or chronic rectal and urinary toxicity (AU-ROC ranging from 61.4% for endorectal coil acquisitions to 70.8% for the full dataset). We evaluated the reliability of the predictions using an ensemble approximation of simplified random forests obtained by an adaptive procedure of random subsampling of the training data. We used this reliability score to define a not-confident class and then recompute performance metrics more in accordance with a probabilistic approach. The outcomes we obtained (up to 7.9% increase in accuracy) indicate the approximated probabilistic models pledge more reliable predictions, thus being suitable for further investigation.

关键词： Toxicology Magnetic resonance imaging Training data Predictive models Probabilistic logic Radiation therapy Reliability

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Lightweight RF Fingerprint Identification using Cross Modal Knowledge Distillation: Learning from Wired to Wireless

Lightweight RF Fingerprint Identification using Cross Modal ...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Yi Liu Ning Gao Yongyong Chen Michail Matthaiou Xiao Li Shi Jin School of Cyber Science and Engineering Southeast University Nanjing China School of Computer Science and Technology Harbin Institute of Technology (Shenzhen) Shenzhen China Centre for Wireless Innovation (CWI) Queen's University Belfast Belfast U.K. National Mobile Communications Research Laboratory Southeast University Nanjing China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

Radio frequency fingerprint identification (RFFI) is considered as a feasible zero-trust IoT identification, however, the presence of channel effects in wireless propagation significantly impacts its identification performance. In this paper, we propose a cross modal knowledge distillation based RFFI network (DrffNet) to mitigate the channel effects. Specifically, in our proposed DrffNet network, wired and wireless long range (LoRa) RF signals are jointly used as inputs to the teacher network and student network, respectively. By transferring the RFF knowledge from the hidden layers of the teacher network, the student network can achieve effective RFFI that is resilient to the channel effects. The student network used for RFFI of a similar performance has a parameter size of only 10.68 MB, achieving a 27% reduction compared with the teacher network. We conduct experiments with real-world datasets of the LoRa devices and analyze the feasibility of the proposed network via the ablation experiments. The results demonstrate that our proposed network achieves an identification accuracy of above 95% under various channel environments. Additionally, we show that the proposed network outperforms the benchmark convolutional neural network (CNN) networks on RFFI.

关键词： Wireless communication Knowledge engineering Accuracy RF signals LoRa Fingerprint recognition Feature extraction Convolutional neural networks Security Radiofrequency identification

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Dual Z-scheme Pr2Sn2O7/P@g-C3N4/SnS2 heterojunctions for the removal of tetracycline antibiotic by persulfate activation: Kinetics, thermodynamic parameters, density functional theory, and toxicity studies

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Chemical engineering Journal 2024年 479卷

作者： Prasanna, Sanjay Ballur Sakthivel, Rajalakshmi Shanthakumar, Karthik Chimatahalli Shivamurthy, Santhosh Arehalli Lin, Yu-Chien Dhawan, Udesh Liu, Xinke Chung, Ren-Jei Taipei10608 Taiwan Department of Chemistry SJCE JSS Science and Technology University Karnataka570006 India N.M.K.R.V. College for Women Karnataka 560011 India Centre for the Cellular Microenvironment Division of Biomedical Engineering James Watt School of Engineering Mazumdar-Shaw Advanced Research Centre University of Glasgow GlasgowG116EW United Kingdom College of Materials Science and Engineering Chinese Engineering and Research Institute of Microelectronics Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore Taipei10608 Taiwan

In this study, a Pr2Sn2O7/P@g-C3N4/SnS2 ternary nanocomposite photocatalyst is obtained by hydrothermal synthesis followed by mechanical grinding. By separating electrons and holes (e−/h+) effectively through the dual Z-scheme heterojunction and activating persulfate (PS), the heterojunction demonstrated superior visible light-driven catalytic activity. Tetracycline (TC) was degraded (89.48%) in 60 min using 30 mg/L of ternary composite and 30 mg/L of PS. This system displayed the highest pseudo-first-order kinetic constant (0.0989 min−1 and R2 = 0.969). The electron paramagnetic resonance analysis showed that SO4[rad]−, [rad]OH, [rad]O2−, and 1O2 were involved in TC degradation. TC's vulnerability positions and degradation pathways were analyzed using DFT and gas chromatography-mass spectrometry analysis, while toxicity assessment software was used to determine the toxicity of intermediate products. Thus, Pr2Sn2O7/P@g-C3N4/SnS2 was established to be a promising photocatalyst template for pollutant remediation. © 2023 Elsevier B.V.

关键词： Density functional theory

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Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

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computer Systems Science & engineering 2023年第10期47卷 553-574页

作者： Adnan Hasan Bdair Aighuraibawi Selvakumar Manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPenang11800Malaysia Baghdad College of Economic Sciences University BaghdadIraq School of Computer Sciences Universiti Sains MalaysPenang11800Malaysia Information Technology Research and Development Center University of KufaNajafIraq College of Engineering University of Warith Al-AnbiyaaKarbalaIraq Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Business Administration College of Administration and Financial SciencesImam Ja’afar Al-Sadiq UniversityBaghdad10001Iraq College of Computer Science and Information Technology University of AnbarRamadi AnbarIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq

Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the ***6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration ***6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial ***,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of *** paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower Pollinationalgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential ***,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack *** results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)*** proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.

关键词： IPv6 ICMPv6 DDoS feature selection flower pollination algorithm anomaly detection

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Near-field communications:characteristics,technologies,and engineering

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Frontiers of Information technology & Electronic engineering 2024年第12期25卷 1580-1626页

作者： Yajun ZHAO Linglong DAI Jianhua ZHANG Ran JI Mengnan JIAN Hao XUE Hongkang YU Yunqi SUN Yu LU Zidong WU Zhuo XU Jinke LI Haiyang MIAO Zhiqiang YUAN Pan TANG Jiayu SHEN Tierui GONG Haixia LIU Jiaqi HAN Qiang FENG Zhi CHEN Lingxiang LI Gang YANG Yong ZENG Cunhua PAN Wang LIU Kangda ZHI Weidong HU Yuanwei LIU Xidong MU Chau YUEN Mérouane DEBBAH Chongwen HUANG Long LI Ping ZHANG State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen 518055China ZTE Corporation Beijing 100192China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310007China Key Laboratory of High Speed Circuit Design and EMC of Ministry of Education School of Electronic EngineeringXidian UniversityXi’an 710071China Collaborative Innovation Center of Information Sensing and Understanding Xidian UniversityXi’an 710071China National Key Laboratory of Wireless Communications University of Electronic Science and Technology of ChinaChengdu 611731China National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 211111China School of Electrical Engineering and Computer Science Technical University of BerlinBerlin 10623Germany School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081China Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina Centre for Wireless Innovation(CWI) School of ElectronicsElectrical Engineering and Computer ScienceQueen’s University BelfastBelfast BT39DTUK School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore KU 6G Research Center Khalifa University of Science and TechnologyAbu DhabiUnited Arab Emirates

Near-field technology is increasingly recognized due to its transformative potential in communication systems,establishing it as a critical enabler for sixth-generation(6G)telecommunication *** paper presents a comprehensive survey of recent advancements in near-field technology ***,we explore the near-field propagation fundamentals by detailing definitions,transmission characteristics,and performance ***,we investigate various near-field channel models—deterministic,stochastic,and electromagnetic information theory based models,and review the latest progress in near-field channel testing,highlighting practical performance and *** evolving channel models,traditional mechanisms such as channel estimation,beamtraining,and codebook design require redesign and optimization to align with near-field propagation *** then introduce innovative beam designs enabled by near-field technologies,focusing on non-diffractive beams(such as Bessel and Airy)and orbital angular momentum(OAM)beams,addressing both hardware architectures and signal processing frameworks,showcasing their revolutionary potential in near-field communication ***,we highlight progress in both engineering and standardization,covering the primary 6G spectrum allocation,enabling technologies for near-field propagation,and network deployment ***,we conclude by identifying promising future research directions for near-field technology development that could significantly impact system *** comprehensive review provides a detailed understanding of the current state and potential of near-field technologies.

关键词： 6G Near-field technology Channel model Codebook Non-diffractive beams Orbital angular momentum engineering and standardization

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Spear or Shield: Leveraging Generative AI to Tackle Security Threats of Intelligent Network Services

arXiv

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arXiv 2023年

作者： Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Lam, Kwok-Yan Fang, Yuguang Li, Yonghui School of Computer Science and Engineering Nanyang Technological University Singapore School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore National Centre for Research in Digital Trust School of Computer Science and Engineering Nanyang Technological University Singapore Department of Computer Science City University of Hong Kong Hong Kong School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia

Generative AI (GAI) models have been rapidly advancing, with a wide range of applications including intelligent networks and mobile AI-generated content (AIGC) services. Despite their numerous applications and potential, such models create opportunities for novel security challenges. In this paper, we examine the challenges and opportunities of GAI in the realm of the security of intelligent network AIGC services such as suggesting security policies, acting as both a "spear" for potential attacks and a "shield" as an integral part of various defense mechanisms. First, we present a comprehensive overview of the GAI landscape, highlighting its applications and the techniques underpinning these advancements, especially large language and diffusion models. Then, we investigate the dynamic interplay between GAI’s spear and shield roles, highlighting two primary categories of potential GAI-related attacks and their respective defense strategies within wireless networks. A case study illustrates the impact of GAI defense strategies on energy consumption in an image request scenario under data poisoning attack. Our results show that by employing an AI-optimized diffusion defense mechanism, energy can be reduced by 8.7%, and retransmission count can be decreased from 32 images, without defense, to just 6 images, showcasing the effectiveness of GAI in enhancing network security. © 2023, CC BY.

关键词： Network security

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A Conflict Degree-Guided Quantum Group Consensus Method Based on Graph Convolutional Networks with Enhanced Sentiment Analysis for Consumer Electronics Products

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IEEE Transactions on Consumer Electronics 2024年

作者： Zhang, Chao Liang, Xinyu Sangaiah, Arun Kumar Li, Deyu Shanxi University School of Computer and Information Technology Key Laboratory of Computational Intelligence Chinese Information Processing Ministry of Education Taiyuan030006 China National Yunlin University of Science and Technology International Graduate Institute of Artificial Intelligence Douliou64002 Taiwan Sunway University School of Engineering and Technology Petaling Jaya Selangor 47500 Malaysia Chandigarh University University Centre for Research and Development Punjab Mohali140413 India

Artificial intelligence-based human-computer interaction (AI-HCI) and consumer electronics (CE) are closely linked, making AI-HCI crucial in e-commerce by providing intelligent and personalized product recommendations. In this context, consumers often select from multiple websites and products when purchasing CE products. This makes CE product selections conflicting and random to reach a consensus, often modeled as a quantum group consensus problem. Therefore, this paper aims to enhance consumer selections via intelligent decision support using online reviews. First, an ensemble technique, multi-objective salp swarm optimization bi-directional long short-term memory (MOSSO-BiLSTM) with gate recurrent unit (GRU), is employed for sentiment analysis (SA). Second, graph convolutional networks (GCN) is used to calculate weights for key indicators. Meanwhile, according to hybrid distances, an improved fuzzy C-means three-way (FCMTW) clustering analysis is explored. Third, a conflict degree-guided quantum two-stage consensus reaching process (CRP) is designed. It includes identification rules determined by quantum frameworks and modification rules determined by regret theory (RT). Fourth, multi-objective optimization by ratio analysis plus the full MULTIplicative form (MULTIMOORA) and RT are combined for stable optimal product selections. Finally, a case study of selecting solar emergency lights verifies the viability of the proposed methodology. © 1975-2011 IEEE.

关键词： Quantum electronics

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