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A Novel Fractional Dengue Transmission Model in the Presence of Wolbachia Using Stochastic Based Artificial Neural Network

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Computer Modeling in Engineering & sciences 2024年第5期139卷 1217-1238页

作者： Zeshan Faiz Iftikhar Ahmed Dumitru Baleanu Shumaila Javeed Department of Mathematics COMSATS University IslamabadIslamabad45550Pakistan Department of Mathematics Cankaya UniversityAnkara06790Turkey Institute of Space sciences Magurele-Bucharest077125Romania Department of Medical Research China Medical University HospitalChina Medical UniversityTaichung40402Taiwan Department of Computer Science and Mathematics Lebanese American UniversityBeirut135053Lebanon Department of Mathematics Mathematics Research CenterNear East UniversityNicosia/Mersin99138Turkey

The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model(FDTM)in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network(LM-NN)*** fractional dengue transmission model(FDTM)consists of 12 *** human population is divided into four compartments;susceptible humans(S_(h)),exposed humans(E_(h)),infectious humans(I_(h)),and recovered humans(R_(h)).Wolbachia-infected and Wolbachia-uninfected mosquito population is also divided into four compartments:aquatic(eggs,larvae,pupae),susceptible,exposed,and *** investigated three different cases of vertical transmission probability(η),namely when Wolbachia-free mosquitoes persist only(η=0.6),when both types of mosquitoes persist(η=0.8),and when Wolbachia-carrying mosquitoes persist only(η=1).The objective of this study is to investigate the effectiveness of Wolbachia in reducing dengue and presenting the numerical results by using the stochastic structure LM-NN approach with 10 hidden layers of neurons for three different cases of the fractional order derivatives(α=0.4,0.6,0.8).LM-NN approach includes a training,validation,and testing procedure to minimize the mean square error(MSE)values using the reference dataset(obtained by solving the model using the Adams-Bashforth-Moulton method(ABM).The distribution of data is 80% data for training,10% for validation,and,10% for testing purpose)results.A comprehensive investigation is accessible to observe the competence,precision,capacity,and efficiency of the suggested LM-NN approach by executing the MSE,state transitions findings,and regression *** effectiveness of the LM-NN approach for solving the FDTM is demonstrated by the overlap of the findings with trustworthy measures,which achieves a precision of up to 10^(-4).

关键词： Wolbachia dengue neural network vertical transmission mean square error Levenberg-Marquardt

Correlative Mn-Co catalyst excels Pt in oxygen reduction reaction of quasi-solid-state zinc-air batteries

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Nano Research 2024年第5期17卷 4118-4124页

作者： Tingting Wang Jincheng Huang Wei Sang Cai Zhou Bohan Zhang Wei Zhu Kang Du Zongkui Kou Shengxiang Wang School of Mathematical and Physical sciences Wuhan Textile UniversityWuhan 430200China State Key Laboratory of Advanced technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China

Zn-air batteries(ZABs)as a class of promising energy storage setups are generally powered by efficient and robust catalysts at the oxygen-involving *** the existing non-noble catalysts have outperformed noble Pt benchmark in the alkaline liquid-state ZABs,to the best of our knowledge few have excelled Pt in quasi-solid-state(QSS)***,we found that an integrated Mn-Co cathode derived from the bimetallic Mn/Co metal organic frameworks generates a 1.4-fold greater power density in the QSS ZABs than a Pt cathode while its power density in liquid-state ZABs is only 0.8-fold of the ***,such Mn-Co catalyst delivers high-rate oxygen reduction reaction(ORR)capability with half-wave potential of 0.84 *** in-depth characterizations and analyses have demonstrated that the Co and Mn species show the specific affinity towards H_(2)O and O_(2),respectively,synergizing the ORR process in the water-deficient environment of QSS *** work has enlightened the rational design of non-noble metal catalysts to improve the power density of QSS ZABs.

关键词： non-noble metal catalysts zinc-air battery quasi-solid-state synergistic effect

Deep Learning-Based ECG Classification for Arterial Fibrillation Detection

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Computers, Materials & Continua 2024年第6期79卷 4805-4824页

作者： Muhammad Sohail Irshad Tehreem Masood Arfan Jaffar Muhammad Rashid Sheeraz Akram Abeer Aljohani Faculty of Computer Science&Information technology The Superior UniversityLahore54000Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54000Pakistan Department of Computer Science National University of TechnologyIslamabad45000Pakistan Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Department of Computer Science Applied CollegeTaibah UniversityMedina42353Saudi Arabia

The application of deep learning techniques in the medical field,specifically for Atrial Fibrillation(AFib)detection through Electrocardiogram(ECG)signals,has witnessed significant *** and timely diagnosis increases the patient’s chances of ***,issues like overfitting and inconsistent accuracy across datasets remain *** a quest to address these challenges,a study presents two prominent deep learning architectures,ResNet-50 and DenseNet-121,to evaluate their effectiveness in AFib *** aim was to create a robust detection mechanism that consistently performs *** such as loss,accuracy,precision,sensitivity,and Area Under the Curve(AUC)were utilized for *** findings revealed that ResNet-50 surpassed DenseNet-121 in all evaluated *** demonstrated lower loss rate 0.0315 and 0.0305 superior accuracy of 98.77%and 98.88%,precision of 98.78%and 98.89%and sensitivity of 98.76%and 98.86%for training and validation,hinting at its advanced capability for AFib *** insights offer a substantial contribution to the existing literature on deep learning applications for AFib detection from ECG *** comparative performance data assists future researchers in selecting suitable deep-learning architectures for AFib ***,the outcomes of this study are anticipated to stimulate the development of more advanced and efficient ECG-based AFib detection methodologies,for more accurate and early detection of AFib,thereby fostering improved patient care and outcomes.

关键词： Convolution neural network atrial fibrillation area under curve ECG false positive rate deep learning classification

Efficient synthesis of bottle-brush polymers enabled by selective photoactivation strategy in NIR-induced PET-RAFT polymerization

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Science China Chemistry 2024年第7期67卷 2353-2361页

作者： Hao Zha Lin Cheng Zuowei Wang Chao Liu Chunyan Hong Department of Polymer Science and Engineering University of Science and Technology of ChinaHefei 230026China Hefei National Laboratory for Physical sciences at the Microscale University of Science and Technology of ChinaHefei 230026China

Bottle-brush polymers possessing densely grafted side chains have special properties that are distinct from linear ***,an efficient method for preparing bottle-brush polymers based on a selective photoactivation strategy in the photoinduced electron/energy transfer reversible addition-fragmentation chain transfer(PET-RAFT)polymerization was developed.A methacrylate monomer 2-(2-(dodecylthiocarbonothioylthio)propionate)ethyl methacrylate(DTPEMA)containing a 2-(dodecylthiocarbonothioylthio)propionate(DTP)unit with a secondary R group was *** the unique selectivity of metal naphthalocyanine photocatalyst zinc 2,11,20,29-tetra-tert-butyl-2,3-naphthalocyanine(ZnTtBNc)toward trithiocarbonate with tertiary R group,the PET-RAFT polymerization of DTPEMA catalyzed by ZnTtBNc was performed under near infrared(NIR)light(λ_(max)=760 nm)irradiation at room temperature,using 4-cyano-4-[(dodecylsulfanylthiocarbonyl)-sulfanyl]pentanoic acid(CDTPA)with a tertiary R group as a chain transfer agent(CTA).Proton nuclear magnetic resonance(1H NMR)and gel permeation chromatography(GPC)results demonstrated that the DTP units in the side chains were inert during the *** grafting poly(methyl acrylate)(PMA)from PDTPEMA via thermal-initiated RAFT polymerization,welldefined P(DTPEMA-g-PMA)bottle-brush polymers could be ***,the film prepared from the bottle-brush polymer exhibited excellent scratch self-healing property due to the interlocking of side chains.

关键词： bottle-brush polymers PET-RAFT polymerization selective photoactivation scratch self-healing

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The effect of salt anion in ether‐based electrolyte for electrochemical performance of sodium‐ion batteries:A case study of hard carbon

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Carbon Energy 2024年第8期6卷 285-297页

作者： Jiabao Li Jingjing Hao Quan Yuan Ruoxing Wang Frederick Marlton Tianyi Wang Chengyin Wang Xin Guo Guoxiu Wang College of Chemistry and Chemical Engineering Yangzhou UniversityYangzhouJiangsuChina School of Mathematical and Physical sciences Centre for Clean Energy TechnologyFaculty of ScienceUniversity of Technology SydneySydneyAustralia

Compared with the extensively used ester‐based electrolyte,the hard carbon(HC)electrode is more compatible with the ether‐based counterpart in sodium‐ion batteries,which can lead to improved cycling stability and robust rate ***,the impact of salt anion on the electrochemical performance of HC electrodes has yet to be fully *** this study,the anionic chemistry in regulating the stability of electrolytes and the performance of sodium‐ion batteries have been systematically *** work shows discrepancies in the reductive stability of the anionic group,redox kinetics,and component/structure of solid electrolyte interface(SEI)with different salts(NaBF_(4),NaPF_(6),and NaSO_(3)CF_(3))in the typical ether solvent(diglyme).Particularly,the density functional theory calculation manifests the preferred decomposition of PF_(6)−due to the reduced reductive stability of anions in the solvation structure,thus leading to the formation of NaF‐rich *** investigation on redox kinetics reveals that the NaPF_(6)/diglyme can induce the fast ionic diffusion dynamic and low charge transfer barrier for HC electrode,thus resulting in superior sodium storage performance in terms of rate capability and cycling life,which outperforms those of NaBF_(4)/diglyme and NaSO_(3)CF_(3)/***,this work offers valuable insights for optimizing the electrochemical behaviors of electrode materials by regulating the anionic group in the electrolyte.

关键词： ether‐based electrolyte reaction kinetics salt anion SEI components sodium storage

Aubry-Mather theory for contact Hamiltonian systems Ⅲ

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Science China Mathematics 2024年第11期67卷 2541-2570页

作者： Panrui Ni Lin Wang Shanghai Center for Mathematical sciences Fudan University School of Mathematics and Statistics Beijing Institute of Technology

By exploiting the contact Hamiltonian dynamics（T*M × R,Φ_t） around the Aubry set of contact Hamiltonian systems,we provide a relation among the Mather set,the Φ_t-recurrent set,the strongly static set,the Aubry set,the Ma?é set,and the Φ_t-non-wandering ***,we consider the strongly static set,as a new flow-invariant set between the Mather set and the Aubry set in the strictly increasing *** show that this set plays an essential role in the representation of certain minimal forward weak Kolmogorov-Arnold-Moser（KAM） solutions and the existence of transitive orbits around the Aubry set.

关键词： Aubry-Mather theory weak KAM theory contact Hamiltonian systems Hamilton-Jacobi equations

N-doped graphene quantum dot-decorated N-TiO2/P-doped porous hollow g-C_(3)N_(4) nanotube composite photocatalysts for antibiotic photodegradation and H2 production

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International Journal of Minerals,Metallurgy and Materials 2024年第1期31卷 165-178页

作者： Jingshu Yuan Yao Zhang Xiaoyan Zhang Junjie Zhang Shen’gen Zhang Institute for Advanced Materials and technology University of Science and Technology BeijingBeijing 100083China Xi’an Fanyi university Xi’an 710105China Shunde Graduate School of university of Science and technology Beijing Foshan 528399China State Key Laboratory of Lunar and Planetary sciences Macao University of Science and TechnologyMacao SAR 820000China

Exclusive responsiveness to ultraviolet light (~3.2 eV) and high photogenerated charge recombination rate are the two primary drawbacks of pure TiO_(2). We combined N-doped graphene quantum dots (N-GQDs), morphology regulation, and heterojunction construction strategies to synthesize N-GQD/N-doped TiO_(2)/P-doped porous hollow g-C_(3)N_(4) nanotube (PCN) composite photocatalysts (denoted as G-TPCN). The optimal sample (G-TPCN doped with 0.1wt% N-GQD, denoted as 0.1% G-TPCN) exhibits significantly enhanced photoabsorption, which is attributed to the change in bandgap caused by elemental doping (P and N), the improved light-harvesting resulting from the tube structure, and the upconversion effect of N-GQDs. In addition, the internal charge separation and transfer capability of0.1% G-TPCN are dramatically boosted, and its carrier concentration is 3.7, 2.3, and 1.9 times that of N-TiO_(2), PCN, and N-TiO_(2)/PCN(TPCN-1), respectively. This phenomenon is attributed to the formation of Z-scheme heterojunction between N-TiO_(2) and PCNs, the excellent electron conduction ability of N-GQDs, and the short transfer distance caused by the porous nanotube structure. Compared with those of N-TiO_(2), PCNs, and TPCN-1, the H2 production activity of 0.1%G-TPCN under visible light is enhanced by 12.4, 2.3, and 1.4times, respectively, and its ciprofloxacin (CIP) degradation rate is increased by 7.9, 5.7, and 2.9 times, respectively. The optimized performance benefits from excellent photoresponsiveness and improved carrier separation and migration efficiencies. Finally, the photocatalytic mechanism of 0.1% G-TPCN and five possible degradation pathways of CIP are proposed. This study clarifies the mechanism of multiple modification strategies to synergistically improve the photocatalytic performance of 0.1% G-TPCN and provides a potential strategy for rationally designing novel photocatalysts for environmental remediation and solar energy conversion.

关键词： N-doped TiO_(2) N-doped graphene quantum dots P-doped g-C_(3)N_(4) porous hollow nanotube heterojunction photocatalysis

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Effects of nitrogen deposition on the carbon budget and water stress in Central Asia under climate change

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Journal of Arid Land 2024年第8期16卷 1118-1129页

作者： HAN Qifei XU Wei LI Chaofan School of Geographical sciences Nanjing University of Information Science&TechnologyNanjing 210044China

Atmospheric deposition of nitrogen(N)plays a significant role in shaping the structure and functioning of various terrestrial ecosystems ***,the magnitude of N deposition on grassland ecosystems in Central Asia still remains highly *** this study,a multi-data approach was adopted to analyze the distribution and amplitude of N deposition effects in Central Asia from 1979 to 2014 using a process-based denitrification decomposition(DNDC)*** showed that total vegetation carbon(C)in Central Asia was 0.35(±0.09)Pg C/a and the averaged water stress index(WSI)was 0.20(±0.02)for the whole *** N deposition led to an increase in the vegetation C of 65.56(±83.03)Tg C and slightly decreased water stress in Central *** of this study will expand both our understanding and predictive capacity of C characteristics under future increases in N deposition,and also serve as a valuable reference for decision-making regarding water resources management and climate change mitigation in arid and semi-arid areas globally.

关键词： carbon dynamics climate change grassland ecosystems nitrogen deposition water stress index

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CMN: a co-designed neural architecture search for efficient computing-in-memory-based mixture-of-experts

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Science China(Information sciences) 2024年第10期67卷 100-114页

作者： Shihao HAN Sishuo LIU Shucheng DU Mingzi LI Zijian YE Xiaoxin XU Yi LI Zhongrui WANG Dashan SHANG Department of Electrical and Electronic Engineering The University of Hong Kong ACCESS-AI Chip Center for Emerging Smart Systems InnoHK Centers Key Lab of Fabrication Technologies for Integrated Circuits Chinese Academy of Sciences Laboratory of Microelectronics Devices and Integrated technology Institute of MicroelectronicsChinese Academy of Sciences university of Chinese Academy of sciences School of Microelectronics Southern University of Science and Technology

Artificial intelligence(AI) has experienced substantial advancements recently, notably with the advent of large-scale language models(LLMs) employing mixture-of-experts(MoE) techniques, exhibiting human-like cognitive skills. As a promising hardware solution for edge MoE implementations, the computing-in-memory(CIM) architecture collocates memory and computing within a single device, significantly reducing the data movement and the associated energy consumption. However, due to diverse edge application scenarios and constraints, determining the optimal network structures for MoE, such as the expert's location,quantity, and dimension on CIM systems remains elusive. To this end, we introduce a software-hardware co-designed neural architecture search(NAS) framework, CIM-based MoE NAS(CMN), focusing on identifying a high-performing MoE structure under specific hardware constraints. The results of the NYUD-v2 dataset segmentation on the RRAM(SRAM) CIM system reveal that CMN can discover optimized MoE configurations under energy, latency, and performance constraints, achieving 29.67×(43.10×) energy savings,175.44×(109.89×) speedup, and 12.24× smaller model size compared to the baseline MoE-enabled Visual Transformer, respectively. This co-design opens up an avenue toward high-performance MoE deployments in edge CIM systems.

关键词： mixture-of-experts computing-in-memory neural architecture search resistive random-access memory static random-access memory