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Ensemble Approach Combining Deep Residual Networks and BiGRU with Attention Mechanism for Classification of Heart Arrhythmias

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Computers, Materials & Continua 2024年第7期80卷 341-359页

作者： Batyrkhan Omarov Meirzhan Baikuvekov Daniyar Sultan Nurzhan Mukazhanov Madina Suleimenova Maigul Zhekambayeva Department of Information Systems Al-Farabi Kazakh National UniversityAlmaty050040Kazakhstan Department of Mathematical and Computer Modeling International Information Technology UniversityAlmaty050040Kazakhstan Department of Software Engineering Satbayev UniversityAlmaty050013Kazakhstan

This research introduces an innovative ensemble approach,combining Deep Residual Networks(ResNets)and Bidirectional Gated Recurrent Units(BiGRU),augmented with an Attention Mechanism,for the classification of heart *** escalating prevalence of cardiovascular diseases necessitates advanced diagnostic tools to enhance accuracy and *** model leverages the deep hierarchical feature extraction capabilities of ResNets,which are adept at identifying intricate patterns within electrocardiogram(ECG)data,while BiGRU layers capture the temporal dynamics essential for understanding the sequential nature of ECG *** integration of an Attention Mechanism refines the model’s focus on critical segments of ECG data,ensuring a nuanced analysis that highlights the most informative features for arrhythmia *** on a comprehensive dataset of 12-lead ECG recordings,our ensemble model demonstrates superior performance in distinguishing between various types of arrhythmias,with an accuracy of 98.4%,a precision of 98.1%,a recall of 98%,and an F-score of 98%.This novel combination of convolutional and recurrent neural networks,supplemented by attention-driven mechanisms,advances automated ECG analysis,contributing significantly to healthcare’s machine learning applications and presenting a step forward in developing non-invasive,efficient,and reliable tools for early diagnosis and management of heart diseases.

关键词： CNN BiGRU ensemble deep learning ECG arrhythmia heart disease

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IndRT-GCNets: Knowledge Reasoning with Independent Recurrent Temporal Graph Convolutional Representations

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Computers, Materials & Continua 2024年第1期78卷 695-712页

作者： Yajing Ma Gulila Altenbek Yingxia Yu College of Information Science and Engineering Xinjiang UniversityUrumqi830017China Xinjiang Laboratory of Multilanguage Information Technology Xinjiang UniversityUrumqi830017China The Base of kazakh and Kirghiz Language of national Language Resource Monitoring and Research Center on Minority Languages Xinjiang UniversityUrumqi830017China

Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute *** framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each ***,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each ***,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive ***,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity ***,the evolution of entity and relation representations is utilized to predict events in the next subsequent *** multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.

关键词： Knowledge reasoning entity and relation representation structural dependency relationship evolutionary representation temporal graph convolution

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Astrophysical S-factor and reaction rate for 15N(p,γ)16O within the modified potential cluster model

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Chinese Physics C 2024年第4期48卷 130-145页

作者： S.B.Dubovichenko A.S.Tkachenko R.Ya.Kezerashvili N.A.Burkova B.M.Yeleusheva Fesenkov Astrophysical Institute 050020 AlmatyKazakhstan New York City College of Technology City University of New YorkBrooklyn11201 New YorkUSA Graduate School and university Center City University of New York10016 New YorkUSA al-Farabi kazakh national university 050040 AlmatyKazakhstan

We study radiative p^(15)N capture on the ground state of ^(16)O at stellar energies within the framework of a modified potential cluster model(MPCM)with forbidden states,including low-lying *** investigation of the ^(15)N(p,γ0)^(16)O reaction includes the consideration of ^(3)S_(1) resonances due to E1 transitions and the contribution of the ^(3)P_(1) scattering wave in the p+^(15)N channel due to the ^(3)P_(1)→^(3)P_(0)M1 *** calculated the astrophysical low-energy S-factor,and the extrapolated S(0)turned out to be within 34.7−40.4 keV·*** important role of the asymptotic constant(AC)for the ^(15)N(p,γ0)16O process with interfering ^(3)S_(1)(312)and ^(3)S_(1)(962)resonances is elucidated.A comparison of our calculation for the S-factor with existing experimental and theoretical data is addressed,and a reasonable agreement is *** reaction rate is calculated and compared with the existing *** has negligible dependence on the variation of AC but shows a strong impact of the interference of ^(3)S_(1)(312)and ^(3)S_(1)(962)resonances in reference to the CNO Gamow windows,especially at low *** estimate the contribution of cascade transitions to the reaction rate based on the exclusive experimental data from ***.C.85,065810(2012).The reaction rate enhancement due to the cascade transitions is observed from T_(9)>0.3 and reaches the maximum factor~1.3 at T_(9)=*** present the Gamow energy window and a comparison of rates for radiative proton capture reactions ^(12)N(p,γ)^(13)O,^(13)N(p,γ)^(14)O,^(14)N(p,γ)^(15)O,and ^(15)N(p,γ)^(16)O obtained in the framework of the MPCM and provide the temperature windows,prevalence,and significance of each process.

关键词： low and astrophysical energies p^(15)N system thermonuclear reaction rate potential cluster model CNO-cycle

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Assessment of molecular markers and marker-assisted selection for drought tolerance in barley(Hordeum vulgare L.)

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Journal of Integrative Agriculture 2024年第1期23卷 20-38页

作者： Akmaral Baidyussen Gulmira Khassanova Maral Utebayev Satyvaldy Jatayev Rystay Kushanova Sholpan Khalbayeva Aigul Amangeldiyeva Raushan Yerzhebayeva KulpashBulatova Carly Schramm Peter Anderson Colin L.D.Jenkins Kathleen LSoole Yuri Shavrukov Faculty of Agronomy S.Seifullin Kazakh AgroTechnical Research UniversityAstana 010000Kazakhstan A.I.Barayev Research and Production Centre of Grain Farming Shortandy 021601Kazakhstan kazakh Research Institute of Agriculture and Plant Growing AlmalybakAlmaty District 040909Kazakhstan College of Science and Engineering Biological SciencesFlinders UniversityAdelaideSA 5042Australia

This review updates the present status of the field of molecular markers and marker-assisted selection(MAS),using the example of drought tolerance in *** accuracy of selected quantitative trait loci(QTLs),candidate genes and suggested markers was assessed in the barley genome *** common strategies are described for molecular marker development,candidate gene identification and verification,and their possible applications in MAS to improve the grain yield and yield components in barley under drought *** strategies are based on the following five principles:(1)Molecular markers are designated as genomic‘tags’,and their‘prediction’is strongly dependent on their distance from a candidate gene on genetic or physical maps;(2)plants react differently under favourable and stressful conditions or depending on their stage of development;(3)each candidate gene must be verified by confirming its expression in the relevant conditions,e.g.,drought;(4)the molecular marker identified must be validated for MAS for tolerance to drought stress and improved grain yield;and(5)the small number of molecular markers realized for MAS in breeding,from among the many studies targeting candidate genes,can be explained by the complex nature of drought stress,and multiple stress-responsive genes in each barley genotype that are expressed differentially depending on many other factors.

关键词： barley candidate genes drought tolerance gene verification via expression grain yield marker-assisted selection(MAS) molecular markers quantitative trait loci(QTLs) strategy for MAS

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Performance and enhanced oil recovery efficiency of an acid-resistant polymer microspheres of anti-CO2 channeling in low-permeability reservoirs

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Petroleum Science 2024年第4期21卷 2420-2432页

作者： Hai-Zhuang Jiang Hong-Bin Yang Ruo-Sheng Pan Zhen-Yu Ren Wan-Li Kang Jun-Yi Zhang Shi-Long Pan Bauyrzhan Sarsenbekuly State Key Laboratory of Deep Oil and Gas China University of Petroleum (East China) School of Petroleum Engineering China University of Petroleum (East China) Oil and Gas Engineering Research Institute School of Energy and Petroleum Industry Kazakh-British Technical University

CO2flooding is a vital development method for enhanced oil recovery in low-permeability reservoirs,However,micro-fractures are developed in low-permeability reservoirs,which are essential oil flow channels but can also cause severe CO2gas channeling ***,anti-gas channeling is a necessary measure to improve the effect of *** kind of anti-gas channeling refers to the plugging of fractures in the deep formation to prevent CO2gas channeling,which is different from the wellbore *** microspheres have the characteristics of controllable deep plugging,which can achieve the profile control of low-permeability fractured *** acidic environments with supercritical CO2,traditional polymer microspheres have poor expandability and plugging *** on previous work,a systematic evaluation of the expansion performance,dispersion rheological properties,stability,deep migration,anti-CO2channeling and enhanced oil recovery ability of a novel acid-resistant polymer microsphere（DCNPM-A） was carried out under CQ oilifield conditions（salinity of85,000 mg/L,80℃,pH=3）.The results show that the DCNPM-A microsphere had a better expansion performance than the traditional microsphere,with a swelling rate of *** microsphere dispersion with a concentration of 0.1%-0.5% had the advantages of low viscosity,high dispersion and good injectability in the low permeability fractured *** the acidic environment of supercritical CO2,DCNPM-A microspheres showed excellent stability and could maintain strength for over 60 d with less *** core experiments,DCNPM-A microspheres exhibited delayed swelling characteristics and could effectively plug deep *** a plugging rate of 95%,the subsequent enhanced oil recovery of CO2flooding could reach 21.03%.The experimental results can provide a theoretical basis for anti-CO2channeling and enhanced oil recovery in low-permeability fractured reservoirs.

关键词： Low-permeability reservoir Anti-CO 2 channeling Polymer microsphere Acid resistance

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Machine Learning-Assisted Fabrication of PCBM-Perovskite Solar Cells with Nanopatterned TiO2 Layer

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Energy & Environmental Materials 2024年第4期7卷 223-230页

作者： Siti Norhasanah Sanimu Hwa-Young Yang Jeevan Kandel Ye-Chong Moon Gangasagar Sharma Gaudel Seung-Ju Yu Yong Ju Kim Sejung Kim Bong-Hyun Jun Won-Yeop Rho Graduate School of Integrated Energy-AI Jeonbuk National University School of Energy and Chemical Engineering Ulsan National Institute of Science and Technology (UNIST) Department of Herbal Medicine Resources College of Environmental and Bioresource Sciences Jeonbuk National University School of Chemical Engineering Jeonbuk National University Department of Bioscience and Biotechnology Konkuk University School of International Engineering and Science Jeonbuk National University

To unlock the full potential of PSCs,machine learning （ML） was implemented in this research to predict the optimal combination of mesoporous-titanium dioxide （mp-TiO2） and weight percentage （wt%） of phenyl-C61-butyric acid methyl ester （PCBM）,along with the current density(Jsc),open-circuit voltage (Voc),fill factor （ff）,and energy conversion efficiency （ECE）.

关键词： machine learning nanopatterning PCBM perovskite solar cells prediction

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Synergistic anionic/zwitterionic mixed surfactant system with high emulsification efficiency for enhanced oil recovery in low permeability reservoirs

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Petroleum Science 2024年第2期21卷 936-950页

作者： Hai-Rong Wu Rong Tan Shi-Ping Hong Qiong Zhou Bang-Yu Liu Jia-Wei Chang Tian-Fang Luan Ning Kang Ji-Rui Hou national Key Laboratory of Petroleum Resources and Engineering China University of Petroleum-BeijingBeijing102249China Unconventional Petroleum Research Institute China University of Petroleum-BeijingBeijing102249China Gas Production Plant 5 of PetroChina Changqing Oilfield Company PetroChinaXi'an710000ShaanxiChina College of Petroleum Engineering China University of Petroleum-BeijingBeijing102249China College of Science China University of Petroleum-BeijingBeijing102249China kazakh-British Technical university Almaty050000Kazakhstan

Emulsification is one of the important mechanisms of surfactant flooding. To improve oil recovery for low permeability reservoirs, a highly efficient emulsification oil flooding system consisting of anionic surfactant sodium alkyl glucosyl hydroxypropyl sulfonate(APGSHS) and zwitterionic surfactant octadecyl betaine(BS-18) is proposed. The performance of APGSHS/BS-18 mixed surfactant system was evaluated in terms of interfacial tension, emulsification capability, emulsion size and distribution, wettability alteration, temperature-resistance and salt-resistance. The emulsification speed was used to evaluate the emulsification ability of surfactant systems, and the results show that mixed surfactant systems can completely emulsify the crude oil into emulsions droplets even under low energy conditions. Meanwhile,the system exhibits good temperature and salt resistance. Finally, the best oil recovery of 25.45% is achieved for low permeability core by the mixed surfactant system with a total concentration of 0.3 wt%while the molar ratio of APGSHS:BS-18 is 4:6. The current study indicates that the anionic/zwitterionic mixed surfactant system can improve the oil flooding efficiency and is potential candidate for application in low permeability reservoirs.

关键词： Anionic/zwitterionic mixed surfactant system Emulsification Synergistic effect Low permeability reservoir Enhanced oil recovery

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Symmetry quantification and segmentation in STEM imaging through Zernike moments

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Chinese Physics B 2024年第8期33卷 39-48页

作者： Jiadong Dan Cheng Zhang 赵晓续 N.Duane Loh Department of Biological Sciences National University of SingaporeSingapore Center for Bioimaging Sciences(CBIS) National University of SingaporeSingapore Department of Physics National University of SingaporeSingapore School of Materials Science and Engineering Peking UniversityBeijing 100871China

We present a method using Zernike moments for quantifying rotational and reflectional symmetries in scanning transmission electron microscopy(STEM)images,aimed at improving structural analysis of materials at the atomic *** technique is effective against common imaging noises and is potentially suited for low-dose imaging and identifying quantum *** showcase its utility in the unsupervised segmentation of polytypes in a twisted bilayer TaS_(2),enabling accurate differentiation of structural phases and monitoring transitions caused by electron beam *** approach enhances the analysis of structural variations in crystalline materials,marking a notable advancement in the characterization of structures in materials science.

关键词： scanning transmission electron microscopy(STEM) symmetry segmentation

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Sparse Reconstructive Evidential Clustering for Multi-View Data

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 459-473页

作者： Chaoyu Gong Yang You School of Computing National University of SingaporeSingapore

Although many multi-view clustering(MVC) algorithms with acceptable performances have been presented, to the best of our knowledge, nearly all of them need to be fed with the correct number of clusters. In addition, these existing algorithms create only the hard and fuzzy partitions for multi-view objects,which are often located in highly-overlapping areas of multi-view feature space. The adoption of hard and fuzzy partition ignores the ambiguity and uncertainty in the assignment of objects, likely leading to performance degradation. To address these issues, we propose a novel sparse reconstructive multi-view evidential clustering algorithm(SRMVEC). Based on a sparse reconstructive procedure, SRMVEC learns a shared affinity matrix across views, and maps multi-view objects to a 2-dimensional humanreadable chart by calculating 2 newly defined mathematical metrics for each object. From this chart, users can detect the number of clusters and select several objects existing in the dataset as cluster centers. Then, SRMVEC derives a credal partition under the framework of evidence theory, improving the fault tolerance of clustering. Ablation studies show the benefits of adopting the sparse reconstructive procedure and evidence theory. Besides,SRMVEC delivers effectiveness on benchmark datasets by outperforming some state-of-the-art methods.

关键词： Evidence theory multi-view clustering(MVC) optimization sparse reconstruction

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Span-based joint entity and relation extraction augmented with sequence tagging mechanism

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Science China(Information Sciences) 2024年第5期67卷 84-98页

作者： Bin JI Shasha LI Hao XU Jie YU Jun MA Huijun LIU Jing YANG College of Computer National University of Defense Technology

Span-based joint extraction simultaneously conducts named entity recognition(NER) and relation extraction(RE) in a text span form. However, since previous span-based models rely on span-level classifications, they cannot benefit from token-level label information, which has been proven advantageous for the task. In this paper, we propose a sequence tagging augmented span-based network(STSN), a spanbased joint model that can make use of token-level label information. In STSN, we construct a core neural architecture by deep stacking multiple attention layers, each of which consists of three basic attention *** the one hand, the core architecture enables our model to learn token-level label information via the sequence tagging mechanism and then uses the information in the span-based joint extraction; on the other hand, it establishes a bi-directional information interaction between NER and RE. Experimental results on three benchmark datasets show that STSN consistently outperforms the strongest baselines in terms of F1,creating new state-of-the-art results.

关键词： joint extraction named entity recognition relation extraction span sequence tagging mechanism

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