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AutoRhythmAI: A Hybrid Machine and Deep Learning Approach for Automated Diagnosis of Arrhythmias

Computers, Materials & Continua 2024年第2期78卷 2137-2158页

作者： S.Jayanthi S.Prasanna Devi Department of Computer science and Engineering SRM Institute of Science and Technology-Vadapalani CampusChennaiTamil NaduIndia

In healthcare,the persistent challenge of arrhythmias,a leading cause of global mortality,has sparked extensive research into the automation of detection using machine learning(ML)***,traditional ML and AutoML approaches have revealed their limitations,notably regarding feature generalization and automation *** glaring research gap has motivated the development of AutoRhythmAI,an innovative solution that integrates both machine and deep learning to revolutionize the diagnosis of *** approach encompasses two distinct pipelines tailored for binary-class and multi-class arrhythmia detection,effectively bridging the gap between data preprocessing and model *** validate our system,we have rigorously tested AutoRhythmAI using a multimodal dataset,surpassing the accuracy achieved using a single dataset and underscoring the robustness of our *** the first pipeline,we employ signal filtering and ML algorithms for preprocessing,followed by data balancing and split for *** second pipeline is dedicated to feature extraction and classification,utilizing deep learning ***,we introduce the‘RRI-convoluted trans-former model’as a novel addition for binary-class *** ensemble-based approach then amalgamates all models,considering their respective weights,resulting in an optimal model *** our study,the VGGRes Model achieved impressive results in multi-class arrhythmia detection,with an accuracy of 97.39%and firm performance in precision(82.13%),recall(31.91%),and F1-score(82.61%).In the binary-class task,the proposed model achieved an outstanding accuracy of 96.60%.These results highlight the effectiveness of our approach in improving arrhythmia detection,with notably high accuracy and well-balanced performance metrics.

关键词： Automated machine learning neural networks deep learning arrhythmias

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A universal additive concept yields record-high efficient organic solar cells

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science China Materials 2024年第5期67卷 1670-1671页

作者： Mariano Campoy Quiles Institute of Materials science of Barcelona ICMAB-CSICCampus UAB08193BellaterraSpain

Organic photovoltaics(OPVs)are an emerging light-to-electricity conversion technology that promises flexible,lightweight,semitransparent devices based on abundant and non-toxic organic *** power conversion efficiency under one sun has been increasing at an average pace of approximately 1%every year over the past 10 years,up to current values circa 20%.This has been possible through the continuous synthesis of improved semiconductors.

关键词： additive semiconductors approximate

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Quantum multicast based on joint remote state preparation

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Communications in Theoretical Physics 2024年第10期76卷 41-56页

作者： Zhihua Zhang Beining Shen Hanchen Zhang Zhipeng Qiu Interdisciplinary Center for Fundamental and Frontier sciences Nanjing University of Science and TechnologyJiangyin Campus School of Cyber science and Engineering Nanjing University of Science and TechnologyJiangyin Campus School of Mathematics and Statistics Nanjing University of Science and Technology

Effective propagation of information among multiple users is the purpose of realizing large-scale quantum communication networks. In this paper, multicast protocols for any single, two and three qubits with real amplitude and complex phase information are presented. They were realized using a composite of Greenberger–Horne–Zeilinger states as shared channels. Joint remote state preparation was the main method for completing quantum multicast. At the same time, quantum state tomography of the schemes was carried out on the IBM Quantum *** obtained states were compared with the target states by fidelity. The analysis of communication efficiency and noise effects shows that our protocol has advantages in the case of complex coefficients.

关键词： Greenberger-Horne-Zeilinger state joint remote state preparation quantum multicast quantum state tomography

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Wormhole solutions under the effect of dark matter in f(R,L_(m))gravity

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Communications in Theoretical Physics 2024年第5期76卷 102-113页

作者： Lakhan V Jaybhaye Moreshwar Tayde PK Sahoo Department of Mathematics Birla Institute of Technology and Science-PilaniHyderabad CampusHyderabad-500078India

In the background of f(R,L_(m))gravity,this work investigates three distinct dark matter halo profiles to test the possibility of generalised wormhole geometry within the galactic halo *** current study aims to accomplish these goals by examining various dark matter profiles including universal rotation curves(URC),Navarro-Frenk-White(NFW)model-Ⅰ,and NFW model-Ⅱinside two distinct f(R,L_(m))gravity *** to the f(R,L_(m))=R/2+L^(a)_(m)model,the dark matter(DM)halo density profiles produce suitable shape functions that meet all the necessary requirements for exhibiting the wormhole geometries with appropriate choice of free *** addition,to examine DM profiles under the f(R,L_(m))=R/2+(1+λR)L_(m) model,we consider a specific shape ***,we observed that the derived solution from both two models violates the null energy constraints,confirming that the DM supports wormholes to maintain in the galactic halo.

关键词： f(R L_(m))gravity wormhole dark matter(Some figures may appear in colour only in the online journal)

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Image classification of lotus in Nong Han Chaloem Phrakiat Lotus Park using convolutional neural networks

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Artificial Intelligence in Agriculture 2024年第1期11卷 23-33页

作者： Thanawat Phattaraworamet Sawinee Sangsuriyun Phoempol Kutchomsri Susama Chokphoemphun Department of Electrical and Computer Engineering Faculty of Science and EngineeringKasetsart University Chalermphrakiat Sakonnakhon Province Campus SakonnakhonThailand Department of Computer and Information science Faculty of Science and EngineeringKasetsart University Chalermphrakiat Sakonnakhon Province Campus SakonnakhonThailand

The Nong Han Chaloem Phrakiat Lotus Park is a tourist attraction and a source of learning regarding lotus ***,as a training area,it lacks appeal and learning motivation due to its conventional presentation of information regarding lotus *** current study introduced the concept of smart learning in this setting to increase interest and motivation for *** neural networks(CNNs)were used for the classification of lotus plant species,for use in the development of a mobile application to display details about each *** scope of the study was to classify 11 species of lotus plants using the proposed CNN model based on different techniques(augmentation,dropout,and L2)and hyper parameters(dropout and epoch number).The expected outcome was to obtain a high-performance CNN model with reduced total parameters compared to using three different pre-trained CNN models(Inception V3,VGG16,and VGG19)as *** performance of the model was presented in terms of accuracy,F1-score,precision,and recall *** results showed that the CNN model with the augmentation,dropout,and L2 techniques at a dropout value of 0.4 and an epoch number of 30 provided the highest testing accuracy of *** best proposed model was more accurate than the pre-trained CNN models,especially compared to Inception *** addition,the number of total parameters was reduced by approximately 1.80–2.19 *** findings demonstrated that the proposed model with a small number of total parameters had a satisfactory degree of classification accuracy.

关键词： Lotus Park Classification Smart learning park Convolutional neural network

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Deep Convolutional Neural Networks for Accurate Classification of Gastrointestinal Tract Syndromes

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Computers, Materials & Continua 2024年第1期78卷 1207-1225页

作者： Zahid Farooq Khan Muhammad Ramzan Mudassar Raza Muhammad Attique Khan Khalid Iqbal Taerang Kim Jae-Hyuk Cha Department of Computer science COMSATS University IslamabadWah CampusWah47040Pakistan Department of Computer science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon Department of Computer science HITEC UniversityTaxila47080Pakistan Department of Computer science COMSATS University IslamabadAttock CampusAttock43600Pakistan Department of Computer science Hanyang UniversitySeoul04763Korea

Accurate detection and classification of artifacts within the gastrointestinal(GI)tract frames remain a significant challenge in medical image *** science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous *** to this is the development of robust algorithms for image classification and detection,crucial in designing sophisticated systems for diagnosis and *** study makes a small contribution to endoscopic image *** proposed approach involves multiple operations,including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and ***,feature optimization utilizes the binary dragonfly algorithm(BDA),with the fusion of the obtained feature *** fused feature set is input into the ensemble subspace k nearest neighbors(ESKNN)*** Kvasir-V2 benchmark dataset,and the COMSATS University Islamabad(CUI)Wah private dataset,featuring three classes of endoscopic stomach images were *** assessments considered various feature selection techniques,including genetic algorithm(GA),particle swarm optimization(PSO),salp swarm algorithm(SSA),sine cosine algorithm(SCA),and grey wolf optimizer(GWO).The proposed model excels,achieving an overall classification accuracy of 98.25% on the Kvasir-V2 benchmark and 99.90% on the CUI Wah private *** approach holds promise for developing an automated computer-aided system for classifying GI tract syndromes through endoscopy images.

关键词： Feature fusion Darknet-53 Xception binary dragonfly algorithm ensemble

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Transcranial photobiomodulation for the brain: a wide range of clinical applications

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Neural Regeneration Research 2024年第3期19卷 483-484页

作者： Michael R.Hamblin Laser Research Centre Faculty of Health ScienceUniversity of Johannesburg-Doornfontein CampusDoornfonteinSouth Africa

Photobiomodulation therapy(PBMT)is a rapidly growing approach to the healing,stimulation,protection,and regeneration of many human organs and tissue *** started in the 1960s as low-level laser therapy for wound healing,but since then the introduction of light-emitting diodes(LEDs)has dramatically increased the number of applications and reports of positive *** generally uses red(620-700 nm)and/or near-infrared(780-1270 nm)wavelengths of light at an intensity that causes no tissue heating,and its activity is based on well-established biological and cellular mechanisms(de Freitas and Hamblin,2016).While laser therapists continue to use various types of laser in their office practice,LEDs are ideally suited for home use devices because they are completely safe and without any known significant adverse *** the various body parts on which PBMT has been shown to exert beneficial effects,the brain stands out as perhaps the most promising *** has been shown to reduce neuroinflammation,while increasing mitochondrial function,oxygen consumption,and blood flow within the brain(Hamblin,2016).Moreover,PBMT can stimulate the processes of synaptogenesis,neurogenesis,and neuroplasticity thus helping the brain to heal itself.

关键词： healing stimulation wound

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Dynamical system analysis of Dirac-Born-Infeld scalar field cosmology in coincident f(Q)gravity

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Chinese Physics C 2024年第9期48卷 199-209页

作者： Sayantan Ghosh Raja Solanki P.K.Sahoo Department of Mathematics Birla Institute of Technology and Science-PilaniHyderabad CampusHyderabad-500078India

In this article,we present a dynamical system analysis of a Dirac-Born-Infeld scalar field in a modified f(Q)gravity *** considered a polynomial form of modified gravity,used two different types of scalar potential,polynomial and exponential,and found a closed autonomous dynamical system of *** analyzed the fixed points of such a system and evaluated the conditions under which deceleration to late-time acceleration occurs in this *** note the similarity of the two models and show that our result is consistent with a previous study on Einstein s *** also investigated the phenomenological implications of our models by plotting EoS(ω),energy density(Ω),and deceleration parameter(q)*** e-fold time and comparing to the present *** conclude the paper by observing how the dynamical system analysis differs in the modified f(Q)gravity,and present the future scope of our research.

关键词： Dirac-Born-Infeld field f(Q)gravity dark energy dynamical system analysis

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Automatic area estimation of algal blooms in water bodies from UAV images using texture analysis

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Water science and Engineering 2024年第1期17卷 62-71页

作者： Ajmeria Rahul Gundu Lokesh Siddhartha Goswami R.N.Ponnalagu Radhika Sudha Department of Electrical and Electronics Engineering Birla Institute of Technology&SciencePilani Hyderabad CampusTelangana 500078India

Algal blooms,the spread of algae on the surface of water bodies,have adverse effects not only on aquatic ecosystems but also on human *** adverse effects of harmful algal blooms(HABs)necessitate a convenient solution for detection and *** aerial vehicles(UAVs)have recently emerged as a tool for algal bloom detection,efficiently providing on-demand images at high spatiotemporal *** study developed an image processing method for algal bloom area estimation from the aerial images(obtained from the internet)captured using *** a remote sensing method of HAB detection,analysis,and monitoring,a combination of histogram and texture analyses was used to efficiently estimate the area of *** features like entropy(using the Kullback-Leibler method)were emphasized with the aid of a gray-level co-occurrence *** results showed that the orthogonal images demonstrated fewer errors,and the morphological filter best detected algal blooms in real time,with a precision of 80%.This study provided efficient image processing approaches using on-board UAVs for HAB monitoring.

关键词： Algal bloom Image processing Texture analysis Histogram analysis Unmanned aerial vehicles

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Hemin blocks TIGIT/PVR interaction and induces ferroptosis to elicit synergistic effects of cancer immunotherapy

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science China(life sciences) 2024年第5期67卷 996-1009页

作者： Xiaowen Zhou Yang Li Xiangrui Zhang Beibei Li Shengzhe Jin Menghan Wu Xiuman Zhou Qingyu Dong Jiangfeng Du Wenjie Zhai Yahong Wu Lu Qiu Guodong Li Yuanming Qi Wenshan Zhao Yanfeng Gao School of life sciences Zhengzhou UniversityZhengzhou 450001China School of Pharmaceutical sciences(Shenzhen) Shenzhen Campus of Sun Yat-sen UniversityShenzhen 518107China

The immune checkpoint TIGIT/PVR blockade exhibits significant antitumor effects through activation of NK and CD8^(+)T cell-mediated *** checkpoint blockade(ICB)could induce tumor ferroptosis through IFN-γreleased by immune cells,indicating the synergetic effects of ICB with ferroptosis in inhibiting tumor ***,the development of TIGIT/PVR inhibitors with ferroptosis-inducing effects has not been explored *** this study,the small molecule Hemin that could bind withTIGIT to block TIGIT/PVR interaction was screened by virtual molecular docking and cell-based blocking *** could effectively restore the IL-2 secretion from Jurkat-hTIGIT *** reinvigorated the function of CD8^(+)T cells to secrete IFN-γand the elevated IFN-γcould synergize with Hemin to induce ferroptosis in tumor *** inhibited tumor growth by boosting CD8^(+)T cell immune response and inducing ferroptosis in CT26 tumor *** importantly,Hemin in combination with PD-1/PD-L1 blockade exhibited more effective antitumor efficacy in anti-PD-1 resistant B16 tumor *** summary,our finding indicated that Hemin blocked TIGIT/PVR interaction and induced tumor cell ferroptosis,which provided a new therapeutic strategy to combine immunotherapy and ferroptosis for cancer treatment.

关键词： cancer immunotherapy TIGIT/PVR small molecule Hemin ferroptosis

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