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arXiv 2020年

作者： Zhang, Ge Torquato, Salvatore Department of Physics and Astronomy University of Pennsylvania PhiladelphiaPA19104 United States Department of Chemistry Princeton University PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

The capacity to identify realizable many-body configurations associated with targeted functional forms for the pair correlation function g2(r) or its corresponding structure factor S(k) is of great fundamental and practical importance. While there are obvious necessary conditions that a prescribed structure factor at number density ρ must satisfy to be configurationally realizable, sufficient conditions are generally not known due to the infinite degeneracy of configurations with different higher-order correlation functions. A major aim of this paper is to expand our theoretical knowledge of the class of pair correlation functions or structure factors that are realizable by classical disordered ensembles of particle configurations, including exotic "hyperuniform" varieties. We first introduce a theoretical formalism that provides a means to draw classical particle configurations from canonical ensembles with certain pairwise-additive potentials that could correspond to targeted analytical functional forms for the structure factor. This formulation enables us to devise an improved algorithm to construct systematically canonical-ensemble particle configurations with such targeted pair statistics, whenever realizable. As a proof-of-concept, we test the algorithm by targeting several different structure factors across dimensions that are known to be realizable and one hyperuniform target that is known to be nontrivially unrealizable. Our algorithm succeeds for all realizable targets and appropriately fails for the unrealizable target, demonstrating the accuracy and power of the method to numerically investigate the realizability problem. Subsequently, we also target several families of structure-factor functions that meet the known necessary realizability conditions but were heretofore not known to be realizable by disordered hyperuniform point configurations, including d-dimensional Gaussian structure factors, d-dimensional generalizations of the 2D one-component plasm

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Investigating the Efficacy of Data Mining Techniques for Crowdsourced Biological Datasets

Investigating the Efficacy of Data Mining Techniques for Cro...

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2019 IEEE MIT Undergraduate Research Technology Conference, URTC 2019

作者： Regan, Ilona Alkurdi, Dany Paisarnsrisomsuk, Sarun Ruiz, Carolina Ryder, Elizabeth F. Gegear, Rob Bioinformatics and Computational Biology Program Worcester Polytechnic Institute WorcesterMA United States Princeton University Department of Near Eastern Studies PrincetonNJ United States Worcester Polytechnic Institute Department of Computer Science WorcesterMA United States Worcester Polytechnic Institute Department of Biology and Biotechnology WorcesterMA United States University of Massachusetts Dartmouth Department of Biology DartmouthMA United States

ISBN: (纸本)9781728158181

The rapid worldwide decline of wild pollinators over recent years poses a significant environmental threat due to the critical keystone role that pollinators play in terrestrial ecosystems. In order to gain insight into the major anthropogenic factors causing these declines, researchers have collected large amounts of ecological data. Yet, they often lack the computational tools needed to analyze the information contained in such datasets. We investigate various data analysis techniques for the Beecology Project, which is a citizen science based effort to rapidly collect data on foraging habits of bumblebee species native to Massachusetts. Different data mining approaches were explored, including association analysis, trend analysis, classification, regression, and clustering. It was found that different techniques were more suitable depending on the biological research question. Future work will focus on making tools utilizing these approaches available online through the Beecology website, where they can be used by the public to determine how best to protect our native pollinators and the diverse ecosystems they support. © 2019 IEEE.

关键词： Data mining

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Single-cell transcriptomic and chromatin dynamics of the human brain in PTSD

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Nature 2025年 1-11页

作者： Ahyeon Hwang Mario Skarica Siwei Xu Jensine Coudriet Che Yu Lee Lin Lin Rosemarie Terwilliger Alexa-Nicole Sliby Jiawei Wang Tuan Nguyen Hongyu Li Min Wu Yi Dai Ziheng Duan Shushrruth Sai Srinivasan Xiangyu Zhang Yingxin Lin Dianne Cruz P J Michael Deans Bertrand R Huber Daniel Levey Jill R Glausier David A Lewis Joel Gelernter Paul E Holtzheimer Matthew J Friedman Mark Gerstein Nenad Sestan Kristen J Brennand Ke Xu Hongyu Zhao John H Krystal Keith A Young Douglas E Williamson Alicia Che Jing Zhang Matthew J Girgenti Mathematical Computational and Systems Biology Program University of California Irvine Irvine CA USA. Department of Computer Science University of California Irvine Irvine CA USA. Department of Psychiatry Yale University School of Medicine New Haven CT USA. Department of Biostatistics Yale University School of Public Health New Haven CT USA. Department of Psychiatry and Behavioral Sciences Duke University Medical Center Durham NC USA. National Center for PTSD US Department of Veterans Affairs White River Junction VT USA. Department of Psychiatry University of Pittsburgh School of Medicine Pittsburgh PA USA. Department of Psychiatry Geisel School of Medicine at Dartmouth Lebanon NH USA. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT USA. Department of Computer Science Yale University New Haven CT USA. Department of Statistics and Data Science Yale University New Haven CT USA. Department of Neuroscience Yale School of Medicine New Haven CT USA. Department of Genetics Yale School of Medicine New Haven CT USA. Central Texas Veterans Health Care System Research Service Temple TX USA. Department of Psychiatry and Behavioral Sciences Texas A&M University College of Medicine Bryan TX USA. Mathematical Computational and Systems Biology Program University of California Irvine Irvine CA USA. zhang.jing@uci.edu. Department of Psychiatry Yale University School of Medicine New Haven CT USA. matthew.girgenti@yale.edu. National Center for PTSD US Department of Veterans Affairs White River Junction VT USA. matthew.girgenti@yale.edu. Department of Neuroscience Yale School of Medicine New Haven CT USA. matthew.girgenti@yale.edu.

Post-traumatic stress disorder (PTSD) is a polygenic disorder occurring after extreme trauma exposure. Recent studies have begun to detail the molecular biology of PTSD. However, given the array of PTSD-perturbed molecular pathways identified so far, it is implausible that a single cell type is responsible. Here we profile the molecular responses in over two million nuclei from the dorsolateral prefrontal cortex of 111 human brains, collected post-mortem from individuals with and without PTSD and major depressive disorder. We identify neuronal and non-neuronal cell-type clusters, gene expression changes and transcriptional regulators, and map the epigenomic regulome of PTSD in a cell-type-specific manner. Our analysis revealed PTSD-associated gene alterations in inhibitory neurons, endothelial cells and microglia and uncovered genes and pathways associated with glucocorticoid signalling, GABAergic transmission and neuroinflammation. We further validated these findings using cell-type-specific spatial transcriptomics, confirming disruption of key genes such as SST and FKBP5. By integrating genetic, transcriptomic and epigenetic data, we uncovered the regulatory mechanisms of credible variants that disrupt PTSD genes, including ELFN1, MAD1L1 and KCNIP4, in a cell-type-specific context. Together, these findings provide a comprehensive characterization of the cell-specific molecular regulatory mechanisms that underlie the persisting effects of traumatic stress response on the human prefrontal cortex.

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Cross-Species Functional Genomic Screens Identify Novel Therapeutic Targets in Malignant Peripheral Nerve Sheath Tumors

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The American journal of pathology 2025年

作者： Brittany Turner-Ivey Amanda M Prechtl Stephen T Guest Shannon W Doutt Jody F Longo Elizabeth Garrett-Mayer Steven L Carroll Departments of Pathology and Laboratory Medicine Medical University of South Carolina Charleston SC 29425-9080. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor Michigan 48409-2218. Departments of Pathology and Laboratory Medicine Medical University of South Carolina Charleston SC 29425-9080 Medical Scientist Training Program Medical University of South Carolina Charleston SC 29425-9080. Public Health Science Medical University of South Carolina Charleston SC 29425-9080. Departments of Pathology and Laboratory Medicine Medical University of South Carolina Charleston SC 29425-9080. Electronic address: carrolst@musc.edu.

As oncogenic pathways are highly conserved in vertebrates, genetically engineered mouse models can potentially be used to identify therapeutic targets relevant to rare human cancers such as malignant peripheral nerve sheath tumors (MPNSTs). To test this, genome-scale shRNA screens designed to identify genes driving proliferation and survival were performed in five MPNST cultures derived from P-GGFβ3 mice and three human MPNST cell lines. Several hundred gene hits mediating proliferation and survival were identified in human and mouse MPNST cells, many of which have been implicated in proliferation and survival in other cancers and/or mediate the pathogenesis of other cancer types. These hits and their associated signaling pathways extensively overlapped in human and mouse MPNST cells. A drug discovery pathway based on the Drug-Gene Interaction Database was developed to identify hits encoding druggable targets. Five druggable targets were selected for validation, with four of the five agents tested proving effective against human MPNST cells (the POLA1 inhibitor clofarabine, DNTT inhibitor cordycepin, BCL6 inhibitor 79-6 and LPAR1/3 inhibitor Ki16425). Clofarabine was especially effective, potently reducing cell numbers at low nanomolar concentrations and inducing a senescent phenotype, possibly via the p53/p21 pathway. These results demonstrate the utility of cross-species functional oncogenomics for the discovery of novel therapeutic targets relevant to human MPNSTs and suggest that clofarabine warrants further evaluation for its therapeutic potential.

关键词： POLA1 clofarabine malignant peripheral nerve sheath tumor proliferation shRNA screen small molecule inhibitor

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Inference of Antimicrobial Resistance (AMR) from a Whole Genome Database Outperforming AMR Gene Detection

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iscience 2025年

作者： Pornsawan Cholsaktrakool Kornthara Kawang Nicha Sangpiromapichai Pannaporn Thongsuk Songtham Anuntakarun Pattapon Kunadirek Natthaya Chuaypen Sumanee Nilgate Naris Kueakulpattana Ubolrat Rirerm Tanittha Chatsuwan Elita Jauneikaite Frances Davies Ploy N. Pratanwanich Sira Sriswasdi Voraphoj Nilaratanakul Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok Thailand Division of Infectious Diseases Department of Medicine Faculty of Medicine Chulalongkorn University and King Chulalongkorn Memorial Hospital Thai Red Cross Society Bangkok Thailand Excellence Center for Infectious Diseases King Chulalongkorn Memorial Hospital Thai Red Cross Society Bangkok Thailand Master of Science Program in Medical Sciences Faculty of Medicine Chulalongkorn University Bangkok Thailand Center of Excellence in Hepatitis and Liver Cancer Department of Biochemistry Faculty of Medicine Chulalongkorn University Bangkok Thailand Bumrungrad International Hospital Bangkok Thailand Metabolic Diseases in Gut and Urinary System Research Unit (MeDGURU) Department of Biochemistry Faculty of Medicine Chulalongkorn University Bangkok Thailand Department of Microbiology Faculty of Medicine Chulalongkorn University and King Chulalongkorn Memorial Hospital Thai Red Cross Society Bangkok Thailand Center of Excellence in Antimicrobial Resistance and Stewardship Faculty of Medicine Chulalongkorn University Bangkok Thailand NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance Department of Infectious Disease Imperial College London London United Kingdom Imperial College Healthcare NHS Trust London United Kingdom Department of Microbiology North West London Pathology London United Kingdom Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok Thailand Center of Excellence in Computational Molecular Biology Faculty of Medicine Chulalongkorn University Bangkok Thailand Center for Artificial Intelligence in Medicine Research Affairs Faculty of Medicine Chulalongkorn University Bangkok Thailand Healthcare-associated Infection Research Group STAR (Special Task Force for Activating Research) Chulalongkorn University Bangkok Thailand

This study focuses on the rapid detection of antimicrobial resistance (AMR) in Klebsiella pneumoniae . The "Align-Search-Infer" pipeline aligned query sequences from 24 urine samples against a curated genome database of 40 Klebsiella isolates, searched for the best matches, and inferred their antimicrobial susceptibility. Carbapenem resistance inference achieved 77.3% accuracy (95%CI: 59.8–94.8%) within 10 minutes using whole-genome matching, and 85.7% accuracy (95%CI: 70.7–100.0%) within 1 hour using plasmid matching—both surpassing the 54.2% accuracy (95%CI: 34.2–74.1%) of AMR gene detection at 6 hours. The proposed method requires less bacterial DNA and is suitable for low-load clinical samples. Our small local database performed comparably to large public databases. This study supports the integration of pathogen-specific genome databases into clinical workflows to enable rapid and accurate antimicrobial susceptibility prediction. Further research is needed to validate and refine the method using larger genomic-phenotypic datasets across diverse pathogens and sample types.

关键词： antimicrobial resistance Klebsiella pneumoniae nanopore sequencing de novo whole genome assembly database

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Harmonized-Multinational qEEG norms (HarMNqEEG)

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NEUROIMAGE 2022年 256卷 119190-119190页

作者： Li, Min Wang, Ying Lopez-Naranjo, Carlos Hu, Shiang Reyes, Ronaldo Cesar Garcia Paz-Linares, Deirel Areces-Gonzalez, Ariosky Hamid, Aini Ismafairus Abd Evans, Alan C. Savostyanov, Alexander N. Calzada-Reyes, Ana Villringer, Arno Tobon-Quintero, Carlos A. Garcia-Agustin, Daysi Yao, Dezhong Dong, Li Aubert-Vazquez, Eduardo Reza, Faruque Razzaq, Fuleah Abdul Omar, Hazim Abdullah, Jafri Malin Galler, Janina R. Ochoa-Gomez, John F. Prichep, Leslie S. Galan-Garcia, Lidice Morales-Chacon, Lilia Valdes-Sosa, Mitchell J. Trondle, Marius Zulkifly, Mohd Faizal Mohd Rahman, Muhammad Riddha Bin Abdul Milakhina, Natalya S. Langer, Nicolas Rudych, Pavel Koenig, Thomas Virues-Alba, Trinidad A. Lei, Xu Bringas-Vega, Maria L. Bosch-Bayard, Jorge F. Valdes-Sosa, Pedro Antonio [a]The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China [b]Cuban Center for Neurocience La Habana Cuba [c]McGill Centre for Integrative Neuroscience Ludmer Centre for Neuroinformatics and Mental Health Montreal Neurological Institute Canada [d]Department of Neurosciences School of Medical Sciences Universiti Sains Malaysia Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [e]Brain and Behaviour Cluster School of Medical Sciences Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [f]Hospital Universiti Sains Malaysia Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [g]Humanitarian Institute Novosibirsk State University Novosibirsk 630090 Russia [h]Laboratory of Psychophysiology of Individual Differences Federal State Budgetary Scientific Institution Scientific Research Institute of Neurosciences and Medicine Novosibirsk 630117 Russia [i]Laboratory of Psychological Genetics at the Institute of Cytology and Genetics Siberian Branch of the Russian Academy of Sciences Novosibirsk 630090 Russia [j]University of Pinar del Río “Hermanos Saiz Montes de Oca” Pinar del Río Cuba [k]Department of Neurology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany [l]Department of Cognitive Neurology University Hospital Leipzig Leipzig Germany [m]Center for Stroke Research Charité-Universitätsmedizin Berlin Berlin Germany [n]Grupo Neuropsicología y Conducta - GRUNECO Faculty of Medicine Universidad de Antioquia Colombia [o]Research Department Institución Prestadora de Servicios de Salud IPS Universitaria Colombia [p]The Cuban center aging longevity and health Havana Cuba [q]Research Unit of NeuroInformation Chinese Academy of Medical Sciences Chengdu 2019RU035 China [r]School of Electrical Engineering Zhengzhou University Zhengzhou 4500

This paper extends frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. (i) Create lifespan Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross spectral tensors were shared. After visual and automatic quality control, developmental equations for the mean and standard deviation of qEEG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qEEG "batch effects " and provide methods to calculate harmonized z-scores. (ii) We also show that harmonized Riemannian norms produce z-scores with increased diagnostic accuracy predicting brain dysfunction produced by malnutrition in the first year of life and detecting COVID induced brain dysfunction. (iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings.

关键词： Quantitative EEG EEG cross-spectrum Riemannian geometry Batch effects Z-score Harmonization Malnutrition Covid induced brain dysfunction Developmental Brain Chart

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Seebeck coefficient in a cuprate superconductor: Particle-hole asymmetry in the strange metal phase and Fermi surface transformation in the pseudogap phase

arXiv

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arXiv 2021年

作者： Gourgout, A. Grissonnanche, G. Laliberté, F. Ataei, A. Chen, L. Verret, S. Zhou, J.-S. Mravlje, J. Georges, A. Doiron-Leyraud, N. Taillefer, Louis Institut Quantique Département de physique and RQMP Université de Sherbrooke SherbrookeQC Canada Laboratory of Atomic and Solid State Physics Cornell University IthacaNY United States Kavli Institute at Cornell for Nanoscale Science IthacaNY United States Materials Science and Engineering Program/Mechanical Engineering University of Texas - Austin AustinTX United States Department of Theoretical Physics Institute Jožef Stefan Ljubljana Slovenia Collège de France 11 place Marcelin Berthelot Paris France Center for Computational Quantum Physics Flatiron Institute New YorkNY United States CPHT CNRS Ecole Polytechnique IP Paris Palaiseau France DQMP Université de Genève Geneva Switzerland Canadian Institute for Advanced Research TorontoON Canada

We report measurements of the Seebeck effect in both the ab plane (Sa) and along the c axis (Sc) of the cuprate superconductor La1:6-xNd0:4SrxCuO4(Nd-LSCO), performed in magnetic fields large enough to suppress superconductivity down to low temperature. We use the Seebeck coefficient as a probe of the particle-hole asymmetry of the electronic structure across the pseudogap critical doping p∗ = 0:23. Outside the pseudogap phase, at p = 0:24 > p∗, we observe a positive and essentially isotropic Seebeck coefficient as T → 0. That S > 0 at p = 0:24 is at odds with expectations given the electronic band structure of Nd-LSCO above p∗ and its known electron-like Fermi surface. We can reconcile this observation by invoking an energy-dependent scattering rate with a particle-hole asymmetry, possibly rooted in the non-Fermi liquid nature of cuprates just above p∗. Inside the pseudogap phase, for p Copyright © 2021, The Authors. All rights reserved.

关键词： Electronic structure

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Detecting anomalous citation groups in journal networks

arXiv

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arXiv 2020年

作者： Kojaku, Sadamori Livan, Giacomo Masuda, Naoki Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Computer Science University College London LondonWC1E 6EA United Kingdom Systemic Risk Centre London School of Economics and Political Science LondonWC2A 2AE United Kingdom Department of Mathematics University at Buffalo State University of New York BuffaloNY United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-2900 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

The ever-increasing competitiveness in the academic publishing market incentivizes journal editors to pursue higher impact factors. This translates into journals becoming more selective, and, ultimately, into higher publication standards. However, the fixation on higher impact factors leads some journals to artificially boost impact factors through the coordinated effort of a "citation cartel" of journals. "Citation cartel" behavior has become increasingly common in recent years, with several instances being reported. Here, we propose an algorithm—-named CIDRE—to detect anomalous groups of journals that exchange citations at excessively high rates when compared against a null model that accounts for scientific communities and journal size. CIDRE detects more than half of the journals suspended from Journal Citation Reports due to anomalous citation behavior in the year of suspension or in advance. Furthermore, CIDRE detects many new anomalous groups, where the impact factors of the member journals are lifted substantially higher by the citations from other member journals. We describe a number of such examples in detail and discuss the implications of our findings with regard to the current academic climate. Copyright © 2020, The Authors. All rights reserved.

关键词： Publishing

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Cross-platform transcriptomic profiling of the response to recombinant human erythropoietin

Research Square

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Research Square 2021年

作者： Wang, Guan Kitaoka, Traci Crawford, Ali Mao, Qian Hesketh, Andrew Guppy, Fergus M. Ash, Garrett I. Liu, Jason Gerstein, Mark B. Pitsiladis, Yannis P. Sport and Exercise Science and Sports Medicine Research and Enterprise Group University of Brighton Brighton United Kingdom Centre for Regenerative Medicine and Devices University of Brighton Brighton United Kingdom Illumina San DiegoCA United States BGI Shenzhen China School of Pharmacy and Biomolecular Sciences University of Brighton Brighton United Kingdom Centre for Stress and Age-related Disease University of Brighton Brighton United Kingdom Veterans Affairs Connecticut Healthcare System West HavenCT United States Center for Medical Informatics Yale University New HavenCT United States Program in Computational Biology & Bioinformatics Yale University New HavenCT United States Department of Molecular Biophysics & Biochemistry Yale University New HavenCT United States Department of Computer Science Yale University New HavenCT United States Department of Statistics and Data Science Yale University New HavenCT United States

RNA-seq has matured and become an important tool for studying RNA biology. Here we compared two RNA-seq (Illumina sequencing by synthesis and MGI DNBSEQTM) and two microarray platforms (Illumina Expression BeadChip and GeneChipTM Human Transcriptome Array 2.0) in healthy individuals administered recombinant human erythropoietin for transcriptome-wide quantification of differential gene expression. The results show that total RNA sequencing combined with DNB-seq produced a multitude of genes of biological relevance and significance in response to recombinant human erythropoietin, in contrast to other platforms. Through data triangulation linking genes to functions, genes representing the processes of erythropoiesis as well as non-erythropoietic functions of erythropoietin were unveiled. This study provides a knowledge base of genes characterising the responses to recombinant human erythropoietin through cross-platform comparison and validation. © 2021, CC BY.

关键词： RNA

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Magnetized and quadratic convection based thermal transport in ternary radiative bio-nanofluid via intelligent neural networks: Two hidden layers mechanism

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Results in Physics 2024年 65卷

作者： Ayub, Assad Darvesh, Adil Shah, Syed Zahir Hussain Junjua, Moin-ud-Din Santos, Elizaldo Domingues dos Ahmad, Shabbir Hendy, Ahmed S. Ragab, Adham E. Department of Mathematics & Statistics Hazara University Manshera Pakistan School of Mathematical Sciences Zhejiang Normal University Zhejiang Jinhua 321004 China Programa de Pós-Graduação em Modelagem Computacional/LMCE Escola de Engenharia Universidade Federal do Rio Grande – FURG RS Rio Grande 96203900 Brazil FURG Escola de Engenharia RS Rio Grande Brazil Department of Basic Sciences and Humanities Muhammad Nawaz Sharif University of Engineering and Technology Multan 60000 Pakistan Department of Computational Mathematics and Computer Science Institute of Natural Sciences and Mathematics Ural Federal University 19 Mira St. Yekaterinburg 620002 Russian Federation Department of Industrial Engineering College of Engineering King Saud University P.O. Box 800 Riyadh 11421 Saudi Arabia Department of Mathematics Ghazi University Dera Ghazi Khan 32200 Pakistan Graduate Program of Ocean Engineering School of Engineering Universidade Federal do Rio Grande Italia Avenue km 8 96201-900 Rio Grande Brazil Department of Mechanics and Mathematics Western Caspian University Baku 1001 Azerbaijan

Significance: The thermal analysis of nanofluid in a vertical cylinder (artery) in a magnetized environment holds significant implications in physiological and thermal regulation networks. This research is significant in biomedical engineering with applications like medical diagnostics and treatment strategies. Motive: This study investigates the thermal behavior of a magnetized blood-based ternary Carreau nanofluid flowing through a vertically bounded artery with quadratic convection. Velocity and heat transfer analysis is conducted within the artery, utilizing thermal radiation and quadratic convection in a magnetized setting. The base fluid consists of blood, augmented with three nanoparticles: CuO, Al₂O₃, and TiO₂. The investigation centers on examining the properties of blood nanofluid, arterial geometry, and thermal dynamics. Methodology: The physical model generates a set of partial differential equations (PDEs) and similarities mechanism is utilized to fetch its non dimensional form in terms of ordinary differential equations (ODEs). Furthermore, numerical outcomes are obtained with Matlab function bvp4c and obtained data set is trained through robust scheme Levenberg-Marquardt neural network (LMNN) procedure to predict the solution. Findings: Velocity of blood is reduced with increased values of wiessenberg number, magnetic parameter and mixed convection parameter and velocity increases for Second-order convection parameter. Temperature profile decreases with curvature parameter, mixed convection parameter and permeability parameter. © 2024

关键词： Blood fluid Intelligent neural network Magnetized environment Ternary nanoparticles Thermal scrutiny

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