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Relative magnetic field and slipping effect on Casson dusty fluid of two phase fluctuating flow over inclined parallel plate

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South African Journal of Chemical Engineering 2023年 44卷 135-146页

作者： khan, Dolat Kumam, Poom Kumam, Wiyada Suttiarporn, Panawan Rehman, Ali Fixed Point Research Laboratory Fixed Point Theory and Applications Research Group Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Applied Mathematics for Science and Engineering Research Unit (AMSERU) Program in Applied Statistics Department of Mathematics and Computer Science Faculty of Science and Technology Rajamangala University of Technology Thanyaburi (RMUTT) Pathum Thani 12110 Thailand Faculty of Science Energy and Environment King Mongkut's University of Technology North Bangkok Rayong Campus Rayong 21120 Thailand Special Interest Group for Modelling and Data Analytics Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus 21030 Malaysia

Due to its significant applications in magnetic devices for cell separation, magnetic drugs for cancer tumor treatment, blood flow adjustment during surgery, magnetic endoscopy, and fluid pumping in industrial and engineering processes, magnetohydrodynamics (MHD) has a wide range of applications. Therefore, the aim of this study to investigate the Relative Magnetic Field and slipping effect on Casson dusty fluid of two-phase fluctuating flow over inclined parallel plate. More exactly, the relative magnetic phenomena are fixed relatively to the plate (MFFRP) or fixed relatively to the fluid (MFFRF). The mathematical modeling was established as the set of partial differential equations for dusty Casson fluid. Buckingham's pi theorem is used to find out the dimensionless variables, to make our system dimensionless. The solution in perturb form is to find out by incorporating Poincare–Lighthill perturbation technique (PLPT). To know in-depth different parameters the graphical results for both velocities are plotted with the help of software Mathcad- 15. It is clearly detected that the relative magnetic field performs a vital part in the fluid as well as particle motion. Moreover, the relative magnetic field play a vital role in the decreasing of skin friction of both plates. © 2023

关键词： Brinkman fluid Dust particles Fluctuating vertical plate Inclined relative magnetic field PLPT

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Assessing Rice Phenological Features with Hyperspectral Imaging Insights from Earth Surface Mineral Dust Source Investigation (EMIT)

Assessing Rice Phenological Features with Hyperspectral Imag...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Shahryar Fazli Wenzhao Li Surendra Maharjan Hesham El Askary Computational and Data Sciences Graduate Program Schmid College of Science and Technology Chapman University Orange CA USA Earth Systems Science and Data Solutions Lab Chapman University Orange CA USA Department of Environmental Sciences Faculty of Science Alexandria University Alexandria Egypt

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

In California's Central Valley, water management and crop health, particularly in rice cultivation, are critical. This paper details the application of Earth surface Mineral dust source InvesTigation (EMIT) hyperspectral imaging, specifically employing Spectral Correlation Mapper (SCM) and Spectral Information Divergence (SID), for precise phenological analysis. By aligning EMIT data with Hyperion satellite references, we address spectral and geographical discrepancies. Our methodology includes seasonal sampling of spectral curves to capture the phenological stages of rice. Results show a strong correlation (R 2 = 0.86) between August EMIT and Reference dataset, emphasizing EMIT's utility in enhancing agricultural practices and water efficiency in the region, and highlighting the importance of understanding rice phenology for sustainable farming.

关键词： Earth Correlation Satellites Accuracy Uncertainty Phenology Minerals

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New insight into pyrrolic-N site effect towards the first NIR window absorption of pyrrolic-N-rich carbon dots

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Nano Research 2023年第4期16卷 6001-6009页

作者： Fitri Aulia Permatasari Reza Umami Citra Deliana Dewi Sundari Tirta Rona Mayangsari Atthar Luqman Ivansyah Fahdzi Muttaqien Takashi Ogi Ferry Iskandar Department of Physics Faculty Mathematics and Natural SciencesInstitut Teknologi BandungJalan Ganesha 10BandungWest Java 40132Indonesia Collaboration Research Center for Advanced Energy Materials National Research and Innovation Agency-Institut Teknologi BandungJalan Ganesha 10BandungWest Java 40132Indonesia Department of Chemistry Faculty of Mathematics and Natural SciencesInstitut Teknologi BandungJl.Ganesha 10BandungWest Java 40132Indonesia Department of Chemistry Education UIN Sunan Gunung Djati BandungJl.CimincrangBandungWest Java 40292Indonesia Department of Chemistry Universitas PertaminaJakarta 12220Indonesia Master Program in Computational Science Faculty of Mathematics and Natural SciencesInstitut Teknologi BandungJl.Ganesha 10BandungWest Java 40132Indonesia Instrumentation and Computational Physics Research Group Faculty of Mathematics and Natural SciencesInstitut Teknologi BandungJl.Ganesha 10Bandung 40132Indonesia Research Center for Nanoscience and Nanotechnology Institut Teknologi BandungJalan Ganesha 10BandungWest Java 40132Indonesia Chemical Engineering Program Department of Advanced Science and EngineeringGraduate School of Advanced Science and EngineeringHiroshima UniversityHigashi-Hiroshima 739-8527Japan

Controlled C-N configurations,i.e.,pyrrolic-N,pyridinic-N,and graphitic-N,are promising strategies to tailor the carbon dots’(CDs)optical properties into the first near infrared(NIR)window(650-900 nm),a responsive range for biomedical ***,a deep understanding of the role of the C-N configuration in the CDs’properties is still challenging and thoughtprovoking owing to their complex ***,an underlying pyrrolic-N concentration and position effect on the pyrrolic-N-rich CDs’absorption was comprehensively elucidated based on the integrated experimental and computational *** assynthesized pyrrolic-N-rich CDs exhibit a first NIR window absorption centered at 650 nm with high photothermal ***-N concentrations from 1.4%to 11.3%and positions(edge and mid-site)were systematically investigated.A mid-site pyrrolic-N was subsequently generated after the pyrrolic-N concentration more than 10%.Edge-site pyrrolic-N induces a frontier orbital hybridization,reducing bandgap energy,while mid-site pyrrolic-N plays a critical role in inducing a first NIR window absorption owing to their high charge ***,pyrrolic-N-rich CDs inherit a bowl-like topological feature,elevating the CDs’layer thickness as much as 0.71 *** study shed light on the design and optimization of pyrrolic-N on CDs for the first NIR window responsive materials in any biomedical application.

关键词： absorption carbon dots charge transfer first near infrared(NIR)window frontier orbital hybridization mid-site pyrrolic-N

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Deciphering Water Quality and Algal Dynamics in Clear Lake Through Hyperspectral Analysis Using Emit Data

Deciphering Water Quality and Algal Dynamics in Clear Lake T...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Wenzhao Li Shahryar Fazli Surendra Maharjan Hesham El-Askary Earth Systems Science and Data Solutions Lab Schmid College of Science and Technology Chapman University Orange CA USA Computational and Data Sciences Graduate Program Schmid College of Science and Technology Chapman University Orange CA USA Department of Environmental Sciences Faculty of Science Alexandria University Alexandria Egypt

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

This study evaluates the potential application of hyperspectral Earth Surface Mineral Dust Source Investigation (EMIT) remote sensing for monitoring harmful algal blooms (HABs) and water quality in Clear Lake, California. The research focuses on correlating the chlorophyll-a (Chl-a) concentrations with EMIT spectral signatures, using waterbody-wide statistical analysis of Chl-a and EMIT data sampling at various lake locations. Results demonstrate distinct spectral signatures associated with varying Chl-a levels, highlighting the potential of hyperspectral imaging in differentiating algae levels and assessing water quality variables. It also indicates the EMIT’s utility in filling data gaps and offering high-resolution monitoring. This study underscores the need for further research in hyperspectral imaging for aquatic ecosystems, especially under challenging atmospheric conditions, enhancing our understanding of water quality dynamics.

关键词： Satellites Statistical analysis Algae Water quality Lakes Filling Minerals

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Bayesian Spectral Graph Denoising with Smoothness Prior

Bayesian Spectral Graph Denoising with Smoothness Prior

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Annual Conference on Information sciences and Systems (CISS)

作者： Sam Leone Xingzhi Sun Michael Perlmutter Smita Krishnaswamy Program for Applied Mathematics Yale University Department of Computer Science Yale University Department of Mathematics Boise State University Department of Genetics Yale School of Medicine Wu Tsai Institute Yale University FAIR Meta AI Computational Biology and Bioinformatics Program Yale University

Here we consider the problem of denoising features associated to complex data, modeled as signals on a graph, via a smoothness prior. This is motivated in part by settings such as single-cell RNA where the data is very high-dimensional, but its structure can be captured via an affinity graph. This allows us to utilize ideas from graph signal processing. In particular, we present algorithms for the cases where the signal is perturbed by Gaussian noise, dropout, and uniformly distributed noise. The signals are assumed to follow a prior distribution defined in the frequency domain which favors signals which are smooth across the edges of the graph. By pairing this prior distribution with our three models of noise generation, we propose Maximum A Posteriori (M.A.P.) estimates of the true signal in the presence of noisy data and provide algorithms for computing the M.A.P. Finally, we demonstrate the algorithms’ ability to effectively restore signals from white noise on image data and from severe dropout in single-cell RNA sequence data.

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APIR:Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control

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Genomics, Proteomics & Bioinformatics 2024年第2期22卷 171-187页

作者： Yiling Elaine Chen Xinzhou Ge Kyla Woyshner MeiLu McDermott Antigoni Manousopoulou Scott B.Ficarro Jarrod A.Marto Kexin Li Leo David Wang Jingyi Jessica Li Department of Statistics and Data Science University of CaliforniaLos AngelesCA 90095USA Department of Immuno-Oncology Beckman Research InstituteCity of Hope National Medical CenterDuarteCA 91010USA Department of Quantitative and Computational Biology University of Southern CaliforniaLos AngelesCA 90089USA Department of Cancer Biology and Blais Proteomics Center Dana-Farber Cancer InstituteDepartment of PathologyBrigham and Women’s Hospital and Harvard Medical SchoolBostonMA 02215USA Department of Pediatrics City of Hope National Medical CenterDuarteCA 91010USA Bioinformatics Interdepartmental Program University of CaliforniaLos AngelesCA 90095USA Department of Human Genetics University of CaliforniaLos AngelesCA 90095USA Department of Computational Medicine University of CaliforniaLos AngelesCA 90095USA Department of Biostatistics University of CaliforniaLos AngelesCA 90095USA

Advances in mass spectrometry(MS)have enabled high-throughput analysis of proteomes in biological *** state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide–spectrum matches(PSMs),which convert mass spectra to peptide *** database search algorithms use distinct search strategies and thus may identify unique ***,no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and a control on the false discovery rate(FDR).To fill in this gap,we proposed a statistical framework,Aggregation of Peptide Identification Results(APIR),that is universally compatible with all database search ***,under an FDR threshold,APIR is guaranteed to identify at least as many,if not more,peptides as individual database search algorithms *** of APIR on a complex proteomics standard dataset showed that APIR outpowers individual database search algorithms and empirically controls the *** data studies showed that APIR can identify disease-related proteins and post-translational modifications missed by some individual database search *** APIR framework is easily extendable to aggregating discoveries made by multiple algorithms in other high-throughput biomedical data analysis,e.g.,differential gene expression analysis on RNA sequencing *** APIR R package is available at https://***/yiling0210/APIR.

关键词： Shotgun proteomics Peptide–spectrum match Peptide identification Aggregation of lists FDR control

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E2Former: A Linear-time Efficient and Equivariant Transformer for Scalable Molecular Modeling

arXiv

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arXiv 2025年

作者： Li, Yunyang Huang, Lin Ding, Zhihao Wang, Chu Wei, Xinran Yang, Han Wang, Zun Liu, Chang Shi, Yu Jin, Peiran Zhang, Jia Gerstein, Mark B. Qin, Tao Department of Computer Science Yale University New Haven United States Microsoft Research AI4Science The Hong Kong Polytechnic University Hong Kong Huazhong University of Science and Technology Wuhan China Program in Computational Biology and Biomedical Informatics Yale University New Haven United States

Equivariant Graph Neural Networks (EGNNs) have demonstrated significant success in modeling microscale systems, including those in chemistry, biology and materials science. However, EGNNs face substantial computational challenges due to the high cost of constructing edge features via spherical tensor products, making them impractical for large-scale systems. To address this limitation, we introduce E2Former, an equivariant and efficient transformer architecture that incorporates the Wigner 6j convolution (Wigner 6j Conv). By shifting the computational burden from edges to nodes, the Wigner 6j Conv reduces the complexity from O(|E|) to O(|V|) while preserving both the model’s expressive power and rotational equivariance. We show that this approach achieves a 7x–30x speedup compared to conventional SO(3) convolutions. Furthermore, our empirical results demonstrate that the derived E2Former mitigates the computational challenges of existing approaches without compromising the ability to capture detailed geometric information. This development could suggest a promising direction for scalable and efficient molecular modeling. © 2025, CC BY.

关键词： Large scale systems

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Modeling of Measurement Error in Financial Returns Data

arXiv

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arXiv 2024年

作者： Jasra, Ajay Maama, Mohamed Mijatović, Aleksandar School of Data Science The Chinese University of Hong Kong Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Statistics University of Warwick United Kingdom

In this paper we consider the modeling of measurement error for fund returns data. In particular, given access to a time-series of discretely observed log-returns and the associated maximum over the observation period, we develop a stochastic model which models the true log-returns and maximum via a Lévy process and the data as a measurement error there-of. The main technical difficulty of trying to infer this model, for instance Bayesian parameter estimation, is that the joint transition density of the return and maximum is seldom known, nor can it be simulated exactly. Based upon the novel stick breaking representation of [12] we provide an approximation of the model. We develop a Markov chain Monte Carlo (MCMC) algorithm to sample from the Bayesian posterior of the approximated posterior and then extend this to a multilevel MCMC method which can reduce the computational cost to approximate posterior expectations, relative to ordinary MCMC. We implement our methodology on several applications including for real data. Copyright © 2024, The Authors. All rights reserved.

关键词： Markov chains

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Correlating Environmental Facts and Social Media Trends Leveraging Commonsense Reasoning and Human Sentiments 2

Correlating Environmental Facts and Social Media Trends Leve...

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2nd Workshop on Sentiment Analysis and Linguistic Linked Data, SALLD 2022

作者： McNamee, Brad Varde, Aparna S. Razniewski, Simon Computational Linguistics Program Montclair State University MontclairNJ United States Department of Computer Science Montclair State University MontclairNJ United States Max Planck Institute for Informatics Saarbrucken Germany Max Planck Institute for Informatics Germany

ISBN: (纸本)9791095546764

As climate change alters the physical world we inhabit, opinions surrounding this hot-button issue continue to fluctuate. This is apparent on social media, particularly Twitter. In this paper, we explore concrete climate change data concerning the Air Quality Index (AQI), and its relationship to tweets. We incorporate commonsense connotations for appeal to the masses. Earlier work focuses primarily on accuracy and performance of sentiment analysis tools/models, much geared towards experts. We present commonsense interpretations of results, such that they are not impervious to the masses. Moreover, our study uses real data on multiple environmental quantities comprising AQI. We address human sentiments gathered from linked data on hashtagged tweets with geolocations. Tweets are analyzed using VADER, subtly entailing commonsense reasoning. Interestingly, correlations between climate change tweets and air quality data vary not only based upon the year, but also the specific environmental quantity. We anticipate that this study will shed light on possible areas to increase awareness of climate change, and methods to address it, by the scientists as well as the common public. In line with Linked Data initiatives, we aim to make this work openly accessible on a network, published with the Creative Commons license. © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.

关键词： Linked data

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A variational approach to Bayesian phylogenetic inference

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2024年第1期25卷 6890-6945页

作者： Cheng Zhang Frederick A. Matsen IV School of Mathematical Sciences and Center for Statistical Science Peking University Beijing China Howard Hughes Medical Institute Computational Biology Program Fred Hutchinson Cancer Research Center Seattle WA and Department of Genome Sciences and Department of Statistics University of Washington Seattle WA

Bayesian phylogenetic inference is currently done via Markov chain Monte Carlo (MCMC) with simple proposal mechanisms. This hinders exploration efficiency and often requires long runs to deliver accurate posterior estimates. In this paper, we present an alternative approach: a variational framework for Bayesian phylogenetic analysis. We propose combining subsplit Bayesian networks, an expressive graphical model for tree topology distributions, and a structured amortization of the branch lengths over tree topologies for a suitable variational family of distributions. We train the variational approximation via stochastic gradient ascent and adopt gradient estimators for continuous and discrete variational parameters separately to deal with the composite latent space of phylogenetic models. We show that our variational approach provides competitive performance to MCMC, while requiring much fewer (though more costly) iterations due to a more efficient exploration mechanism enabled by variational inference. Experiments on a benchmark of challenging real data Bayesian phylogenetic inference problems demonstrate the effectiveness and efficiency of our methods.

关键词： Bayesian phylogenetic inference variational inference subsplit Bayesian networks structured amortization

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