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Prediction of methylene blue dye sorption to sulfonated date palm kernel biochar using statistical regression and machine learning methods and DFT studies

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Journal of Molecular Liquids 2025年 429卷

作者： Aigbe, Uyiosa Osagie Ukhurebor, Kingsley Eghonghon Onyancha, Robert Birundu Osibote, Adelaja Otolorin Hassaan, Mohamed A. ElKatory, Marwa R. Nemr, Ahmed El Center for Space Research North-West University Private Bag X6001 Potchefstroom2531 South Africa National Institute of Theoretical and Computational Science Johannesburg2000 South Africa School of Chemistry & Physics University of KwaZulu-Natal Pietermaritzburg Campus Private Bag X01 Scottsville3209 South Africa Department of Physics Faculty of Science Edo State University Uzairue Edo State Nigeria School of Physics and Earth Science Faculty of Applied Science and Technology Technical University of Kenya Nairobi Kenya College of Graduate Studies School of Interdisciplinary Research and Graduate Studies Muckleneuk Campus University of South Africa Pretoria0003 South Africa Department of Mathematics and Physics Cape Peninsula University of Technology Cape Town South Africa Kayet Bey Alexandria Elanfoushy Egypt Advanced Technology and New Materials Research Institute SRTA-City New Borg El-Arab City 21934 Alexandria Egypt

In this study, methylene blue (MB) dye adsorption to synthesised sulfonated date palm kernel biochar (SDPKB) was predicted and optimized using statistical-based regression approach (response surface methodology (RSM), machine-learning algorithms (artificial-neural-network (ANN), and adaptive-neuro-fuzzy-inference-system (ANFIS) models), and quantum chemistry calculations performed using density function theory (DFT) to link the electrical properties of the MB dye with the experimental findings. The percentage (%) of MB dye removed using SDPKB was found to be proportional to the biosorbent dosage and interaction time and inversely proportional to the solution pH and initial concentrations based on different used models results. It was observed that these models were accurate and comparable for the prediction of the removal of MB with coefficient of regression (R2) values of 0.9174, 0.9742, and 0.9999, mean square error (MSE) values of 181.71, 94.50, and 0.00000049, and root MSE (RMSE) values of 13.48, 9.72, and 0.0007 for the RSM, ANN, and ANFIS, respectively. The ANFIS model was found to be more effective in the prediction of MB sorption to SDPKB than the other models (ANFIS > ANN > RSM), and it was highly applicable in the sorption process. This study has revealed that the SDPKB can serve as a better biosorbent for MB adsorption. Therefore, this study will serve as a first reference point data that will be of great assistance in industrial effluent management as well as decision-making on the adoption of statistical and machine learning models for adsorption study. © 2025 Elsevier B.V.

关键词： Adversarial machine learning

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Error Estimate of a New Conservative Finite Difference Scheme for the Klein-Gordon-Dirac System

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Numerical mathematics(Theory,Methods and Applications) 2023年第1期16卷 140-164页

作者： Shasha Bian Yue Cheng Boling Guo Tingchun Wang The Graduate School of China Academy of Engineering Physics Beijing 100088China School of Mathematics and Statistics Nanjing University of Information Science and TechnologyNanjing 210044China Institute of Applied Physics and Computational Mathematics Beijing 100088China

In this paper,we derive and analyze a conservative Crank-Nicolson-type finite difference scheme for the Klein-Gordon-Dirac(KGD)*** from the derivation of the existing numerical methods given in literature where the numerical schemes are proposed by directly discretizing the KGD system,we translate the KGD equations into an equivalent system by introducing an auxiliary function,then derive a nonlinear Crank-Nicolson-type finite difference scheme for solving the equivalent *** scheme perfectly inherits the mass and energy conservative properties possessed by the KGD,while the energy preserved by the existing conservative numerical schemes expressed by two-level’s solution at each time *** using energy method together with the‘cut-off’function technique,we establish the optimal error estimate of the numerical solution,and the convergence rate is O(τ^(2)+h^(2))in l∞-norm with time stepτand mesh size *** experiments are carried out to support our theoretical conclusions.

关键词： Klein-Gordon-Dirac equation nonlinear finite difference scheme conservation error analysis

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A Gas-Kinetic Scheme for Collisional Vlasov-Poisson Equations in Cylindrical Coordinates

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Communications in computational Physics 2022年第8期32卷 779-809页

作者： Yi Wang Jiexing Zhang Guoxi Ni University of Science and Technology of China HefeiChina Graduate school of China Academy of Engineering Physics BeijingChina Institute of Applied Physics and computational mathematics BeijingChina

Many configurations in plasma physics are axisymmetric,it will be more convenient to depict them in cylindrical coordinates compared with Cartesian *** this paper,a gas-kinetic scheme for collisional Vlasov-Poisson equations in cylindrical coordinates is proposed,our algorithm is based on Strang *** equation is divided into two parts,one is the kinetic transport-collision part solved by multiscale gas-kinetic scheme,and the other is the acceleration part solved by a Runge-Kutta *** asymptotic preserving property of whole algorithm is proved and it’s applied on the study of charge separation problem in plasma edge and 1D Z-pinch *** results show it can capture the process fromnon-equilibrium to equilibrium state by Coulomb collisions,and numerical accuracy is obtained.

关键词： Vlasov-BGK-Poisson equations cylindrical coordinates gas-kinetic scheme asymptotic preserving property Coulomb collisions

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Overview of the Head and Neck Tumor Segmentation for Magnetic Resonance Guided Applications (HNTS-MRG) 2024 Challenge 1st

Overview of the Head and Neck Tumor Segmentation for Magneti...

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1st Challenge on Head and Neck Tumor Segmentation for MRI-Guided Applications, HNTS-MRG 2024, Held in Conjunction with 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2024

作者： Wahid, Kareem A. Dede, Cem El-Habashy, Dina M. Kamel, Serageldin Rooney, Michael K. Khamis, Yomna Abdelaal, Moamen R. A. Ahmed, Sara Corrigan, Kelsey L. Chang, Enoch Dudzinski, Stephanie O. Salzillo, Travis C. McDonald, Brigid A. Mulder, Samuel L. McCullum, Lucas Alakayleh, Qusai Sjogreen, Carlos He, Renjie Mohamed, Abdallah S. R. Lai, Stephen Y. Christodouleas, John P. Schaefer, Andrew J. Naser, Mohamed A. Fuller, Clifton D. Department of Radiation Oncology The University of Texas MD Anderson Cancer HoustonTX United States Department of Imaging Physics The University of Texas MD Anderson Cancer HoustonTX United States Transitional Year Program Corewell Health Wiliam Beaumont Royal OakMI United States Department of Radiation Oncology University of Maryland School of Medicine BaltimoreMD United States Department of Clinical Oncology and Nuclear Medicine Faculty of Medicine Alexandria University Alexandria Egypt UT MD Anderson Cancer CenterUTHealth Houston Graduate School of Biomedical Sciences Houston United States Department of Radiation Oncology Baylor College of Medicine HoustonTX United States Department of Head and Neck Surgery The University of Texas MD Anderson Cancer HoustonTX United States Elekta AtlantaGA United States Department of Computational Applied Mathematics and Operations Research Rice University HoustonTX United States

ISBN: (纸本)9783031832734

Magnetic resonance (MR)-guided radiation therapy (RT) is enhanc- ing head and neck cancer (HNC) treatment through superior soft tissue con- trast and longitudinal imaging capabilities. However, manual tumor segmentation remains a significant challenge, spurring interest in artificial intelligence (AI)- driven automation. To accelerate innovation in this field, we present the Head and Neck Tumor Segmentation for MR-Guided Applications (HNTS-MRG) 2024 Challenge, a satellite event of the 27th International Conference on Medical Image Computing and Computer Assisted Intervention. This challenge addresses the scarcity of large, publicly available AI-ready adaptive RT datasets in HNC and explores the potential of incorporating multi-timepoint data to enhance RT auto- segmentation performance. Participants tackled two HNC segmentation tasks: automatic delineation of primary gross tumor volume (GTVp) and gross metastatic regional lymph nodes (GTVn) on pre-RT (Task 1) and mid-RT (Task 2) T2- weighted scans. The challenge provided 150 HNC cases for training and 50 for final testing hosted on *** using a Docker submission framework. In total, 19 independent teams from across the world qualified by submitting both their algorithms and corresponding papers, resulting in 18 submissions for Task 1 and 15 submissions for Task 2. Evaluation using the mean aggregated Dice Simi- larity Coefficient showed top-performing AI methods achieved scores of 0.825 in Task 1 and 0.733 in Task 2. These results surpassed clinician interobserver vari- ability benchmarks, marking significant strides in automated tumor segmentation for MR-guided RT applications in HNC. © The Author(s) 2025.

关键词： Deep learning

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Stylistic analysis of paintings using wavelets and machine learning

Stylistic analysis of paintings using wavelets and machine l...

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17th European Signal Processing Conference, EUSIPCO 2009

作者： Jafarpour, Sina Polatkan, Güngör Brevdo, Eugene Hughes, Shannon Brasoveanu, Andrei Daubechies, Ingrid Princeton University Departments of Electrical Engineering Computer Science and Mathematics Program in Applied and Computational Mathematics Princeton NJ 08544 United States

Wavelet transforms and machine learning tools can be used to assist art experts in the stylistic analysis of paintings. A dual-tree complex wavelet transform, Hidden Markov Tree modeling and Random Forest classifiers are used here for a stylistic analysis of Vincent van Gogh's paintings with results on two stylometry challenges that concern "dating, resp. extracting distinguishing features". © EURASIP, 2009.

关键词： Decision trees

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Anomalous suppression of large-scale density fluctuations in classical and quantum spin liquids

arXiv

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arXiv 2025年

作者： Chen, Duyu Samajdar, Rhine Jiao, Yang Torquato, Salvatore Materials Research Laboratory University of California Santa BarbaraCA93106 United States Department of Physics Princeton University PrincetonNJ08544 United States Princeton Center for Theoretical Science Princeton University PrincetonNJ08544 United States Materials Science and Engineering Arizona State University TempeAZ85287 United States Department of Physics Arizona State University TempeAZ85287 United States Department of Chemistry Princeton University PrincetonNJ08544 United States Princeton Materials Institute Princeton University PrincetonNJ08540 United States Program in Applied and Computational Mathematics PrincetonNJ08544 United States

Classical spin liquids (CSLs) are intriguing states of matter that do not exhibit long-range magnetic order and are characterized by an extensive ground-state degeneracy. Adding quantum fluctuations, which induce dynamics between these different classical ground states, can give rise to quantum spin liquids (QSLs). QSLs are highly entangled quantum phases of matter characterized by fascinating emergent properties, such as fractionalized excitations and topological order. One such exotic quantum liquid is the Z2 QSL, which can be regarded as a resonating valence bond (RVB) state formed from superpositions of dimer coverings of an underlying lattice. In this work, we unveil a hidden large-scale structural property of archetypal CSLs and QSLs known as hyperuniformity, i.e., normalized infinite-wavelength density fluctuations are completely suppressed in these systems. In particular, we first demonstrate that classical ensembles of close-packed dimers and their corresponding quantum RVB states are perfectly hyperuniform in general. Subsequently, we focus on a ruby-lattice spin liquid that was recently realized in a Rydberg-atom quantum simulator, and show that the QSL remains effectively hyperuniform even in the presence of a finite density of spinon and vison excitations, as long as the dimer constraint is still largely preserved. Moreover, we demonstrate that metrics based on the framework of hyperuniformity can be used to distinguish the QSL from other proximate quantum phases. These metrics can help identify potential QSL candidates, which can then be further analyzed using more advanced, computationally-intensive quantum numerics to confirm their status as true QSLs. © 2025, CC BY-NC-ND.

关键词： Quantum entanglement

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Majorana's stellar representation for the quantum geometric tensor of symmetric states

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Communications in Theoretical Physics 2022年第6期74卷 31-38页

作者： Xingyu Zhang Jiancheng Pei Libin Fu Xiaoguang Wang Zhejiang Institute of Modern Physics Department of PhysicsZhejiang UniversityHangzhou 310027China National Laboratory of Science and Technology on Computational Physics Institute of Applied Physics and Computational MathematicsBeijing 100088China Graduate School of China Academy of Engineering Physics Beijing 100193China

Majorana's stellar representation provides an intuitive picture in which quantum states in highdimensional Hilbert space can be observed using the trajectory of Majorana *** consider the Majorana's stellar representation of the quantum geometric tensor for a spin state up to spin-3/*** real and imaginary parts of the quantum geometric tensor,corresponding to the quantum metric tensor and Berry curvature,are therefore obtained in terms of the Majorana ***,we work out the expressions of quantum geometric tensor for arbitrary spin in some important *** results will benefit the comprehension of the quantum geometric tensor and provide interesting relations between the quantum geometric tensor and Majorana's stars.

关键词： quantum geometric tensor Berry curvature quantum metric tensor Majorana's stellar representation

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NUMERICAL STUDY OF A 2-POINT CORRELATION-FUNCTION AND LIOUVILLE FIELD PROPERTIES IN 2-DIMENSIONAL QUANTUM-GRAVITY

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MODERN PHYSICS LETTERS A 1991年第12期6卷 1115-1131页

作者： AGISHTEIN, ME BENAV, R MIGDAL, AA SOLOMON, S Program in Applied and Computational Mathematics Fine Hall Princeton University Princeton NJ 08544–1000 USA Nuclear Physics Department Weizmann Institute of Science Rehovot 76100 Israel Physics Department and Program in Applied and Computational Mathematics Fine Hall Princeton University Princeton NJ 08544–1000 USA Physics Department Hebrew University Jerusalem Israel

Two-point Green's function is measured on the manifolds of a 2-dimensional quantum gravity. The recursive sampling technique is used to generate the triangulations, lattice sizes being up to hundred thousand triangles. The grid Laplacian was inverted by means of the algebraic multi-grid solver. The free field model of the Quantum Gravity assumes the Gaussian behavior of Liouville field and curvature. We measured histograms as well as six momenta of these fields. Our results support the Gaussian assumption.

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Motor cortex repetitive transcranial magnetic stimulation in fibromyalgia: a multicentre randomised controlled trial

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British Journal of Anaesthesia 2025年第6期134卷 1756-1764页

作者： Silva, Valquíria A. Baptista, Abrahão F. Fonseca, Alessandra S. Carneiro, Adriana M. Brunoni, André R. Carrilho, Paulo.E.M. Lins, Catarina C. Kubota, Gabriel T. Fernandes, Ana Mércia B.L. Lapa, Jorge.D.S. dos Santos, Lucas M. Sasso, Ivo Monte-Silva, Katia Poindessous-Jazat, Frédérique Mori, Nobuhiko Miki, Kenji Baltar, Adriana Tanaka, Clarice Teixeira, Manoel J. Hosomi, Koichi Bouhassira, Didier Attal, Nadine Ciampi de Andrade, Daniel LIM 62 - Pain Center Department of Neurology São Paulo Brazil Service of Interdisciplinary Neuromodulation (SIN) Department and Institute of Psychiatry São Paulo Brazil Medical-Surgical Nursing Department University of São Paulo São Paulo Brazil Center for Mathematics Computation and Cognition Federal University of ABC São Paulo Brazil Mood Disorder Program (Pro-GRUDA) Department of Psychiatry University of São Paulo São Paulo Brazil Medicine School “Professor Orival Alves” State University of Western Paraná (UNIOESTE) Paraná Brazil Neurosurgery Unit Hospital de Cirurgia Sergipe Aracaju Brazil Department of Medicine Federal University of Sergipe Sergipe São Cristóvão Brazil LIM 54 - Physiotherapy Research Laboratory University of São Paulo São Paulo Brazil Applied Neuroscience Laboratory Universidade Federal de Pernambuco Cidade Universitária Pernambuco Brazil UVSQ-Paris-Saclay University Ambroise Paré Hospital Boulogne-Billancourt U987 France Department of Neurosurgery Osaka University Graduate School of Medicine Osaka Japan Faculty of Health Science Osaka Yukioka College of Health Science Osaka Japan Center for Pain Management Hayaishi Hospital Osaka Japan Center for Neuroplasticity and Pain (CNAP) Department of Health Science and Technology University of Aalborg Gistrup Denmark

Background: Despite affecting 2–4% of the population worldwide, fibromyalgia often remains refractory to treatment. Here we report the first international randomised double-blind, sham-controlled trial developed to assess the efficacy of repetitive transcranial magnetic stimulation (rTMS) as an add-on therapy for fibromyalgia. Methods: Women aged ≥18 yr with fibromyalgia refractory to best available treatment were enrolled in Brazil, France, and Japan, and randomised to 10 Hz motor cortex (M1) rTMS, 3000 pulses day⁻¹, or sham stimulation. This included 10 induction sessions over 2 weeks, followed by weekly maintenance (6 weeks), and fortnightly extended maintenance (8 weeks). Primary outcome was ≥50% pain reduction at week 8 compared with baseline. Secondary outcomes included pain interference, mood, global impression of change, and Fibromyalgia Impact Questionnaire (FIQ) scores at weeks 8 and 16. Results: We randomised 101 women (mean age 48 [range 25-83] yr) into active (n=52) or sham (n=49) arms. Bayesian analysis revealed a 99.4% probability of ≥50% pain reduction at week 8 in the active group vs sham (odds ratio [OR] 3.04;95% credible interval [95% CrI] 1.26–8.06), with a number needed to treat of 4.54. Frequentist analysis confirmed that relative pain reduction was higher in the active than in the sham group (40.4% vs 18.4%, P=0.028). At week 16, this probability reduced to 34.2% (OR 0.815;95% CrI 0.313–2.1), but the likelihood of FIQ score reduction was 79.1%. The intervention appeared safe. Conclusions: Add-on M1-repetitive transcranial magnetic stimulation reduced pain intensity up to 8 weeks in women with fibromyalgia. Although analgesic effects waned, functional improvements remained during extended maintenance at week 16. © 2025 The Authors

关键词： chronic pain clinical trial fibromyalgia neuromodulation transcranial magnetic stimulation

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Quadratic Finite Volume Element Schemes over Triangular Meshes for a Nonlinear Time-Fractional Rayleigh-Stokes Problem

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Computer Modeling in Engineering & sciences 2021年第5期127卷 487-514页

作者： Yanlong Zhang Yanhui Zhou Jiming Wu Graduate School of China Academy of Engineering Physics Beijing100088China School of Data and Computer Science Sun Yat-Sen UniversityGuangzhou510275China Institute of Applied Physics and Computational Mathematics Beijing100088China

In this article,we study a 2D nonlinear time-fractional Rayleigh-Stokes problem,which has an anomalous subdiffusion term,on triangular meshes by quadratic finite volume element ***-fractional derivative,defined by Caputo fractional derivative,is discretized through L2−1σformula,and a two step scheme is used to approximate the time first-order derivative at time tn−α/2,where the nonlinear term is approximated by using a matching linearized difference scheme.A family of quadratic finite volume element schemes with two parameters are proposed for the spatial discretization,where the range of values for two parameters areβ1∈(0,1/2),β2∈(0,2/3).For testing the precision of numerical algorithms,we calculate some numerical examples which have known exact solution or unknown exact solution by several kinds of quadratic finite volume element schemes,and contrast with the results of an existing quadratic finite element scheme by drawing diversified comparison plots and showing the detailed data of L2 error results and convergence *** results indicate that,L2 error estimate of one scheme with parameters β_(1)=(3−√3)/6,β2=(6+√3−√21+6√3)/9 is O(h^(3)+△t^(2)),and L^(2) error estimates of other schemes are O(h^(2)+△t^(2)),where h and △t denote the spatial and temporal discretization parameters,respectively.

关键词： Quadratic finite volume element schemes anomalous sub-diffusion term L2 error estimate quadratic finite element scheme

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