Centroid-AME: An open-source software for estimating avian migration trajectories using population centroids movement in the annual cycle by Shi Feng, Alice C. Hughes, Qinmin Yang, Leyi Li, Chao Li

“…To address the inherent spatial and temporal biases of observations, the preprocessing steps include the interpolation of missing values, the application of sliding window, and the detection of outliers, which will address gaps and errors. …”
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An Adaptive X‐Ray Dynamic Image Estimation Method Based on OMNI Solar Wind Parameters and SXI Simulated Observations by R. C. Wang, Anders M. Jorgensen, Dalin Li, Tianran Sun, Zhen Yang, Xiaodong Peng

“…Experimental validation demonstrates apparent improvements in Peak signal‐to‐noise ratio (PSNR) and Structural Similarity (SSIM) compared to traditional linear and optical flow interpolation methods. The method's flexibility, considering input‐output consistency, enables easy extension to any interval (>3 min), meeting diverse application needs. …”
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H-AMR FORGE’d in FIRE. I. Magnetic State Transitions, Jet Launching, and Radiative Emission in Super-Eddington, Highly Magnetized Quasar Disks Formed from Cosmological Initial Cond... by Nicholas Kaaz, Matthew Liska, Alexander Tchekhovskoy, Philip F. Hopkins, Jonatan Jacquemin-Ide

“…To answer this, we must follow the gas to the event horizon. For this, we interpolated the quasar into the general-relativistic radiation magnetohydrodynamics code H-AMR and performed 3D simulations with BH spins a = 0 and a = 0.9375. …”
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Fusion of Remotely Sensed Data with Monitoring Well Measurements for Groundwater Level Management by César de Oliveira Ferreira Silva, Rodrigo Lilla Manzione, Epitácio Pedro da Silva Neto, Ulisses Alencar Bezerra, John Elton Cunha

“…We utilized the 90 m resolution TanDEM-X digital surface model and STEEP (Seasonal Tropical Ecosystem Energy Partitioning) data with a 500 m resolution to support the spatial interpolation of groundwater table depth measurements collected from 56 locations during the hydrological year 2015–16. …”
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SFMHANet: Surface Fitting Constrained Multidimensional Hybrid Attention Network for Aero-Optics Thermal Radiation Effect Correction by Yu Shi, ShanLin Niu, Lei Wang, Liang Ye, YaoZong Zhang, HanYu Hong

“…First, according to the characteristics of the aero-optics thermal radiation bias field belonging to low frequency, we initially estimate the aero-optics thermal radiation bias field using biharmonic spline interpolation surface fitting based on wavelet decomposition. …”
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Estimation of Dendrocalamus giganteus leaf area index by combining multi-source remote sensing data and machine learning optimization model by Zhen Qin, Huanfen Yang, Qingtai Shu, Jinge Yu, Zhengdao Yang, Xu Ma, Dandan Duan

“…Thus, a new method for large-scale estimation of Dendrocalamus giganteus LAI was proposed, which integrates ICESat-2/ATLAS, and Sentinel-1/-2 data, and refines machine learning models through the application of Bayesian Optimization (BO), Particle Swarm Optimization (PSO), Genetic Algorithms (GA), and Simulated Annealing (SA). First, spatial interpolation was performed using the Sequential Gaussian Conditional Simulation (SGCS) method. …”
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Computer simulation of the soil water regime under an apple orchard in a mountainous area (using the example of the leached chernozem of the experimental agricultural station Gorno... by Svetlana V. Baboshkina, Olga A. Elchininova, Alexander V. Puzanov, Tamara A. Rozhdestvenskaya

“…The method of graphic interpolation was used for transition the soil texture classification from Russian to international one. …”
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PM2.5 in Sri Lanka: Trend Analysis, Low-cost Sensor Correlations and Spatial Distribution by Ranil Dhammapala, Ashani Basnayake, Sarath Premasiri, Lakmal Chathuranga, Karen Mera

“…With these corrected data, we interpolated satellite and model-derived PM2.5 annual averages at 1 km intervals. …”
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Newton–Simpson-based predictor–corrector methods for milling chatter stability prediction by Yongjian Ji, Xiaokang Xu, Yulin Yang, Runnan Liu, Shuyao Liu, Zhenghu Yan

“…During the forced vibration period, the time-delayed term and the periodic coefficient matrix are approximated as a holistic operator over two different time intervals using the Newton interpolation polynomials and the Simpson formula, respectively. …”
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How many trees to see the forest? Assessing the effects of morphospace coverage and sample size in performance surface analysis by Stephanie M. Smith, C. Tristan Stayton, Kenneth D. Angielczyk

“…To do this, we subsampled a pre‐existing set of turtle shell performance surfaces in four different ways: first, uniform subsampling of theoretical morphologies across the surface; second, random subsampling of theoretical morphologies across the surface; third, a combination uniform/random subsampling method called close‐pairs sampling and fourth, subsampling only points on the surface known to correspond to a naturally occurring turtle shell morphology. Each subset was interpolated with ordinary Kriging to produce a new performance surface for comparison to the original. …”
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Geospatial digital mapping of soil organic carbon using machine learning and geostatistical methods in different land uses by Yahya Parvizi, Shahrokh Fatehi

“…The spherical variogram model with MAE = 0.41 best fits to interpolate and map SOC using ordinary kriging in different land uses. …”
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Variation Characteristics of the Main Hydrochemical Indexes in Typical Subterranean Rivers in the South China Karst Region Based on Curve Fitting by Shuyi Liu, Chuan Liang, Lina Wang, Lingwei Zeng, Chunyi Wang

“…Additionally, we consolidated the data collected since 1960 and, by applying MATLAB, a variety of fitting curve methods were used to fit all the data, and the results showed that cubic spline interpolation fitting performed the best. The squared correlation coefficients (R2) of the obtained fitting curves for Ca2+, HCO3-, and Mg2+ are 0.8545, 0.8689, and 0.7632, respectively, and the corrected R2 values are 0.6739, 0.7088, and 0.4853, respectively. …”
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Estimation for Reduction Potential Evaluation of CO₂ Emissions from Individual Private Passenger Cars Using Telematics by Masahiro Mae, Ziyang Wang, Shoma Nishimura, Ryuji Matsuhashi

“…The estimation performance for interpolation and extrapolation of car models is also evaluated, and it keeps enough estimation accuracy with slight performance degradation. …”
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Crime and birth rate in Ukraine: modelling and statistical analysis by O. F. Shevchuk

“…The combined two-period birth rate model built as a result of the correlation and regression analysis proved to be adequate, with a fairly high interpolation accuracy (R = 0.865; MAPE = 5.38 %). In addition, for the first period (1992–2018), an overall decrease in the crime rate by 1 % was accompanied by an increase in the birth rate by 0.71 % with a time shift of two years. …”
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Forecasting Weather using Deep Learning from the Meteorological Stations Data : A Study of Different Meteorological Stations in Kaski District, Nepal by Supath Dhital, Kapil Lamsal, Sulav Shrestha, Umesh Bhurtyal

“…Averaging and linear interpolation techniques were used to fill out the missing values and outliers were detected using Box Plot and replaced with threshold value for each parameter. …”
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Completion of the Central Italy daily precipitation instrumental data series from 1951 to 2019 by Gamal AbdElNasser Allam Abouzied, Guoqiang Tang, Simon Michael Papalexiou, Martyn P. Clark, Eleonora Aruffo, Piero Di Carlo

“…This method combines the outcome of 15 strategies based on four various gap‐filling techniques (quantile mapping, spatial interpolation, machine learning, and multi‐strategy merging). …”
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Spatiotemporal dynamics and prevention strategies of cervical cancer incidence in Addis Ababa, Ethiopia: an ecological study by Mathewos Assefa, Eva Johanna Kantelhardt, Teferi Gedif Fenta, Tariku Shimels

“…Techniques such as Bayesian empirical testing with a block weighting matrix for hotspot identification, Global Moran’s I for spatial autocorrelation, nearest neighbour imputation and universal Kriging interpolation were used to manage data gaps. Joinpoint trend analysis and direct age-standardised incidence rate (ASIR) using the Segi’s World standard population was applied to compare trends across subcities. …”
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Optimizing Subsurface Geotechnical Data Integration for Sustainable Building Infrastructure by Nauman Ijaz, Zain Ijaz, Nianqing Zhou, Zia ur Rehman, Hamdoon Ijaz, Aashan Ijaz, Muhammad Hamza

“…In this framework, this paper aimed to develop SMs for the first time in the rapidly growing district of Gujrat using the optimal interpolation technique (OIT). The subsurface conditions were evaluated using the standard penetration test (SPT) N-values and soil classification including seismic wave velocity to account for seismic effects. …”
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Estimating ocean currents from the joint reconstruction of absolute dynamic topography and sea surface temperature through deep learning algorithms by D. Ciani, C. Fanelli, B. Buongiorno Nardelli

“…Retrieving consistent high-resolution ADT and SST information from space is challenging, due to instrument limitations, sampling constraints, and degradations introduced by the interpolation algorithms used to obtain gap-free (L4) analyses. …”
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Supersymmetric $$AdS_6$$ A d S 6 black holes from ISO(3) $$\times $$ × U(1) F(4) gauged supergravity by Parinya Karndumri

“…We give numerical black hole solutions interpolating between all of these $$AdS_2\times \mathcal {M}_4$$ A d S 2 × M 4 near horizon geometries and the asymptotically locally $$AdS_6$$ A d S 6 vacuum. …”
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