Processing debris from destroyed and damaged buildings in Gaza: carbon emissions, time frames, and implications for rebuilding by Samer Abdelnour, Nicholas Roy

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Valuing the Recreational Uses of Pakistan’s Wetlands: An Application of the Travel Cost Method by Iftikhar Hussain Adil, Ali Dehlavi

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Bootstrap Confidence Intervals for the Parameter of the Poisson-Sujatha Distribution and Their Applications to Agriculture by Wararit Panichkitkosolkul, ch Ponkaew

“…Moreover, the effectiveness of the bootstrap confidence intervals was proven through their application to agricultural data sets. The calculations offer significant evidence in favor of the suggested bootstrap confidence intervals.…”
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Improving lameness detection in cows: A machine learning algorithm application by Elma Dervić, Caspar Matzhold, Christa Egger-Danner, Franz Steininger, Peter Klimek

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Innovative practice of archival data development workflow in the AGI era: a case study of scientist archives project by Yaming Fu, Jie Song, Xinran Zhang, Jingyun Bi

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Broadband a priori temporal cross-covariances for the geomagnetic inverse problem: application to the satellite era by Romain Claveau, Nicolas Gillet, Pierre-Olivier Amblard, Christopher C. Finlay

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A New Zero–Inflated Regression Model with Applications to Australian Health Survey and Biochemistry Graduate Students Data by Caner Tanış, Mahmoud M. Mansour, Enayat M. Abd Elrazik, Christophe Chesneau, Hazem Al-Mofleh, Ahmed Z. Afify

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A Dynamic Model-Fitting Algorithm for Batch Laboratory Data: Application to Constant-Pressure Cake Filtration Experiments by Belmiro P. M. Duarte, Maria J. Moura, Lino O. Santos, Nuno M. C. Oliveira

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Evaluating the Application of a Perturbation-Based Inertia Estimation Methodology With Synchrophasor Data of the Brazilian Interconnected Power System by Juliana Luiza Pereira, Guido Rossetto Moraes, Raul Torres Bernardo, Daniel Dotta, Augusto Tietz, Antonio Felipe da Cunha De Aquino, Diego Issicaba

“…This paper presents the application of a methodology for estimating the inertia of generator groups of the Brazilian Interconnected Power System (BIPS) using phasor measurement unit (PMU) data acquired at 230 kV transmission substations. …”
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A Synthetic Data Generation Approach With Dynamic Camera Poses for Long-Range Object Detection in AI Applications by Misbah Bibi, Anam Nawaz Khan, Muhammad Faseeh, Qazi Waqas Khan, Rashid Ahmad, do-Hyeun Kim

“…Accurate long-range object detection is essential for applications such as security and surveillance. However, existing datasets often lack the complexity needed to represent real-world outdoor environments, resulting in limited performance of object detection algorithms at extended distances.Synthetic data generation offers a way to address these limitations by creating varied and realistic training scenarios. …”
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Exploration of the Application Rules and Clinical Significance of Acupoints in Acupuncture Treatment of Migraine Based on Data Mining [Response to Letter] by He Y, Wu Y, Li X

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Application of CIBERSORTx and BayesPrism to deconvolution of bulk RNA-seq data from human myocardium and skeletal muscle by Marcella Conning-Rowland, Chew W. Cheng, Oliver Brown, Marilena Giannoudi, Eylem Levelt, Lee D. Roberts, Kathryn J. Griffin, Richard M. Cubbon

“…Here, we describe the application and in silico validation of two pipelines to deconvolute human right atrium, left ventricle and skeletal muscle bulk RNA-seq data. …”
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Transformers deep learning models for missing data imputation: an application of the ReMasker model on a psychometric scale by Monica Casella, Nicola Milano, Pasquale Dolce, Davide Marocco

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Cluster Analysis of Comparative Genomic Hybridization (CGH) Data Using Self-Organizing Maps: Application to Prostate Carcinomas by Torsten Mattfeldt, Hubertus Wolter, Ralf Kemmerling, Hans‐Werner Gottfried, Hans A. Kestler

“…In this paper we present the application of a self‐organizing map (Genecluster) as a tool for cluster analysis of data from pT2N0 prostate cancer cases studied by CGH. …”
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A novel family of beta mixture models for the differential analysis of DNA methylation data: An application to prostate cancer. by Koyel Majumdar, Romina Silva, Antoinette Sabrina Perry, Ronald William Watson, Andrea Rau, Florence Jaffrezic, Thomas Brendan Murphy, Isobel Claire Gormley

“…To address this, a family of beta mixture models (BMMs) is proposed that (i) objectively infers methylation state thresholds and (ii) identifies differentially methylated CpG sites (DMCs) given untransformed, beta-valued methylation data. The BMMs achieve this through model-based clustering of CpG sites and by employing parameter constraints, facilitating application to different study settings. …”
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Application of Empirical Orthogonal Function Interpolation to Reconstruct Hourly Fine Particulate Matter Concentration Data in Tianjin, China by Hongwu Zhou, Haidong Pan, Shuang Li, Xianqing Lv

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Correction to: A robust implicit Jungck iterative scheme: stability, data dependency, and applications to nonlinear integral equations by Kapil Kumar, Hind Alamri, Vivek Kumar, Faik Gürsoy, Ioannis K. Argyros, Nawab Hussain

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Statistical Inferences to the Parameter and Reliability Characteristics of Gamma-mixed Rayleigh Distribution under Progressively Censored Data with Application by Kousik Maiti, Suchandan Kayal

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Assessing the Preprocessing Benefits of Data-Driven Decomposition Methods for Phase Permutation Entropy—Application to Econometric Time Series by Erwan Pierron, Meryem Jabloun

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A Rule Based Feature Selection Approach for Target Classification in Wireless Sensor Networks with Sensitive Data Applications by Zhiyong Hao, Bin Liu

“…Hence, minimizing energy consumption of sensors while maintaining a given classification accuracy is a key problem in this research area, especially for sensitive data applications. This paper proposes a rule based feature selection approach rather than all-features approach that aims at increasing the energy efficiency of the system without losing much classification accuracy. …”
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