The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1) by M. Buehner, J.-F. Caron, E. Lapalme, A. Caya, P. Du, Y. Rochon, S. Skachko, M. Bani Shahabadi, S. Heilliette, M. Deshaies-Jacques, W. Chang, M. Sitwell

“…In addition to describing the current MIDAS applications, a sample of the results from these systems is presented to demonstrate their performance in comparison with either systems from before the switch to using MIDAS software or similar systems at other numerical weather prediction (NWP) centres. The modular software design also allows the code that implements high-level components (e.g. observation operators, error covariance matrices, state vectors) to easily be used in many different ways depending on the application, such as for both variational and ensemble DA algorithms, for estimating the observation impact on short-term forecasts, and for performing various observation pre-processing procedures. …”
Get full text

Machine learning integrates region-specific microbial signatures to distinguish geographically adjacent populations within a province by Li Luo, Li Luo, Bangwei Chen, Bangwei Chen, Shengyin Zeng, Shengyin Zeng, Yaxin Li, Yaxin Li, Xiaolin Chen, Xiaolin Chen, Jianguo Zhang, Xiangjie Guo, Shujin Li, Lei Ruan, Shida Zhu, Cairong Gao, Cuntai Zhang, Tao Li

“…Among the three ML algorithms, the random forest algorithm achieved the best performance, with an AUC of 0.943.ConclusionThe gut microbiota of individuals residing in the same province is significantly similar; however, pronounced differences in bacterial composition were noted between individuals. …”
Get full text

Variable Selection for Additive Quantile Regression with Nonlinear Interaction Structures by Yongxin Bai, Jiancheng Jiang, Maozai Tian

“…Effective variable selection is crucial for avoiding the curse of dimensionality and enhancing the predictive performance of a model. In this paper, we introduce a nonlinear interaction structure into the additive quantile regression model and propose an innovative penalization method. …”
Get full text

MACAW: a method for semi-automatic detection of errors in genome-scale metabolic models by Devlin C. Moyer, Justin Reimertz, Daniel Segrè, Juan I. Fuxman Bass

“…Abstract Genome-scale metabolic models (GSMMs) are used to predict metabolic fluxes, with applications ranging from identifying novel drug targets to engineering microbial metabolism. …”
Get full text

Machine learning approaches for modelling of molecular polarizability in gold nanoclusters by Abhishek Ojha, Satya S. Bulusu, Arup Banerjee

“…Our results demonstrate the efficacy of machine-learning in accurately predicting the polarizability of gold nanoclusters. …”
Get full text

An Enterprise-Naming Inspiration in the United States by Michael D. Sublett

“…Data collection tools involved standard online searches; Google’s predictive searching algorithm; business and nonprofit searching tools on the websites of the states’ secretaries of state; and several subscription databases, including Newspapers.com. …”
Get full text

Applications of AI Technology in Radiation Safety and Protection by Xiaowa WANG

“…Despite technical challenges and ethical issues such as accuracy, data processing, and algorithmic transparency, the application prospects of AI in radiation protection remain broad. …”
Get full text

Remote Sensing Applications in Ocean Observation (Second Edition) by Chung-Ru Ho

“…This information is valuable for developing predictive models and informing policy decisions related to climate change mitigation and adaptation.…”
Get full text

Mapping Data to Concepts: Enhancing Quantum Neural Network Transparency with Concept-Driven Quantum Neural Networks by Jinkai Tian, Wenjing Yang

“…Experimental results demonstrate that CD-QNN maintains high predictive accuracy while offering clear and meaningful explanations of its decision-making process. …”
Get full text

How to crack a SMILES: automatic crosschecked chemical structure resolution across multiple services using MoleculeResolver by Simon Müller

“…MoleculeResolver systematically crosschecks structures retrieved from multiple reputable chemical databases, implements rigorous identifier plausibility checks, standardizes molecular structures, and intelligently selects the most accurate representation based on a unique resolution algorithm. Scientific contribution Benchmarks across diverse datasets confirm that MoleculeResolver significantly enhances precision, recall, and overall reliability compared to traditional single-source methods, proving its utility as a valuable resource for chemists, data scientists, and researchers engaged in high-quality molecular data analysis and predictive model development. …”
Get full text

Differential Evolution for Optimizing Model Parameters in Simulation of Direct Dimethyl Carbonate Synthesis by Outi Ruusunen, Riitta Keiski, Mika Ruusunen

“…When validated with data of a real-world batch process, the model accurately predicted evolution of reaction composition ratios in time, offering a tool for predictive optimization. …”
Get full text

Three-Dimensional Impact Time and Angle Control Guidance Based on MPSP by Yang Li, Hao Zhou, Wanchun Chen

“…The guidance law is devised using the model predictive static programming (MPSP) method, and the control saturation constraint is incorporated in the MPSP algorithm. …”
Get full text

The Relationship Between Surface Meteorological Variables and Air Pollutants in Simulated Temperature Increase Scenarios in a Medium-Sized Industrial City by Ronan Adler Tavella, Daniele Feijó das Neves, Gustavo de Oliveira Silveira, Gabriella Mello Gomes Vieira de Azevedo, Rodrigo de Lima Brum, Alicia da Silva Bonifácio, Ricardo Arend Machado, Letícia Willrich Brum, Romina Buffarini, Diana Francisca Adamatti, Flavio Manoel Rodrigues da Silva Júnior

“…This study utilized five years of daily meteorological data (from 1 January 2019 to 31 December 2023) to model atmospheric conditions and two years of daily air pollutant data (from 21 December 2021 to 20 December 2023) to simulate how pollutant levels would respond to annual temperature increases of 1 °C and 2 °C, employing a Support Vector Machine, a supervised machine learning algorithm. Predictive models were developed for both annual averages and seasonal variations. …”
Get full text

A New Finite-Difference Method for Nonlinear Absolute Value Equations by Peng Wang, Yujing Zhang, Detong Zhu

Get full text

Deep Ocean Learning of Small Scale Turbulence by Ali Mashayek, Nick Reynard, Fangming Zhai, Kaushik Srinivasan, Adam Jelley, Alberto Naveira Garabato, Colm‐cille P. Caulfield

“…Here, we show that supervised machine learning algorithms can be trained on the existing turbulence data to develop skillful predictions of the key properties of turbulence from T, S, Z, and topographic data. …”
Get full text

Natural Killer (NK) Cell Alloreactivity in Haploidentical Stem Cell Transplantation by Mar Luis-Hidalgo, José Luis Piñana, Carlos Solano, Dolores Planelles

“…These models consider the presence or absence of specific ligands or receptors and/or <i>KIR</i> genes in the donor and recipient to predict alloreactivity. Determining the best model for predicting KIR alloreactivity and its significance in donor selection algorithms for haploidentical transplantation is still under investigation.…”
Get full text

Performance of digital filtering and synchronization method for APD communication receiver by Hui-Jun Zhang, Peng Lin, Tong Wang, Zi-Qi Zhang, Bai-Qiu Zhao, Wen-Fang Jiao, Xiao-Nan Yu

Get full text

Meta-Learning Amidst Heterogeneity and Ambiguity by Kyeongryeol Go, Mingyu Kim, Seyoung Yun

“…However, typical meta-learning algorithms have assumed the tasks to be similar such that a single meta-learner is sufficient to aggregate the variations in all aspects. …”
Get full text

Error-Mask-Adaptive Dynamic Filtering for Image Inpainting by Keunsoo Ko, Seunggyun Woo, Chang-Su Kim

“…Experimental results on diverse datasets show that the proposed EMDF algorithm outperforms existing inpainting algorithms significantly. …”
Get full text

Edge of excellence: JEC's Scopus achievement, doors 2025 breakthroughs, and Volume 4 Issue 1 (2025) highlights by Serhiy O. Semerikov, Tetiana A. Vakaliuk

“…The paper examines innovative solutions addressing distributed systems challenges, including IoT-based monitoring systems, intelligent traffic prediction algorithms, and security implementations for resource-constrained environments. …”
Get full text