Photochemical Ozone Production Along Flight Trajectories in the Upper Troposphere and Lower Stratosphere and Route Optimisation by Allan W. Foster, Richard G. Derwent, M. Anwar H. Khan, Dudley E. Shallcross, Mark H. Lowenberg, Rukshan Navaratne

“…Based on these models, route optimisation has been investigated, through the use of network theory and algorithms. This is to show the potential inclusion of an understanding of climate-sensitive regions of the atmosphere on route planning can have on aviation’s impact on Earth’s Thermal Radiation balance with existing resources and technology. …”
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Revolutionizing Diabetes Management Through Nanotechnology-Driven Smart Systems by Aayush Kaushal, Aanchal Musafir, Gourav Sharma, Shital Rani, Rajat Kumar Singh, Akhilesh Kumar, Sanjay Kumar Bhadada, Ravi Pratap Barnwal, Gurpal Singh

“…The integration of artificial intelligence (AI) with nanotechnology marks a new frontier in personalised care. AI algorithms can analyse individual patient data to adjust insulin doses and predict glucose fluctuations, paving the way for more responsive, customised treatment plans. …”
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Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients by Aref Andishgar, Sina Bazmi, Kamran B. Lankarani, Seyed Alireza Taghavi, Mohammad Hadi Imanieh, Gholamreza Sivandzadeh, Samira Saeian, Nazanin Dadashpour, Alireza Shamsaeefar, Mahdi Ravankhah, Hamed Nikoupour Deylami, Reza Tabrizi, Mohammad Hossein Imanieh

“…Seven survival machine learning algorithms were used: LASSO, Ridge, RSF, E-NET, GBS, C-GBS, and FS-SVM. …”
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Multi-Camera Machine Learning for Salt Marsh Species Classification and Mapping by Marco Moreno, Sagar Dalai, Grace Cott, Ben Bartlett, Matheus Santos, Tom Dorian, James Riordan, Chris McGonigle, Fabio Sacchetti, Gerard Dooly

“…UAV surveys were conducted with RGB, MSI, and HSI sensors, and the collected data were classified using Random Forest (RF), Spectral Angle Mapper (SAM), and Support Vector Machine (SVM) algorithms. The classification performance was assessed using Overall Accuracy (<i>OA</i>), Kappa Coefficient (<i>k</i>), Producer’s Accuracy (<i>PA</i>), and User’s Accuracy (<i>UA</i>), for both individual sensor datasets and the fused dataset generated via band stacking. …”
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Design and Evaluation of ACAFiB-APP, a clinical decision support system for anticoagulant considerations in patients with atrial fibrillation by Ramin Ansari, Sorayya Rezayi, Ali Asghar Safaei, Reza Mollazadeh, Eisa Rezaei, Mahboobeh Khabaz Mafinejad, Soha Namazi, Keyhan Mohammadi

“…According to the designed algorithms, the application was developed using Asp.net with the Microsoft SQL Server database platform. …”
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Time series forecasting of Valley fever infection in Maricopa County, AZ using LSTMResearch in context by Xueting Jin, Fangwu Wei, Srinivasa Srivatsav Kandala, Tejas Umesh, Kayleigh Steele, John N. Galgiani, Manfred D. Laubichler

“…Interpretation: LSTM algorithms, combined with traditional statistical methods, could help with the forecasting of CM cases. …”
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Seminal plasma proteomics of asymptomatic COVID-19 patients reveals disruption of male reproductive function by Jialyu Huang, Yufang Su, Jiawei Wang, Zheng Fang, Yiwei Zhang, Hong Chen, Xinxia Wan, Yuanhuan Xiong, Ning Song, Houyang Chen, Xingwu Wu

“…Four proteins were significantly correlated with one or more semen parameters in Spearman’s coefficient analysis, and seven were filtered as potential hub proteins from the interaction network by MCODE and Cytohubba algorithms. Furthermore, we verified the proteomic results by Western blot analysis of three representative proteins (ITLN1, GSTM2, and PSAP) in the validation cohort. …”
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A Novel Approach for Rapid Detection of Forest Degradation and Diseases Through Anomaly Analysis of Sentinel-2 Spectral Data by Sofiia Drozd, Nataliia Kussul, Hanna Yailymova

“…The aim of this study was to develop an accessible and reliable technique that could match the performance of more complex algorithms while using minimal computational resources. …”
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The Comprehensive Effect of Depression, Anxiety, and Headache on Pain Intensity and Painkiller Use in Patients with Headache Analyzed by Unsupervised Clustering Using Machine Learn... by Jong-Ho Kim, Minha Ahn, Jong-Hee Sohn, Sung-Mi Hwang, Jae-Jun Lee, Young-Suk Kwon

“…<b>Methods</b>: Comprehensive patient groups were formed based on unsupervised clustering using machine learning algorithms, and their associations were analyzed via ordinary least square regression. …”
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Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data by Zhiwei Xun, Farag M. A. Altalbawy, Prakash Kanjariya, R. Manjunatha, Debasish Shit, M. Nirmala, Ajay Sharma, Sarbeswara Hota, Shirin Shomurotova, Fadhil Faez Sead, Hojjat Abbasi, Mohammad Mahtab Alam

“…Gradient boosting machine (GBM) models were optimized using advanced algorithms like self-adaptive differential evolution (SADE), evolution strategy (ES), Bayesian probability improvement (BPI), and Batch Bayesian optimization (BBO). …”
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A Study on the Management and Evolution of Land Use and Land Cover in Romania During the Period 1990–2022 in the Context of Political and Environmental Changes by Jenica Călina, Aurel Călina, Gheorghe Marian Vangu, Alin Constantin Croitoru, Marius Miluț, Nicolae Ion Băbucă, Ion Stan

“…The purpose of this article is to identify sources of official data and to build an updated dataset upon which analysis algorithms can be applied. Basic analyses were performed on the dataset to study the evolution of land use and land cover in Romania during the period 1990–2022 and to analyze whether they align with and support national and European strategies for economic development. …”
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Selection and Validation of Stable Reference Genes for RT-qPCR in <i>Scotogramma trifolii</i> (Lepidoptera: Noctuidae) by Anpei Yang, Hang Zhang, Weiwei Bai, Ruifeng Ding, Weipeng Li, Guangkuo Li

“…To address the lack of validated reference genes in <i>S. trifolii</i>, we evaluated six candidate genes (<i>β-actin</i>, <i>RPL9</i>, <i>GAPDH</i>, <i>RPL10</i>, <i>EF1-α</i>, and <i>TUB</i>) across four developmental stages (egg, larva, pupa, and adult) and six adult tissues (head, thorax, abdomen, wings, legs, and antennae) using geNorm, NormFinder, BestKeeper, and RefFinder algorithms. Stability analysis identified <i>β-actin</i>, <i>RPL9</i>, and <i>GAPDH</i> as the most reliable reference genes for developmental stage normalization, while <i>RPL10</i>, <i>GAPDH</i>, and <i>TUB</i> were validated for adult tissues. …”
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Dynamic time-varying transfer function for cancer gene expression data feature selection problem by Hao-Ming Song, Yu-Cai Wang, Jie-Sheng Wang, Yu-Wei Song, Shi Li, Yu-Liang Qi, Jia-Ning Hou

“…Subsequently, to assess the generalizability of our proposed approach across 12 cancer gene expression datasets for testing purposes five algorithms (AOA, COA, PSO, WOA and ZOA) are employed. …”
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Internet of Things Applications for Energy Management in Buildings Using Artificial Intelligence—A Case Study by Izabela Rojek, Dariusz Mikołajewski, Adam Mroziński, Marek Macko, Tomasz Bednarek, Krzysztof Tyburek

“…By using IoT sensors and smart meters, buildings can collect real-time data on energy usage patterns, occupancy, temperature, and lighting conditions.AI algorithms then analyze this data to identify inefficiencies, predict energy demand, and suggest or automate adjustments to optimize energy use. …”
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Transforming machine learning model knowledge into material insights for multi-principal-element superalloy phase design by Qiuling Tao, Xintong Yang, Longke Bao, Yuexin Zhou, Tao Yang, Yilu Zhao, Rongpei Shi, Zhifu Yao, Xingjun Liu

“…First, we construct two classification models using ML algorithms to predict the presence or absence of the L12 phase and other phases, respectively. …”
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Sustainable Energy and Exergy Analysis in Offshore Wind Farms Using Machine Learning: A Systematic Review by Hamid Reza Soltani Motlagh, Seyed Behbood Issa-Zadeh, Abdul Hameed Kalifullah, Arife Tugsan Isiacik Colak, Md Redzuan Zoolfakar

“…By integrating theoretical insights with empirical evidence, this study proposes a unified framework that leverages ML algorithms to optimize turbine performance, reduce maintenance costs, and minimize environmental impacts. …”
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A model for classifying information objects using neural networks and fuzzy logic by Vadym Mukhin, Valerii Zavgorodnii, Viacheslav Liskin, Sergiy Syrota, Aleksandra Czupryna-Nowak, Bohdan Rusyn, Arkadiusz Banasik, Jacek Woloszyn, Wojciech Kempa

“…Improve the efficiency of classification algorithms by fine-tuning neural network parameters and fuzzy logic rules, ensuring high accuracy and computational efficiency when processing large-scale educational datasets. …”
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Infrastructure Assisted Autonomous Driving: Research, Challenges, and Opportunities by Roshan George, Joseph Clancy, Tim Brophy, Ganesh Sistu, William O'Grady, Sunil Chandra, Fiachra Collins, Darragh Mullins, Edward Jones, Brian Deegan, Martin Glavin

“…This paper identifies the specific information required from infrastructure nodes, proposes an optimized sensor suite, discusses data processing algorithms, and investigates effective spatial model representations for cooperative sensing. …”
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Land Surface Temperature Super-Resolution With a Scale-Invariance-Free Neural Approach: Application to MODIS by Romuald Ait-Bachir, Carlos Granero-Belinchon, Aurelie Michel, Julien Michel, Xavier Briottet, Lucas Drumetz

“…The second contribution of this work is the release of an evaluation database with ASTER LST images concomitant with MODIS ones that can be used for evaluation of super-resolution algorithms. We compare the two proposed models, SIF-CNN-SR1 and SIF-CNN-SR2, with four state-of-the-art methods: Bicubic, Data Mining Sharpener, ATPRK and Tsharp, and a CNN sharing the same architecture as SIF-CNN-SR but trained under the scale-invariance hypothesis. …”
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A Multivariate Phenotypical Approach of Sepsis and Septic Shock—A Comprehensive Narrative Literature Review by Alina Tita, Sebastian Isac, Teodora Isac, Cristina Martac, Geani-Danut Teodorescu, Lavinia Jipa, Cristian Cobilinschi, Bogdan Pavel, Maria Daniela Tanasescu, Liliana Elena Mirea, Gabriela Droc

“…This has led to the devise of a phenotypical approach in sepsis, further dividing patients based on host and trigger-related factors, clinical manifestations and progression towards organ deficiencies, dynamic prognosis algorithms, and patient trajectory in the Intensive Care Unit (ICU). …”
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