Prediction of barite scale formation and inhibition in hydrocarbon reservoirs using AI modeling: Focus on different optimization algorithms by Ouafa Belkacem, Ahmed Rezrazi, Kamel Aizi, Lokmane Abdelouahed, Maamar Laidi, Abdelhafid Touil, Leila Cherifi, Salah Hanini

“…The performance of the models was rigorously evaluated using statistical criteria and graphical tools, demonstrating exceptional accuracy with minimal errors. The ELM model emerged as the most precise (RMSE = 0.0005, R² = 0.999), closely followed by the SVR-PSO model (RMSE = 0.0008, R² = 0.999). …”
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Improved Artificial Bee Colony Optimization Underwater Localization Algorithm by Logistic Chaos Mapping and Differential Evolution by Jiaxing CHEN, Yang LIU, Xiaoqian LIU, Zhihua LIU

“…Moreover, in terms of maximum and average error, the LDIABC algorithm exhibited a lower localization error than the other algorithms, indicating an effective optimization effect.Conclusions The LDIABC algorithm has proven effective in improving convergence speed and preventing the process from becoming trapped in local optima during iterations. …”
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Exploring the effectiveness of virtual reality-based training for sustainable health and occupational safety in industry 4.0 by Yousef Qawqzeh, Ata Al Shraah, Ali Rizwan, Manuel Sánchez-Chero, Leandro Alonso Vallejos More, Mohammad Shabaz

“…The research primarily focuses on how VR-based training can enhance the sustainability of occupational safety for industrial workers, thereby reducing the likelihood of human errors and industrial accidents. A quasi-experimental design was employed in the current study, with 200 participants divided into two groups: intervention and control. …”
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Exploring the role of self-led debriefings within simulation-based education: time to challenge the status quo? by Prashant Kumar, Neil Malcolm Harrison, Katy McAleer, Ibraaheem Khan, Susan Geraldine Somerville

“…Careful consideration and due diligence must go into the design and implementation of SLDs to augment the advantages of this debriefing format, such as enhancing flexibility and learner autonomy, whilst mitigating potential risks, such as reinforcing errors and biases or causing psychological harm. In situations where resources for facilitator-led debriefings (FLDs) are limited, simulation educators should recognise SLDs as a potential avenue to explore in their local contexts. …”
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Multi-scenario analysis of green water resource efficiency under carbon emission constraints in the Chengdu-Chongqing urban agglomeration, China: A system dynamics approach by Keyao Yu, Zhigang Li

“…Finally, this study provides policy implications to enhance technological innovation, optimize industrial structures, and strengthen water ecosystem protection, offering theoretical and policy insights for sustainable development in the CCUA and similar regions.…”
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A Panpsychist Interpretation of Evolutionary Theory by Ferhat Onur

“… If there is a questionable element in the theory of evolution, it is likely the randomness of mutations, which is seen as the primary source of evolutionary change. The idea that errors in DNA sequences are the source of species change does not seem acceptable to many scientists and philosophers. …”
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Transitioning from Analog to Digitalization of Essential Vaccination for Travellers through National Immunization Management System (NIMS) at the Points of Entry in Pakistan by Dr Nadia Noreen

“…It enhances data accuracy, reduces manual errors, and provides timely access to critical information for decision-making and issuance of digital certificates to passengers with achievement in terms of better validity, and reliability. …”
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Entrepreneurship among People with Disabilities in Unstable Macroenvironment Conditions by Andrzej Koza, Adriana Politaj

“…This will allow to avoid typical errors resulting from a relatively short time range of observations. …”
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Energy utilization potential of Saravan landfill in Rasht with life cycle assessment approach by Ali Ahmadi Orkomi, Maryam Malekpour

“…Results and discussion: The results showed that in the first and second scenarios, the total amount of biogas generated in the landfill was over 6,600 and 10,500 Gigagrams, respectively. Also, the relative error of LandGem in predicting the generated methane was almost 3.3%. …”
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Micro-electrical Discharge Machining of Micro-holes Based on Integrated Orthogonal Experiments and CNN Methods by Yuandong MO, Yazhi WANG, Shuqi HUANG, Jiajun ZHONG

“…All the predicted values have relative errors below 12%, affirming a resilient fit of the PyTorch-based CNN and demonstrating exceptional predictive performance. …”
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In-Depth Analysis of Ka-Band Integrated Commercial Beamformer Non-Idealities in Phased Array Calibration and Pattern Prediction Methods for 5G Scenarios by Jorge Calatayud Maeso, Xiaoliang Sun, Alfonso Tomas Muriel-Barrado, Fernando Rodriguez Varela, Pablo Sanchez-Olivares, Jose-Manuel Fernandez-Gonzalez, Manuel Sierra Castaner

“…Finally, anechoic chamber measurements assess the pattern prediction capabilities of the analyzed methods, and an iterative calibration scheme is proposed to compensate for the studied beamformer errors due to its behavior.…”
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Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study by Xiaolei Lu, Chenye Qiao, Hujun Wang, Yingqi Li, Jingxuan Wang, Congxiao Wang, Yingpeng Wang, Shuyan Qie

“…Model performance was evaluated using mean squared error (MSE), the coefficient of determination (R²), and mean absolute error (MAE). …”
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Prediction of Rut Depth in Soil Caused by Wheels Using Artificial Neural Networks by N. Farhadi, A. Mardani, A. Hosainpour, B. Golanbari

“…Specifically, the root mean square error (RMSE) for the optimal MLP model, which utilized a learning rate of 0.001 and a momentum of 0.67, was 0.10. …”
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Automated Recognition of Abnormalities in Gastrointestinal Endoscopic Images – Evaluation of an AI Tool for Identifying Polyps and Other Irregularities by Weronika Jarych, Elżbieta Tokarczyk, Patryk Iglewski, Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Michał Kociński, Jan Reinald Wendt

“…Key advantages of AI integration in endoscopy include improved sensitivity, minimized detection errors, and the potential to optimize clinical workflow efficiency. …”
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Diffraction studies of WS2 crystallographic ordering during laser MBE growth on Al2O3(0001) by E. Lobanova, M. Dorogov, V. Fedorov, T. Grasser, Y. Illarionov, I. Eliseyev, V. Davydov, A. Korovin, S. Suturin, N. Sokolov

“…For optimal integration of 2D materials into fab-compatible processes, it is essential to grow them directly onto suitable insulating substrates, thereby avoiding error-prone transfer procedures. In the present paper, ultrathin films of WS2 were grown on Al2O3 using laser molecular beam epitaxy (LMBE). …”
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Enhancing whole-profile soil organic carbon predictions in croplands through a depth-resolved modelling approach by Hangxin Zhou, Yuchen Wei, Mingming Wang, Liujun Xiao, Zhongkui Luo

“…This depth-resolved modelling approach has implications for predicting whole-profile SOC dynamics in response to nitrogen fertilization, tillage and residue management scenarios. …”
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Navigating Uncertainty: Advanced Techniques in Pedestrian Intention Prediction for Autonomous Vehicles—A Comprehensive Review by Alireza Mirzabagheri, Majid Ahmadi, Ning Zhang, Reza Alirezaee, Saeed Mozaffari, Shahpour Alirezaee

“…This highlights the critical need to enhance pedestrian safety, especially given the significant role human error plays in road accidents. Autonomous vehicles present a promising solution to mitigate these fatalities by improving road safety through advanced prediction of pedestrian behavior. …”
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What Can DKIST/DL-NIRSP Tell Us about Quiet-Sun Magnetism? by Jiayi Liu, Xudong Sun, Peter W. Schuck, Sarah A. Jaeggli

“…However, the net Poynting flux tends to be significantly underestimated. The error mainly arises from the underestimated contribution of the horizontal motion. …”
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Prediction of Pilot Performance During Startle Events Based on Neuropsychophysiological Features of Stress Resilience and Cognitive Task Scores by Mate Gambiraza, Sinisa Popovic, Matej Kurtak, Tanja Jovanovic, Seth Norrholm, Kresimir Cosic

“…The obtained MRA models demonstrated significant predictive validity across left-out participants, as indicated by a Pearson correlation coefficient of 0.7039 (p =0.0034) between the actual and predicted simulator performance, with a mean absolute error (MAE) of 2.5457° versus a dummy median regressor MAE of 3.4881°. …”
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Large-Scale Completion of Ionospheric TEC Maps Using Machine Learning Models With Constraints Conditions by Qingfeng Li, Hanxian Fang, Chao Xiao, Die Duan, Hongtao Huang, Ganming Ren

“…Results show that the CGVAE-label model excels in TEC completion, achieving a mean structural similarity of 93.80% and a root mean square error of 2.20 TECU. It outperforms the baseline CGVAE model, particularly in reconstructing peak ionospheric structures. …”
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