Well Placement Optimization for Fractured Reservoirs: Coupling StoSAG and EDFM by Jianchun Xu, Wanhang Guo, Wenxin Zhou

“…Well placement optimization is a significant task in oil field development which aims to find the optimal well locations by maximizing the net present value (NPV) or other objective function. It is a highly nonlinear problem involving large number of variables. …”
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Reliability-Based Topology Optimization Considering Overhang Constraints for Additive Manufacturing Design by Fahri Murat, Irfan Kaymaz, Abdullah Tahir Şensoy

“…RBTO addresses uncertainties in design variables to enhance reliability. This research investigates build direction parameter solutions using deterministic and RBTO algorithms. …”
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Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

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Multi-objective trajectory planning for connected and autonomous vehicles in mixed traffic flow by Hui Li, Yunfei Ge, Yahui Guo, Yu Guan, Xu Zhang

“…The reward function integrates multiple objectives, including safety, fuel consumption, and traffic efficiency. …”
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Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…The results revealed a significant negative correlation between SWHC and the smoothed leaf spectral reflectance, with the best correlation coefficient was r = − 0.59. The use of third-order derivatives and logarithmic second-order derivatives further enhanced this correlation, yielding optimal coefficients of r = − 0.78 and r = − 0.72, respectively. …”
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Development of Speech Therapy Application for Children with Stuttering (STACS) by Janith Raj Jayaraju, Amudhu Sankar

“…Conclusion: Most parents found this prototype app easy to use, efficient in training their children, and highly functional. …”
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Integrating UAV-Based RGB Imagery with Semi-Supervised Learning for Tree Species Identification in Heterogeneous Forests by Bingru Hou, Chenfeng Lin, Mengyuan Chen, Mostafa M. Gouda, Yunpeng Zhao, Yuefeng Chen, Fei Liu, Xuping Feng

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Possibilities of Using Artificial Intelligence in Security Analysis by Maciej Norbert Ciesielski

“…In total, out of twelve features/variables that make up analytical imagination, artificial intelligence already functions efficiently (or will function efficiently soon) in practically all of them.…”
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Identification of Factors Affecting Project Financing Risk by Gholamreza Sharafi, Kiamars Fathi Hafashjani, Faegh Ahmadi

“…Risk management is now an important part of project management and has a specific function for improving the efficiency of implementing the project, saving prices, and improving the profitability of projects. …”
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p53 transactivation and the impact of mutations, cofactors and small molecules using a simplified yeast-based screening system. by Virginia Andreotti, Yari Ciribilli, Paola Monti, Alessandra Bisio, Mattia Lion, Jennifer Jordan, Gilberto Fronza, Paola Menichini, Michael A Resnick, Alberto Inga

“…<h4>Methodology/principal findings</h4>Given the many factors that might influence p53 function, including expression levels, mutations, cofactor proteins and small molecules, we expanded our previously described yeast-based system to provide the opportunity for efficient investigation of their individual and combined impacts in a miniaturized format. …”
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The association between age and long-term quality of life after curative treatment for prostate cancer: a cross-sectional study by Reidun Sletten, Ola Berger Christiansen, Line Merethe Oldervoll, Lennart Åstrøm, Håvard Kjesbu Skjellegrind, Jūratė Šaltytė Benth, Øyvind Kirkevold, Sverre Bergh, Bjørn Henning Grønberg, Siri Rostoft, Asta Bye, Paul Jarle Mork, Marit Slaaen

“…We found no statistically significant independent association between age at treatment and global QoL, PF or side effects, except for sexual function (regression coefficient [RC] −0.77; p < 0.001) and hormonal/vitality (RC 0.30; p = 0.006) function. …”
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Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications by Aditya Venkatraman, Mark A. Wilson, David Montes de Oca Zapiain

“…This demonstrates the excellent accuracy, computational efficiency, and validity of the developed model. Lastly, even though developed for corrosion, these protocols are formulated in a phenomenon-agnostic manner, allowing application to various variable-charge interatomic potentials and related fields.…”
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Stress Estimation Based on Stochastic Method for Strength Evaluation of Floating Wind Turbines by Byungmo Kim, Beomil Kim

“…Next, each time series was stochastically fitted to Weibull distribution function. The most probable maximum (MPM) von-Mises stresses were estimated according to the probability level corresponding to the design life of the platform on the fitted curves. …”
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Stability analysis of grid-connected hydropower plant considering turbine nonlinearity and parameter-varying penstock model by Chen Feng, Na sun, Chuang Zheng, Yongqi Zhu, Nan Zhang, Yahui Shan, Liping Shi, Xiaoming Xue

“…The nonlinear state space equations of GCHTGS with PVM and variable transfer coefficients are established. First, the influence of different penstock models on stability is investigated, and the comparison results show that the proposed PVM has a more precise stability region. …”
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Exploring the nexus of many-body theories through neural network techniques: the tangent model by Senwei Liang, Karol Kowalski, Chao Yang, Nicholas P Bauman

“…The NN representation not only allows us to evaluate the effective interactions efficiently for various geometrical configurations of chemical systems corresponding to various levels of complexity of the underlying wave functions, but also reveals that the bare and effective interactions are related by a tangent function of some latent variables. …”
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First-principles investigation on structural, electronic, and optical properties of (Cd1-xZnx)3As2 by Yu Deng, Xun Ge, Rongxiu Feng, Yunye Liang, Xiaohao Zhou

“…Calculations on the optical properties (dielectric function, absorption coefficient) of (Cd1-xZnx)3As2 show that it behaves well in the near infrared and far infrared. …”
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Estimating Daily Rice Crop Evapotranspiration in Limited Climatic Data and Utilizing the Soft Computing Algorithms MLP, RBF, GRNN, and GMDH by Pouya Aghelpour, Hadigheh Bahrami-Pichaghchi, Farzaneh Karimpour

“…The ETc rates were calculated by seven meteorological variables, the FAO-56 Penman-Monteith equation, and the regional calibrated rice crop coefficient and considered as the reference data. …”
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Enhancing Thermal–Hydraulic Performance in Nuclear Reactor Subchannels with Al₂O₃ Nanofluids: A CFD Analysis by Mohammad A. I. Sardar, Mushfiqur Rahman, Philip Rubini

“…This analysis has been carried out using the RNG k-epsilon turbulence model with standard wall function in ANSYS FLUENT 2022R1. The impact of various flow conditions and nanofluid concentrations has been examined. …”
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Impedance-based sensitivity analysis for enhanced dynamic stability in DC off-grid hydrogen production systems by Chenguang Zhang, Zhongjian Kang, Bin Li, Hongyang Zhang, Di Zhu

“…DC off-grid hydrogen production systems, employing source–hydrogen interface converters to achieve efficient renewable energy conversion and electrolysis coupling, represent a core technological solution for green hydrogen generation. …”
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Dynamic ensemble-based machine learning models for predicting pest populations by Ankit Kumar Singh, Md Yeasin, Ranjit Kumar Paul, A. K. Paul, Anita Sarkar

“…This study introduces a dynamic ensemble model with absolute log error (ALE) and logistic error functions using four machine learning models—artificial neural networks (ANNs), support vector regression (SVR), k-nearest neighbors (kNN), and random forests (RF). …”
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