Exploring target selectivity in designing and identifying PI3Kα inhibitors for triple negative breast cancer with fragment-based and bioisosteric replacement approach by Debojyoti Halder, Shreya Mukherjee, R. S. Jeyaprakash

“…Further, the top 2 moieties – Djh1 and Djh2 were selected after MMGBSA analysis and target selectivity prediction towards kinase. Further induced fit docking (IFD) analysis, DFT analysis, and MD simulation were employed to establish that – Djh1 and Djh2 could act as potential hit molecules for selective inhibition of PI3Kα. …”
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Data stochasticity and model parametrisation impact the performance of species distribution models: insights from a simulation study by Lambert, Charlotte, Virgili, Auriane

“…Species distribution models (SDM) are widely used to describe and explain how species relate to their environment and predict their spatial distributions. As such, they are the cornerstone of most of spatial planning efforts worldwide. …”
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Combination of an E-Nose and an E-Tongue for Adulteration Detection of Minced Mutton Mixed with Pork by Xiaojing Tian, Jun Wang, Zhongren Ma, Mingsheng Li, Zhenbo Wei

“…And BPNN was proved to be the most effective method for the prediction of pork proportions with R2 higher than 0.97 both for the calibration and validation data set. …”
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Modelling the Isotope composition of groundwater using hydrochemical properties in eastern Saudi Arabia: Implementation of innovative data intelligence techniques by Mohammed Benaafi, Waleed M. Hamanah, Ebrahim Al-Wajih

“…The study demonstrates the potential of AI-based models to predict the isotopic signature and groundwater dynamics in similar coastal arid environments.…”
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Impact of stock market indices and raw material prices on the yield movements of Caterpillar company securities by Petrović Nevena, Novićević-Čečević Bojana, Krstajić Goran

“…In this study, we use multiple linear regression to predict the returns of CAT shares. The model results can be analyzed to identify patterns, trends, and insights that may be useful for forecasting. …”
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Evaluation of the Effectiveness of Multiple Machine Learning Methods in Remote Sensing Quantitative Retrieval of Suspended Matter Concentrations: A Case Study of Nansi Lake in Nort... by Xiuyu Liu, Zhen Zhang, Tao Jiang, Xuehua Li, Yanyi Li

“…Among them, the GA_RF model retrieves the suspended solids concentration with the best performance and the highest prediction accuracy, with a determination coefficient R2 of 0.98, a root mean square error (RMSE) of 1.715 mg/L, and an average relative error (ARE) of 6.83%. …”
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A Novel Active Learning Technique for Fetal Health Classification Based on XGBoost Classifier by Kaushal Bhardwaj, Niyati Goyal, Bhavika Mittal, Vandna Sharma, Shiv Naresh Shivhare

“…Ensuring safe pregnancy and reducing maternal and infant mortality rates require early prediction of fetal health. The application of machine learning algorithms in monitoring fetal health helps to improve the chances of timely intervention and better outcomes in the event of any possible health issues in fetuses. …”
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Pharmacophore-based approach for the identification of prospective UDP-2,3-diacylglucosamine hydrolase (LpxH) inhibitor from natural product database against Salmonella Typhi by Divyapriya Karthikeyan, Sanjit Kumar, NS Jayaprakash

“…Both compounds underwent toxicity prediction and ADMET analysis, showing favorable drug-like properties, with compound 1615 emerging as the most promising inhibitor due to its optimal electronic energy and minimal chemical potential. …”
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3D Chaotic Nonlinear Dynamic Population-Growing Mathematical System Modeling with Multiple Controllers by Shaymaa Hussain, Suzan Obaıys, Nadia Al-saidi, Yeliz Karaca

“…Modeling, stabilization, and identification processes are significant stages in the process of developing knowledge about chaotic dynamical systems which entail the effective prediction depending on the degree of uncertainty toleration in the forecast, accuracy of the current state to be measured as well as a time scale resting on the dynamics of the system. …”
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The Humanistic and Economic Burden Associated with Anxiety and Depression among Adults with Comorbid Diabetes and Hypertension by Kimberly Wallace, Xiaohui Zhao, Ranjita Misra, Usha Sambamoorthi

“…The incremental burden associated with depression and/or anxiety was estimated with the counterfactual recycled prediction. Of the 4560 adults with comorbid diabetes and hypertension, 13.2% reported depression only, 8.7% reported anxiety only, and 7.7% reported both. …”
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Innovative machine learning approaches for indoor air temperature forecasting in smart infrastructure by Nataliya Shakhovska, Lesia Mochurad, Rosana Caro, Sotirios Argyroudis

“…This paper presents an innovative approach to surrogate modeling for predicting indoor air temperature (IAT) in buildings, leveraging advanced machine learning techniques. …”
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Energy Release Analysis of a Severe Rockburst in a Headrace Tunnel Crossing a Tectonic Stress Zone by H. M. Tian, W. Z. Chen, C. S. Ma, D. S. Yang, X. J. Tan

“…The comparisons between the predictions and the field observations show that the strength-stress ratio criteria based on the uniaxial tests do not consider the influence of the tectonic stress on the strength of the rock. …”
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Analysis of Dynamic Biogas Consumption in Chinese Rural Areas at Village, Township, and County Levels by Gongyi Li, Tao Luo, Jianghua Xiong, Yanna Gao, Xi Meng, Yaoguo Zuo, Yi Liu, Jing Ma, Qiuwen Chen, Yuxin Liu, Yichong Xin, Yangjie Ye

“…The results showed that the predicted and measured biogas consumption and dynamic load were consistent. …”
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Systematic Exploration of the Knowledge Graph on Rock Porosity Structure by Chengwei Geng, Fei Xiong, Yong Liu, Yun Zhang, Yi Xue, Tongqiang Xia, Ming Ji

“…The porosity structure of rocks is an important research topic in fields such as civil engineering, geology, and petroleum engineering, with significant implications for groundwater flow, oil and gas reservoir exploitation, and geological hazard prediction. This paper systematically explores the research progress and knowledge graph construction methods for rock porosity structure, aiming to provide scientific foundations for a multidimensional understanding and application of rock porosity structure. …”
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Progress in quality assessment of Italian saffron by Irene Locatelli, Davide Pedrali, Silvia Grassi, Susanna Buratti, Annamaria Giorgi, Luca Giupponi

“…Discriminant and class-modelling approaches were developed to predict saffron quality subcategory. Best results were obtained by linear discriminant analysis models with accuracy in calibration (92.7%), cross-validation (86.4%) and prediction (87.0%). …”
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THE ROLE OF ARTIFICIAL INTELLIGENCE (AI) ON MRI BRAIN EXAMINATION WITH CLINICAL ISCHEMIC STROKE by Oktaviani Aulia WMS, Emi Murniati, Agustina Dwi Prastanti

“…Result: The role of AI in MRI brain examination with clinical ischemic stroke, namely its role in automatic lesion segmentation, Time Since Stroke (TSS) classification, and infarct volume prediction. The advantages of AI included short image processing times and accurate results. …”
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Typhoon Maria Precipitation Retrieval and Evolution Based on the Infrared Brightness Temperature of the Feng-Yun 4A/Advanced Geosynchronous Radiation Imager by Gen Wang, Kefu Wang, Wei Han, Dongyong Wang, Xuexing Qiu

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Simulation and Experimental Study of the Single-Pulse Femtosecond Laser Ablation Morphology of GaN Films by Mingyuan Wang, Tong Zhang, Yanping Yuan, Zhiyong Wang, Yanlei Liu, Lin Chen

“…The predicted errors of the ablation diameters and depths were within 4.71% and 10.9%, respectively. …”
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Reaction Kinetics of Cinnamaldehyde Hydrogenation over Pt/SiO2: Comparison between Bulk and Intraparticle Diffusion Models by Ali Al-Shathr, Zaidoon M. Shakor, Bashir Y. Al-Zaidi, Hasan Sh. Majdi, Adnan A. AbdulRazak, Safa Aal-Kaeb, Adel A. Shohib, James McGregor

“…Five Langmuir–Hinshelwood kinetic models were investigated to fit the experimental data. The predictions from the bulk model were compared with predictions from the intraparticle diffusion model. …”
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Methods of yeast genome editing by A. S. Rozanov, V. N. Shlyahtun, L. A. Tekutieva, O. M. Son, S. V. Sizova, S. E. Peltek

“…As a result, the rate of analysis and prediction of targets for genome editing is currently higher than the rate of genome editing, which led to the development of new methods of genetic engineering. …”
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