Bioinformatic and clinical experimental assay uncovers resistance and susceptibility mechanisms of human glioblastomas to temozolomide and identifies new combined and individual su... by Alexander Modestov, Marianna Zolotovskaia, Maria Suntsova, Galina Zakharova, Aleksander Seryakov, Ivana Jovcevska, Jernej Mlakar, Elena Poddubskaya, Aleksey Moisseev, Grigory Vykhodtsev, Sergey Roumiantsev, Maksim Sorokin, Victor Tkachev, Aleksander Simonov, Anton Buzdin

“…Conclusion: In this study, a comprehensive analysis of the expression of 361 DNA repair genes and activation levels of 38 DNA repair pathways revealed 13 potential survival biomarkers with increased prognostic potential compared to MGMT methylation. We algorithmically reconstructed the TMZ sensitivity pathway with strong predictive capacity in GBM.…”
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Modelling Ergonomic Hazard Risks in Manual Handling: Insights from Ponorogo’s Traditional Industry by Dian Afif Arifah, Ratih Andhika Akbar Rahma, Triana Harmini, Dhiya Irsyad Hafidz

“…This study aims to develop a model to evaluate and predict ergonomic hazards using a neural network algorithm, focusing on the relationship between manual handling postures and musculoskeletal pain in 12 body regions. …”
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Selective Cleaning Enhances Machine Learning Accuracy for Drug Repurposing: Multiscale Discovery of MDM2 Inhibitors by Mohammad Firdaus Akmal, Ming Wah Wong

“…We identified two clinical CB1 antagonists, MePPEP and otenabant, and the statin drug atorvastatin as promising repurposing candidates based on their high predicted potency and binding affinity toward MDM2. …”
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The impact of environmental variables on reed stands of the intermittent Lake Cerknica, Slovenia: 40 years of change by Nik Ojdanič, Alenka Gaberščik, Igor Zelnik, Aleksandra Golob

“…Smaller changes were less reliably predicted, but temperature data emerged as a more influential predictor in such cases. …”
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Early Warning for Stepwise Landslides Based on Traffic Light System: A Case Study in China by Shuangshuang Wu, Zhigang Tao, Li Zhang, Song Chen

“…Furthermore, leveraging the C5.0 machine learning algorithm, a comparison between the predictive capabilities of the TLS model and a pure rate threshold model reveals that the TLS model achieves a 93% accuracy rate, outperforming the latter by 7 percentage points. …”
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Application of artificial intelligence and red-tailed hawk optimization for boosting biohydrogen production from microalgae by Hegazy Rezk, Ali Alahmer, Abdul Ghani Olabi, Enas Taha Sayed

“…The performance of ANFIS model in predicting hydrogen yield is assessed using root mean square error (RMSE) and coefficient-of-determination (R2) values. …”
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Optimization of MXene-based aqueous ionic liquids for solar systems using conventional and AI-based techniques by Mohamed Bechir Ben Hamida, Ali B. M. Ali, Narinderjit Singh Sawaran Singh, Loghman Mostafa

“…Response surface methodology (RSM) is used for predictive modeling, while enhanced hill climbing (EHC), non-dominated sorting genetic algorithm II (NSGA-II), and the multi-objective generalized normal distribution optimizer (MOGNDO) are applied for multi-objective optimization. …”
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Automated analysis of vessel morphometry in retinal images from a Danish high street optician setting. by Josefine Freiberg, Roshan A Welikala, Jens Rovelt, Christopher G Owen, Alicja R Rudnicka, Miriam Kolko, Sarah A Barman, FOREVER consortium

“…<h4>Method</h4>The dataset FOREVERP (Finding Ophthalmic Risk and Evaluating the Value of Eye exams and their predictive Reliability, Pilot) contains retinal images obtained from a Danish high street optician chain. …”
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Optimizing concrete strength: How nanomaterials and AI redefine mix design by Dan Huang, Guangshuai Han, Ziyang Tang

“…XGB was identified as the most effective ML algorithm for predicting compressive strength among others in this study (R2=0.974). …”
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Glypican-3 regulated epithelial mesenchymal transformation-related genes in osteosarcoma: based on comprehensive tumor microenvironment profiling by Jiaming Zhang, Wei Wang

“…The model effectively predicted immune-related features and immunotherapy responses in high-risk and low-risk patient groups. …”
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QSAR, Molecular Docking, and Pharmacokinetic Studies of 1,8-Naphthyridine Derivatives as Potential Anticancer Agents Targeting DNA Topoisomerase II by Garba Suleiman, Auwal Salisu Isa, Adamu Uzairu, Nabil El Brahmi, Saïd El Kazzouli

“…External validation demonstrated high predictive ability, with Q2 (F1) and Q2 (F2) scores of 0.8683 and 0.8670, respectively, indicating substantial reliability in predicting the biological activity of new compounds. …”
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A critical assessment of ionic liquid-based aqueous biphasic systems for biomolecules extraction and CO2 absorption by Viggy Wee Gee Tan, Yazan Abuhasheesh, Doris Ying Ying Tang, Yongyu Zhang, Zengling Ma, Lin Chen, Rambabu Krishnamoorthy, Pau Loke Show

“…The incorporation of machine learning (ML) algorithms to predict the toxicity and CO2 capture properties, as well as the scaling up of IL-ABSs, is also explored.…”
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An efficient enhanced stacked auto encoder assisted optimized deep neural network for forecasting Dry Eye Disease by Steffi Rajan, Suresh Ponnan

“…The approach described here is novel because it merges chaotic maps into FS, employs SLSTM-STSA for improved classification accuracy (CA), and optimizes with the adaptive quantum rotation of the Enhanced Quantum Bacterial Foraging Optimisation Algorithm (EQBFOA). The present study enhances prediction functions by extracting MGD-related features and complicated relationships from the DED dataset. …”
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Modern advancements of energy storage systems integrated with hybrid renewable energy sources for water pumping application by Marwa M. Ahmed, Haneen M. Bawayan, Mohamed A. Enany, Mahmoud M. Elymany, Ahmed A. Shaier

“…The manuscript also highlights the integration of artificial intelligence (AI) to optimize energy management, predict irrigation demands, and improve operational efficiency. …”
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Integrated remote sensing, machine learning and geospatial approach for site selection of sewage treatment plants in the metropolitan city by S. Rajalakshmi, S. Subathradevi, Abdulaziz G. Alghamdi, Hadeel Alsolai

“…A Random Forest (RF) algorithm was applied to enhance spatial prediction. …”
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Anomaly Detection Method for Hydropower Units Based on KSQDC-ADEAD Under Complex Operating Conditions by Tongqiang Yi, Xiaowu Zhao, Yongjie Shi, Xiangnan Jing, Wenyang Lei, Jiang Guo, Yang Meng, Zhengyu Zhang

“…This method provides a systematic technical solution for hydropower unit condition monitoring and predictive maintenance.…”
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Impact of foam-mat drying conditions of “Gấc” aril on drying rate and bioactive compounds: Optimization by novel statistical approaches by Nguyen Minh Thuy, Vo Quoc Tien, Tran Ngoc Giau, Hong Van Hao, Vo Quang Minh, Ngo Van Tai

“…ANN model of 3–10–3 showed more accuracy and faster prediction capacity than RSM model did. ANN-GA model predicted the optimal conditions to be 13.31 % EA, 0.26 % xanthan gum and drying temperature of 73.1 °C, with the drying rate of 1.89 g-water/g-dry matter/min, β-carotene content of 395.88 μg/g, TPC of 1.68 mgGAE/g. …”
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Implementation of new technique for Face recognition based on quantum computing by Amjed Yousif Sahib

“…This technique is transforming the oracle of Grover's search algorithm into correlation oracle with feeding image. …”
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Smart Real-time Attendance System for Nigerian Universities by Mikailu Habila, Faseki N. Francisca, Luwani Ishaya, Muhammed Kabir Ahmed, Umar A. Muhammad, Haruna P. Charles

“…The system employs Convolutional Neural Networks (CNNs) and the ArcFace algorithm for facial feature extraction and identity verification. …”
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Persistence and Burn-in in Solar Coronal Magnetic Field Simulations by Eric J. Hall, Karen A. Meyer, Anthony R. Yeates

“…Simulations of solar phenomena play a vital role in space-weather prediction. A critical computational question for automating research workflows in the context of data-driven solar coronal magnetic field simulations is quantifying a simulation's burn-in time, after which a solar quantity has evolved away from an arbitrary initial condition to a physically more realistic state. …”
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