Enhancing Venetian traditional marmorino with TiO2 and ZnO for antimicrobial protection – A case study by Andrea Campostrini, Sabrina Manente, Elena Ghedini, Alessandro Di Michele, Federica Menegazzo

“…This inhibition leads to a reduction in biodegradation, resulting in a diminished ability to take root and lack of spore development.…”
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Prediction of formation energy for oxides in ODS steels by machine learning by Tian-Xing Yang, Peng Dou

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Evaluation of antibacterial and antibiofilm activities of green-synthesized iron oxide nanoparticles using Cyperus rotundus extract as a reducing and stabilizing agent by Ankita Parmanik, Prafful Pradeep Kothari, Anindya Bose, Swati Biswas

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Microstructure examination of the biocorrosion susceptibility of mild steel coated with Zn and Zn-CaCO3 in a biodiesel environment by Vivi A. Fardilah, Ilham Alkian, Yustina M. Pusparizkita, Cristian Aslan, Mohammad Tauviqirrahman, J. Jamari, Athanasius P. Bayuseno

“…The AFM parametric values of root mean square roughness (Rq), average roughness (Ra), and maximum peak-to-valley height (Rpv) for the surface of steel-coated Zn and Zn binary composites are higher than those of uncoated carbon steel substrates, signifying potential biodiesel corrosion protection. …”
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Plasma-assisted molecular beam epitaxy growth of high-density nitrogen-doped Ga2O3 thin films on Ga2O3 (010) substrates by simultaneously supplying oxygen and nitrogen radicals by Kura Nakaoka, Shoki Taniguchi, Tomoki Uehara, Jin Inajima, Kohki Tsujimoto, Yusuke Teramura, Satoko Honda, YongGu Shim, Masataka Higashiwaki

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Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning by Muhammad Salman Khan, Tianbo Peng, Tianbo Peng, Muhammad Adeel Khan, Asad Khan, Mahmood Ahmad, Mahmood Ahmad, Kamran Aziz, Mohanad Muayad Sabri Sabri, N. S. Abd EL-Gawaad

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Extreme high accuracy prediction and design of Fe-C-Cr-Mn-Si steel using machine learning by Hao Wu, Jianyuan Zhang, Jintao Zhang, Chengjie Ge, Lu Ren, Xinkun Suo

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The role of electrodeposition conditions in creating MnO2-based flexible non-enzymatic glucose sensors by Ivan S. Filimonenkov, Anna I. Mokhova, Didar Zh. Kurzhumbaev, Sergey A. Urvanov

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Strategies for effective waste management in hydropower construction projects by Hishila Sujakhu, Warangkana Jutidamrongphan

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Hysteresis feedforward and fuzzy PID feedback compound control of piezoelectric ceramics by Qian Lu, Mengmeng Bai, Dongming Lv, Chao Ma, Bowen Zhao, Chengyang Wang

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Phase-field simulation study of dendritic growth in directional solidification of Fe-C alloy under varied initial solute concentrations by Hong-bo Zeng, Xin-gang Ai, Ming Chen, Rui Guan, Qing-song Chen, Zhong-lin Hou

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Exploring the fresh and rheology properties of 3D printed concrete with fiber reinforced composites (3DP-FRC): a novel approach using machine learning techniques by Risul Islam Rasel, Md Minaz Hossain, Md Hasib Zubayer, Chaoqun Zhang

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Auditor general of South Africa (AGSA) as an oversight body in local government sphere by Xolani Thusi, Mandisi Matyana

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Overview on natural dyes and their IR-spectra – Part I: Plant based dyes with naphthoquinone and anthraquinone structure by Boris Mahltig

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Overview on natural dyes and their IR-spectra – Part I: Plant based dyes with naphthoquinone and anthraquinone structure by Boris Mahltig

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Efficiently charting the space of mixed vacancy-ordered perovskites by machine-learning encoded atomic-site information by Fan Zhang, Li Fu, Weiwei Gao, Peihong Zhang, Jijun Zhao

“…This approach accurately predicts band gaps and formation energies for mixed VODPs, achieving Root Mean Square Errors of 21 meV and 3.9 meV/atom, respectively. …”
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Enhancing Marshall stability of asphalt concrete using a hybrid deep neural network and ensemble learning by Henok Desalegn Shikur, Ming-Der Yang, Yared Bitew Kebede

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Performance assessment and optimization of Ti6Al4V helical hole milling process by Gururaj Bolar, Vikas Marakini, Raviraj Shetty, Sawan Shetty, Adithya Hegde

“…Using Analysis of Variance (ANOVA), the effects of helical milling parameters such as axial feed, cutting speed, and tangential feed on surface roughness (SR), cutting forces such as thrust force (TF) and radial force (RF), and machining temperature (MT) were investigated. Metrics like R ^2 , root mean square error (RMSE), and error percentage were used to assess the predictive models that were developed using Response Surface Methodology (RSM) and Back Propagation Artificial Neural Networks (BPANN). …”
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Hydrogen embrittlement of ferrite-pearlite OCTG steels under electrochemical and gaseous hydrogen environment by Dong-Kyu Oh, Byoungchul Hwang

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Static shear performance of small diameter short stud connectors embedded in UHPC by Wenhao Chai, Xu Hou, Yuncheng Feng, Jin Di, Fengjiang Qin, Jie Wang

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