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

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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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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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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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USE OF BIOSTIMULATING SALIX SOLUTIONS FOR THE VEGETATIVE PROPAGATION OF CHRYSANTHEMUM: A REVIEW by Ana COJOCARIU, Alina Elena CRÎŞMARU, Cristiana Virginia PETRE

“…Preserving and maintaining the desired plants traits are essential and thus, vegetative reproduction via cuttings is usually the preferred way to obtain high quality material. Today, there are plenty of commercially available synthetic products that promise better and faster rooting and development of cuttings, but in most cases the price is very high and the environmental impact, due to their chemical composition, is another thing that must be taken into consideration. …”
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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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Evaluation of the psychometric properties of the Copenhagen burnout inventory–student survey (CBI-SS) among health profession educational students at a university in south India by Pushpanjali Krishnappa, Medha A. Joshi, Aileen J Abraham, Avinash Prabhu, Anam Tasneem

“…The CFA fit indices included the degree of freedom, Tucker Lewis index (TLI), freedom ratio (χ²/df), Goodness-of-Fit Index (GFI), Comparative Fit Index (CFI), Root Mean Square Error Of Approximation (RMSEA), and Normed Fit Index (NFI). …”
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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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