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Machine Learning Enables Highly Accurate Predictions of Photophysical Properties of Organic Fluorescent Materials: Emission Wavelengths and Quantum Yields
Toward a Generalized Treatment of the Solvent Effect Based on Four Empirical Scales: Dipolarity (SdP, a New Scale), Polarizability (SP), Acidity (SA), and Basicity (SB) of the Medium
A comparative study of conventional FRET and light harvesting properties of Rh-110/Rh-6G and Rh-19/Rh-B organic dye pairs impregnated in sol-gel glasses
Modeling and Predicting the Cell Migration Properties from Scratch Wound Healing Assay on Cisplatin-Resistant Ovarian Cancer Cell Lines Using Artificial Neural Network
Determining the Shear Capacity of Steel Beams with Corrugated Webs by Using Optimised Regression Learner Techniques
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