AI is a viable alternative to high throughput screening: a 318-target study by Wallach, Izhar, Bernard, Denzil, Nguyen, Kong, Ho, Gregory, Morrison, Adrian, Stecula, Adrian, Rosnik, Andreana, O’Sullivan, Ann Marie, Davtyan, Aram, Samudio, Ben, Thomas, Bill, Worley, Brad, Butler, Brittany, Laggner, Christian, Thayer, Desiree, Moharreri, Ehsan, Friedland, Greg, Truong, Ha, van den Bedem, Henry, Ng, Ho Leung, Stafford, Kate, Sarangapani, Krishna, Giesler, Kyle, Ngo, Lien, Mysinger, Michael, Ahmed, Mostafa, Anthis, Nicholas J., Henriksen, Niel, Gniewek, Pawel, Eckert, Sam, de Oliveira, Saulo, Suterwala, Shabbir, PrasadPrasad, Srimukh Veccham Krishna, Shek, Stefani, Contreras, Stephanie, Hare, Stephanie, Palazzo, Teresa, O’Brien, Terrence E., Van Grack, Tessa, Williams, Tiffany, Chern, Ting-Rong, Kenyon, Victor, Lee, Andreia H., Cann, Andrew B., Bergman, Bastiaan, Anderson, Brandon M., Cox, Bryan D., Warrington, Jeffrey M., Sorenson, Jon M., Goldenberg, Joshua M., Young, Matthew A., DeHaan, Nicholas, Pemberton, Ryan P., Schroedl, Stefan, Abramyan, Tigran M., Gupta, Tushita, Mysore, Venkatesh, Presser, Adam G., Ferrando, Adolfo A., Andricopulo, Adriano D., Ghosh, Agnidipta, Ayachi, Aicha Gharbi, Mushtaq, Aisha, Shaqra, Ala M., Toh, Alan Kie Leong, Smrcka, Alan V., Ciccia, Alberto, de Oliveira, Aldo Sena, Sverzhinsky, Aleksandr, de Sousa, Alessandra Mara, Agoulnik, Alexander I., Kushnir, Alexander, Freiberg, Alexander N., Statsyuk, Alexander V., Gingras, Alexandre R., Degterev, Alexei, Tomilov, Alexey, Vrielink, Alice, Garaeva, Alisa A., Bryant-Friedrich, Amanda, Caflisch, Amedeo, Patel, Amit K., Rangarajan, Amith Vikram, Matheeussen, An, Battistoni, Andrea, Caporali, Andrea, Chini, Andrea, Ilari, Andrea, Mattevi, Andrea, Foote, Andrea Talbot, Trabocchi, Andrea, Stahl, Andreas, Herr, Andrew B., Berti, Andrew, Freywald, Andrew, Reidenbach, Andrew G., Lam, Andrew, Cuddihy, Andrew R., White, Andrew, Taglialatela, Angelo

“…Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. …”
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Learning stock market dynamics using the kinetic ising model by Nguyen, Ai Linh

“…In this approach, the states in the time series data are represented by configurations of N spins, and the time evolution of these states in the time series data by an update rule that depends on the spin configuration {σ_i (t)}_(i=1,…,N), and the connection weights {W_ij }_(i,j=1,…N) between the spins. …”
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A comparative analysis of missing data imputation techniques on sedimentation data by Loh, Wing Son, Ling, Lloyd, Chin, Ren Jie, Lai, Sai Hin, Loo, Kar Kuan, Seah, Choon Sen

“…A comparative analysis on the missing fine sediment data imputation performance was made based on four different techniques, namely the k-Nearest Neighbourhood (k-NN), Support Vector Regression (SVR), Multiple Regression (MR), and Artificial Neural Network (ANN), under the single imputation (SI) and multiple imputation (MI) regimes. …”
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Experimental Characterization of Iron-Sulfur Cluster Excited States and their Relevance to Electron Transfer Reactions by Skeel, Brighton A.

“…We find that the energy scale associated with both of these phenomena is commensurate with that of the thermal energy at ambient temperature, and that these alternate valence arrangements and spin configurations are thus relevant to understanding the room temperature reactivity of biological Fe−S systems. …”
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Compositional dependence of spintronic properties in Pt/GdCo films by Suzuki, Daniel H, Lee, Byung Hun, Beach, Geoffrey SD

“…We find a 5× increase in effective spin Hall angle with increasing Gd concentration, suggesting an improvement in spin transfer efficiency in rare earth materials. …”
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Narrowband Searches for Continuous and Long-duration Transient Gravitational Waves from Known Pulsars in the LIGO-Virgo Third Observing Run by Sudhir, Vivishek

“…Isolated neutron stars that are asymmetric with respect to their spin axis are possible sources of detectable continuous gravitational waves. …”
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Quantum Monte Carlo study of the phase diagram of the two-dimensional uniform electron liquid by Azadi, S, Drummond, ND, Vinko, SM

“…We present a study of spin-unpolarized and spin-polarized two-dimensional uniform electron liquids using variational and diffusion quantum Monte Carlo (VMC and DMC) methods with SlaterJastrow-backflow trial wave functions. …”

Design and investigation of air-cooled heat sinks using 3D printing technology by Lim, Ming Chong

“…This study presents the heat transfer performance of five pin fin heat sinks that have been fabricated using Selective Laser Melting. …”
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Home by Pei, Qianru

“…This project is a self-exploitary journey to find out where is home for me and people like me. …”
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Synthesis, structure, and magnetic properties of extended 2-D triangular lattices by Bartlett, Bart M

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Artificial neural network-salp-swarm algorithm for stock price prediction by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan, Abdul Aziz

“…The study’s findings indicate that the SSA-ANN model performs better in predicting the dataset based on the evaluation criteria used.…”
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Spectroscopic study of emergent electronic phases in transition metal based compounds by Song, Qian

“…Our findings represent the first observation of a p-wave antiferromagnet, and open a new frontier of voltage-based switching of non-relativistic spin splitting in vdW antiferromagnets.…”
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Real time analysis of social behavior from video and kinect recordings by Ramasamy, Pandi Ramesh

“…Finally,analysis will be performed using pattern recognition algorithms and machine learning classifiers to detect the emotion of the subject.In this project,machine learning classifiers such as K-nearest neighbors,Naive Bayes and C4.5 Decision tree learning has been used. The prime aim is to pin point the most seemly machine learning classifier for obtaining highest accuracy for classification.…”
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Low-cost machine learning prediction of excited state properties of iridium-centered phosphors by Terrones, Gianmarco G, Duan, Chenru, Nandy, Aditya, Kulik, Heather J

“…Using artificial neural network (ANN) models, we predict the mean emission energy of phosphorescence, the excited state lifetime, and the emission spectral integral for iridium complexes with accuracy competitive with or superseding that of TDDFT. …”
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Dynamics of housing markets by Tay, Darrell Jiajie

“…While reviewing previous works on housing bubbles, we find that housing bubbles are often poorly defined. …”
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Modeling the evolution of a primitive supply chain. by Tay, Darrell Jiajie.

“…By allowing the system to evolve in a way postulated by the Reformulated 2nd Law of Thermodynamics (Schneider and Kay, 1994), we inspected the end state energy of the primitive supply chain for different types of evolution. We find that contrary to mature supply chains, primitive supply chains is less affected by information sharing due to a high level of symmetric information shared. …”
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Prediction of rainfall-runoff processes through black-box techniques by Lee, Liang Cen

“…Levenberg-Marquardt Backpropagation (LMBP) was used as training algorithm in ANN model. In order to generate an optimum prediction, different numbers and combinations of data were used as inputs to maximize the efficiency of ANN model. …”
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A meta-analysis of functional neuroimaging studies of dyslexia in alphabetic words and chinese characters. by Kwok, Fu Yu.

“…Results from the Chinese language meta-analysis study replicates the results from previous empirical studies showing low activation primarily in areas such as the left middle frontal gyrus and the right middle occipital gyrus (Liu et al., 2012; Siok, Niu, Jin, Perfetti, & Tan, 2008; Siok, Perfetti, Jin, & Tan, 2004; Siok, Spink, Jin & Tan, 2009; Yang, 2005). In addition, functional neuroimaging single studies examining the effect of dyslexia in both alphabetical languages and Chinese language have shown that there are differences in the brain activations between these languages (Paulesu et al., 2001; Richlan et al., 2010; Siok et al., 2004). …”
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Organic donor-acceptor cocrystals for multiferroic applications by Wang, Zongrui, Zhang, Qichun

“…The cocrystallization strategy has provided an efficient route to fulfill room temperature magnetoelectricity in single phase owing to the long-range ordered π-π stacking (donor-acceptor assembled) network, long-lived excitons (with μs lifetime), spin orders (±1/2 s pin) and charge transfer (CT) dipoles in the assembled crystal lattice. …”
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Predictive modeling and optimization of noise emissions in a palm oil methyl ester-fueled diesel engine using response surface methodology and artificial neural network integrated... by Muhammad Zikri, Japri, Mohd Shahrir, Mohd Sani, Mohd Fadzil Faisae, Ab Rashid, Muriban, Jackly, Galang Sandy, Prayogo

“…These findings endorse the feasibility of applying ANN-GA in scenarios where precise noise prediction is crucial, particularly in relation to alternative fuels like POME.…”
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