Northern gene flow into southeastern East Asians inferred from genome-wide array genotyping by He, Guang-Lin, Li, Ying-Xiang, Zou, Xing, Yeh, Hui-Yuan, Tang, Ren-Kuan, Wang, Pei-Xin, Bai, Jing-Ya, Yang, Xiao-Min, Wang, Zheng, Guo, Jian-Xin, Chen, Jin-Wen, Chen, Jing, Yang, Mei-Qing, Zhao, Jing, Sun, Jin, Zhu, Kong-Yang, Ma, Hao, Wang, Rui, Yang, Wen-Jiao, Hu, Rong, Wei, Lan-Hai, Hou, Yi-Ping, Wang, Meng-Ge, Chen, Gang, Wang, Chuan-Chao

“…The southeastern Han Chinese could be modeled with the primary ancestry deriving from the group related to the Yellow River Basin millet farmers and the remaining from groups related to rice farmers, which was consistent with the northern China origin of modern southeastern Han Chinese and in line with the historically and archaeologically attested southward migrations of Han people and their ancestors. …”
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Ultrahigh electromechanical response from competing ferroic orders by Lin, Baichen, Ong, Khuong Phuong, Yang, Tiannan, Zeng, Qibin, Hui, Hui Kim, Ye, Zhen, Sim, Celine, Yen, Zhihao, Yang, Ping, Dou, Yanxin, Li, Xiaolong, Gao, Xingyu, Tan, Ivan Chee Kiang, Lim, Zhi Shiuh, Zeng, Shengwei, Luo, Tiancheng, Xu, Jinlong, Tong, Xin, Li, Patrick Wen Feng, Ren, Minqin, Zeng, Kaiyang, Sun, Chengliang, Ramakrishna, Seeram, Breese, Mark B. H., Boothroyd, Chris, Lee, Chengkuo, Singh, David J., Lam, Yeng Ming, Liu, Huajun

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Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation by Li, Guoliang, Ruan, Xiaoan, Auerbach, Raymond K., Sandhu, Kuljeet Singh, Zheng, Meizhen, Wang, Ping, Poh, Huay Mei, Goh, Yufen, Lim, Joanne, Zhang, Jingyao, Sim, Hui Shan, Peh, Su Qin, Mulawadi, Fabianus Hendriyan, Ong, Chin Thing, Orlov, Yuriy L., Hong, Shuzhen, Zhang, Zhizhuo, Landt, Steve, Raha, Debasish, Euskirchen, Ghia, Wei, Chia-Lin, Ge, Weihong, Wang, Huaien, Davis, Carrie, Fisher-Aylor, Katherine I., Mortazavi, Ali, Gerstein, Mark, Gingeras, Thomas, Wold, Barbara, Sun, Yi, Cheung, Edwin, Liu, Edison, Sung, Wing-Kin, Snyder, Michael, Ruan, Yijun, Fullwood, Melissa Jane

“…Comparative analyses of different cell lines showed that cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription, and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions. …”
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Dynamic altruistic cooperation within breast tumors by Muhammad Sufyan Bin Masroni, Lee, Kee Wah, Lee, Victor Kwan Min, Ng, Siok Bian, Law, Chao Teng, Poon, Kok Siong, Lee, Bernett Teck Kwong, Liu, Zhehao, Tan, Yuen Peng, Chng, Wee Ling, Tucker, Steven, Ngo, Lynette Su-Mien, Yip, George Wai Cheong, Nga, Min En, Hue, Susan Swee Shan, Putti, Thomas Choudary, Bay, Boon Huat, Lin, Qingsong, Zhou, Lihan, Hartman, Mikael, Loh, Tze Ping, Lakshmanan, Manikandan, Lee, Sook Yee, Tergaonkar, Vinay, Chua, Huiwen, Lee, Adeline Voon Hui, Yeo, Eric Yew Meng, Li, Mo-Huang, Chang, Chan Fong, Kee, Zizheng, Tan, Karen Mei-Ling, Tan, Soo Yong, Koay, Evelyn Siew-Chuan, Archetti, Marco, Leong, Sai Mun

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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

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Modelling of traffic control delays at priority junctions using artificial neural network by Mohammad Ali Sahraei

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Software defined network : user centric network by Lim, Derrick Teck Leong.

“…A test of the application was done by running two continuous pings, one from each host to the other. Then, the path in use was disconnected. …”
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Artificial neural network-salp-swarm algorithm for stock price prediction by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan, Abdul Aziz

“…Additionally, the SSA-ANN model is compared with other two hybrid models: the ANN optimized by the Whale Optimization Algorithm (WOA-ANN) and Moth-Flame Optimizer (MOA-ANN), as well as a single model, namely the Autoregressive Integrated Moving Average (ARIMA). …”
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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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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

“…The average error for the ANN-GA model was 1.03%, significantly less than the 1.82% average error found with the RSM model. …”
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Towards Synergistic Understanding of Language Processing in Biological and Artificial Systems by Hosseini Asl, Eghbal

“…How does the amount of training data affect convergence between the human brain and ANN language models? 3. What computational mechanisms could underlie similarities in language processing between human brains and ANN language models? …”
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Data-driven power system stability assessment by Kang, Hongyu

“…Through experiments and data results visualization, the accuracy of DT is obtained as 0.9953, SVM as 0.9967 and ANN as 0.9968. Meanwhile, the ROC and AUC curves of ANN and SVM are close to the upper-left intersection, which proves that the model achievement is good. …”
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Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

“…The LSB_ANN has a unique weight update mechanism which employs network layer input-output sensitivity analysis. …”
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Modeling distance-dependent individual head-related transfer functions in the horizontal plane using frontal projection headphones by Sunder, Kaushik, Gan, Woon-Seng, Tan, Ee-Leng

“…Soc. 61, 989–1000] project the sound directly onto the pinnae from the front, and thus inherently create listener's idiosyncratic pinna cues at the eardrum. …”
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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

“…The imputation performance ranking is as follows: ANN, SVR, MR, and k-NN.…”
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Selecting correct methods to extract fuzzy rules from artificial neural network by Tan, Xiao, Zhou, Yuan, Ding, Zuohua, Liu, Yang

“…Artificial neural network (ANN) inherently cannot explain in a comprehensible form how a given decision or output is generated, which limits its extensive use. …”
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Genetic algorithm LQG and neural network controllers for gust response alleviation of flying wing unmanned aerial vehicles by Ang, Elijah Hao Wei, Ng, Bing Feng

“…In this paper, a genetic algorithm linear quadratic Gaussian controller (GA-LQG) and an artificial neural network (ANN) controller are implemented for gust response alleviation of lightweight flying wings undergoing body-freedom oscillations. …”
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Hybrid finite element and machine learning approach for covered linkway sheltering factor assessment by Tok, Wei Sheng

“…An Artificial Neural Network (ANN) model is implemented to predict penetration outcomes of UAV impacts, while an ANN-Convolutional Neural Network (CNN) model is used to predict FEA deformation images resulting from these impacts. …”
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Future reservoir performance projection using integrated models in the framework of climate change by Hamidon, Nuramidah

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Investigation of logarithmic signatures for feature extraction and application to marine engine fault diagnosis by Patil, C, Theotokatos, G, Wu, Y, Lyons, T

“…A parametric study is performed to quantify the logS number impact on the ANN regression models accuracy and training time. …”