Predicting glaucoma progression using deep learning framework guided by generative algorithm by Hussain, Shaista, Chua, Jacqueline, Wong, Damon, Lo, Justin, Kadziauskiene, Aiste, Asoklis, Rimvydas, Barbastathis, George, Schmetterer, Leopold, Yong, Liu

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Energy transfer driven brightening of MoS2 by ultrafast polariton relaxation in microcavity MoS2/hBN/WS2 heterostructures by Hu, Zehua, Krisnanda, Tanjung, Fieramosca, Antonio, Zhao, Jiaxin, Sun, Qianlu, Chen, Yuzhong, Liu, Haiyun, Luo, Yuan, Su, Rui, Wang, Junyong, Watanabe, Kenji, Taniguchi, Takashi, Eda, Goki, Wang, Renshaw Xiao, Ghosh, Sanjib, Dini, Kevin, Sanvitto, Daniele, Liew, Timothy Chi Hin, Xiong, Qihua

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High-quality semiconductor fibres via mechanical design by Wang, Zhixun, Wang, Zhe, Li, Dong, Yang, Chunlei, Zhang, Qichong, Chen, Ming, Gao, Huajian, Wei, Lei

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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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Yeast9: a consensus genome-scale metabolic model for S. cerevisiae curated by the community by Zhang, Chengyu, Sánchez, Benjamín J., Li, Feiran, Cheng, Eiden Wei Quan, Scott, William T., Liebal, Ulf W., Blank, Lars M., Mengers, Hendrik G., Anton, Mihail, Rangel, Albert Tafur, Mendoza, Sebastián N., Zhang, Lixin, Nielsen, Jens, Lu, Hongzhong, Kerkhoven, Eduard J.

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Modeling and optimization of photovoltaic systems under partially shaded and rapidly changing conditions by Jiang, Lian Lian

“…Since the existing methods show either low accuracy in derived parameters of the PV array or too much complexity in their calculation, in Chapter 3, we proposed a Chebyshev functional link neural network (CFLNN) to model the PV module. …”
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Cell-free hemoglobin mediated oxidative stress is associated with acute kidney injury and renal replacement therapy in severe falciparum malaria: an observational study by Plewes, Katherine, Kingston, Hugh W.F., Ghose, Aniruddha, Maude, Richard J., Herdman, M. Trent, Leopold, Stije J., Ishioka, Haruhiko, Hasan, Md. Mahtab Uddin, Haider, Md. Shafiul, Alam, Shamsul, Piera, Kim A., Charunwatthana, Prakaykaew, Silamut, Kamolrat, Yeo, Tsin Wen, Faiz, Md. Abul, Lee, Sue J., Mukaka, Mavuto, Turner, Gareth D. H., Anstey, Nicholas M., Jackson Roberts II, L., White, Nicholas J., Day, Nicholas P. J., Hossain, Md. Amir, Dondorp, Arjen M.

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Physiological stress responses and meat quality of rabbits subjected to different road transportation and slaughter methods by Khadijah, Nakyinsige

“…This study describes the link between physiological stress responses to transport and slaughter to meat quality using rabbit as a model. …”
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Effects of nnav1.5 expression modulation on mhc I antigen processing machinery and invasion potential of breast cancer cells by Din, Ahmad Hafiz Murtadha Noor

“…Loss of immune surveillance enables cancer cells to metastasize hence this study is to explore the possible role of nNav1.5 in regulating the expression of immune components, MHC I antigen processing machinery (APM), which is deregulated in breast cancer. Several reports link VGSC and APM in neurons, but the correlation between nNav1.5 and APM in breast cancer is unknown. …”
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The IDentif.AI-x pandemic readiness platform: rapid prioritization of optimized COVID-19 combination therapy regimens by Blasiak, Agata, Truong, Anh T. L., Remus, Alexandria, Hooi, Lissa, Seah, Shirley Gek Kheng, Wang, Peter, Chye, De Hoe, Lim, Angeline Pei Chiew, Ng, Kim Tien, Teo, Swee Teng, Tan, Yee-Joo, Allen, David Michael, Chai, Louis Yi Ann, Chng, Wee Joo, Lin, Raymond T. P., Lye, David C., Wong, John Eu-Li, Tan, Gladys Gek-Yen, Chan, Conrad En Zuo, Chow, Edward Kai-Hua, Ho, Dean

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Scope, characteristics, behavior change techniques, and quality of conversational agents for mental health and well-being: systematic assessment of apps by Lin, Xiaowen, Martinengo, Laura, Jabir, Ahmad Ishqi, Ho, Andy Hau Yan, Car, Josip, Atun, Rifat, Tudor Car, Lorainne

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Employment of a high throughput functional assay to define the critical factors that influence vaccine induced cross-variant neutralizing antibodies for SARS-CoV-2 by Gu, Yue, Shunmuganathan, Bhuvaneshwari, Qian, Xinlei, Gupta, Rashi, Tan, Rebecca S. W., Kozma, Mary, Purushotorman, Kiren, Murali, Tanusya M., Tan, Nikki Y. J., Preiser, Peter Rainer, Lescar, Julien, Nasir, Haziq, Somani, Jyoti, Tambyah, Paul A., Smith, Kenneth G. C., Renia, Laurent, Ng, Lisa F. P., Lye, David C., Young, Barnaby E., MacAry, Paul A.

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Ultrastrong exciton-plasmon couplings in WS2 multilayers synthesized with a random multi-singular metasurface at room temperature by Wu, Tingting, Wang, Chongwu, Hu, Guangwei, Wang, Zhixun, Zhao, Jiaxin, Wang, Zhe, Chaykun, Ksenia, Liu, Lin, Chen, Mengxiao, Li, Dong, Zhu, Song, Xiong, Qihua, Shen, Zexiang, Gao, Huajian, Garcia-Vidal, Francisco J., Wei, Lei, Wang, Qi Jie, Luo, Yu

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Correlates of lifestyle patterns among children in Singapore aged 10 years: the growing up in Singapore towards healthy outcomes (GUSTO) study by Tan, Sarah Yi Xuan, Chia, Airu, Tai, Bee Choo, Toh, Jia Ying, Colega, Marjorelee, Padmapriya, Natarajan, Setoh, Peipei, Kee, Michelle Zhi Ling, Yuan, Wen Lun, Lee, Yung Seng, Loo, Benny Kai Guo, Yap, Fabian Kok Peng, Tan, Kok Hian, Godfrey, Keith M., Chong, Yap Seng, Eriksson, Johan, Müller-Riemenschneider, Falk, Chong, Mary Foong-Fong

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Artificial neural networks solutions for solving differential equations: A focus and example for flow of viscoelastic fluid with microrotation by Abdullah, null, Faye, Ibrahima, Laila Amera, Aziz

“…Additionally, investigating new application domains like linked multi-physics issues or real-time simulation situations may help to increase the reach and significance of PINN approaches.…”
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Understanding the role of Enterococcus faecalis in polymicrobial wounds by Davient, Bala

“…Since E. faecalis T7SS encodes toxins involved in bacterial competition, but not the MPT and EET systems, I hypothesized that a link between the energy metabolism systems and the T7SS may exist. …”
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Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes by McAllan, Liam, Baranasic, Damir, Villicaña, Sergio, Brown, Scarlett, Zhang, Weihua, Lehne, Benjamin, Adamo, Marco, Jenkinson, Andrew, Elkalaawy, Mohamed, Mohammadi, Borzoueh, Hashemi, Majid, Fernandes, Nadia, Lambie, Nathalie, Williams, Richard, Christiansen, Colette, Yang, Youwen, Zudina, Liudmila, Lagou, Vasiliki, Tan, Sili, Castillo-Fernandez, Juan, King, James W. D., Soong, Richie, Elliott, Paul, Scott, James, Prokopenko, Inga, Cebola, Inês, Loh, Marie, Lenhard, Boris, Batterham, Rachel L., Bell, Jordana T., Chambers, John Campbell, Kooner, Jaspal S., Scott, William R.

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An omics-based machine learning approach to predict diabetes progression: a RHAPSODY study by Slieker, Roderick C., Münch, Magnus, Donnelly, Louise A., Bouland, Gerard A., Dragan, Iulian, Kuznetsov, Dmitry, Elders, Petra J. M., Rutter, Guy A., Ibberson, Mark, Pearson, Ewan R., Hart, Leen M. 't, van de Wiel, Mark A., Beulens, Joline W. J.

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Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk by Zhu, Yinghan, Maikusa, Norihide, Radua, Joaquim, Sämann, Philipp G., Fusar-Poli, Paolo, Agartz, Ingrid, Andreassen, Ole A., Bachman, Peter, Baeza, Inmaculada, Chen, Xiaogang, Choi, Sunah, Corcoran, Cheryl M., Ebdrup, Bjørn H., Fortea, Adriana, Garani, Ranjini Rg, Glenthøj, Birte Yding, Glenthøj, Louise Birkedal, Haas, Shalaila S., Hamilton, Holly K., Hayes, Rebecca A., He, Ying, Heekeren, Karsten, Kasai, Kiyoto, Katagiri, Naoyuki, Kim, Minah, Kristensen, Tina D., Kwon, Jun Soo, Lawrie, Stephen M., Lebedeva, Irina, Lee, Jimmy, Loewy, Rachel L., Mathalon, Daniel H., McGuire, Philip, Mizrahi, Romina, Mizuno, Masafumi, Møller, Paul, Nemoto, Takahiro, Nordholm, Dorte, Omelchenko, Maria A., Raghava, Jayachandra M., Røssberg, Jan I., Rössler, Wulf, Salisbury, Dean F., Sasabayashi, Daiki, Smigielski, Lukasz, Sugranyes, Gisela, Takahashi, Tsutomu, Tamnes, Christian K., Tang, Jinsong, Theodoridou, Anastasia, Tomyshev, Alexander S., Uhlhaas, Peter J., Værnes, Tor G., van Amelsvoort, Therese A. M. J., Waltz, James A., Westlye, Lars T., Zhou, Juan H., Thompson, Paul M., Hernaus, Dennis, Jalbrzikowski, Maria, Koike, Shinsuke

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The effects of atmosphere-ocean-wave coupling during tropical cyclone by Garg, Nikhil

“…This transfer of momentum (from atmosphere to ocean) is not a one-way link, i.e., there are feedback effects from ocean (both in terms of enthalpy and momentum) on the atmospheric boundary layer. …”
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