A Digital Phenotypic Assessment in Neuro-Oncology (DANO): A Pilot Study on Sociability Changes in Patients Undergoing Treatment for Brain Malignancies by Siddi, Francesca, Emedom-Nnamdi, Patrick, Catalino, Michael P., Rana, Aakanksha, Boaro, Alessandro, Dawood, Hassan Y., Sala, Francesco, Onnela, Jukka-Pekka, Smith, Timothy R.

“…Abstract Background: The digital phenotyping tool has great potential for the deep characterization of neurological and quality-of-life assessments in brain tumor patients. …”
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Self-reported weight changes in 1st year university students in England: an analysis of social and physical environment by Vadeboncoeur, C

“…Past research suggest the WC is closer to an average of 2kg and is due to physical inactivity, stress and poor diet. The socio-ecological model (SEM) offers a conceptual framework, reflecting many levels of influence to describe health behaviours in specific settings and is relevant to this context. …”

Geobarrier system for use in underground structure by Leong, Eng Choon, Zhai, Qian, Tan, Sze Tiong, Wang, Chien Looi, Lim, Vincent Han, Kew, Jernice Huiling, Seow, Wei Kiong, Wong, Johnny Liang Heng, Rahardjo, Harianto, Satyanaga, Alfrendo, Gofar, Nurly, Mohamed, Haneena

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Activated Sludge : Developments and Sustainable Solutions / by Gray, Nicholas F., author 370661, World Scientific (Online service) 655444

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Sociospatial reframing of walking through inclusive streets and urban heritage by Wang, Yongcheng

“…The meta-narrative review identified six research traditions, namely the ecological model, the new mobilities paradigm, heritage discourse, public life, rhythmanalysis and space syntax. …”
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Removal of ciprofloxacin by anaerobic membrane bioreactor (AnMBR) and post-treatment of AnMBR effluent by Mai, Do Thi

“…CIP is also one of the antibiotics that poses a high ecological risk, and genotoxicity and the transfer of resistance between different bacterial species were induced at concentrations as low as a few µg/L. …”
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Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures by Belov, Vladimir, Erwin-Grabner, Tracy, Aghajani, Moji, Aleman, Andre, Amod, Alyssa R., Basgoze, Zeynep, Benedetti, Francesco, Besteher, Bianca, Bülow, Robin, Ching, Christopher R. K., Connolly, Colm G., Cullen, Kathryn, Davey, Christopher G., Dima, Danai, Dols, Annemiek, Evans, Jennifer W., Fu, Cynthia H. Y., Gonul, Ali Saffet, Gotlib, Ian H., Grabe, Hans J., Groenewold, Nynke, Hamilton, J. Paul, Harrison, Ben J., Ho, Tiffany C., Mwangi, Benson, Jaworska, Natalia, Jahanshad, Neda, Klimes-Dougan, Bonnie, Koopowitz, Sheri-Michelle, Lancaster, Thomas, Li, Meng, Linden, David E. J., MacMaster, Frank P., Mehler, David M. A., Melloni, Elisa, Mueller, Bryon A., Ojha, Amar, Oudega, Mardien L., Penninx, Brenda W. J. H., Poletti, Sara, Pomarol-Clotet, Edith, Portella, Maria J., Pozzi, Elena, Reneman, Liesbeth, Sacchet, Matthew D., Sämann, Philipp G., Schrantee, Anouk, Sim, Kang, Soares, Jair C., Stein, Dan J., Thomopoulos, Sophia I., Uyar-Demir, Aslihan, van der Wee, Nic J. A., van der Werff, Steven J. A., Völzke, Henry, Whittle, Sarah, Wittfeld, Katharina, Wright, Margaret J., Wu, Mon-Ju, Yang, Tony T., Zarate, Carlos, Veltman, Dick J., Schmaal, Lianne, Thompson, Paul M., Goya-Maldonado, Roberto

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