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URI: http://hdl.handle.net/2144/16844

The Boston University Open Access Articles collection contains scholarly publications written by Boston University faculty. This collection primarily consists of scholarly journal articles and published conference proceedings but open access book chapters, reviews, white papers, conference abstracts, and technical reports are also included. These publications are made available in OpenBU, Boston University’s Open Access Institutional Repository under the provisions of the Boston University Open Access Policy or by other arrangement. Note: Some works in this collection are not currently in open access, and are embargoed at the author's request.

Publications in Boston University’s Open Access collection are primarily one of three versions:

  • First Author Draft. This is the author's manuscript prior to formal peer review.
  • Accepted Manuscript. This is the version that exists after peer review, but before final copy editing and publisher formatting. Note: This is NOT publisher proofs.
  • Published Version. This is the final version that appeared in a formal publication such as a peer-reviewed journal, book, or published conference proceeding.

Citations are always given to the final published version, which may differ from the version made available in the repository. Wherever possible, a link or DOI to the final version is provided.

For more information please see the FAQ about Open Access at BU or contact Digital Scholarship Services at disc@bu.edu.

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  • Mapping the groundwater potentiality of West Qena area, Egypt, using integrated remote sensing and hydro-geophysical techniques 

    Gaber, Ahmed; Mohamed, Adel Kamel; ElGalladi, Ahmed; Abdelkareem, Mohamed; Beshr, Ahmed M.; Koch, Magaly (MDPI AG, 2020-05-14)
    The integrated use of remote sensing imagery and hydro-geophysical field surveys is a well-established approach to map the hydrogeological framework, and thus explore and evaluate the groundwater potentiality of desert ...
  • Neuroimaging markers for studying Gulf-War illness: single-subject level analytical method based on machine learning 

    Guan, Yi; Cheng, Chia-Hsin; Chen, Weifan; Zhang, Yingqi; Koo, Sophia; Krengel, Maxine; Janulewicz, Patricia; Toomey, Rosemary; Yang, Ehwa; Bhadelia, Rafeeque; Steele, Lea; Kim, Jae-Hun; Sullivan, Kimberly; Koo, Bang-Bon (2020-11-20)
    Gulf War illness (GWI) refers to the multitude of chronic health symptoms, spanning from fatigue, musculoskeletal pain, and neurological complaints to respiratory, gastrointestinal, and dermatologic symptoms experienced ...
  • Genetic underpinnings of increased BMI and its association with late midlife cognitive abilities 

    Xian, Hong; Boutwell, Brian; Reynolds, Chandra A.; Lew, Daphne; Logue, Mark; Gustavson, Daniel E.; Kavish, Nicholas; Panizzon, Matthew S.; Tu, Xin; Toomey, Rosemary; Puckett, Olivia K.; Elman, Jeremy A.; Jacobson, Kristen C.; Lyons, Michael J.; Kremen, William S.; Franz, Carol E. (2020-01)
    OBJECTIVES: First, we test for differences in various cognitive abilities across trajectories of body mass index (BMI) over the later life course. Second, we examine whether genetic risk factors for unhealthy BMIs-assessed ...
  • Temporal variability in implicit online learning 

    Campolongo, Nicolò; Orabona, Francesco (2020-12-06)
    In the setting of online learning, Implicit algorithms turn out to be highly suc-cessful from a practical standpoint. However, the tightest regret analyses onlyshow marginal improvements over Online Mirror Descent. In ...
  • A high probability analysis of adaptive SGD with momentum 

    Li, Xiaoyu; Orabona, Francesco (2020-07-17)
    Stochastic Gradient Descent (SGD) and its variants are the most used algorithms in machine learning applications. In particular, SGD with adaptive learning rates and momentum is the industry standard to train deep networks. ...
  • Current status and future prospects of the SNO+ experiment 

    Andringa, S.; Arushanova, E.; Asahi, S.; Askins, M.; Auty, D.J.; Back, A.R.; Barnard, Z.; Barros, N.; Beier, E.W.; Bialek, A.; Biller, S.D.; Blucher, E.; Bonventre, R.; Braid, D.; Caden, E.; Callaghan, E.; Caravaca, J.; Carvalho, J.; Cavalli, L.; Chauhan, D.; Chen, M.; Chkvorets, O.; Clark, K.; Cleveland, B.; Coulter, I.T.; Cressy, D.; Dai, X..; Darrach, C.; Davis-Purcell, B.; Deen, R.; Depatie, M.M.; Descamps, F.; Di Lodovico, F.; Duhaime, N.; Duncan, F.; Dunger, J.; Falk, E.; Fatemighomi, N.; Ford, R.; Gorel, P.; Grant, Christopher; Grullon, S.; Guillian, E.; Hallin, A.L.; Hallman, D.; Hans, S.; Hartnell, J.; Harvey, P.; Hedayatipour, M.; Heintzelman, W.J.; Helmer, R.L.; Hreljac, B.; Hu, J.; Iida, T.; Jackson, C.M.; Jelley, N.A.; Jillings, C.; Jones, C.; Jones, P.G.; Kamdin, K.; Kaptanoglu, T.; Kaspar, J.; Keener, P.; Khaghani, P.; Kippenbrock, L.; Klein, J.R.; Knapik, R.; Kofron, J.N.; Kormos, L.L.; Korte, S.; Kraus, C.; Krauss, C.B.; Labe, K.; Lam, I.; Lan, C.; Land, B.J.; Langrock, S.; LaTorre, A.; Lawson, I.; Lefeuvre, G.M.; Leming, E.J.; Lidgard, J.; Liu, X.; Liu, Y.; Lozza, V.; Maguire, S.; Maio, A.; Majumdar, K.; Manecki, S.; Maneira, J.; Marzec, E.; Mastbaum, A.; McCauley, N.; McDonald, A.B.; McMillan, J.E.; Mekarski, P.; Miller, C.; Mohan, Y.; Mony, E.; Mottram, M.J.; Novikov, V.; O’Keeffe, H.M.; O’Sullivan, E.; Orebi Gann, G.D.; Parnell, M.J.; Peeters, S.J.M.; Pershing, T.; Petriw, Z.; Prior, G.; Prouty, J.C.; Quirk, S.; Reichold, A.; Robertson, A.; Rose, J.; Rosero, R.; Rost, P.M.; Rumleskie, J.; Schumaker, M.A.; Schwendener, M.H.; Scislowski, D.; Secrest, J.; Seddighin, M.; Segui, L.; Seibert, S.; Shantz, T.; Shokair, T.M.; Sibley, L.; Sinclair, J.R.; Singh, K.; Skensved, P.; Sörensen, A.; Sonley, T.; Stainforth, R.; Strait, M.; Stringer, M.I.; Svoboda, R.; Tatar, J.; Tian, L.; Tolich, N.; Tseng, J.; Tseung, H.W.C.; Van Berg, R.; Vázquez-Jáuregui, E.; Virtue, C.; von Krosigk, B.; Walker, J.M.G.; Walker, M.; Wasalski, O.; Waterfield, J.; White, R.F.; Wilson, J.R.; Winchester, T.J.; Wright, A.; Yeh, M.; Zhao, T.; Zuber, K. (Hindawi Limited, 2016)
    SNO+ is a large liquid scintillator-based experiment located 2 km underground at SNOLAB, Sudbury, Canada. It reuses the Sudbury Neutrino Observatory detector, consisting of a 12 m diameter acrylic vessel which will be ...
  • Mean field limits of particle-based stochastic reaction-diffusion models 

    Isaacson, Samuel A.; Ma, Jingwei; Spiliopoulos, Konstantinos (2020)
    Particle-based stochastic reaction-diffusion (PBSRD) models are a popular approach for studying biological systems involving both noise in the reaction process and diffusive transport. In this work we derive coarse-grained ...
  • How reaction-diffusion PDEs approximate the large-population limit of stochastic particle models 

    Isaacson, Samuel A.; Ma, Jingwei; Spiliopoulos, Konstantinos (2021)
    Reaction-diffusion PDEs and particle-based stochastic reaction-diffusion (PBSRD) models are commonly-used approaches for modeling the spatial dynamics of chemical and biological systems. Standard reaction-diffusion PDE ...
  • The mini-CAPTAIN liquid argon time projection chamber 

    Grant, Christopher (Elsevier, 2020)

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