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Article(electronic)#12013

Study on Kink Space-Time in Scale Invariant Theory with Wet Dark Fluid

Mishra, Bivudutta; Sahoo, P. K.

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Article(electronic)#22013

Bianchi Type VI1 Cosmological Model with Wet Dark Fluid in Scale Invariant Theory of Gravitation

In: Amendola, L.: Mon. Not. R. Astron. Soc. 342, 221 (2003) Babichev, et al.: (2004). arXiv:astro-ph/0407190 Bahcall, N.A., et al.: Science 284, 1481 (1999) Bamba, K., Capozzielli, S., Nojiri, S., Odintsov, S.D.: Astrophys. Space Sci. 342, 155 (2012) Beesham, A.: Clasic. Quant. Grav. 3, 481 (1986a)

Mishra, Bivudutta; Sahoo, P. K.

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Article(electronic)#3March 2023

Fluid Bodies: Wet Nurses and Breastmilk Anxieties in Eighteenth-Century Madrid

In: Journal of women's history, Volume 35, Issue 1, p. 121-141

Crifasi, Celia

ISSN: 1527-2036

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Article(electronic)#4

Investigating the Wet-to-Dry Expansion of Organic Fluids for Power Generation

In: HMT-D-21-05324

White, Martin

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Article(electronic)#52016

Flow Analysis of Wet Scrubber and Fabric Filter using Computational Fluid Dynamics

In: Asian journal of research in social sciences and humanities: AJRSH, Volume 6, Issue 8, p. 1840

Janaki, S.; Jayachitra, R.; Kumar, A. P. Senthil

ISSN: 2249-7315

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Article(electronic)#6August 23, 2020

Jan Verplaetse, Blood Rush: The Dark History of a Vital Fluid

In: Social history of medicine, Volume 34, Issue 3, p. 1048-1050

Starr, Douglas

ISSN: 1477-4666

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Open Access#72020

Analysis of the H0 tension problem in the Universe with viscous dark fluid

Elizalde, Emilio; Khurshudyan, Martiros; Odintsov, Sergei D; Myrzakulov, Ratbay

Two inhomogeneous single-fluid models for the Universe, which are able to naturally solve the H0 tension problem, are discussed. The analysis is based on a Bayesian Machine Learning approach that uses a generative process. The method here adopted allows for constraint of the free parameters of each model by making use of the model itself only. The observable is taken to be the Hubble parameter, obtained from the generative process. Using the full advantages of our method, the models are constrained for two redshift ranges. Namely, first this is done with mock H(z) data over z∈[0,2.5], thus covering known H(z) observational data, which are most helpful to validate the fit results. Then, aiming to extend to redshift ranges to be covered by the most recent ongoing and future planned missions, the models are constrained for the range z∈[0,5], too. Full validation of the results for this extended redshift range will have to wait for some years, for when higher-redshift H(z) data become available. This makes our models fully falsifiable. In addition, our second model is able to explain the BOSS reported value for H(z) at z=2.34. ; The work was carried out with the financial support of the Ministry of Education and Science of the Republic of Kazakhstan, Grant No. BR05236277 (S. D. Odintsov and R.Myrzakulov), Grant No. AP05135123 (R.Myrzakulov) and Grant No. 0118RK00935 while S. D. Odintsov was visiting ENU. This work has been partially supported by MINECO (Spain), Projects No. FIS2016-76363-P and No. PID2019–104397 GB-I00, and by AGAUR (Catalan Government), Project No. 2017-SGR-247. ; Peer reviewed

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