Honey varietals differentially impact Bifidobacterium animalis ssp lactis survivability in yogurt through simulated in vitro digestion

Posted by dbos Hopkins

Kavli Affiliate: Michael Miller | Authors: David A. Alvarado, Luis Alberto Ibarra-Sanchez, Annemarie R. Mysonhimer, Tauseef A Khan, Rong Cao, Michael J. Miller and Hannah Holscher | Summary: Background Bifidobacterium animalis ssp. lactis DN-173 010/CNCM I-2494 (B. animalis) is a probiotic strain commonly added to yogurt. Yogurt and honey are a popular culinary pairing. Honey […]


Continue.. Honey varietals differentially impact Bifidobacterium animalis ssp lactis survivability in yogurt through simulated in vitro digestion

Context-invariant socioemotional encoding by prefrontal ensembles

Posted by dbos UCSF

Kavli Affiliate: Vikaas Sohal | Authors: Nicholas A Frost, Kevin C Donohue and Vikaas Sohal | Summary: The prefrontal cortex plays a key role in social interactions, anxiety-related avoidance, and flexible context- dependent behaviors, raising the question: how do prefrontal neurons represent socioemotional information across different environments? Are contextual and socioemotional representations segregated or intermixed, […]


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SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering

Posted by dbos Tokyo

Kavli Affiliate: David Spergel | First 5 Authors: Pablo Lemos, Liam Parker, ChangHoon Hahn, Shirley Ho, Michael Eickenberg | Summary: We present the first simulation-based inference (SBI) of cosmological parameters from field-level analysis of galaxy clustering. Standard galaxy clustering analyses rely on analyzing summary statistics, such as the power spectrum, $P_ell$, with analytic models based […]


Continue.. SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering

Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multidimensional supernova simulations

Posted by dbos Tokyo

Kavli Affiliate: Shunsaku Horiuchi | First 5 Authors: Nick Ekanger, Shunsaku Horiuchi, Hiroki Nagakura, Samantha Reitz, | Summary: The sensitivity of current and future neutrino detectors like Super-Kamiokande (SK), JUNO, Hyper-Kamiokande (HK), and DUNE is expected to allow for the detection of the diffuse supernova neutrino background (DSNB). However, the DSNB model ingredients like the […]


Continue.. Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multidimensional supernova simulations

Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multidimensional supernova simulations

Posted by dbos Tokyo

Kavli Affiliate: Shunsaku Horiuchi | First 5 Authors: Nick Ekanger, Shunsaku Horiuchi, Hiroki Nagakura, Samantha Reitz, | Summary: The sensitivity of current and future neutrino detectors like Super-Kamiokande (SK), JUNO, Hyper-Kamiokande (HK), and DUNE is expected to allow for the detection of the diffuse supernova neutrino background (DSNB). However, the DSNB model ingredients like the […]


Continue.. Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multidimensional supernova simulations

Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multi-dimensional supernova simulations

Posted by dbos Tokyo

Kavli Affiliate: Shunsaku Horiuchi | First 5 Authors: Nick Ekanger, Shunsaku Horiuchi, Hiroki Nagakura, Samantha Reitz, | Summary: The sensitivity of current and future neutrino detectors like Super-Kamiokande (SK), JUNO, Hyper-Kamiokande (HK), and DUNE is expected to allow for the detection of the diffuse supernova neutrino background (DSNB). However, the DSNB model ingredients like the […]


Continue.. Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multi-dimensional supernova simulations

${rm S{scriptsize IM}BIG}$: The First Cosmological Constraints from Non-Gaussian and Non-Linear Galaxy Clustering

Posted by dbos Tokyo

Kavli Affiliate: David Spergel | First 5 Authors: ChangHoon Hahn, Pablo Lemos, Liam Parker, Bruno Régaldo-Saint Blancard, Michael Eickenberg | Summary: The 3D distribution of galaxies encodes detailed cosmological information on the expansion and growth history of the Universe. We present the first cosmological constraints that exploit non-Gaussian cosmological information on non-linear scales from galaxy […]


Continue.. ${rm S{scriptsize IM}BIG}$: The First Cosmological Constraints from Non-Gaussian and Non-Linear Galaxy Clustering

Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects

Posted by dbos MIT

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Natalí S. M. de Santi, Francisco Villaescusa-Navarro, L. Raul Abramo, Helen Shao, Lucia A. Perez | Summary: It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing […]


Continue.. Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects

Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects

Posted by dbos MIT

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Natalí S. M. de Santi, Francisco Villaescusa-Navarro, L. Raul Abramo, Helen Shao, Lucia A. Perez | Summary: It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing […]


Continue.. Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects

Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects

Posted by dbos MIT

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Natalí S. M. de Santi, Francisco Villaescusa-Navarro, L. Raul Abramo, Helen Shao, Lucia A. Perez | Summary: It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing […]


Continue.. Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects