Welcome to The Bárány Society The International Society for Neuro-otology, Vestibular Medicine, and Vestibular Research. Founded in 1960, the Bárány Society is an international interdisciplinary society that facilitates contact between scientists and clinicians involved in vestibular research.

常见的微生物动力学一级模型主要包括四种，Linear 模型、Logistic模型、 Gompertz 模型 及Baranyi & Roberts 模型。其中Gompertz 模型是预测微生物学的基石，美国农业部开发的PMP（Pathogen Modeling Program）系统和英国农粮渔部开发的FM（Food Micromodel）系统都以Gompertz 函数作为 ...

1999年12月1日 · The identifiability properties of the Baranyi model for bacterial growth were investigated, both structurally and applied to real-life data.

AM Gibson, J Baranyi, JI Pitt, MJ Eyles, TA Roberts. International journal of food microbiology 23 (3-4), 419-431, 1994. 314: 1994: Predicting growth of Brochothrix thermosphacta at changing temperature. J Baranyi, TP Robinson, A Kaloti, BM Mackey. International journal of food microbiology 27 (1), 61-75, 1995. 308:

A new member of the family of growth models described by Baranyi et al. (1993a) is introduced in which the physiological state of the cells is represented by a single variable. The duration of lag is determined by the value of that variable at inoculation and by the post-inoculation environment.

2012年3月6日 · Baranyi 模型被广泛使用的原因有：使用方便; 动态. 环境也可使用; 适合多种情况; 模型中的参数都具. 有生理学意义 [9] 。 在近年的微生物预测模型研究中, 更多的使用. Baranyi 模型不仅仅是因为其更准确, 还因为该模型. 更加的简单和实用。理论上, 预测的准确性是 ...

Baranyi is a surname. Notable people with the surname include: John Baranyi (born 1961), Independent candidate in 2000 and Green Party candidate in 2003 and 2004 for the House of Commons of Canada; Szabolcs Baranyi (1944–2016), former …

2024年11月19日 · 本文介绍了如何使用Origin软件拟合Baranyi方程，通过具体步骤展示了从数据准备到拟合评估的整个过程，为食品微生物学的研究提供了实用的方法。

2018年10月1日 · 对 Baranyi模型进行改进，构建波动温度下的微生物生长动力学模型，并运用模拟实验对模型进行验证，验证结果是 偏差因子为1.23，准确因子为1.12，表明所构建的微生物生长动力学模型能够很好的拟合波动温度下鲐鱼中微生物 的变化情况。

2020年4月1日 · The Baranyi model (Baranyi & Roberts, 1994) was used to determine the kinetic growth parameters of Pseudomonas spp. on button mushrooms stored at isothermal conditions: (1) y t = y 0 + μ m a x F t-l n 1 + e μ m a x F t-1 e y m a x-y 0 where µ max is the maximum specific growth rate (h −1), t is the time (h), y(t) is the concentration of ...