Gaussian and Lerch Models for Unimodal Time Series Forcasting.

We consider unimodal time series forecasting. We propose Gaussian and Lerch models for this forecasting problem. The Gaussian model depends on three parameters and the Lerch model depends on four parameters. We estimate the unknown parameters by minimizing the sum of the absolute values of the residuals. We solve these minimizations with and without a weighted median and we compare both approaches. As a numerical application, we consider the daily infections of COVID-19 in China using the Gaussian and Lerch models. We derive a confident interval for the daily infections from each local minima.

Label free shotgun proteomics for the identification of protein biomarkers for beef tenderness in muscle and plasma of heifers.

Meat quality prediction is a priority for the beef industry. Label free shotgun proteomics was performed on Longissimus muscle and plasma from 20 crossbred Charolais x Aubrac beef heifers, classified as subgroups of 5 extreme tender and 5 extreme tough meat according to sensory evaluation, Warner Bratzler shear force, and a synthetic tenderness index. This technique identified 268 proteins in muscle and 136 in plasma. Among them, 71 muscle proteins and 21 plasma proteins discriminated tender and tough groups. These proteins were analyzed to select the most correlated and explicative ones which were used in a linear regression on the 20 heifers. The results validated in heifers 33 muscle proteins previously identified as related with tenderness, and revealed 38 new candidates. Twelve are localized in shear force or tenderness score QTL. Among them ACTN2, ADSSL1, GOT1, HPX, OGDH, OGN, TNNC1 and VCL are proposed as robust candidates with 3 other proteins known to be related with tenderness (MYBPH, CAPZB, MYH1). Examination of the plasma proteome showed 8 putative biomarkers (MYH7, CFH, ENO3, PLA2G2D5, FHL1, GAPDH, MASP2 and SERPINF2). Three of them (MYH7, ENO3 and FHL1) were identified as discriminative of tenderness both in Longissimus muscle and in plasma. SIGNIFICANCE: The label free proteomic approach used in this study allowed to complete the atlas of biomarkers for tenderness of the Longissimus muscle. This innovative proteomic approach applied on plasma samples allowed to identify circulating candidate biomarkers for beef tenderness. This low-invasive approach constitutes an interesting alternative to evaluate early the "beef meat potential" of living animals in farm or of the carcass in slaughterhouses.