Results 181 to 190 of about 635,253 (366)

Effects of a novel feed additive on clinical symptoms and the nasal and cecal microbiome in nursery pigs challenged with PRRSV and <i>Streptococcus suis</i>. [PDF]

Transl Anim Sci
Tran HT, Mercado AJ, Lahoti MM, Murali RR, Davis E, Crowder S, de Rodas B.   +6 more
europepmc   +1 more source

Pigs in medicine [PDF]

BMJ, 1986
openaire   +2 more sources

Estimation of genetic parameters and inbreeding depression in Piau breed pigs

, 2020
Letícia Fernanda da Silva [UNESP] Oliveira
openalex   +1 more source

Breeding and feeding pigs in Australia and Vietnam

This report establishes that ACIAR Research Project AS2/1994/023, ‘Breeding and feeding pigs in Australia and Vietnam’ (supported by ACIAR from July 1995 to the end of 2000) has yielded an extraordinarily high rate of economic return on the funds ...
Wilson, Clevo, Tisdell, Clement A.
core  

The effects of oxytetracycline on the intestinal Escherichia coli flora of newly weaned pigs

, 1985
Four recently weaned pigs were dosed orally with oxytetracycline. This caused a rapid increase in the incidence of tetracycline resistance (TcR) among Escherichia coli isolates from the faecal flora.
Hinton, M., Hampson, E., Hampson, D.J., Linton, A.H.   +3 more
core  

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

The neurophysins of the pig [PDF]

Biochemical Journal, 1967
L O, Uttenthal, Y, Ishida, D B, Hope
openaire   +2 more sources

A Modelling Study for Smart Pigging Technique for Pipeline Leak Detection

, 2020
Caitlyn Thiberville
openalex   +2 more sources

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Serological and molecular evaluation of Senecavirus A (SVA) in pigs from farrow-to-finish farms in Minas Gerais, Brazil. [PDF]

Braz J Microbiol
Santos JC, Calheiros EB, Toledo LT, Uzoka UH, Marks FS, Porto WJN, Borges AA, Pantaleão JAF, Guedes MIIMC, Pereira CER, Schwarz DGG, Silva-Júnior A.   +11 more
europepmc   +1 more source