Enhancing early identification of high-fertile cattle females using infrared blood serum spectra and machine learning.

Artificial insemination (AI) success in bovine reproduction is vital for the cattle industry's economic sustainability and for advancing the understanding of reproductive physiology. Identify high-fertile animals' fertility is a complex task due to multifactorial traits, including hormonal, age-related, and body condition factors. Early high-fertility identification is crucial for timely interventions and enhancing AI success.

Making wood inspection easier: FTIR spectroscopy and machine learning for Brazilian native commercial wood species identification.

The molecular structure of wood is mainly based on cellulose, lignin, and hemicellulose. However, low concentrations of lipids, phenolic compounds, terpenoids, fatty acids, resin acids, and waxes can also be found. In general, their color, smell, texture, quantity, and distribution of pores are used in human sensory analysis to identify native wood species, which may lead to erroneous classification, impairing quality control and inspection of commercialized wood.

Portland Cement/ Endocarp Bricks: Thermal Insulation and Mechanical Properties.

In the last few decades, Portland/residue composites have been researched due to their technological and environmental advantages. In this study, residues of (Jacq.) Lodd endocarp (AE) were introduced in the Portland cement-soil (PC) matrix in different concentrations (0, 5, 10, 15, 20, and 50 wt%) to produce PC/AE bricks.