On the structural, electronic, and optical properties of L-histidine crystal: a DFT study.

CONTEXT: The monoclinic L-histidine crystal is critical for protein structure and function and is also found in the myelin of brain nerve cells. This study numerically examines its structural, electronic, and optical properties. Our findings indicate that the L-histidine crystal has an insulating band gap of approximately 4.38 eV. Additionally, electron and hole effective masses range between 3.92[Formula: see text]-15.33[Formula: see text] and 4.16[Formula: see text]-7.53[Formula: see text], respectively. Furthermore, our investigation suggests that the L-histidine crystal is an excellent UV collector due to its strong optical absorption activity for photon energies exceeding 3.5 eV. METHODS: To investigate the structural, electronic, and optical properties of L-histidine crystals, we used the Biovia Materials Studio software to conduct Density Functional Theory (DFT) simulations as implemented in the CASTEP code. Our DFT calculations were performed using the generalized gradient approximation (GGA) as parameterized by the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional, with an additional dispersion energy correction (PBE [Formula: see text] TS) based on the model proposed by Tkatchenko and Scheffler to describe van der Waals interactions. Additionally, we employed the norm-conserving pseudopotential to treat core electrons.

Caracterização dos fatores de produção e uso de modelos matemáticos para estimar sua influência sobre o consumo diário de ração e a conversão alimentar de suínos nas fases de crescimento e terminação / Characterization of production factors and use of mathematical models to estimate their influence on daily feed intake and feed conversion ratio of grow-finishing pigs

O objetivo deste estudo foi identificar e quantificar os fatores de produção presentes em granjas de crescimento e terminação (CT) de suínos, em um sistema cooperativo do estado do Paraná, Brasil, e determinar a influência desses fatores no consumo diário de ração (CDR) e na conversão alimentar (CA). Foram avaliados, entre os anos de 2010 e 2013, os históricos produtivos de 538 lotes de engorda, alojados em 175 granjas comerciais, totalizando aproximadamente 404.000 animais. Foram considerados 40 fatores de produção, relacionados ao manejo, à sanidade, às instalações e aos equipamentos, à nutrição, à genética e ao ambiente. Em baias com menos de 20 suínos, o CDR diminuiu (P<0,05) e a CA melhorou (P<0,01). Nas baias com comedouros basculantes (lineares), o CDR reduziu (P<0,01) e a CA melhorou (P=0,001). Em baias com lâmina d'água, o CDR aumentou (P<0,01) e a CA piorou (P<0,01). Lotes formados apenas por fêmeas apresentaram menor CDR (P<0,001) e melhor CA (P<0,001), quando comparados aos lotes mistos. As variáveis selecionadas para os modelos finais explicaram cerca de 25% e 46% da variância total para CDR e para a CA, respectivamente. Os modelos constituem um instrumento de auxílio efetivo para tomadas de decisões técnicas dentro do setor suinícola.(AU)

The aim of this study was to identify and quantify the production factors present in growing and finishing (GF) pig farms partners of a cooperative in Paraná State, Brazil, and to determine the influence of these factors on daily feed intake (DFI) and the feed conversion ratio (FCR). From 2010 to 2013, the historical production of 538 batches of fattening pigs in 175 commercial farms were analyzed, in an amount approximately 404,000 animals. A total of 40 production factors regarding the management, sanity, plant and equipment, nutrition, genetics and environment were taken into consideration. Pens with less than 20 pigs resulted in a reduction in DFI (P<0.05) and an improved FCR (P<0.01). In pens that used linear dump feeders, the DFI was less (P<0.01) and the FCR was better (P=0.001). Pens with shallow pools had higher DFI (P<0.01) and worse FCR (P<0.01). Batches of females had lower DFI (P<0.001) and better FCR (P<0.001) compared to mixed-sex batches. The factors used for the final models explained the 25% and 46% of the total variance for the DFI and FCR, respectively. The models consist in effective aid instruments for technical decision making in the swine industry.(AU)