Using compositional mixed-effects models to evaluate responses to amino acid supplementation in milk replacers for calves

The consequences of supplementing Lys, Met, and Thr in milk replacers (MR) for calves have been widely studied, but scarce information exists about potential roles of other AA (whether essential or not). The effects on growth performance of supplementation of 4 different AA combinations in a mixed ration (25.4% crude protein and 20.3% fat) based on skim milk powder and whey protein concentrate were evaluated in 76 Holstein male calves (3 ± 1.7 d old). The 4 MR were as follows: CTRL with no AA supplementation; PG, supplying additional 0.3% Pro and 0.1% Gly; FY, supplying additional 0.2% Phe and 0.2% Tyr; and KMT, providing additional 0.62% Lys, 0.22% Met, and 0.61% Thr. All calves were fed the same milk allowance program and were weaned at 56 d of study. Concentrate intake was limited to minimize interference of potential differences in solid feed intake among treatments. Animals were weighed weekly, intakes recorded daily, and blood samples obtained at 2, 5, and 7 wk of study to determine serum urea and plasma AA concentrations. Plasma AA concentrations were explored using compositional data analysis, and their isometric log-ratio transformations were used to analyze their potential influence on ADG and serum urea concentration using a linear mixed-effects model. We detected no differences in calf performance and feed intake. Plasma relative concentration of the AA supplemented in the KMT and PG treatments increased in their respective treatments, and, in PG calves, a slight increase in the proportion of plasma Gly, Glu, and branched-chain AA was also observed. The proportions of plasma branched-chain AA, His, and Gln increased, and those of Thr, Arg, Lys, and Glu decreased with calves' age. A specific log-contrast balance formed by Arg, Thr, and Lys was found to be the main driver for lowering serum urea concentrations and increasing calf growth. The use of compositional mixed-effects models identified a cluster formed by the combination of Arg, Thr, and Lys, as a potential AA to optimize calf growth.Peer ReviewedPostprint (published version

Data-Driven Optimization of Plasma Electrolytic Oxidation (PEO) Coatings with Explainable Artificial Intelligence Insights

PEO constitutes a promising surface technology for the development of protective and functional ceramic coatings on lightweight alloys. Despite its interesting advantages, including enhanced wear and corrosion resistances and eco-friendliness, the industrial implementation of PEO technology is limited by its relatively high energy consumption. This study explores the development and optimization of novel PEO processes by means of machine learning (ML) to improve the coating thickness. For this purpose, ML models random forest and XGBoost were employed to predict the thickness of the developed PEO coatings based on the key process variables (frequency, current density, and electrolyte composition). The predictive performance was significantly improved by including the composition of the used electrolyte in the models. Furthermore, Shapley values identified the pulse frequency and the TiO2 concentration in the electrolyte as the most influential variables, with higher values leading to increased coating thickness. The residual analysis revealed a certain heteroscedasticity, which suggests the need for additional samples with high thickness to improve the accuracy of the model. This study reveals the potential of artificial intelligence (AI)-driven optimization in PEO processes, which could pave the way for more efficient and cost-effective industrial applications. The findings achieved further emphasize the significance of integrating interactions between variables, such as frequency and TiO2 concentration, into the design of processing operations

Analysis of calf growth with compositional mixed models

In this master's thesis we combine techniques from the field of Compositional Data Analysis (CoDA) with mixed-effects models to study the relationship between dairy calves' growth and their amino acid compositon in blood, being the detection of potentially growth-limiting amino acids that can provoke changes in urea levels of particular interest

Analysis of calf growth with compositional mixed models

In this master's thesis we combine techniques from the field of Compositional Data Analysis (CoDA) with mixed-effects models to study the relationship between dairy calves' growth and their amino acid compositon in blood, being the detection of potentially growth-limiting amino acids that can provoke changes in urea levels of particular interest

Analysis of calf growth with compositional mixed models

In this master's thesis we combine techniques from the field of Compositional Data Analysis (CoDA) with mixed-effects models to study the relationship between dairy calves' growth and their amino acid compositon in blood, being the detection of potentially growth-limiting amino acids that can provoke changes in urea levels of particular interest

Multisectoral models for water management under droughts and climate change

The escalating conflicts and competition for freshwater resources are widely acknowledged. The demand for water is on the rise due to rapid population growth and socioeconomic development, while climate change is disrupting the water cycle by changing precipitation patterns, leading to alterations and increasing uncertainty in the availability, quality and distribution of water resources. This is compounded by extreme weather events, especially droughts, which further aggravate both the supply and reliability of water resources. Water scarcity poses a major threat to human health, ecosystems sustainability and economic development, challenging both global food security and economic stability. The complex interplay between water resources and economic systems requires models that encompass the interconnectedness among all economic activities, to properly understand the economy- and region-wide effects of local scarcity and to guide the design of both demand and supply instruments to cope with water stress. By using environmentally-extended multi-sectoral models, this thesis aims to address the impacts of water-induced supply side disruptions in the economy under climate change, proposing methods and policies to mitigate and adapt to changes in water resources availability. It assesses the macroeconomic impacts of localized droughts on different world regions by evaluating two different allocation regimes adopted to deal with the water shortage (namely, water restrictions borne solely by agricultural sectors vs. uniform reduction of water allotments). The results show that the policy-regime chosen, together with the role of the region in global supply chains, greatly determine the extent of the economic impacts, both in the directly affected region and in third countries. When the drought affects only agriculture, the negative economic impacts can be mitigated by adjusting production and trade. In contrast, when water availability is reduced uniformly across all economic sectors in the drought-stricken region, economic losses spread across the globe. This thesis goes further in the analysis of water allocation policies by developing a model capable of finding the optimal allocation to minimize the overall economic disruption during a droughtEls creixents conflictes i la competència pels recursos hídrics estan àmpliament reconeguts. La demanda d'aigua està en augment a causa del ràpid creixement poblacional i del desenvolupament socioeconòmic, mentre que el canvi climàtic està canviant el cicle hidrològic i els patrons de precipitació, la qual cosa condueix a alteracions i un increment de la incertesa en la disponibilitat, qualitat i distribució dels recursos hídrics. Aquesta situació s’agreuja amb l'increment dels fenòmens climàtics extrems, especialment les sequeres, afectant encara més tant el subministrament com la qualitat dels recursos hídrics. L'escassetat d'aigua representa una gran amenaça per a la salut humana, la sostenibilitat dels ecosistemes i el desenvolupament econòmic, posant en risc tant la seguretat alimentària global com l’estabilitat econòmica. La complexa interacció entre els recursos hídrics i els sistemes econòmics requereix de models que tinguin en compte la interconnexió entre totes les activitats econòmiques, per tal de poder comprendre adequadament els efectes a econòmics i regionals de l'escassetat a nivell local i poder guiar en el disseny d'instruments tant de demanda com d'oferta per fer front a l'estrès hídric. A través de models multisectorials estesos a l'ús de recursos hídrics, aquesta tesi té com a objectiu analitzar els impactes econòmics causats per l'escassetat d'aigua degut al canvi climàtic, proposant mètodes i polítiques per mitigar i adaptar-se als canvis en la disponibilitat dels recursos hídrics. Aquesta tesi avalua els impactes macroeconòmics de sequeres en diferents regions globals a través de dues polítiques d'assignació d'aigua diferents adoptades per fer front a l'escassetat temporal d'aigua (és a dir, restriccions d'aigua implementades només als sectors agrícoles vs. una reducció uniforme en les assignacions d'aigua). Els resultats mostren que la política específica d'assignació, juntament amb la importància del país o regió en les cadenes de subministrament globals, determinen en gran mesura la magnitud dels impactes econòmics, tant a la regió directament afectada com als països no afectats. Aquesta tesi aprofundeix en l'anàlisi de les polítiques d'assignació d'aigua desenvolupant un model capaç de trobar l'assignació òptima que minimitza l'impacte econòmic agregat durant una sequeraPrograma de Doctorat Interuniversitari en Dret, Economia i Empres