A new method for conditioning stochastic groundwater flow models in fractured media

Many geological formations consist of crystalline rocks that have very low matrix permeability but allow flow through an interconnected network of fractures. Understanding the flow of groundwater through such rocks is important in considering disposal of radioactive waste in underground repositories. A specific area of interest is the conditioning of fracture transmissivities on measured values of pressure in these formations. This is the process where the values of fracture transmissivities in a model are adjusted to obtain a good fit of the calculated pressures to measured pressure values. While there are existing methods to condition transmissivity fields on transmissivity, pressure and flow measurements for a continuous porous medium there is little literature on conditioning fracture networks. Conditioning fracture transmissivities on pressure or flow values is a complex problem because the measurements are not linearly related to the fracture transmissivities and they are also dependent on all the fracture transmissivities in the network. We present a new method for conditioning fracture transmissivities on measured pressure values based on the calculation of certain basis vectors; each basis vector represents the change to the log transmissivity of the fractures in the network that results in a unit increase in the pressure at one measurement point whilst keeping the pressure at the remaining measurement points constant. The fracture transmissivities are updated by adding a linear combination of basis vectors and coefficients, where the coefficients are obtained by minimizing an error function. A mathematical summary of the method is given. This algorithm is implemented in the existing finite element code ConnectFlow developed and marketed by Serco Technical Services, which models groundwater flow in a fracture network. Results of the conditioning are shown for a number of simple test problems as well as for a realistic large scale test case.

Sustainable deployment of QTLs conferring quantitative resistance to crops: first lessons from a stochastic model

International audience

Typologies and spatialization of agricultural production systems in Rondônia, Brazil: linking land use, socioeconomics and territorial configuration.

The current Amazon landscape consists of heterogeneous mosaics formed by interactions between the original forest and productive activities. Recognizing and quantifying the characteristics of these landscapes is essential for understanding agricultural production chains, assessing the impact of policies, and in planning future actions. Our main objective was to construct the regionalization of agricultural production for Rondônia State (Brazilian Amazon) at the municipal level. We adopted a decision tree approach, using land use maps derived from remote sensing data (PRODES and TerraClass) combined with socioeconomic data. The decision trees allowed us to allocate municipalities to one of five agricultural production systems: (i) coexistence of livestock production and intensive agriculture; (ii) semi-intensive beef and milk production; (iii) semi-intensive beef production; (iv) intensive beef and milk production, and; (v) intensive beef production. These production systems are, respectively, linked to mechanized agriculture (i), traditional cattle farming with low management, with (ii) or without (iii) a significant presence of dairy farming, and to more intensive livestock farming with (iv) or without (v) a significant presence of dairy farming. The municipalities and associated production systems were then characterized using a wide variety of quantitative metrics grouped into four dimensions: (i) agricultural production; (ii) economics; (iii) territorial configuration, and; (iv) social characteristics. We found that production systems linked to mechanized agriculture predominate in the south of the state, while intensive farming is mainly found in the center of the state. Semi-intensive livestock farming is mainly located close to the southwest frontier and in the north of the state, where human occupation of the territory is not fully consolidated. This distributional pattern reflects the origins of the agricultural production system of Rondônia. Moreover, the characterization of the production systems provides insights into the pattern of occupation of the Amazon and the socioeconomic consequences of continuing agricultural expansion.

Development of new scenario decomposition techniques for linear and nonlinear stochastic programming

Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.

An adaptive neighborhood search algorithm for optimizing stochastic mining complexes

Les métaheuristiques sont très utilisées dans le domaine de l'optimisation discrète. Elles permettent d’obtenir une solution de bonne qualité en un temps raisonnable, pour des problèmes qui sont de grande taille, complexes, et difficiles à résoudre. Souvent, les métaheuristiques ont beaucoup de paramètres que l’utilisateur doit ajuster manuellement pour un problème donné. L'objectif d'une métaheuristique adaptative est de permettre l'ajustement automatique de certains paramètres par la méthode, en se basant sur l’instance à résoudre. La métaheuristique adaptative, en utilisant les connaissances préalables dans la compréhension du problème, des notions de l'apprentissage machine et des domaines associés, crée une méthode plus générale et automatique pour résoudre des problèmes. L’optimisation globale des complexes miniers vise à établir les mouvements des matériaux dans les mines et les flux de traitement afin de maximiser la valeur économique du système. Souvent, en raison du grand nombre de variables entières dans le modèle, de la présence de contraintes complexes et de contraintes non-linéaires, il devient prohibitif de résoudre ces modèles en utilisant les optimiseurs disponibles dans l’industrie. Par conséquent, les métaheuristiques sont souvent utilisées pour l’optimisation de complexes miniers. Ce mémoire améliore un procédé de recuit simulé développé par Goodfellow & Dimitrakopoulos (2016) pour l’optimisation stochastique des complexes miniers stochastiques. La méthode développée par les auteurs nécessite beaucoup de paramètres pour fonctionner. Un de ceux-ci est de savoir comment la méthode de recuit simulé cherche dans le voisinage local de solutions. Ce mémoire implémente une méthode adaptative de recherche dans le voisinage pour améliorer la qualité d'une solution. Les résultats numériques montrent une augmentation jusqu'à 10% de la valeur de la fonction économique.

Development of new scenario decomposition techniques for linear and nonlinear stochastic programming

Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.

An adaptive neighborhood search algorithm for optimizing stochastic mining complexes

Les métaheuristiques sont très utilisées dans le domaine de l'optimisation discrète. Elles permettent d’obtenir une solution de bonne qualité en un temps raisonnable, pour des problèmes qui sont de grande taille, complexes, et difficiles à résoudre. Souvent, les métaheuristiques ont beaucoup de paramètres que l’utilisateur doit ajuster manuellement pour un problème donné. L'objectif d'une métaheuristique adaptative est de permettre l'ajustement automatique de certains paramètres par la méthode, en se basant sur l’instance à résoudre. La métaheuristique adaptative, en utilisant les connaissances préalables dans la compréhension du problème, des notions de l'apprentissage machine et des domaines associés, crée une méthode plus générale et automatique pour résoudre des problèmes. L’optimisation globale des complexes miniers vise à établir les mouvements des matériaux dans les mines et les flux de traitement afin de maximiser la valeur économique du système. Souvent, en raison du grand nombre de variables entières dans le modèle, de la présence de contraintes complexes et de contraintes non-linéaires, il devient prohibitif de résoudre ces modèles en utilisant les optimiseurs disponibles dans l’industrie. Par conséquent, les métaheuristiques sont souvent utilisées pour l’optimisation de complexes miniers. Ce mémoire améliore un procédé de recuit simulé développé par Goodfellow & Dimitrakopoulos (2016) pour l’optimisation stochastique des complexes miniers stochastiques. La méthode développée par les auteurs nécessite beaucoup de paramètres pour fonctionner. Un de ceux-ci est de savoir comment la méthode de recuit simulé cherche dans le voisinage local de solutions. Ce mémoire implémente une méthode adaptative de recherche dans le voisinage pour améliorer la qualité d'une solution. Les résultats numériques montrent une augmentation jusqu'à 10% de la valeur de la fonction économique.

Irrigation with Treated Wastewater: Potential Impacts on Microbial Function and Diversity in Agricultural Soils

The reuse of treated wastewater could be a promising measure to attenuate the water scarcity burden. In agriculture, irrigation with wastewater may contribute to improve production yields, reduce the ecological footprint and promote socioeconomic benefits. However, it cannot be considered exempt of adverse consequences in environmental and human health. Apart from the introduction of some biological and chemical hazardous agents, the disturbance of the indigenous soil microbial communities and, thus, of vital soil functions impacting soil fertility may occur. The consequences of these disturbances are still poorly understood. This chapter summarises the physicochemical and microbiological alterations in soil resultant from irrigation with treated wastewater that are described in scientific literature. These alterations, which involve a high complexity of variables (soil, wastewater, climate, vegetal cover), may have impacts on soil quality and productivity. In addition, possible health risks may arise, in particular through the direct or indirect contamination of the food chain with micropollutants, pathogens or antibiotic resistance determinants. The current state of the art suggests that irrigation with treated wastewater may have a multitude of long-term implications on soil productivity and public health. Although further research is needed, it seems evident that the analysis of risks associated with irrigation with treated wastewater must take into account not only the quality of water, but other aspects as diverse as soil microbiota, soil type or the cultivated plant species.

MicroRNA modulation of aldosterone production in the adrenal gland

Hypertension is the major risk factor for coronary disease worldwide. Primary hypertension is idiopathic in origin but is thought to arise from multiple risk factors including genetic, lifestyle and environmental influences. Secondary hypertension has a more definite aetiology; its major single cause is primary aldosteronism (PA), the greatest proportion of which is caused by aldosteroneproducing adenoma (APA), where aldosterone is synthesized at high levels by an adenoma of the adrenal gland. There is strong evidence to show that high aldosterone levels cause adverse effects on cardiovascular, cerebrovascular, renal and other systems. Extensive studies have been conducted to analyse the role that regulation of CYP11B2, the gene encoding the aldosterone synthase enzyme plays in determining aldosterone production and the development of hypertension. One significant regulatory factor that has only recently emerged is microRNA (miRNA). miRNAs are small non-coding RNAs, synthesized by a series of enzymatic processes, that negatively regulate gene expression at the posttranscriptional level. Detection and manipulation of miRNA is now known to be a viable method in the treatment, prevention and prognosis of certain diseases. The aim of the present study was to identify miRNAs likely to have a role in the regulation of corticosteroid biosynthesis. To achieve this, the miRNA profile of APA and normal human adrenal tissue was compared, as was the H295R adrenocortical cell line model of adrenocortical function, under both basal conditions and following stimulation of aldosterone production. Key differentially-expressed miRNAs were then identified and bioinformatic tools used to identify likely mRNA targets and pathways for these miRNAs, several of which were investigated and validated using in vitro methods. The background to this study is set out in Chapter 1 of this thesis, followed by a description of the major technical methods employed in Chapter 2. Chapter 3 presents the first of the study results, analysing differences in miRNA profile between APA and normal human adrenal tissue. Microarray was implemented to detect the expression of miRNAs in these two tissue types and several miRNAs were found to vary significantly and consistently between them. Furthermore, members of several miRNA clusters exhibited similar changes in expression pattern between the two tissues e.g. members of cluster miR-29b-1 (miR-29a-3p and miR-29b-3p) and of cluster miR-29b-2 (miR-29b-3p and miR-29c- 3p) are downregulated in APA, while members of cluster let-7a-1 (let-7a-5p and let-7d-5p), cluster let-7a-3 (let-7a-5p and let-7b-5p) and cluster miR-134 (miR- 134 and miR-382) are upregulated. Further bioinformatic analysis explored the possible biological function of these miRNAs using Ingenuity® Systems Pathway Analysis software. This led to the identification of validated mRNAs already known to be targeted by these miRNAs, as well as the prediction of other mRNAs that are likely targets and which are involved in processes relevant to APA pathology including cholesterol synthesis (HMGCR) and corticosteroidogenesis (CYP11B2). It was therefore hypothesised that increases in miR-125a-5p or miR- 335-5p would reduce HMGCR and CYP11B2 expression. Chapter 4 describes the characterisation of H295R cells of different strains and sources (H295R Strain 1, 2, 3 and HAC 15). Expression of CYP11B2 was assessed following application of 3 different stimulants: Angio II, dbcAMP and KCl. The most responsive strain to stimulation was Strain 1 at lower passage numbers. Furthermore, H295R proliferation increased following Angio II stimulation. In Chapter 5, the hypothesis that increases in miR-125a-5p or miR-335-5p reduces HMGCR and CYP11B2 expression was tested using realtime quantitative RT-PCR and transfection of miRNA mimics and inhibitors into the H295R cell line model of adrenocortical function. In this way, miR-125a-5p and miR-335-5p were shown to downregulate CYP11B2 and HMGCR expression, thereby validating certain of the bioinformatic predictions generated in Chapter 3. The study of miRNA profile in the H295R cell lines was conducted in Chapter 6, analysing how it changes under conditions that increase aldosterone secretion, including stimulation Angiotensin II, potassium chloride or dibutyryl cAMP (as a substitute for adrenocorticotropic hormone). miRNA profiling identified 7 miRNAs that are consistently downregulated by all three stimuli relative to basal cells: miR-106a-5p, miR-154-3p, miR-17-5p, miR-196b-5p, miR-19a-3p, miR-20b- 5p and miR-766-3p. These miRNAs include those derived from cluster miR-106a- 5p/miR-20b-5p and cluster miR-17-5p/miR-19a-3p, each producing a single polycistronic transcript. IPA bioinformatic analysis was again applied to identify experimentally validated and predicted mRNA targets of these miRNAs and the key biological pathways likely to be affected. This predicted several interactions between miRNAs derived from cluster miR-17-5p/miR-19a-3p and important mRNAs involved in cholesterol biosynthesis: LDLR and ABCA1. These predictions were investigated by in vitro experiment. miR-17-5p/miR-106a-p and miR-20b-5p were found to be consistently downregulated by stimulation of aldosterone biosynthesis. Moreover, miR-766-3p was upregulation throughout. Furthermore, I was able to validate the downregulation of LDLR by miR-17 transfection, as predicted by IPA. In summary, this study identified key miRNAs that are differentially-expressed in vivo in cases of APA or in vitro following stimulation of aldosterone biosynthesis. The many possible biological actions these miRNAs could have were filtered by bioinformatic analysis and selected interactions validated in vitro. While direct actions of these miRNAs on steroidogenic enzymes were identified, cholesterol handling also emerged as an important target and may represent a useful point of intervention in future therapies designed to modulate aldosterone biosynthesis and reduce its harmful effects.

Molecular probes for monitoring mitochondrial movement and function

This thesis explores two distinct parts of mitochondrial physiology: the role of mitochondria in generation of reactive oxygen species (ROS) and mitochondrial morphology and dynamics within cells. The first area of research is covered in Chapters 1-8. Mitochondrial biofunctionality and ROS production are discussed in Chapter 1, followed by the strategy of targeting bioactive compounds to mitochondria by linking them to lipophilic triphenylphosphonium cations (TPP) (Chapter 2). ROS sensors relevant to the research are reviewed in Chapter 3. Chapter 4 presents design and synthesis of novel probes for superoxide detection in mitochondria (MitoNeo-D), cytosol (Neo-D) and extracellular environment (ExCellNeo-D). The results of biological validation of MitoNeo-D and Neo-D performed in the MRC MBU in Cambridge are presented in Chapter 5. A dicationic hydrogen peroxide sensor that utilizes in situ click chemistry is discussed in Chapter 6. Preliminary work on the synthesis of mitochondria-targeted superoxide generators, which led to the development of mitochondria-targeted analogue of paraquat, MitoPQ, is presented in Chapter 7. A set of bifunctional probes (BCN-Mal, BCN-E-BCN and Mito-iTag) for assessing the redox states of protein thiols is discussed in Chapter 8 along with their biological validation. The second part of the thesis is aimed at the study of mitochondrial morphology and dynamics and is presented in Chapters 9-11. Chapter 9 provides background on the classes of fluorophores relevant to the research, the phenomenon of fluorescence quenching and the principle of photoactivation with examples of photoactivatable fluorophores. Next, the background on mitochondrial morphology and heterogeneity is presented in Chapter 10, followed by the ways of imaging and tracking mitochondria within cells by conventional fluorophores and by photoactivatable fluorophores exploiting super-resolution microscopy. Chapter 11 presents the design and synthesis of four photoactivatable fluorophores for mitochondrial tracking, MitoPhotoRhod110, MitoPhotoNIR, Photo-E+, MitoPhoto-E+, along with results of biological validation of MitoPhotoNIR. The results and discussion concludes with Chapter 12, which is a summary and suggestions for future work, followed by the chemistry experimental procedures (Chapter 13), materials and methods for biological experiments (Chapter 14) and references.

Assessment of the Availability of Forest Biomass for Bioenergy Production in Southwest Portugal.

In 2014, Portugal was the seventh largest pellets producer in the World. Since the shortage of raw material is one of the major obstacles that the Portuguese sellets market faces, the need for a good assessment of biomass availability for energy purposes at both country and regional levels is reinforced. This work uses a Geographical Information System environment and remote sensing data to assess the availability and sustainability of forest biomass residues in a management unit with around 940 ha of maritime pine forest. The period considered goes from 2004 to 2015. The study area is located in Southwestern Portugal, close to a pellets factory; therefore the potential Contribution of the residual biomass generated in the management unit to the production of pellets is evaluated. An allometric function is used for the estimation of maritime pine above ground biomass. With this estimate, and considering several forest operations, the residual biomass available was assessed, according to stand composition and structure. This study shows that, when maritime pine forests are managed to produce wood, the amount of residues available for energy production is small (an average of 0.37 t ha -1  year -1 were generated in the study area between 2004 and 2015). As a contribution to the sustainability of the Portuguese pellets industries, new management models for maritime pine forests may be developed. The effect of the pinewood nematode on the availability of residual biomass can be clearly seen in this study. In the management unit considered, cuts were made to prevent dissemination of the disease. This contributes to a higher availability of forest residues in a specific period of time, but, in the medium term, they lead to a decrease in the amount of residues that can be used for energy purposes.

Advances on apple production under semiarid climate: N fertigation

The fertilizing management for apple tree is essential, especially for nitrogen, one of the most important nutrients affecting fruit yield. Thus, an experiment was conducted in 2012 and 2013 to evaluate the fruit production, yield and leaf chlorophyll of ?Princesa? and ?Eva? apples as a function of nitrogen fertigation under Brazilian semiarid conditions. The experimental design consisted of randomised blocks, with treatments distributed in a factorial arrangement 2 x 4, corresponding to apple cultivars (Eva and Princesa); and nitrogen doses (160, 120, 80 and 40 kg of N ha-1), with four replications and three plants. Calcium nitrate was used as nitrogen source (15.5% of N) with applications twice a week during 40 days, reaching 12 fertilizing performances through irrigation water. The following variables were evaluated: i) fruit production per plant (kg plant-1); ii) fruit yield (t ha-1); iii) number of fruits per plant; iv) leaf chlorophyll meter readings (index); and v) leaf nitrogen concentration (g kg-1). Princesa apple cultivar if compared to ?Eva? presents a better fruit production performance under Brazilian semiarid. Furthermore, nitrogen doses fertilized through irrigation water have no effect on fruit production of Eva and Princesa apple cultivars during the first production cycle.

Changes in enzymatic activity, accumulation of proteins and softening of persimmon (Diospyros kaki Thunb.) flesh as a function of pre-cooling acclimatization.

One of the major causes of ?Fuyu? persimmon loss after cold storage (CS) is the breakdown of its flesh, which results in the production of a translucent fruit (a water-soaked fruit). It is believed that the cause of this disturbance is linked to disorganization of the cytoskelet and endomembrane system, which changes the synthesis and transport of proteins and metabolites, resulting in incomplete ripening. To test this hypothesis, ?Fuyu? persimmon was subjected to three different postharvest treatments (T): Control ? harvested and kept at 23±3 ◦C and relative humidity (RH) of 85±5% (room temperature, RT) for 12 days, T1 ? harvested and kept under cold storage (CS) (1±1 ◦C and RH of 85±5%) for 30 days followed by RT storage for 2 days, T2 ? kept under RT for 2 days (acclimatization) followed by CS for 30 days. Control and T2 resulted in fruit with decreased flesh firmness (FF), and increased soluble solids (SS) and ascorbic acid (AA) contents. In these fruit the activity of endo-1,4-ß-glucanase (endo-1,4-ß-gluc), pectin methylesterase (PME), polygalacturonase (PG) and ß-galactosidase (ß-gal) increased. T1 resulted in translucent fruit with decreased FF, without any enzymatic activity changes, probably due to the physical disruption of the cytoskeleton. Further, there was an increased content of proteins corresponding to expansins in fruit kept under Control and T2 conditions, which suggests that these conditions do contribute to the synthesis and/or transport of proteins involved in the process of solubilization of the cell wall. In these fruit, there was also a major accumulation of gene transcripts corresponding to heat shock proteins (HSPs) of organelles related to endomembrane, which suggests participation of these genes in the prevention of damage caused by cold conditions. These data proved the hypotheses that acclimatization contributes to the expression of HSPs, and synthesis and transportat of proteins involved in the solubilization of the cell wall. The expression of these genes results in the normal ripening of the persimmon, as confirmed by the evolution of ethylene production.

Gene expression and genome-wide association studies analysis to select heavy pigs for protected designation of origin cured meats production

The high quality of protected designation of origin (PDO) dry-cured pork products depends largely on the chemical and physical parameters of the fresh meat and their variation during the production process of the final product. The discovery of the mechanisms that regulate the variability of these parameters was aided by the reference genome of swine adjuvant to genetic analysis methods. This thesis can contribute to the discovery of genetic mechanisms that regulate the variability of some quality parameters of fresh meat for PDO dry-cured pork production. The first study is of gene expression and showed that between low and high glycolytic potential (GP) samples of Semimembranosus muscle of Italian Large White (ILW) pigs in early postmortem, the differentially expressed genes were all but one over expressed in low GP. These were involved in ATP biosynthesis processes, calcium homeostasis, and lipid metabolism including the potential master regulator gene Peroxisome Proliferator-Activated Receptor Alpha (PPARA). The second is a study in commercial hybrid pigs to evaluate correlations between carcass and fresh ham traits, including carcass and fresh ham lean meat percentages, the former, a potential predictor of the latter. In addition, a genome-wide association study allowed the identification of chromosome-wide associations with phenotypic traits for 19 SNPs, and genome-wide associations for 14 SNPs for ferrochelatase activity. The latter could be a determinant for color variation in nitrite-free dry-cured ham. The third study showed gene expression differences in the Longissimus thoracis muscle of ILW pigs by feeding diets with extruded linseed (source of polyunsaturated fatty acids) and vitamin E and selenium (diet three) or natural (diet four) antioxidants. The diet three promoted a more rapid and massive immune system response possibly determined by improvement in muscle tissue function, while the diet four promoted oxidative stability and increased the anti-inflammatory potential of muscle tissue.

A deep learning model for controlling the galvanizing process in a production line

In the industry of steelmaking, the process of galvanizing is a treatment which is applied to protect the steel from corrosion. The air knife effect (AKE) occurs when nozzles emit a steam of air on the surfaces of a steel strip to remove excess zinc from it. In our work we formalized the problem to control the AKE and we implemented, with the R&D dept.of MarcegagliaSPA, a DL model able to drive the AKE. We call it controller. It takes as input the tuple : a tuple of the physical conditions of the process line (t,h,s) with the target value of the zinc coating (c); and generates the expected tuple of (pres and dist) to drive the mechanical nozzles towards the (c). According to the requirements we designed the structure of the network. We collected and explored the data set of the historical data of the smart factory. Finally, we designed the loss function as sum of three components: the minimization between the coating addressed by the network and the target value we want to reach; and two weighted minimization components for both pressure and distance. In our solution we construct a second module, named coating net, to predict the coating of zinc resulting from the AKE when the conditions are applied to the prod. line. Its structure is made by a linear and a deep nonlinear “residual” component learned by empirical observations. The predictions made by the coating nets are used as ground truth in the loss function of the controller. By tuning the weights of the different components of the loss function, it is possible to train models with slightly different optimization purposes. In the tests we compared the regularization of different strategies with the standard one in condition of optimal estimation for both; the overall accuracy is ± 3 g/m^2 dal target for all of them. Lastly, we analyze how the controller modeled the current solutions with the new logic: the sub-optimal values of pres and dist can be optimize of 50% and 20%.