Real-time experimental implementation of predictive control schemes in a small-scale pasteurization plant

Model predictive control (MPC) is one of the most used optimization-based control strategies for large-scale systems, since this strategy allows to consider a large number of states and multi-objective cost functions in a straightforward way. One of the main issues in the design of multi-objective MPC controllers, which is the tuning of the weights associated to each objective in the cost function, is treated in this work. All the possible combinations of weights within the cost function affect the optimal result in a given Pareto front. Furthermore, when the system has time-varying parameters, e.g., periodic disturbances, the appropriate weight tuning might also vary over time. Moreover, taking into account the computational burden and the selected sampling time in the MPC controller design, the computation time to find a suitable tuning is limited. In this regard, the development of strategies to perform a dynamical tuning in function of the system conditions potentially improves the closed-loop performance. In order to adapt in a dynamical way the weights in the MPC multi-objective cost function, an evolutionary-game approach is proposed. This approach allows to vary the prioritization weights in the proper direction taking as a reference a desired region within the Pareto front. The proper direction for the prioritization is computed by only using the current system values, i.e., the current optimal control action and the measurement of the current states, which establish the system cost function over a certain point in the Pareto front. Finally, some simulations of a multi-objective MPC for a real multi-variable case study show a comparison between the system performance obtained with static and dynamical tuning.Peer ReviewedPostprint (author's final draft

Assessment of loaded squat jump height with a free-weight barbell and Smith machine : comparison of the take-off velocity and flight time procedures

The aims of this study were to compare the reliability and magnitude of jump height between the two standard procedures of analysing force platform data to estimate jump height (take-off velocity [TOV] and flight time [FT]) in the loaded squat jump (SJ) exercise performed with a free-weight barbell and in a Smith machine. Twenty-three collegiate men (age 23.1 +/- 3.2 years, body mass 74.7 +/- 7.3 kg, height 177.1 +/- 7.0 cm) were tested twice for each SJ type (free-weight barbell and Smith machine) with 17, 30, 45, 60, and 75 kg loads. No substantial differences in reliability were observed between the TOV (Coefficient of variation [CV]: 9.88%; Intraclass correlation coefficient [ICC]: 0.82) and FT (CV: 8.68%; ICC: 0.88) procedures (CV ratio: 1.14), while the Smith SJ (CV: 7.74%; ICC: 0.87) revealed a higher reliability than the free-weight SJ (CV: 9.88%; ICC: 0.81) (CV ratio: 1.28). The TOV procedure provided higher magnitudes of jump height than the FT procedure for the loaded Smith machine SJ (systematic bias: 2.64 cm; P0.05). Heteroscedasticity of the errors was observed for the Smith machine SJ (r2: 0.177) with increasing differences in favour of the TOV procedure for the trials with lower jump height (i.e. higher external loads). Based on these results the use of a Smith machine in conjunction with the FT more accurately determine jump height during the loaded SJ

Exploring wind direction and SO2 concentration by circular-linear density estimation

The study of environmental problems usually requires the description of variables with different nature and the assessment of relations between them. In this work, an algorithm for flexible estimation of the joint density for a circular-linear variable is proposed. The method is applied for exploring the relation between wind direction and SO2 concentration in a monitoring station close to a power plant located in Galicia (NW-Spain), in order to compare the effectiveness of precautionary measures for pollutants reduction in two different years.Comment: 17 pages, 7 figures, 2 table

Kon-tiki/Perdido enhances PS2 integrin adhesion and localizes its ligand, Thrombospondin, in the myotendinous junction.

Cell-extracellular matrix adhesion is mediated by cell receptors, mainly integrins and transmembrane proteoglycans, which can functionally interact. How these receptors are regulated and coordinated is largely unknown and key to understand cell adhesion in development. We show that the conserved transmembrane proteoglycan Kon-tiki/Perdido (Kon) interacts with αPS2βPS integrin to mediate muscle-tendon adhesion. Double mutant embryos for kon and inflated show a synergistic increase in muscle detachment. Furthermore, Kon modulates αPS2βPS signaling at the muscle attachment, since P-Fak is reduced in kon mutants. This reduction in integrin signaling can be rescued by the expression of a truncated Kon protein containing the transmembrane and extracellular domains, suggesting that these domains are sufficient to mediate this signaling. We show that these domains are sufficient to properly localize the αPS2βPS ligand, Thrombospondin, to the muscle attachment, and to partially rescue Kon dependent muscle-tendon adhesion. We propose that Kon can engage in a protein complex with αPS2βPS and enhance integrin-mediated signaling and adhesion by recruiting its ligand, which would increase integrin-binding affinity to the extracellular matrix, resulting in the consolidation of the myotendinous junction.Ramón y Cajal program and the Universidad Pablo de Olavide. Research was funded by the Ministerio de Economıa y Competitividad ́ (Spanish Ministry of Science and Innovation) (BFU2008-036550, BFU2011-26745). Proyecto de Excelencia of the Consejerıa de Econom ́ ıa, ́ Innovación, Ciencia y Empleo, Junta de Andalucıa (PO9-CVI-5058). A.G.E.-Z. and ́ the Ministerio de Ciencia e Innovación (Spanish Ministry of Science and Innovation) (BFU2008-036550, BFU2011-26745)

A high fidelity Milky Way simulation with Kraken, Gaia-Enceladus, and Sequoia analogues: clues to their accretion histories

Within a simulated Milky Way-like galaxy, we identify and analyse analogues of the Gaia-Enceladus (GE), Kraken, and Sequoia mergers that each matches remarkably well observational results, including in velocity and chemical abundance space, and their distributions in the jz-Energy plane. The Kraken analogue is the earliest merger and has the highest total mass ratio. Consistent with previous studies, it is chemically indistinguishable from old in situ stars at the time of its accretion. The GE and Sequoia analogue events accrete at similar times in our simulation, both along filaments but from opposite sides of the main galaxy. The mean stellar ages of the GE and Sequoia analogues are both similar and, from our simulation results, we see that they can be separate entities and still naturally reproduce the observed properties of their stellar remnants at the present day, including the significant retrograde velocities of the Sequoia analogue remnant stars and the difference in the tracks of the two galaxies through chemical abundance space. Our results provide supporting information about the properties of these three merger events, and show for the first time that they can all be reproduced with a fully cosmological simulation, providing a possible self-consistent evolutionary pathway for the Milky Way’s formation

Inaugurating a Dutch Napoleon? Conservative criticism of the 1815 constitution of the United Kingdom of The Netherlands

International audienc

A Novel Stochastic Multi-Scale Model of Francisella tularensis Infection to Predict Risk of Infection in a Laboratory

We present a multi-scale model of the within-phagocyte, within-host and population-level infection dynamics of Francisella tularensis, which extends the mechanistic one proposed by Wood et al. (2014). Our multi-scale model incorporates key aspects of the interaction between host phagocytes and extracellular bacteria, accounts for inter-phagocyte variability in the number of bacteria released upon phagocyte rupture, and allows one to compute the probability of response, and mean time until response, of an infected individual as a function of the initial infection dose. A Bayesian approach is applied to parameterize both the within-phagocyte and within-host models using infection data. Finally, we show how dose response probabilities at the individual level can be used to estimate the airborne propagation of Francisella tularensis in indoor settings (such as a microbiology laboratory) at the population level, by means of a deterministic zonal ventilation model

Microbial Succession in the Gut: Directional Trends of Taxonomic and Functional Change in a Birth Cohort of Spanish Infants

In spite of its major impact on life-long health, the process of microbial succession in the gut of infants remains poorly understood. Here, we analyze the patterns of taxonomic and functional change in the gut microbiota during the first year of life for a birth cohort of 13 infants. We detect that individual instances of gut colonization vary in the temporal dynamics of microbiota richness, diversity, and composition at both functional and taxonomic levels. Nevertheless, trends discernible in a majority of infants indicate that gut colonization occurs in two distinct phases of succession, separated by the introduction of solid foods to the diet. This change in resource availability causes a sharp decrease in the taxonomic richness of the microbiota due to the loss of rare taxa (p = 2.06e-9), although the number of core genera shared by all infants increases substantially. Moreover, although the gut microbial succession is not strictly deterministic, we detect an overarching directionality of change through time towards the taxonomic and functional composition of the maternal microbiota. Succession is however not complete by the one year mark, as significant differences remain between one-year-olds and their mothers in terms of taxonomic (p = 0.009) and functional (p = 0.004) microbiota composition, and in taxonomic richness (p = 2.76e-37) and diversity (p = 0.016). Our results also indicate that the taxonomic composition of the microbiota shapes its functional capacities. Therefore, the observed inter-individual variability in taxonomic composition during succession is not fully compensated by functional equivalence among bacterial genera and may have important physiological consequences. Finally, network analyses suggest that positive interactions among core genera during community assembly contribute to ensure their permanence within the gut, and highlight an expansion of complexity in the interactions network as the core of taxa shared by all infants grows following the introduction of solid foods

A Study of Archiving Strategies in Multi-Objective PSO for Molecular Docking

Molecular docking is a complex optimization problem aimed at predicting the position of a ligand molecule in the active site of a receptor with the lowest binding energy. This problem can be formulated as a bi-objective optimization problem by minimizing the binding energy and the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands. In this context, the SMPSO multi-objective swarm-intelligence algorithm has shown a remarkable performance. SMPSO is characterized by having an external archive used to store the non-dominated solutions and also as the basis of the leader selection strategy. In this paper, we analyze several SMPSO variants based on different archiving strategies in the scope of a benchmark of molecular docking instances. Our study reveals that the SMPSOhv, which uses an hypervolume contribution based archive, shows the overall best performance.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A Model to Define an eHealth Technological Ecosystem for Caregivers

The ageing of world population has a direct impact on the health and care systems, as it means an increase in the number of people needing care which leads to higher care costs and the need for more resources. In this context, informal caregivers play an important role as they enable dependent persons to stay at home and thus reduce care costs. However, long-term continuous care provision has also an impact in the physical and mental health of the caregivers. Moreover, geographical barriers make it difficult for caregivers to accessing psychoeducation as a way to alleviate their problems. To support caregivers in their needs and provide specialized training, technology plays a fundamental role. The present work provides the theoretical basis for the development of a technological ecosystem focused on learning and knowledge management processes to develop and enhance the caregiving competences of formal and informal caregivers, both at home and in care environments. In particular, a platform-specific model to support the definition of the ecosystem based on Open Source software components is presented, along with a Business Model Canvas to define the business structure as part of the human elements of the technological ecosystem