Recursive state and parameter estimation of COVID-19 circulating variants dynamics.

COVID-19 pandemic response with non-pharmaceutical interventions is an intrinsic control problem. Governments weigh social distancing policies to avoid overload in the health system without significant economic impact. The mutability of the SARS-CoV-2 virus, vaccination coverage, and mobility restriction measures change epidemic dynamics over time. A model-based control strategy requires reliable predictions to be efficient on a long-term basis. In this paper, a SEIR-based model is proposed considering dynamic feedback estimation. State and parameter estimations are performed on state estimators using augmented states. Three methods were implemented: constrained extended Kalman filter (CEKF), CEKF and smoother (CEKF & S), and moving horizon estimator (MHE). The parameters estimation was based on vaccine efficacy studies regarding transmissibility, severity of the disease, and lethality. Social distancing was assumed as a measured disturbance calculated using Google mobility data. Data from six federative units from Brazil were used to evaluate the proposed strategy. State and parameter estimations were performed from 1 October 2020 to 1 July 2021, during which Zeta and Gamma variants emerged. Simulation results showed that lethality increased between 11 and 30% for Zeta mutations and between 44 and 107% for Gamma mutations. In addition, transmissibility increased between 10 and 37% for the Zeta variant and between 43 and 119% for the Gamma variant. Furthermore, parameter estimation indicated temporal underreporting changes in hospitalized and deceased individuals. Overall, the estimation strategy showed to be suitable for dynamic feedback as simulation results presented an efficient detection and dynamic characterization of circulating variants.

Evaluation of the optimal performance of ModiCon and ModiCon+VariCol simulated moving bed variants.

The interest in the simulated moving bed (SMB) technology lies in its variants. Some of them that have a high potential to increase the performance in enantioseparations are the ModiCon and the ModiCon+VariCol. These variants are based on the modulation of feed concentration and a combination of feed concentration and length of zones modulations. The concept of the ModiCon process in the literature is that it can be applied only for systems described by nonlinear isotherms. However, there are no numerical or experimental studies that prove that. On the other hand, the hybrid operation of ModiCon+VariCol can be used in systems with a low number of columns due to the flexibility in the use of columns, but it has been little explored. In this work, the maximal performance of the ModiCon process was compared with the SMB process for a linear isotherm. Additionally, the ModiCon+VariCol process was evaluated in systems with a low number of columns. The enantioseparation of guaifenesin was considered as a case study. The result shows that the ModiCon process can also be applied with high performance in systems described by linear isotherms. In the evaluation of the ModiCon+VariCol process for unequal product purity, it was found that the hybrid operation with 3 columns showed a higher throughput and productivity than the SMB process with 6 columns. The productivity of the ModiCon+VariCol was more than three times higher than the conventional operation.

Optimal performance comparison of the simulated moving bed process variants based on the modulation of the length of zones and the feed concentration.

The VariCol and ModiCon processes are two variants of the simulated moving bed (SMB) process, characterized by the modulation of the length of zones of the chromatographic column train and the feed concentration. These features give more flexibility than the conventional operation, leading to essential improvements in the separation and purification of mixtures. The optimal performance comparison of these two variants, the hybrid formed by their combination, and the conventional SMB process are scarce in the literature. This comparison helps discover new characteristics of each single and combined operation mode and creates guidelines to select the appropriate operation mode for possible real applications. In this work, the performance comparison of the ModiCon, VariCol, ModiCon+VariCol, and SMB processes is carried out in terms of maximal throughput for specific product purity values. Particular emphasis is placed on both the ModiCon and the hybrid ModiCon+VariCol processes characteristics. A strategy for combining and optimizing the ModiCon and the VariCol processes was determined. As a case study, the enantioseparation of guaifenesin was considered. In the ModiCon process, more than two modulation subintervals did not improve the performance in the separation. The optimal pattern, based on two subintervals, has zero feed concentration in the first subinterval and the maximal concentration in the second one. The best result for the hybrid operation (ModiCon+VariCol) was reached when the feed port moves simultaneously as the SMB process switching period. The optimal throughput of the ModiCon and the ModiCon+VariCol processes was almost doubled than that of the SMB process. These performances were based on larger zones I and II and not in zones II and III as occur with the SMB and VariCol process. The throughput in the hybrid operation increases more significantly than the ModiCon process when 5 columns were considered instead of 6. The hybrid operation could be more attractive for a system with a few numbers of columns.

One-step optimization strategy in the simulated moving bed process with asynchronous movement of ports: A VariCol case study.

The VariCol process is a variant of the conventional simulated moving bed (SMB) process, distinguished by the asynchronous shifting of the inlet and outlet ports of the chromatographic column train. This feature allows for a more flexible operation in column utilization and can also achieve higher separation performances. However, to take full benefit out of it, the operating parameters, such as the strategy for port switching, must be optimal. in this paper, a novel methodology for optimizing those parameters, based on a single NLP (non-linear programming), is proposed. The main advantage of this approach is that it significantly reduces the complexity of the original MINLP (mixed-integer non-linear programming) formulation currently discussed in the literature. The proposed optimization problem is built, considering that the average column configuration of three zones provides the necessary and sufficient information to describe the VariCol process. Several optimization scenarios for the enantioseparation of 1,1´-bi-2-naphthol and aminoglutethimide were considered to evaluate the proposed methodology and to compare the performance of VariCol and SMB processes. The results have shown that with the single NLP approach, it is possible to explore the optimal solution in all the VariCol process domains with less computational effort than other optimization strategies reported in the literature. That is a great advantage, especially in the context of real-time applications.

Simultaneous parameters identifiability and estimation of an E. coli metabolic network model.

This work proposes a procedure for simultaneous parameters identifiability and estimation in metabolic networks in order to overcome difficulties associated with lack of experimental data and large number of parameters, a common scenario in the modeling of such systems. As case study, the complex real problem of parameters identifiability of the Escherichia coli K-12 W3110 dynamic model was investigated, composed by 18 differential ordinary equations and 35 kinetic rates, containing 125 parameters. With the procedure, model fit was improved for most of the measured metabolites, achieving 58 parameters estimated, including 5 unknown initial conditions. The results indicate that simultaneous parameters identifiability and estimation approach in metabolic networks is appealing, since model fit to the most of measured metabolites was possible even when important measures of intracellular metabolites and good initial estimates of parameters are not available.