Processes — Open Access Journal

Electrical stimulation is ubiquitous as a method for activating neuronal tissue, but there is still significant room for advancement in the ability of these electrical devices to implement smart stimulus waveform design to more selectively target populations of neurons. The capability of a device to encode more complicated and precise messages to a neuronal network greatly increases if the stimulus input space is broadened to include variable shaped waveforms and multiple stimulating electrodes. The relationship between a stimulating electrode and the activated population is unknown; a priori. For that reason, the population of excitable neurons must be characterized in real-time and for every combination of stimulating electrodes and neuronal populations. Our automated experimental system allows investigation into the stimulus-evoked neuronal response to a current pulse using dissociated neuronal cultures grown atop microelectrode arrays (MEAs). The studies presented here demonstrate that differential activation is achievable between two neurons using either multiple stimulating electrodes or variable waveform shapes. By changing the aspect ratio of a rectangular current pulse; the stimulus activated neurons in the strength–duration (SD) waveform space with differing probabilities. Additionally, in the case when two neuronal activation curves intersect each other in the SD space; one neuron can be selectively activated with short-pulse-width; high-current stimuli while the other can be selectively activated with long-pulse-width; low-current stimuli. Exploring the capabilities and limitations of electrical stimulation allows for improvements to the delivery of stimulus pulses to activate neuronal populations. Many state-of-the-art research and clinical stimulation solutions, including those using a single microelectrode, can benefit from waveform design methods to improve stimulus efficacy. These findings have even greater import into multi-electrode systems because spatially distributed electrodes further enhance accessibility to differential neuronal activation. Full article

Background: Magnetic fields can interact with liquid matter in a homogeneous and instantaneous way, without physical contact, independently of its temperature, pressure, and agitation degree, and without modifying recipes nor heat and mass transfer conditions. In addition, magnetic fields may affect the mechanisms of generation and termination of free radicals. This paper is devoted to the elucidation of the appropriate conditions needed to develop magnetic field effects for controlling the kinetics of polymerization of water soluble monomers. Methods: Thermal- and photochemically-initiated polymerizations were investigated at different initiator and monomer concentrations, temperatures, viscosities, and magnetic field intensities. Results: Significant magnetic field impact on the polymerization kinetics was only observed in photochemically-initiated polymerizations carried out in viscous media and performed at relatively low magnetic field intensity. Magnetic field effects were absent in polymerizations in low viscosity media and thermally-initiated polymerizations performed at low and high magnetic field intensities. The effects were explained in terms of the radical pair mechanism for intersystem crossing of spin states. Conclusion: Polymerization kinetics of water soluble monomers can be potentially controlled using magnetic fields only under very specific reaction conditions. Full article

The gut microbiome is a highly complex microbial community that strongly impacts human health and disease. The two dominant phyla in healthy humans are Bacteroidetes and Firmicutes, with minor phyla such as Proteobacteria having elevated abundances in various disease states. While the gut microbiome has been widely studied, relatively little is known about the role of interspecies interactions in promoting microbiome stability and function. We developed a biofilm metabolic model of a very simple gut microbiome community consisting of a representative bacteroidete (Bacteroides thetaiotaomicron), firmicute (Faecalibacterium prausnitzii) and proteobacterium (Escherichia coli) to investigate the putative role of metabolic byproduct cross feeding between species on community stability, robustness and flexibility. The model predicted coexistence of the three species only if four essential cross-feeding relationships were present. We found that cross feeding allowed coexistence to be robustly maintained for large variations in biofilm thickness and nutrient levels. However, the model predicted that community composition and short chain fatty acid levels could be strongly affected only over small ranges of byproduct uptake rates, indicating a possible lack of flexibility in our cross-feeding mechanism. Our model predictions provide new insights into the impact of byproduct cross feeding and yield experimentally testable hypotheses about gut microbiome community stability. Full article

As the demand for textile products and synthetic dyes increases with the growing global population, textile dye wastewater is becoming one of the most significant water pollution contributors. Azo dyes represent 70% of dyes used worldwide, and are hence a significant contributor to textile waste. In this work, the removal of a reactive azo dye (Reactive Orange 16) from water by adsorption with chitosan grafted poly(poly(ethylene glycol) methyl ether methacrylate) (CTS-GMA-g-PPEGMA) was investigated. The chitosan (CTS) was first functionalized with glycidyl methacrylate and then grafted with poly(poly(ethylene glycol) methyl ether methacrylate) using a nitroxide-mediated polymerization grafting to approach. Equilibrium adsorption experiments were carried out at different initial dye concentrations and were successfully fitted to the Langmuir and Freundlich adsorption isotherm models. Adsorption isotherms showed maximum adsorption capacities of CTS-g-GMA-PPEGMA and chitosan of 200 mg/g and 150 mg/g, respectively, while the Langmuir equations estimated 232 mg/g and 194 mg/g, respectively. The fundamental assumptions underlying the Langmuir model may not be applicable for azo dye adsorption, which could explain the difference. The Freundlich isotherm parameters, n and K, were determined to be 2.18 and 17.7 for CTS-g-GMA-PPEGMA and 0.14 and 2.11 for chitosan, respectively. An “n” value between one and ten generally indicates favorable adsorption. The adsorption capacities of a chitosan-PPEGMA 50/50 physical mixture and pure PPEGMA were also investigated, and both exhibited significantly lower adsorption capacities than pure chitosan. In this work, CTS-g-GMA-PPEGMA proved to be more effective than its parent chitosan, with a 33% increase in adsorption capacity. Full article

The process of oxygenic photosynthesis is robust and ubiquitous, relying centrally on input of light, carbon dioxide, and water, which in many environments are all abundantly available, and from which are produced, principally, oxygen and reduced organic carbon. However, photosynthetic machinery can be conflicted by the simultaneous presence of carbon dioxide and oxygen through a process sometimes called photorespiration. We present here a model of phototrophy, including competition for RuBisCO binding sites between oxygen and carbon dioxide, in a chemostat-based microbial population. The model connects to the idea of metabolic pathways to track carbon and degree of reduction through the system. We find decomposition of kinetics into elementary flux modes a mathematically natural way to study synchronization of mismatched rates of photon input and chemostat turnover. In the single species case, though total biomass is reduced by photorespiration, protection from excess light exposures and its consequences (oxidative and redox stress) may result. We also find the possibility that a consortium of phototrophs with heterotrophs can recycle photorespiration byproduct into increased biomass at the cost of increase in oxidative product (here, oxygen). Full article

Nonlinear model predictive control has been established as a powerful methodology to provide feedback for dynamic processes over the last decades. In practice it is usually combined with parameter and state estimation techniques, which allows to cope with uncertainty on many levels. To reduce the uncertainty it has also been suggested to include optimal experimental design into the sequential process of estimation and control calculation. Most of the focus so far was on dual control approaches, i.e., on using the controls to simultaneously excite the system dynamics (learning) as well as minimizing a given objective (performing). We propose a new algorithm, which sequentially solves robust optimal control, optimal experimental design, state and parameter estimation problems. Thus, we decouple the control and the experimental design problems. This has the advantages that we can analyze the impact of measurement timing (sampling) independently, and is practically relevant for applications with either an ethical limitation on system excitation (e.g., chemotherapy treatment) or the need for fast feedback. The algorithm shows promising results with a 36% reduction of parameter uncertainties for the Lotka-Volterra fishing benchmark example. Full article

We present a sensitivity-based predictor-corrector path-following algorithm for fast nonlinear model predictive control (NMPC) and demonstrate it on a large case study with an economic cost function. The path-following method is applied within the advanced-step NMPC framework to obtain fast and accurate approximate solutions of the NMPC problem. In our approach, we solve a sequence of quadratic programs to trace the optimal NMPC solution along a parameter change. A distinguishing feature of the path-following algorithm in this paper is that the strongly-active inequality constraints are included as equality constraints in the quadratic programs, while the weakly-active constraints are left as inequalities. This leads to close tracking of the optimal solution. The approach is applied to an economic NMPC case study consisting of a process with a reactor, a distillation column and a recycler. We compare the path-following NMPC solution with an ideal NMPC solution, which is obtained by solving the full nonlinear programming problem. Our simulations show that the proposed algorithm effectively traces the exact solution. Full article

The complete error-in-variables-model (EVM) framework, consisting of both design of experiments and parameter estimation stages, is applied to the terpolymerization of 2-acrylamido-2-methylpropane sulfonic acid (AMPS, M₁), acrylamide (AAm, M₂) and acrylic acid (AAc, M₃). This water-soluble terpolymer has potential for applications in enhanced oil recovery, but the associated terpolymerization kinetic characteristics are largely unstudied. In the current paper, EVM is used to design optimal experiments (for the first time in the literature), and reactivity ratios are subsequently estimated based on both low and medium-high conversion data. The results from the medium-high conversion data are more precise than those from the low conversion data, and are therefore used next to predict the terpolymer composition trajectory over the full course of conversion. Good agreement is seen between experimental data and model predictions, which confirms the accuracy of the newly determined ternary reactivity ratios: r₁₂ = 0.66, r₂₁ = 0.82, r₁₃ = 0.82, r₃₁ = 0.61, r₂₃ = 1.61, r₃₂ = 0.25. Full article

Nitroxide-mediated polymerization using the succinimidyl ester functional unimolecular alkoxyamine initiator (NHS-BlocBuilder) was used to first copolymerize tert-butyl methacrylate/2-vinylpyridine (tBMA/2VP) with low dispersity (Đ = 1.30–1.41) and controlled growth (linear number average molecular M_n versus conversion, M_n = 3.8–10.4 kg·mol⁻¹) across a wide composition of ranges (initial mol fraction 2VP, f_2VP,0 = 0.10–0.90). The resulting statistical copolymers were first de-protected to give statistical polyampholytic copolymers comprised of methacrylic acid/2VP (MAA/2VP) units. These copolymers exhibited tunable water-solubility due to the different pKas of the acidic MAA and basic 2VP units; being soluble at very low pH < 3 and high pH > 8. One of the tBMA/2VP copolymers was used as a macroinitiator for a 4-acryloylmorpholine/4-acryloylpiperidine (4AM/4AP) mixture, to provide a second block with thermo-responsive behavior with tunable cloud point temperature (CPT), depending on the ratio of 4AM:4AP. Dynamic light scattering of the block copolymer at various pHs (3, 7 and 10) as a function of temperature indicated a rapid increase in particle size >2000 nm at 22–27 °C, corresponding to the 4AM/4AP segment’s thermos-responsiveness followed by a leveling in particle size to about 500 nm at higher temperatures. Full article

In this study, the effect of ultra-high-pressure homogenization (UHPH: 100 or 200 MPa at 25 °C), in comparison to colloid mill (CM: 5000 rpm at 20 °C) and conventional homogenization (CH: 15 MPa at 60 °C), on the stability of oil-in-water emulsions with different oil concentrations (10, 30 or 50 g/100 g) emulsified by whey protein isolate (4 g/100 g) was investigated. Emulsions were characterized for their microstructure, rheological properties, surface protein concentration (SPC), stability to creaming and oxidative stability under light (2000 lux/m²). UHPH produced emulsions containing lipid droplets in the sub-micron range (100–200 nm) and with low protein concentrations on droplet surfaces. Droplet size (d3.2, µm) was increased in CH and UHPH emulsions by increasing the oil concentration. CM emulsions exhibited Newtonian flow behaviour at all oil concentrations studied; however, the rheological behaviour of CH and UHPH emulsions varied from Newtonian flow (n ≈ 1) to shear-thinning (n ˂ 1) and thixotropic behaviour in emulsions containing 50% oil. This was confirmed by the non-significant differences in the d4.3 (µm) value between the top and bottom of emulsions in tubes left at room temperature for nine days and also by a low migration velocity measured with a Turbiscan LAB instrument. UHPH emulsions showed significantly lower oxidation rates during 10 days storage in comparison to CM and CH emulsions as confirmed by hydroperoxides and thiobarbituric acid-reactive substances (TBARS). UHPH emulsions treated at 100 MPa were less oxidized than those treated at 200 MPa. The results from this study suggest that UHPH treatment generates emulsions that have a higher stability to creaming and lipid oxidation compared to colloid mill and conventional treatments. Full article

Biofilms are spatially-structured communities of different microbes, which have a huge impact on both ecosystems and human life. Mathematical models are powerful tools for understanding the function and evolution of biofilms as diverse communities. In this article, we give a review of some recently-developed models focusing on the interactions of different species within a biofilm, the evolution of biofilm due to genetic and environmental causes and factors that affect the structure of a biofilm. Full article

This paper discusses the problems associated with the implementation of Real Time Optimization/Model Predictive Control (RTO/MPC) systems, taking as reference the hydrogen distribution network of an oil refinery involving eighteen plants. This paper addresses the main problems related to the operation of the network, combining data reconciliation and a RTO system, designed for the optimal generation and redistribution of hydrogen, with a predictive controller for the on-line implementation of the optimal policies. This paper describes the architecture of the implementation, showing how RTO and MPC can be integrated, as well as the benefits obtained in terms of improved information about the process, increased hydrocarbon load to the treatment plants and reduction of the hydrogen required for performing the operations. Full article

We address in the paper the problem of designing an economic model predictive control (EMPC) algorithm that asymptotically achieves the optimal performance despite the presence of plant-model mismatch. To motivate the problem, we present an example of a continuous stirred tank reactor in which available EMPC and tracking model predictive control (MPC) algorithms do not reach the optimal steady state operation. We propose to use an offset-free disturbance model and to modify the target optimization problem with a correction term that is iteratively computed to enforce the necessary conditions of optimality in the presence of plant-model mismatch. Then, we show how the proposed formulation behaves on the motivating example, highlighting the role of the stage cost function used in the finite horizon MPC problem. Full article

The modifier approach has been extensively explored and offers a theoretically-sound and practically-useful method to deploy real-time optimization. The recent directional-modifier adaptation algorithm offers a heuristic to tackle the modifier approach. The directional-modifier adaptation algorithm, supported by strong theoretical properties and the ease of deployment in practice, proposes a meaningful compromise between process optimality and quickly improving the quality of the estimation of the gradient of the process cost function. This paper proposes a novel view of the directional-modifier adaptation algorithm, as an approximation of the optimal trade-off between the underlying experimental design problem and the process optimization problem. It moreover suggests a minor modification in the tuning of the algorithm, so as to make it a more genuine approximation. Full article

This paper presents an overview of the recent developments of modifier-adaptation schemes for real-time optimization of uncertain processes. These schemes have the ability to reach plant optimality upon convergence despite the presence of structural plant-model mismatch. Modifier Adaptation has its origins in the technique of Integrated System Optimization and Parameter Estimation, but differs in the definition of the modifiers and in the fact that no parameter estimation is required. This paper reviews the fundamentals of Modifier Adaptation and provides an overview of several variants and extensions. Furthermore, the paper discusses different methods for estimating the required gradients (or modifiers) from noisy measurements. We also give an overview of the application studies available in the literature. Finally, the paper briefly discusses open issues so as to promote future research in this area. Full article

The expected world population growth by 2050 is likely to pose great challenges in the global food demand and, in turn, in the fertilizer consumption. The Food and Agricultural Organization of the United Nations has forecasted that 46% of this projected growth will be attributed to Africa. This, in turn, raises further concerns about the sustainability of Africa’s contemporary fertilizer production, considering also its high dependence on fertilizer imports. Based on these facts, a novel “green” route for the synthesis of fertilizers has been considered in the context of the African agriculture by means of plasma technology. More precisely, a techno-economic feasibility study has been conducted for a small-scale plasma-assisted nitric acid plant located in Kenya and South Africa with respect to the electricity provision by renewable energy sources. In this study, standalone solar and wind power systems, as well as a hybrid system, have been assessed for two different electricity loads against certain economic criteria. The relevant simulations have been carried out in HOMER software and the optimized configurations of each examined renewable power system are presented in this study. Full article

Quench hardening is the process of strengthening and hardening ferrous metals and alloys by heating the material to a specific temperature to form austenite (austenitization), followed by rapid cooling (quenching) in water, brine or oil to introduce a hardened phase called martensite. The material is then often tempered to increase toughness, as it may decrease from the quench hardening process. The austenitization process is highly energy-intensive and many of the industrial austenitization furnaces were built and equipped prior to the advent of advanced control strategies and thus use large, sub-optimal amounts of energy. The model computes the energy usage of the furnace and the part temperature profile as a function of time and position within the furnace under temperature feedback control. In this paper, the aforementioned model is used to simulate the furnace for a batch of forty parts under heuristic temperature set points suggested by the operators of the plant. A model predictive control (MPC) system is then developed and deployed to control the the part temperature at the furnace exit thereby preventing the parts from overheating. An energy efficiency gain of $5.3\%$ was obtained under model predictive control compared to operation under heuristic temperature set points tracked by a regulatory control layer. Full article

In this work, we consider the problem of daily production optimization in the upstream oil and gas domain. The objective is to find the optimal decision variables that utilize the production systems efficiently and maximize the revenue. Typically, mathematical models are used to find the optimal operation in such processes. However, such prediction models are subject to uncertainty that has been often overlooked, and the optimal solution based on nominal models can thus render the solution useless and may lead to infeasibility when implemented. To ensure robust feasibility, worst case optimization may be employed; however, the solution may be rather conservative. Alternatively, we propose the use of scenario-based optimization to reduce the conservativeness. The results of the nominal, worst case and scenario-based optimization are compared and discussed. Full article

In a previous study, the two nitrifying functions (ammonia oxidizing bacteria (AOB) or nitrite-oxidizing bacteria (NOB)) of a nitrification reactor—operated continuously over 525 days with varying inputs—were assigned using a mathematical modeling approach together with the monitoring of bacterial phylotypes. Based on these theoretical identifications, we develop here a chemostat model that does not explicitly include only the resources’ dynamics (different forms of soluble nitrogen) but also explicitly takes into account microbial inter- and intra-species interactions for the four dominant phylotypes detected in the chemostat. A comparison of the models obtained with and without interactions has shown that such interactions permit the coexistence of two competing ammonium-oxidizing bacteria and two competing nitrite-oxidizing bacteria in competition for ammonium and nitrite, respectively. These interactions are analyzed and discussed. Full article