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Processes, Volume 5, Issue 4 (December 2017)

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Cover Story (view full-size image) The study of radical copolymerization in water is challenging due to the influence of both solvent [...] Read more.
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Open AccessArticle Systematic and Model-Assisted Evaluation of Solvent Based- or Pressurized Hot Water Extraction for the Extraction of Artemisinin from Artemisia annua L.
Processes 2017, 5(4), 86; https://doi.org/10.3390/pr5040086
Received: 24 November 2017 / Revised: 12 December 2017 / Accepted: 15 December 2017 / Published: 20 December 2017
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Abstract
In this study, the solvent based extraction of artemisinin from Artemisia annua L. using acetone in percolation mode is compared to the method of pressurized hot water extraction. Both techniques are simulated by a physico-chemical process model. The model as well as the
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In this study, the solvent based extraction of artemisinin from Artemisia annua L. using acetone in percolation mode is compared to the method of pressurized hot water extraction. Both techniques are simulated by a physico-chemical process model. The model as well as the model parameter determination, including the thermal degradation of artemisinin are shown and discussed. For the conventional extraction, a solvent screening is performed considering various organic solvents. A temperature screening is presented for the systematic design of the pressurized hot water extraction. The best temperature with regards to thermal decomposition and high productivity was found to be 80 °C. Both, conventional percolation and Pressurized Hot Water Extraction (PHWE) are suitable for the extraction of artemisinin. The extraction curves show a high conformity with the simulation results. Full article
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Open AccessFeature PaperArticle Efficient Control Discretization Based on Turnpike Theory for Dynamic Optimization
Processes 2017, 5(4), 85; https://doi.org/10.3390/pr5040085
Received: 12 November 2017 / Revised: 8 December 2017 / Accepted: 11 December 2017 / Published: 18 December 2017
Cited by 1 | PDF Full-text (2062 KB) | HTML Full-text | XML Full-text
Abstract
Dynamic optimization offers a great potential for maximizing performance of continuous processes from startup to shutdown by obtaining optimal trajectories for the control variables. However, numerical procedures for dynamic optimization can become prohibitively costly upon a sufficiently fine discretization of control trajectories, especially
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Dynamic optimization offers a great potential for maximizing performance of continuous processes from startup to shutdown by obtaining optimal trajectories for the control variables. However, numerical procedures for dynamic optimization can become prohibitively costly upon a sufficiently fine discretization of control trajectories, especially for large-scale dynamic process models. On the other hand, a coarse discretization of control trajectories is often incapable of representing the optimal solution, thereby leading to reduced performance. In this paper, a new control discretization approach for dynamic optimization of continuous processes is proposed. It builds upon turnpike theory in optimal control and exploits the solution structure for constructing the optimal trajectories and adaptively deciding the locations of the control discretization points. As a result, the proposed approach can potentially yield the same, or even improved, optimal solution with a coarser discretization than a conventional uniform discretization approach. It is shown via case studies that using the proposed approach can reduce the cost of dynamic optimization significantly, mainly due to introducing fewer optimization variables and cheaper sensitivity calculations during integration. Full article
(This article belongs to the Special Issue Combined Scheduling and Control) Printed Edition available
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Open AccessFeature PaperArticle Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes
Processes 2017, 5(4), 84; https://doi.org/10.3390/pr5040084
Received: 14 November 2017 / Revised: 3 December 2017 / Accepted: 7 December 2017 / Published: 13 December 2017
Cited by 2 | PDF Full-text (804 KB) | HTML Full-text | XML Full-text
Abstract
Performance of integrated production scheduling and advanced process control with disturbances is summarized and reviewed with four progressive stages of scheduling and control integration and responsiveness to disturbances: open-loop segregated scheduling and control, closed-loop segregated scheduling and control, open-loop scheduling with consideration of
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Performance of integrated production scheduling and advanced process control with disturbances is summarized and reviewed with four progressive stages of scheduling and control integration and responsiveness to disturbances: open-loop segregated scheduling and control, closed-loop segregated scheduling and control, open-loop scheduling with consideration of process dynamics, and closed-loop integrated scheduling and control responsive to process disturbances and market fluctuations. Progressive economic benefit from dynamic rescheduling and integrating scheduling and control is shown on a continuously stirred tank reactor (CSTR) benchmark application in closed-loop simulations over 24 h. A fixed horizon integrated scheduling and control formulation for multi-product, continuous chemical processes is utilized, in which nonlinear model predictive control (NMPC) and continuous-time scheduling are combined. Full article
(This article belongs to the Special Issue Combined Scheduling and Control) Printed Edition available
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Open AccessFeature PaperArticle Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes
Processes 2017, 5(4), 83; https://doi.org/10.3390/pr5040083
Received: 14 November 2017 / Revised: 7 December 2017 / Accepted: 8 December 2017 / Published: 13 December 2017
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Abstract
A novel formulation for combined scheduling and control of multi-product, continuous chemical processes is introduced in which nonlinear model predictive control (NMPC) and noncyclic continuous-time scheduling are efficiently combined. A decomposition into nonlinear programming (NLP) dynamic optimization problems and mixed-integer linear programming (MILP)
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A novel formulation for combined scheduling and control of multi-product, continuous chemical processes is introduced in which nonlinear model predictive control (NMPC) and noncyclic continuous-time scheduling are efficiently combined. A decomposition into nonlinear programming (NLP) dynamic optimization problems and mixed-integer linear programming (MILP) problems, without iterative alternation, allows for computationally light solution. An iterative method is introduced to determine the number of production slots for a noncyclic schedule during a prediction horizon. A filter method is introduced to reduce the number of MILP problems required. The formulation’s closed-loop performance with both process disturbances and updated market conditions is demonstrated through multiple scenarios on a benchmark continuously stirred tank reactor (CSTR) application with fluctuations in market demand and price for multiple products. Economic performance surpasses cyclic scheduling in all scenarios presented. Computational performance is sufficiently light to enable online operation in a dual-loop feedback structure. Full article
(This article belongs to the Special Issue Combined Scheduling and Control) Printed Edition available
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Open AccessArticle Dry Reforming of Methane Using a Nickel Membrane Reactor
Processes 2017, 5(4), 82; https://doi.org/10.3390/pr5040082
Received: 27 October 2017 / Revised: 25 November 2017 / Accepted: 8 December 2017 / Published: 12 December 2017
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Abstract
Dry reforming is a very interesting process for synthesis gas generation from CH4 and CO2 but suffers from low hydrogen yields due to the reverse water–gas shift reaction (WGS). For this reason, membranes are often used for hydrogen separation, which in
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Dry reforming is a very interesting process for synthesis gas generation from CH 4 and CO 2 but suffers from low hydrogen yields due to the reverse water–gas shift reaction (WGS). For this reason, membranes are often used for hydrogen separation, which in turn leads to coke formation at the process temperatures suitable for the membranes. To avoid these problems, this work shows the possibility of using nickel self-supported membranes for hydrogen separation at a temperature of 800 C. The higher temperature effectively suppresses coke formation. The paper features the analysis of the dry reforming reaction in a nickel membrane reactor without additional catalyst. The measurement campaign targeted coke formation and conversion of the methane feedstock. The nickel approximately 50% without hydrogen separation. The hydrogen removal led to an increase in methane conversion to 60–90%. Full article
(This article belongs to the Special Issue Membrane Materials, Performance and Processes)
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Open AccessArticle Optimization of Stimulation Parameters for Targeted Activation of Multiple Neurons Using Closed-Loop Search Methods
Processes 2017, 5(4), 81; https://doi.org/10.3390/pr5040081
Received: 18 July 2017 / Revised: 2 December 2017 / Accepted: 4 December 2017 / Published: 11 December 2017
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Abstract
Differential activation of neuronal populations can improve the efficacy of clinical devices such as sensory or cortical prostheses. Improving stimulus specificity will facilitate targeted neuronal activation to convey biologically realistic percepts. In order to deliver more complex stimuli to a neuronal population, stimulus
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Differential activation of neuronal populations can improve the efficacy of clinical devices such as sensory or cortical prostheses. Improving stimulus specificity will facilitate targeted neuronal activation to convey biologically realistic percepts. In order to deliver more complex stimuli to a neuronal population, stimulus optimization techniques must be developed that will enable a single electrode to activate subpopulations of neurons. However, determining the stimulus needed to evoke targeted neuronal activity is challenging. To find the most selective waveform for a particular population, we apply an optimization-based search routine, Powell’s conjugate direction method, to systematically search the stimulus waveform space. This routine utilizes a 1-D sigmoid activation model and a 2-D strength–duration curve to measure neuronal activation throughout the stimulus waveform space. We implement our search routine in both an experimental study and a simulation study to characterize potential stimulus-evoked populations and the associated selective stimulus waveform spaces. We found that for a population of five neurons, seven distinct sub-populations could be activated. The stimulus waveform space and evoked neuronal activation curves vary with each new combination of neuronal culture and electrode array, resulting in a unique selectivity space. The method presented here can be used to efficiently uncover the selectivity space, focusing experiments in regions with the desired activation pattern. Full article
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Open AccessFeature PaperArticle Mathematical Modeling of Tuberculosis Granuloma Activation
Processes 2017, 5(4), 79; https://doi.org/10.3390/pr5040079
Received: 23 October 2017 / Revised: 28 November 2017 / Accepted: 4 December 2017 / Published: 11 December 2017
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Abstract
Tuberculosis (TB) is one of the most common infectious diseases worldwide. It is estimated that one-third of the world’s population is infected with TB. Most have the latent stage of the disease that can later transition to active TB disease. TB is spread
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Tuberculosis (TB) is one of the most common infectious diseases worldwide. It is estimated that one-third of the world’s population is infected with TB. Most have the latent stage of the disease that can later transition to active TB disease. TB is spread by aerosol droplets containing Mycobacterium tuberculosis (Mtb). Mtb bacteria enter through the respiratory system and are attacked by the immune system in the lungs. The bacteria are clustered and contained by macrophages into cellular aggregates called granulomas. These granulomas can hold the bacteria dormant for long periods of time in latent TB. The bacteria can be perturbed from latency to active TB disease in a process called granuloma activation when the granulomas are compromised by other immune response events in a host, such as HIV, cancer, or aging. Dysregulation of matrix metalloproteinase 1 (MMP-1) has been recently implicated in granuloma activation through experimental studies, but the mechanism is not well understood. Animal and human studies currently cannot probe the dynamics of activation, so a computational model is developed to fill this gap. This dynamic mathematical model focuses specifically on the latent to active transition after the initial immune response has successfully formed a granuloma. Bacterial leakage from latent granulomas is successfully simulated in response to the MMP-1 dynamics under several scenarios for granuloma activation. Full article
(This article belongs to the Special Issue Biological Networks)
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Open AccessArticle Fuel Evaporation in an Atmospheric Premixed Burner: Sensitivity Analysis and Spray Vaporization
Processes 2017, 5(4), 80; https://doi.org/10.3390/pr5040080
Received: 28 October 2017 / Revised: 23 November 2017 / Accepted: 4 December 2017 / Published: 7 December 2017
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Abstract
Calculation of evaporation requires accurate thermophysical properties of the liquid. Such data are well-known for conventional fossil fuels. In contrast, e.g., thermal conductivity or dynamic viscosity of the fuel vapor are rarely available for modern liquid fuels. To overcome this problem, molecular models
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Calculation of evaporation requires accurate thermophysical properties of the liquid. Such data are well-known for conventional fossil fuels. In contrast, e.g., thermal conductivity or dynamic viscosity of the fuel vapor are rarely available for modern liquid fuels. To overcome this problem, molecular models can be used. Currently, the measurement-based properties of n-heptane and diesel oil are compared with estimated values, using the state-of-the-art molecular models to derive the temperature-dependent material properties. Then their effect on droplet evaporation was evaluated. The critical parameters were liquid density, latent heat of vaporization, boiling temperature, and vapor thermal conductivity where the estimation affected the evaporation time notably. Besides a general sensitivity analysis, evaporation modeling in a practical burner ended up with similar results. By calculating droplet motion, the evaporation number, the evaporation-to-residence time ratio can be derived. An empirical cumulative distribution function is used for the spray of the analyzed burner to evaluate evaporation in the mixing tube. Evaporation number did not exceed 0.4, meaning a full evaporation prior to reaching the burner lip in all cases. As droplet inertia depends upon its size, the residence time has a minimum value due to the phenomenon of overshooting. Full article
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Open AccessArticle Dynamics of the Bacterial Community Associated with Phaeodactylum tricornutum Cultures
Processes 2017, 5(4), 77; https://doi.org/10.3390/pr5040077
Received: 17 October 2017 / Revised: 24 November 2017 / Accepted: 28 November 2017 / Published: 7 December 2017
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Abstract
The pennate diatom Phaeodactylum tricornutum is a model organism able to synthesize industrially-relevant molecules. Commercial-scale cultivation currently requires large monocultures, prone to bio-contamination. However, little is known about the identity of the invading organisms. To reduce the complexity of natural systems, we systematically
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The pennate diatom Phaeodactylum tricornutum is a model organism able to synthesize industrially-relevant molecules. Commercial-scale cultivation currently requires large monocultures, prone to bio-contamination. However, little is known about the identity of the invading organisms. To reduce the complexity of natural systems, we systematically investigated the microbiome of non-axenic P. tricornutum cultures from a culture collection in reproducible experiments. The results revealed a dynamic bacterial community that developed differently in “complete” and “minimal” media conditions. In complete media, we observed an accelerated “culture crash”, indicating a more stable culture in minimal media. The identification of only four bacterial families as major players within the microbiome suggests specific roles depending on environmental conditions. From our results we propose a network of putative interactions between P. tricornutum and these main bacterial factions. We demonstrate that, even with rather sparse data, a mathematical model can be reconstructed that qualitatively reproduces the observed population dynamics, thus indicating that our hypotheses regarding the molecular interactions are in agreement with experimental data. Whereas the model in its current state is only qualitative, we argue that it serves as a starting point to develop quantitative and predictive mathematical models, which may guide experimental efforts to synthetically construct and monitor stable communities required for robust upscaling strategies. Full article
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Open AccessArticle Effect of Moisture Content on Lignocellulosic Power Generation: Energy, Economic and Environmental Impacts
Processes 2017, 5(4), 78; https://doi.org/10.3390/pr5040078
Received: 7 October 2017 / Revised: 1 December 2017 / Accepted: 4 December 2017 / Published: 6 December 2017
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Abstract
The moisture content of biomass affects its processing for applications such as electricity or steam. In this study, the effects of variation in moisture content of banagrass and energycane was evaluated using techno-economic analysis and life-cycle assessments. A 25% loss of moisture was
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The moisture content of biomass affects its processing for applications such as electricity or steam. In this study, the effects of variation in moisture content of banagrass and energycane was evaluated using techno-economic analysis and life-cycle assessments. A 25% loss of moisture was assumed as a variation that was achieved by field drying the biomass. Techno-economic analysis revealed that high moisture in the biomass was not economically feasible. Comparing banagrass with energycane, the latter was more economically feasible; thanks to the low moisture and ash content in energycane. About 32 GWh/year of electricity was produced by field drying 60,000 dry MT/year energycane. The investment for different scenarios ranged between $17 million and $22 million. Field-dried energycane was the only economically viable option that recovered the investment after 11 years of operation. This scenario was also more environmentally friendly, releasing 16-gCO2 equivalent/MJ of electricity produced. Full article
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Open AccessArticle A Validated Model for Design and Evaluation of Control Architectures for a Continuous Tablet Compaction Process
Processes 2017, 5(4), 76; https://doi.org/10.3390/pr5040076
Received: 2 October 2017 / Revised: 27 November 2017 / Accepted: 28 November 2017 / Published: 1 December 2017
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Abstract
The systematic design of an advanced and efficient control strategy for controlling critical quality attributes of the tablet compaction operation is necessary to increase the robustness of a continuous pharmaceutical manufacturing process and for real time release. A process model plays a very
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The systematic design of an advanced and efficient control strategy for controlling critical quality attributes of the tablet compaction operation is necessary to increase the robustness of a continuous pharmaceutical manufacturing process and for real time release. A process model plays a very important role to design, evaluate and tune the control system. However, much less attention has been made to develop a validated control relevant model for tablet compaction process that can be systematically applied for design, evaluation, tuning and thereby implementation of the control system. In this work, a dynamic tablet compaction model capable of predicting linear and nonlinear process responses has been successfully developed and validated. The nonlinear model is based on a series of transfer functions and static polynomial models. The model has been applied for control system design, tuning and evaluation and thereby facilitate the control system implementation into the pilot-plant with less time and resources. The best performing control algorithm was used in the implementation and evaluation of different strategies for control of tablet weight and breaking force. A characterization of the evaluated control strategies has been presented and can serve as a guideline for the selection of the adequate control strategy for a given tablet compaction setup. A strategy based on a multiple input multiple output (MIMO) model predictive controller (MPC), developed using the simulation environment, has been implemented in a tablet press unit, verifying the relevance of the simulation tool. Full article
(This article belongs to the Special Issue Combined Scheduling and Control) Printed Edition available
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Open AccessArticle RadViz Deluxe: An Attribute-Aware Display for Multivariate Data
Processes 2017, 5(4), 75; https://doi.org/10.3390/pr5040075
Received: 12 October 2017 / Revised: 8 November 2017 / Accepted: 17 November 2017 / Published: 22 November 2017
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Abstract
Modern data, such as occurring in chemical engineering, typically entail large collections of samples with numerous dimensional components (or attributes). Visualizing the samples in relation of these components can bring valuable insight. For example, one may be able to see how a
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Modern data, such as occurring in chemical engineering, typically entail large collections of samples with numerous dimensional components (or attributes). Visualizing the samples in relation of these components can bring valuable insight. For example, one may be able to see how a certain chemical property is expressed in the samples taken. This could reveal if there are clusters and outliers that have specific distinguishing properties. Current multivariate visualization methods lack the ability to reveal these types of information at a sufficient degree of fidelity since they are not optimized to simultaneously present the relations of the samples as well as the relations of the samples to their attributes. We propose a display that is designed to reveal these multiple relations. Our scheme is based on the concept of RadViz, but enhances the layout with three stages of iterative refinement. These refinements reduce the layout error in terms of three essential relationships—sample to sample, attribute to attribute, and sample to attribute. We demonstrate the effectiveness of our method via various real-world domain examples in the domain of chemical process engineering. In addition, we also formally derive the equivalence of RadViz to a popular multivariate interpolation method called generalized barycentric coordinates. Full article
(This article belongs to the collection Process Data Analytics)
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Open AccessArticle An Integrated Mathematical Model of Microbial Fuel Cell Processes: Bioelectrochemical and Microbiologic Aspects
Processes 2017, 5(4), 73; https://doi.org/10.3390/pr5040073
Received: 19 September 2017 / Revised: 29 October 2017 / Accepted: 7 November 2017 / Published: 20 November 2017
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Abstract
Microbial Fuel Cells (MFCs) represent a still relatively new technology for liquid organic waste treatment and simultaneous recovery of energy and resources. Although the technology is quite appealing due its potential benefits, its practical application is still hampered by several drawbacks, such as
[...] Read more.
Microbial Fuel Cells (MFCs) represent a still relatively new technology for liquid organic waste treatment and simultaneous recovery of energy and resources. Although the technology is quite appealing due its potential benefits, its practical application is still hampered by several drawbacks, such as systems instability (especially when attempting to scale-up reactors from laboratory prototypes), internally competing microbial reactions, and limited power generation. This paper is an attempt to address some of the issues related to MFC application in wastewater treatment with a simulation model. Reactor configuration, operational schemes, electrochemical and microbiological characterization, optimization methods and modelling strategies were reviewed and have been included in a mathematical simulation model written with a multidisciplinary, multi-perspective approach, considering the possibility of feeding real substrates to an MFC system while dealing with a complex microbiological population. The conclusions drawn herein can be of practical interest for all MFC researchers dealing with domestic or industrial wastewater treatment. Full article
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Open AccessArticle Stochasticity in the Parasite-Driven Trait Evolution of Competing Species Masks the Distinctive Consequences of Distance Metrics
Processes 2017, 5(4), 74; https://doi.org/10.3390/pr5040074
Received: 28 September 2017 / Revised: 10 November 2017 / Accepted: 13 November 2017 / Published: 17 November 2017
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Abstract
Various distance metrics and their induced norms are employed in the quantitative modeling of evolutionary dynamics. Minimization of these distance metrics, when applied to evolutionary optimization, are hypothesized to result in different outcomes. Here, we apply the different distance metrics to the evolutionary
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Various distance metrics and their induced norms are employed in the quantitative modeling of evolutionary dynamics. Minimization of these distance metrics, when applied to evolutionary optimization, are hypothesized to result in different outcomes. Here, we apply the different distance metrics to the evolutionary trait dynamics brought about by the interaction between two competing species infected by parasites (exploiters). We present deterministic cases showing the distinctive selection outcomes under the Manhattan, Euclidean, and Chebyshev norms. Specifically, we show how they differ in the time of convergence to the desired optima (e.g., no disease), and in the egalitarian sharing of carrying capacity between the competing species. However, when randomness is introduced to the population dynamics of parasites and to the trait dynamics of the competing species, the distinctive characteristics of the outcomes under the three norms become indistinguishable. Our results provide theoretical cases of when evolutionary dynamics using different distance metrics exhibit similar outcomes. Full article
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Open AccessArticle Development of Molecularly Imprinted Polymers to Target Polyphenols Present in Plant Extracts
Processes 2017, 5(4), 72; https://doi.org/10.3390/pr5040072
Received: 29 September 2017 / Revised: 7 November 2017 / Accepted: 9 November 2017 / Published: 14 November 2017
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Abstract
The development of molecularly imprinted polymers (MIPs) to target polyphenols present in vegetable extracts was here addressed. Polydatin was selected as a template polyphenol due to its relatively high size and amphiphilic character. Different MIPs were synthesized to explore preferential interactions between the
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The development of molecularly imprinted polymers (MIPs) to target polyphenols present in vegetable extracts was here addressed. Polydatin was selected as a template polyphenol due to its relatively high size and amphiphilic character. Different MIPs were synthesized to explore preferential interactions between the functional monomers and the template molecule. The effect of solvent polarity on the molecular imprinting efficiency, namely owing to hydrophobic interactions, was also assessed. Precipitation and suspension polymerization were examined as a possible way to change MIPs morphology and performance. Solid phase extraction and batch/continuous sorption processes were used to evaluate the polyphenols uptake/release in individual/competitive assays. Among the prepared MIPs, a suspension polymerization synthesized material, with 4-vinylpyridine as the functional monomer and water/methanol as solvent, showed a superior performance. The underlying cause of such a significant outcome is the likely surface imprinting process caused by the amphiphilic properties of polydatin. The uptake and subsequent selective release of polyphenols present in natural extracts was successfully demonstrated, considering a red wine solution as a case study. However, hydrophilic/hydrophobic interactions are inevitable (especially with complex natural extracts) and the tuning of the polarity of the solvents is an important issue for the isolation of the different polyphenols. Full article
(This article belongs to the Special Issue Water Soluble Polymers) Printed Edition available
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