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Processes, Volume 6, Issue 1 (January 2018)

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Cover Story (view full-size image) Alkyl acrylates (such as methyl, ethyl, and n-butyl acrylate) self-initiate polymer chains at high [...] Read more.
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Open AccessFeature PaperArticle Computational Package for Copolymerization Reactivity Ratio Estimation: Improved Access to the Error-in-Variables-Model
Processes 2018, 6(1), 8; https://doi.org/10.3390/pr6010008
Received: 12 December 2017 / Revised: 9 January 2018 / Accepted: 13 January 2018 / Published: 19 January 2018
Cited by 1 | PDF Full-text (6329 KB) | HTML Full-text | XML Full-text
Abstract
The error-in-variables-model (EVM) is the most statistically correct non-linear parameter estimation technique for reactivity ratio estimation. However, many polymer researchers are unaware of the advantages of EVM and therefore still choose to use rather erroneous or approximate methods. The procedure is straightforward but
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The error-in-variables-model (EVM) is the most statistically correct non-linear parameter estimation technique for reactivity ratio estimation. However, many polymer researchers are unaware of the advantages of EVM and therefore still choose to use rather erroneous or approximate methods. The procedure is straightforward but it is often avoided because it is seen as mathematically and computationally intensive. Therefore, the goal of this work is to make EVM more accessible to all researchers through a series of focused case studies. All analyses employ a MATLAB-based computational package for copolymerization reactivity ratio estimation. The basis of the package is previous work in our group over many years. This version is an improvement, as it ensures wider compatibility and enhanced flexibility with respect to copolymerization parameter estimation scenarios that can be considered. Full article
(This article belongs to the Special Issue Feature Papers for Celebrating the Fifth Founding Year of Processes)
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Open AccessFeature PaperArticle In Silico Identification of Microbial Partners to Form Consortia with Anaerobic Fungi
Processes 2018, 6(1), 7; https://doi.org/10.3390/pr6010007
Received: 27 December 2017 / Revised: 10 January 2018 / Accepted: 12 January 2018 / Published: 15 January 2018
Cited by 1 | PDF Full-text (1148 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Lignocellulose is an abundant and renewable resource that holds great promise for sustainable bioprocessing. However, unpretreated lignocellulose is recalcitrant to direct utilization by most microbes. Current methods to overcome this barrier include expensive pretreatment steps to liberate cellulose and hemicellulose from lignin. Anaerobic
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Lignocellulose is an abundant and renewable resource that holds great promise for sustainable bioprocessing. However, unpretreated lignocellulose is recalcitrant to direct utilization by most microbes. Current methods to overcome this barrier include expensive pretreatment steps to liberate cellulose and hemicellulose from lignin. Anaerobic gut fungi possess complex cellulolytic machinery specifically evolved to decompose crude lignocellulose, but they are not yet genetically tractable and have not been employed in industrial bioprocesses. Here, we aim to exploit the biomass-degrading abilities of anaerobic fungi by pairing them with another organism that can convert the fermentable sugars generated from hydrolysis into bioproducts. By combining experiments measuring the amount of excess fermentable sugars released by the fungal enzymes acting on crude lignocellulose, and a novel dynamic flux balance analysis algorithm, we screened potential consortia partners by qualitative suitability. Microbial growth simulations reveal that the fungus Anaeromyces robustus is most suited to pair with either the bacterium Clostridia ljungdahlii or the methanogen Methanosarcina barkeri—both organisms also found in the rumen microbiome. By capitalizing on simulations to screen six alternative organisms, valuable experimental time is saved towards identifying stable consortium members. This approach is also readily generalizable to larger systems and allows one to rationally select partner microbes for formation of stable consortia with non-model microbes like anaerobic fungi. Full article
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Open AccessArticle Effect of Alkane Chain Length on Crystallization in Emulsions during Supercooling in Quiescent Systems and under Mechanical Stress
Processes 2018, 6(1), 6; https://doi.org/10.3390/pr6010006
Received: 15 November 2017 / Revised: 10 January 2018 / Accepted: 12 January 2018 / Published: 15 January 2018
Cited by 1 | PDF Full-text (9113 KB) | HTML Full-text | XML Full-text
Abstract
Crystallization behavior of hexadecane (C16H34), octadecane (C18H38), eicosane (C20H42), and docosane (C22H46) dispersions of similar mean droplet diameter (x50.2 ≈ 15 µm) was investigated in quiescent
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Crystallization behavior of hexadecane (C16H34), octadecane (C18H38), eicosane (C20H42), and docosane (C22H46) dispersions of similar mean droplet diameter (x50.2 ≈ 15 µm) was investigated in quiescent systems and compared to crystallization under mechanical stress. In quiescent systems, the required supercooling decreased with increasing chain length of the alkanes to initiate crystallization. Crystallization of alkane dispersions under mechanical stress resulted in similar onset crystallization supercooling, as during quiescent crystallization. Increase of mechanical stress did not affect the onset crystallization supercooling within alkane dispersions. Full article
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Open AccessReview RNA-Seq as an Emerging Tool for Marine Dinoflagellate Transcriptome Analysis: Process and Challenges
Processes 2018, 6(1), 5; https://doi.org/10.3390/pr6010005
Received: 16 November 2017 / Revised: 28 December 2017 / Accepted: 5 January 2018 / Published: 11 January 2018
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Abstract
Dinoflagellates are the large group of marine phytoplankton with primary studies interest regarding their symbiosis with coral reef and the abilities to form harmful algae blooms (HABs). Toxin produced by dinoflagellates during events of HABs cause severe negative impact both in the economy
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Dinoflagellates are the large group of marine phytoplankton with primary studies interest regarding their symbiosis with coral reef and the abilities to form harmful algae blooms (HABs). Toxin produced by dinoflagellates during events of HABs cause severe negative impact both in the economy and health sector. However, attempts to understand the dinoflagellates genomic features are hindered by their complex genome organization. Transcriptomics have been employed to understand dinoflagellates genome structure, profile genes and gene expression. RNA-seq is one of the latest methods for transcriptomics study. This method is capable of profiling the dinoflagellates transcriptomes and has several advantages, including highly sensitive, cost effective and deeper sequence coverage. Thus, in this review paper, the current workflow of dinoflagellates RNA-seq starts with the extraction of high quality RNA and is followed by cDNA sequencing using the next-generation sequencing platform, dinoflagellates transcriptome assembly and computational analysis will be discussed. Certain consideration needs will be highlighted such as difficulty in dinoflagellates sequence annotation, post-transcriptional activity and the effect of RNA pooling when using RNA-seq. Full article
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Open AccessEditorial Acknowledgement to Reviewers of Processes in 2017
Processes 2018, 6(1), 4; https://doi.org/10.3390/pr6010004
Received: 8 January 2018 / Revised: 8 January 2018 / Accepted: 8 January 2018 / Published: 10 January 2018
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Abstract
Peer review is an essential part of the publication process, ensuring that Processes maintains high quality standards for its published papers.[...] Full article
Open AccessFeature PaperArticle On the Thermal Self-Initiation Reaction of n-Butyl Acrylate in Free-Radical Polymerization
Processes 2018, 6(1), 3; https://doi.org/10.3390/pr6010003
Received: 13 December 2017 / Revised: 30 December 2017 / Accepted: 31 December 2017 / Published: 4 January 2018
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Abstract
This experimental and theoretical study deals with the thermal spontaneous polymerization of n-butyl acrylate (n-BA). The polymerization was carried out in solution (n-heptane as the solvent) at 200 and 220 °C without adding any conventional initiators. It was
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This experimental and theoretical study deals with the thermal spontaneous polymerization of n-butyl acrylate (n-BA). The polymerization was carried out in solution (n-heptane as the solvent) at 200 and 220 °C without adding any conventional initiators. It was studied with the five different n-BA/n-heptane volume ratios: 50/50, 70/30, 80/20, 90/10, and 100/0. Extensive experimental data presented here show significant monomer conversion at all temperatures and concentrations confirming the occurrence of the thermal self-initiation of the monomer. The order, frequency factor, and activation energy of the thermal self-initiation reaction of n-BA were estimated from n-BA conversion, using a macroscopic mechanistic model. The estimated reaction order agrees well with the order obtained via our quantum chemical calculations. Furthermore, the frequency factor and activation energy estimates agree well with the corresponding values that we already reported for bulk polymerization of n-BA. Full article
(This article belongs to the Special Issue Feature Papers for Celebrating the Fifth Founding Year of Processes)
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Open AccessArticle Individual-Based Modelling of Invasion in Bioaugmented Sand Filter Communities
Processes 2018, 6(1), 2; https://doi.org/10.3390/pr6010002
Received: 28 August 2017 / Revised: 24 October 2017 / Accepted: 30 October 2017 / Published: 1 January 2018
Cited by 1 | PDF Full-text (726 KB) | HTML Full-text | XML Full-text
Abstract
Using experimental data obtained from in vitro bioaugmentation studies of a sand filter community of 13 bacterial species, we develop an individual-based model representing the in silico counterpart of this synthetic microbial community. We assess the inter-species interactions, first by identifying strain identity
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Using experimental data obtained from in vitro bioaugmentation studies of a sand filter community of 13 bacterial species, we develop an individual-based model representing the in silico counterpart of this synthetic microbial community. We assess the inter-species interactions, first by identifying strain identity effects in the data then by synthesizing these effects into a competition structure for our model. Pairwise competition outcomes are determined based on interaction effects in terms of functionality. We also consider non-deterministic competition, where winning probabilities are assigned based on the relative intrinsic competitiveness of each strain. Our model is able to reproduce the key qualitative dynamics observed in in vitro experiments with similar synthetic sand filter communities. Simulation outcomes can be explained based on the underlying competition structures and the resulting spatial dynamics. Our results highlight the importance of community diversity and in particular evenness in stabilizing the community dynamics, allowing us to study the establishment and development of these communities, and thereby illustrate the potential of the individual-based modelling approach for addressing microbial ecological theories related to synthetic communities. Full article
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Open AccessEditorial Announcing the 2018 Processes Travel Award for Post-Doctoral Fellows and Ph.D. Students
Processes 2018, 6(1), 1; https://doi.org/10.3390/pr6010001
Received: 20 December 2017 / Revised: 20 December 2017 / Accepted: 22 December 2017 / Published: 1 January 2018
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Abstract
With the goal of promoting the development of early career investigators in the fields of chemical process and biological systems engineering [...] Full article
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