Low-cost arabinose induced genetic circuit for protein production: Modeling.

A low-cost reagent-producing genetic circuit was designed during this work. Its functioning is based on a positive feedback loop induced by a small amount of arabinose, allowing users to obtain reactants in a safe, constant, and controlled manner. The design-only approach to the project allows us to work in different kinds of computational models, thus, an ODE-based model was thoroughly developed and a cellular automata-based one was experimented with. Working on the ODE model, equilibrium states and system stability were studied. Circuit properties were also focused on one of which was a high concentration of interest protein produced by low inductor inputs. As a result, a mathematical expression capable of describing the quantity of produced reagent was obtained. In addition, the cellular automata model offers a new perspective, given its differences from the ODE model e.g. this type of model is a stochastic analysis and describes each cell individually instead of describing the whole cellular population.

Combined Proppant Placement and Early Production Modeling Achieve Increased Fracture Performance in Ecuador's Oriente Basin

In the paper, we document one iteration of the continuous improvement of well performance undertaken in the Oriente Basin in Ecuador. In the past, it had been observed that well economics was sometimes degraded by the issues related to proppant flowback from hydraulic fractures. Proppant flowback resulted in extra costs from well cleanouts, pump replacement, and damage to fracture conductivity. After evaluation of proppant flowback cases using the combined modeling workflow that simulates fracture growth, proppant placement, and early production of solids and fluids, it had been proposed to modify fracture designs and well startup strategy. In this paper, we review the first results of implementation of these modifications in the field and evaluate the significance of improvements.

Auxetic Polymer Foams: Production, Modeling and Applications

: Auxetic materials have high potential due to their exceptional properties resulting from their negative Poisson ratio. Recently, several auxetic polymer-based materials have been developed. In fact, several applications are looking for a lightweight (less material consumed in production and transport) while having high mechanical performances (impact absorption, rigidity, strength, resistance, etc.). So, a balance between density and toughness/strength is of high importance, especially for military, sporting, and transport applications. So auxetic materials (especially foams) can provide high impact protection while limiting the material’s weight. This article presents a review of recent advances with a focus on auxetic polymers, with particular emphasis on the auxetic polymer foams in terms of their fabrication methods and processing conditions (depending on the nature of the cellular structure), the effect of the fabrication parameters on their final properties, as well as their models and potential applications.

Biogas efficiency from cow dung waste in strengthening energy security during the covid-19 pandemic through a dynamic modeling system

During Covid-19 pandemic, the increase in LPG types was 0.6-2.4 million BOE, while in the household sector it was 2.3-6.9 million BOE, so causes LPG import growth ratio to increase by 4.8%/year (BPPT, 2020). Therefore, it is necessary to make efforts to suppress LPG imports by increasing the supply of EBT in the household sector with biogas production. The research aims to look at the biogas production modeling system from the resulting cow dung waste. The research method that studies the literature is based on modeling data based on data obtained using Powersim 10. The results showed that LPG demand in 2020 is 2.4 million BOE that could be fulfilled by a biogas source from 9539238.75 kg ~ 0.9 metric tons cow dung waste. This cow dung waste is able to produce 381569.55 m3/kg of methane gas which is equivalent to 0.59 metric tons LPG, savings Rp 690 M; 103 million liters gasoline, savings Rp 793 M; 64.8 million liters diesel fuel, savings Rp 333.8 M; 80 million liters kerosene, savings Rp 1 T; 4.53 metric tons wood, savings Rp 4.5 T. This favorable situation must be immediately felt by the community with an estimate of future benefits.

Morpho-Phonetic Effects in Speech Production: Modeling the Acoustic Duration of English Derived Words With Linear Discriminative Learning

Recent evidence for the influence of morphological structure on the phonetic output goes unexplained by established models of speech production and by theories of the morphology-phonology interaction. Linear discriminative learning (LDL) is a recent computational approach in which such effects can be expected. We predict the acoustic duration of 4,530 English derivative tokens with the morphological functions DIS, NESS, LESS, ATION, and IZE in natural speech data by using predictors derived from a linear discriminative learning network. We find that the network is accurate in learning speech production and comprehension, and that the measures derived from it are successful in predicting duration. For example, words are lengthened when the semantic support of the word's predicted articulatory path is stronger. Importantly, differences between morphological categories emerge naturally from the network, even when no morphological information is provided. The results imply that morphological effects on duration can be explained without postulating theoretical units like the morpheme, and they provide further evidence that LDL is a promising alternative for modeling speech production.

mAb Production Modeling and Design Space Evaluation Including Glycosylation Process

Due to high demand, monoclonal antibodies (mAbs) production needs to be efficient, as well as maintaining a high product quality. Quality by design (QbD) via predictive process modeling greatly facilitates process understanding and can be used to adjust process parameters to further improve the unit operations. In this work, mechanistic and dynamic kriging models are developed to capture the protein productivity and glycan fractions under different temperatures and pH levels. The design of experiments is used to generate input and output data for model training. The dynamic kriging model shows good performance in capturing the dynamic profiles of cell cultures and glycosylation using only limited input data. The developed model is further used for feasibility analysis, and successfully identifies the operating design space, maintaining high productivity and guaranteed product quality.