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Records Added in October 2021
Records added in October 2021
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Showing records 28 to 52 of 52. [First] Page: 1 2 3 Last
Investigation of Ni−Fe−Cu-Layered Double Hydroxide Catalysts in Steam Reforming of Toluene as a Model Compound of Biomass Tar
David Díez, Ana Urueña, Gregorio Antolín
October 14, 2021 (v1)
Keywords: gasification, hydrogen production, hydrotalcite, layered double hydroxide, Ni-based catalyst, tar, toluene steam reforming
This work focused on the synthesis of a catalyst based on layered double hydroxides with a molar cation concentration Ni/Cu/Fe/Mg/Al of 30/5/5/40/20 and its performance in the steam reforming of toluene as a model compound of biomass tar. Its performance at different temperatures (500, 600, 700, 800, and 900 °C) and steam/carbon molar ratios (S/C ratios) (1, 2, 4, 6, 8) was studied. The contact time used was 0.32 g h mol−1. The catalyst obtained allowed us to reach 98−99.87% gas conversion of toluene with a low carbon deposition on catalyst surface (1.4 wt %) at 800 °C and S/C = 4. In addition, conversions in the range of 600−700 °C were higher than 80% and 90%, respectively, and the type of carbon deposited on the catalyst was found to be filamentous, which did not significantly reduce the performance of the catalyst.
Research on Optimization of Coal Slime Fluidized Bed Boiler Desulfurization Cooperative Operation
Yangjian Xiao, Yudong Xia, Aipeng Jiang, Xiaofang Lv, Yamei Lin, Hanyu Zhang
October 14, 2021 (v1)
Keywords: boiler thermal efficiency, cooperative optimization, mechanism model, Simulation, slime fluidized bed
The semi-dry desulfurization of slime fluidized bed boilers (FBB) has been widely used due to its advantages of low cost and high desulfurization efficiency. In this paper, the cooperative optimization of a two-stage desulfurization processes in the slime fluidized bed boiler was studied, and a model-based optimization strategy was proposed to minimize the operational cost of the desulfurization system. Firstly, a mathematical model for the FBB with a two-stage desulfurization process was established. The influences of coal slime elements on combustion flue gas and the factors that may affect the thermal efficiency of the boiler were then analyzed. Then, on the basis of the developed model, a number of parameters affecting the SO2 concentration at the outlet of the slime fluidized bed boiler were simulated and deeply analyzed. In addition, the effects of the sulfur content of coal slime, excess air coefficient, and calcium to sulfur ratio were also discussed. Finally, according to the... [more]
Using Neural Networks to Obtain Indirect Information about the State Variables in an Alcoholic Fermentation Process
Anca Sipos, Adrian Florea, Maria Arsin, Ugo Fiore
October 14, 2021 (v1)
Keywords: fermentation process, neural network, prediction application
This work provides a manual design space exploration regarding the structure, type, and inputs of a multilayer neural network (NN) to obtain indirect information about the state variables in the alcoholic fermentation process. The main benefit of our application is to help experts reduce the time needed for making the relevant measurements and to increase the lifecycles of sensors in bioreactors. The novelty of this research is the flexibility of the developed application, the use of a great number of variables, and the comparative presentation of the results obtained with different NNs (feedback vs. feed-forward) and different learning algorithms (Back-Propagation vs. Levenberg−Marquardt). The simulation results show that the feedback neural network outperformed the feed-forward neural network. The NN configuration is relatively flexible (with hidden layers and a number of nodes on each of them), but the number of input and output nodes depends on the fermentation process parameters.... [more]
Encapsulation of Lactoferrin for Sustained Release Using Particles from Gas-Saturated Solutions
Kento Ono, Hiroki Sakai, Shinichi Tokunaga, Tanjina Sharmin, Taku Michael Aida, Kenji Mishima
October 14, 2021 (v1)
Subject: Biosystems
Keywords: enteric polymer, gastric digestion, lactoferrin, PGSS, shellac
The particles from gas saturated solutions (PGSS) process were performed to encapsulate lactofer-rin, an iron-binding milk glycoprotein, using supercritical carbon dioxide (scCO2). A natural en-teric polymer, shellac, was used as a coating material of lactoferrin carried out by the PGSS pro-cess. Conditions were optimized by applying different temperatures (20−50 °C) and pressures (8−10 MPa) and the particles were evaluated for particle shape and size, lactoferrin encapsulation ef-ficiency, Fourier transform infrared (FTIR) spectroscopy to confirm lactoferrin entrapment and in vitro dissolution studies at different pH values. Particles with an average diameter of 75.5 ± 7 μm were produced with encapsulation efficiency up to 71 ± 2%. Furthermore, particles that showed high stability in low pH (pH 1.2) and a sustained release over time (t2h = 75%) in higher pH (pH 7.4) suggested an effective encapsulation process for the protection of lactoferrin from gastric di-gestion.
Snapse: A Visual Tool for Spiking Neural P Systems
Aleksei Dominic C. Fernandez, Reyster M. Fresco, Francis George C. Cabarle, Ren Tristan A. de la Cruz, Ivan Cedric H. Macababayao, Korsie J. Ballesteros, Henry N. Adorna
October 14, 2021 (v1)
Keywords: membrane computing, spiking neural P systems, visual simulator
Spiking neural P (SN P) systems are models of computation inspired by spiking neurons and part of the third generation of neuron models. SN P systems are equivalent to Turing machines and are able to solve computationally hard problems using a space-time trade-off. Research in SN P systems theory is especially active, more so in recent years as more efforts are directed towards their real-world applications. Usually, SN P systems are represented visually as a directed graph and simulated through mainly text-based simulations or tables. Thus, there is a need for tools that can simulate and create SN P Systems in a visual and easy-to-use manner. Snapse is such a tool which aims to hasten the speed and ease at which researchers may create and experiment with SN P systems. Furthermore, visual tools such as Snapse can help further bring SN P systems outside of theoretical computer science.
Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
Outi M. H. Salo-Ahen, Ida Alanko, Rajendra Bhadane, Alexandre M. J. J. Bonvin, Rodrigo Vargas Honorato, Shakhawath Hossain, André H. Juffer, Aleksei Kabedev, Maija Lahtela-Kakkonen, Anders Støttrup Larsen, Eveline Lescrinier, Parthiban Marimuthu, Muhammad Usman Mirza, Ghulam Mustafa, Ariane Nunes-Alves, Tatu Pantsar, Atefeh Saadabadi, Kalaimathy Singaravelu, Michiel Vanmeert
October 14, 2021 (v1)
Subject: Biosystems
Keywords: binding free energy, computational pharmaceutics, computer-aided drug design, conformational ensemble, drug formulations, drug targets, enhanced sampling methods, ligand binding kinetics, membrane interactions, protein flexibility
Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels a... [more]
Optimization Studies of AC4CH Material in the Cylinder Block of a Diesel Engine Application
Bum Youl Park, Youngkun Kim, Kihyung Lee
October 14, 2021 (v1)
Subject: Materials
Keywords: AC4CH, diesel engine, refinement, weight reduction
The reduction of the weight of the engine of a vessel or an automobile can result in improved engine efficiency and lower CO2 emissions. Therefore, this study was conducted to improve the mechanical properties of the AC4CH alloy, an alternative to cast iron for engine fabrication, through the addition of Si and Mg to aluminum. The mechanical properties of the alloy were improved through refinement of the Si structure, grain refinement, and heat treatment. In addition, the applicability of a cylinder block fabricated with the modified AC4CH alloy to a diesel engine was validated through a 300 h durability test.
Research on Rotating Machinery Fault Diagnosis Method Based on Energy Spectrum Matrix and Adaptive Convolutional Neural Network
Yiyang Liu, Yousheng Yang, Tieying Feng, Yi Sun, Xuejian Zhang
October 14, 2021 (v1)
Keywords: convolutional neural network, dynamic adjustment of the learning rate, energy spectrum matrix, hierarchical fault diagnosis, rotating machinery
Traditional intelligent fault diagnosis methods focus on distinguishing different fault modes, but ignore the deterioration of fault severity. This paper proposes a new two-stage hierarchical convolutional neural network for fault diagnosis of rotating machinery bearings. The failure mode and failure severity are modeled as a hierarchical structure. First, the original vibration signal is transformed into an energy spectrum matrix containing fault-related information through wavelet packet decomposition. Secondly, in the model training method, an adaptive learning rate dynamic adjustment strategy is further proposed, which adaptively extracts robust features from the spectrum matrix for fault mode and severity diagnosis. To verify the effectiveness of the method, the bearing fault data was collected using a rotating machine test bench. On this basis, the diagnostic accuracy, convergence performance and robustness of the model under different signal-to-noise ratios and variable load env... [more]
Analysis and Optimization of Two Film-Coated Tablet Production Processes by Computer Simulation: A Case Study
Stefanie Hering, Nico Schäuble, Thomas M. Buck, Brigitta Loretz, Thomas Rillmann, Frank Stieneker, Claus-Michael Lehr
October 14, 2021 (v1)
Keywords: 3D simulation modeling and analysis, bottleneck analysis, model implementation, production costs, resource conservation
Increasing regulatory demands are forcing the pharmaceutical industry to invest its available resources carefully. This is especially challenging for small- and middle-sized companies. Computer simulation software like FlexSim allows one to explore variations in production processes without the need to interrupt the running process. Here, we applied a discrete-event simulation to two approved film-coated tablet production processes. The simulations were performed with FlexSim (FlexSim Deutschland—Ingenieurbüro für Simulationsdienstleistung Ralf Gruber, Kirchlengern, Germany). Process visualization was done using Cmap Tools (Florida Institute for Human and Machine Cognition, Pensacola, FL, USA), and statistical analysis used MiniTab® (Minitab GmbH, Munich, Germany). The most critical elements identified during model building were the model logic, operating schedule, and processing times. These factors were graphically and statistically verified. To optimize the utilization of employees,... [more]
The Influence of Hydrodynamic Changes in a System with a Pitched Blade Turbine on Mixing Power
Jacek Stelmach, Czesław Kuncewicz, Szymon Szufa, Tomas Jirout, Frantisek Rieger
October 14, 2021 (v1)
Subject: Other
Keywords: impeller, Mixing, pitched blade turbine, power consumption
This paper presents an analysis of hydrodynamics in a tank with a 45° and 60° pitched blade turbine impeller operating while emptying the mixer and with an axial agitator working during axial pumping-down of water at different water levels above the impeller. Measurements made with the PIV method confirmed the change in direction of pumping liquid after the level dropped below the critical value, with an almost unchanged liquid stream flowing through the mixer. It was found that an increase in the value of the tangential velocity in the area of the impeller took place and the quantity of this increase depended on the angle of the blade pitch and the rotational frequency of the impeller. Change in this velocity component increased the mixing power.
Graphitic Carbon Nitride-Based Composite in Advanced Oxidation Processes for Aqueous Organic Pollutants Removal: A Review
Yu Shen, Antonio J. Dos santos-Garcia, María José Martín de Vidales
October 14, 2021 (v1)
Subject: Materials
Keywords: advanced oxidation processes, aqueous organic pollutants removal, graphitic carbon nitride
In recent decades, a growing number of organic pollutants released have raised worldwide concern. Graphitic carbon nitride (g-C3N4) has drawn increasing attention in environmental pollutants removal thanks to its unique electronic band structure and excellent physicochemical stability. This paper reviews the recent progress of g-C3N4-based composites as catalysts in various advanced oxidation processes (AOPs), including chemical, photochemical, and electrochemical AOPs. Strategies for enhancing catalytic performance such as element-doping, nanostructure design, and heterojunction construction are summarized in detail. The catalytic degradation mechanisms are also discussed briefly.
Machine Learning for Ionic Liquid Toxicity Prediction
Zihao Wang, Zhen Song, Teng Zhou
October 14, 2021 (v1)
Keywords: ionic liquid, Machine Learning, neural network, support vector machine, toxicity
In addition to proper physicochemical properties, low toxicity is also desirable when seeking suitable ionic liquids (ILs) for specific applications. In this context, machine learning (ML) models were developed to predict the IL toxicity in leukemia rat cell line (IPC-81) based on an extended experimental dataset. Following a systematic procedure including framework construction, hyper-parameter optimization, model training, and evaluation, the feedforward neural network (FNN) and support vector machine (SVM) algorithms were adopted to predict the toxicity of ILs directly from their molecular structures. Based on the ML structures optimized by the five-fold cross validation, two ML models were established and evaluated using IL structural descriptors as inputs. It was observed that both models exhibited high predictive accuracy, with the SVM model observed to be slightly better than the FNN model. For the SVM model, the determination coefficients were 0.9289 and 0.9202 for the training... [more]
LC-UV and UPLC-MS/MS Methods for Analytical Study on Degradation of Three Antihistaminic Drugs, Ketotifen, Epinastine and Emedastine: Percentage Degradation, Degradation Kinetics and Degradation Pathways at Different pH
Anna Gumieniczek, Izabela Kozak, Paweł Żmudzki, Urszula Hubicka
October 14, 2021 (v1)
Subject: Biosystems
Keywords: degradation in solutions, epinastine and emedastine, ketotifen, LC-UV and UPLC-MS/MS methods, new degradation products, pH and high temperature
Evaluation of pH-dependent reactivity of drugs is an essential component in the pharmaceutical industry. Thus, the stability of three antihistaminic drugs, i.e., ketotifen, epinastine and emedastine, was tested, in solutions of five pH values, i.e., 1.0, 3.0, 7.0, 10.0 and 13.0, at high temperature (70 °C). LC-UV isocratic methods were developed to estimate percentage degradation as well as the kinetics of degradation. Generally, epinastine was shown to be the most stable compound with degradation below 14%. Emedastine was labile in all pH conditions, with degradation in the range 29.26−51.88%. Ketotifen was moderately stable at pH 1−7 (degradation ≤ 14.04%). However, at pH ≥ 10, its degradation exceeded 30%. The kinetics of degradation of ketotifen, epinastine and emedastine was shown as a pseudo-first-order reaction with the rate constants in the range 10−4−10−3 min−1 Finally, the UPLC-MS/MS method was applied to identify the main degradants and suggest degradation pathways. Degradat... [more]
Nano-Intermediate of Magnetite Nanoparticles Supported on Activated Carbon from Spent Coffee Grounds for Treatment of Wastewater from Oil Industry and Energy Production
Laura Acosta, Dahiana Galeano-Caro, Oscar E. Medina, Farid B. Cortés, Camilo A. Franco
October 14, 2021 (v1)
Keywords: activated carbon, Adsorption, Catalysis, coffee residue, crude oil, magnetite nanoparticles
This work focused on evaluating the adsorptive removal of crude oil using a nano-intermediate based on magnetite nanoparticles supported on activated carbon synthesized from spent coffee grounds and the subsequent catalytic oil decomposition to recover by-products and regenerate the support material. The magnetite nanoparticles were synthesized by the co-precipitation method and were used as active phases on prepared activated carbon. The amount of crude oil adsorbed was determined by adsorption isotherms. In addition, dynamic tests were performed on a packed bed to evaluate the efficiency of the removal process. Thermogravimetric analysis and mass spectrometry were used to evaluate the catalytic powder and the quantification of by-products. Contrasting the results with commercial carbon, the one synthesized from the coffee residue showed a greater affinity for the oil. Likewise, the adsorption capacity increased by doping activated carbon with magnetite nanoparticles, obtaining an eff... [more]
Modified Multi-Crossover Operator NSGA-III for Solving Low Carbon Flexible Job Shop Scheduling Problem
Xingping Sun, Ye Wang, Hongwei Kang, Yong Shen, Qingyi Chen, Da Wang
October 14, 2021 (v1)
Keywords: co-evolution, flexible job shop scheduling problem, Genetic Algorithm, low carbon, multi-crossover operator, multi-objective optimization
Low carbon manufacturing has received increasingly more attention in the context of global warming. The flexible job shop scheduling problem (FJSP) widely exists in various manufacturing processes. Researchers have always emphasized manufacturing efficiency and economic benefits while ignoring environmental impacts. In this paper, considering carbon emissions, a multi-objective flexible job shop scheduling problem (MO-FJSP) mathematical model with minimum completion time, carbon emission, and machine load is established. To solve this problem, we study six variants of the non-dominated sorting genetic algorithm-III (NSGA-III). We find that some variants have better search capability in the MO-FJSP decision space. When the solution set is close to the Pareto frontier, the development ability of the NSGA-III variant in the decision space shows a difference. According to the research, we combine Pareto dominance with indicator-based thought. By utilizing three existing crossover operators... [more]
Integration of a Combined Cycle Power Plant with MED-RO Desalination Based on Conventional and Advanced Exergy, Exergoeconomic, and Exergoenvironmental Analyses
Mohammad Hasan Khoshgoftar Manesh, Reza Shojaei Ghadikolaei, Hossein Vazini Modabber, Viviani Caroline Onishi
October 11, 2021 (v1)
Keywords: advanced exergy analysis, combined cycle power plant (CCPP), desalination, exergoeconomic analysis, exergoenvironmental analysis, mathematical modelling and simulation, multi-effect distillation (MED), reverse osmosis (RO), water and power production
The ever-increasing world population, change in lifestyle, and limited natural water and energy resources have made industrial seawater desalination plants the leading contenders for cost-efficient freshwater production. In this study, the integration of a combined cycle power plant (CCPP) with multi-effect distillation (MED) and reverse osmosis (RO) desalination units is investigated through comprehensive conventional and advanced exergy, exergoeconomic, and exergoenvironmental analyses. Firstly, the thermodynamic modelling of the CCPP is performed by using a mathematical programming procedure. Then, a mathematical model is developed for the integration of the existing CCPP plant with MED and RO desalination units. Finally, conventional and advanced exergy, exergoeconomic, and exergoenvironmental analyses are carried out to assess the main performance parameters of the integrated CCPP and MED-RO desalination system, as well as to identify potential technical, economic, and environment... [more]
A Discrete Element Method Study of Solids Stress in Cylindrical Columns Using MFiX
Filippo Marchelli, Renzo Di Felice
October 11, 2021 (v1)
Keywords: Coulomb friction force, discrete element method, Janssen effect, solids pressure
Friction phenomena play a key role in discrete element method (DEM) modeling. To analyze this aspect, we employed the open-source program MFiX to perform DEM simulations of cylindrical vertical columns filled with solid particles. These are still associated with and described by the pioneering model by the German engineer H.A. Janssen. By adapting the program’s code, we were able to gather numerous insights on the stress distribution within the solids. The column was filled with different amounts of solids and, after the system had stabilized, we assessed the pressure in the vertical and radial directions and the distribution of the friction force for all particles. An analysis of the bottom pressure for varying particle loads allowed us to infer that the program can correctly predict the expected asymptotical behavior. After a detailed assessment of the behavior of a single system, we performed a sensitivity analysis taking into account several of the variables employed in the simulat... [more]
Kanchan Arsenic Filters and the Future of Fe0-Based Filtration Systems for Single Household Drinking Water Supply
Zhe Huang, Viet Cao, Esther Laurentine Nya, Willis Gwenzi, Chicgoua Noubactep
October 11, 2021 (v1)
Subject: Materials
Keywords: arsenic removal, groundwater contamination, household filter, removal efficiency, zero-valent iron
Biological and chemical contamination of natural water bodies is a global health risk for more than one billion people, mostly living in low-income countries. Innovative, affordable, and efficient decentralized solutions for safe drinking water supply are urgently needed. Metallic iron (Fe0)-based filtration systems have been described as such an appropriate solution. This communication focuses on the Kanchan arsenic filter (KAF), presented in the early 2000s and widely assessed during the past decade. The KAF contains iron nails as the Fe0 source and is primarily designed to remove As from polluted tube well waters. Recent independent works assessing their performance have all reported on a high degree of variability in efficiency depending mostly on the following factors: (1) the current operating conditions, (2) the design, and (3) the groundwater chemistry. This communication shows that the major problems of the KAF are two-fold: (1) a design mistake as the Fe0 units disturb the op... [more]
Fabrication and Analysis of Polydimethylsiloxane (PDMS) Microchannels for Biomedical Application
Shahzadi Tayyaba, Muhammad Waseem Ashraf, Zubair Ahmad, Ning Wang, Muhammad Javaid Afzal, Nitin Afzulpurkar
October 11, 2021 (v1)
Subject: Biosystems
Keywords: biocompatibility, curvilinear microchannel, fuzzy, internet of things (IoT), polydimethylsiloxane (PDMS), sterilization
In this research work, Polydimethylsiloxane (PDMS) has been used for the fabrication of microchannels for biomedical application. Under the internet of things (IoT)-based controlled environment, the authors have simulated and fabricated bio-endurable, biocompatible and bioengineered PDMS-based microchannels for varicose veins implantation exclusively to avoid tissue damaging. Five curved ascending curvilinear micro-channel (5CACMC) and five curved descending curvilinear micro-channels (5CDCMC) are simulated by MATLAB (The Math-Works, Natick, MA, USA) and ANSYS (ANSYS, The University of Lahore, Pakistan) with actual environments and confirmed experimentally. The total length of each channel is 1.6 cm. The diameter of both channels is 400 µm. In the ascending channel, the first to fifth curve cycles have the radii of 2.5 mm, 5 mm, 7.5 mm, 10 mm, and 2.5 mm respectively. In the descending channel, the first and second curve cycles have the radii of 12.5 mm and 10 mm respectively. The thir... [more]
Modeling the Spread of Epidemics Based on Cellular Automata
Jindong Dai, Chi Zhai, Jiali Ai, Jiaying Ma, Jingde Wang, Wei Sun
October 11, 2021 (v1)
Keywords: cellular automata, dynamic simulation, mathematical model, process system engineering
Mathematical modeling is a powerful tool to study the process of the spread of infectious diseases. Among various mathematical methods for describing the spread of infectious diseases, the cellular automaton makes it possible to explicitly simulate both the spatial and temporal evolution of epidemics with intuitive local rules. In this paper, a model is proposed and realized on a cellular automata platform, which is applied to simulate the spread of coronavirus disease 2019 (COVID-19) for different administrative districts. A simplified social community is considered with varying parameters, e.g., sex ratio, age structure, population movement, incubation and treatment period, immunity, etc. COVID-19 confirmation data from New York City and Iowa are adopted for model validation purpose. It can be observed that the disease exhibits different spread patterns in different cities, which could be well accommodated by this model. Then, scenarios under different control strategies in the next... [more]
Expression of the Thermobifida fusca β-1,3-Glucanase in Yarrowia lipolytica and Its Application in Hydrolysis of β-1,3-Glucan from Four Kinds of Polyporaceae
Wei-Lin Chen, Jo-Chieh Hsu, Chui-Li Lim, Cheng-Yu Chen, Chao-Hsun Yang
October 11, 2021 (v1)
Subject: Biosystems
Keywords: antioxidant activity, Pycnoporus sanguineus, Thermobifida fusca, Wolfiporia cocos, Yarrowia lipolytica, β-1,3-glucanase
The gene encoding a thermostable β-1,3-glucanase was cloned from Thermobifida fusca and expressed constitutively by Yarrowia lipolytica using plasmid pYLSC1. The expression level of the recombinant β-1,3-glucanase reached up to 270 U/mL in the culture medium. After a treatment with endo-β-N-acetyl-glucosaminidase H, the recombinant protein appeared as a single protein band, with a molecular size of approximately 66 kDa on the SDS-polyacrylamide gel. The molecular weight was consistent with the size predicted from the nucleotide sequence. The optimum temperature and pH of the transformant β-1,3-glucanase were 60 °C and pH 8.0, respectively. This β-1,3-glucanase was tolerant to 10% methanol, ethanol, and DMSO, retaining 70% activity. The enzyme markedly hydrolyzed Wolfiporia cocos and Pycnoporus sanguineus glucans. The DPPH and ABTS scavenging potential, reducing power and total phenolic contents of these two Polyporaceae hydrolysates, were significantly increased after 18 h of the enzym... [more]
Reversible Bonding of Thermoplastic Elastomers for Cell Patterning Applications
Byeong-Ui Moon, Keith Morton, Kebin Li, Caroline Miville-Godin, Teodor Veres
October 11, 2021 (v1)
Subject: Biosystems
Keywords: cell migration, cell patterning, reversible bonding, thermoplastic elastomers
In this paper, we present a simple, versatile method that creates patterns for cell migration studies using thermoplastic elastomer (TPE). The TPE material used here can be robustly, but reversibly, bonded to a variety of plastic substrates, allowing patterning of cultured cells in a microenvironment. We first examine the bonding strength of TPE to glass and polystyrene substrates and com-pare it to thermoset silicone-based PDMS under various conditions and demonstrate that the TPE can be strongly and reversibly bonded on commercially available polystyrene culture plates. In cell migration studies, cell patterns are templated around TPE features cored from a thin TPE film. We show that the significance of fibroblast cell growth with fetal bovine serum (FBS)-cell culture media compared to the cells cultured without FBS, analyzed over two days of cell culture. This simple approach allows us to generate cell patterns without harsh manipulations like scratch assays and to avoid damaging th... [more]
Identification of Penicillium verrucosum, Penicillium commune, and Penicillium crustosum Isolated from Chicken Eggs
Soňa Demjanová, Pavlina Jevinová, Monika Pipová, Ivana Regecová
October 11, 2021 (v1)
Keywords: colony morphology, creatine, egg, Ehrlich reaction, mold, PCR, PCR-ITS-RFLP, Penicillium, restriction enzyme
Penicillium species belong to main causative agents of food spoilage leading to significant economic losses and potential health risk for consumers. These fungi have been isolated from various food matrices, including table eggs. In this study, both conventional Polymerase Chain Reaction (PCR) and Polymerase Chain Reaction-Internal Transcribed Spacer-Restriction Fragment Length Polymorphism (PCR-ITS-RFLP) methods were used for species identification of Penicillium (P.) spp. isolated from the eggshells of moldy chicken eggs. Seven restriction endonucleases (Bsp1286I, XmaI, HaeIII, HinfI, MseI, SfcI, Hpy188I) were applied to create ribosomal restriction patterns of amplified ITS regions. To identify P. verrucosum, P. commune, and P. crustosum with the help of conventional PCR assay, species-specific primer pairs VERF/VERR, COMF/COMR, and CRUF/CRUR were designed on the base of 5.8 subunit-Internal Transcribed Spacer (5.8S-ITS) region. Altogether, 121 strains of microscopic filamentous fun... [more]
Modeling and Flowsheet Simulation of Vibrated Fluidized Bed Dryers
Soeren E. Lehmann, Moritz Buchholz, Alfred Jongsma, Fredrik Innings, Stefan Heinrich
October 11, 2021 (v1)
Keywords: drying kinetics, Dyssol, flowsheet simulation, fluidized bed drying, Modelling, vibrated fluidized bed
Drying in fluidized beds is an important step in the production of powdered materials. Especially in the food and pharmaceutical industry, fluidized bed dryers are often vibrated to improve the drying process. In the current work, a continuous fluidized bed drying model is implemented in the novel, open-source flowsheet simulation framework Dyssol. The new model accounts for the hydrodynamic characteristics of all Geldart groups as well as the impact of mechanical vibration on the drying process. Distributed particle properties are considered by the model. Comprehensive validation of the model was conducted for a wide range of process parameters, different materials, dryer geometries and dimensions as well as the impact of vibration. Particle properties are predicted accurately and represent the broad experimental data well. A sensitivity analysis of the model confirmed grid independence and the validity of underlying model assumptions.
Integrating FMEA and the Kano Model to Improve the Service Quality of Logistics Centers
Ling-Lang Tang, Shun-Hsing Chen, Chia-Chen Lin
October 11, 2021 (v1)
Keywords: failure mode and effect analysis (FMEA), Kano model, logistics center, service failure, service quality
This study uses the logistics center of a large organic retail store in Taiwan to analyze service blueprint and workflow, identifying the potential points of failure and thus serving as a basis for quality improvement. The failure mode and effect analysis (FMEA) model is an effective problem prevention methodology that can easily interface with many engineering and reliability methods. The utilized method integrates the failure mode and effect analysis (FMEA) and the Kano model to explore the possible occurrence of failures in the internal workflow and services of the studied logistics center. A two-stage survey was conducted. In the first stage, an investigation was conducted by 20 logistics experts on the FMEA’s key service failures. In the second stage, a questionnaire was filled out by 220 store staff to summarize the logistics service quality factors found in the Kano model. The results show that the degree of attention and satisfaction in the priority improvement items when there... [more]
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