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An Individual-based Model for Simulating Antibiotic Resistance Spread in Bacterial Flocs in Wastewater Treatment Plants
Get PDFWastewater treatment plants (WWTPs) receive wastewater that carries a variety of pollutants, including antibiotics and antibiotic-resistant bacteria. The potential for horizontal gene transfer of resistance through conjugation – direct cell-to-cell transfer of genes carried on a plasmid – is high in WWTPs because of high cell density and residence time in bacterial flocs. To better understand how resistance spreads by growth and conjugation in such flocs, we propose an individual-based model with a solver algorithm for dynamic simulation. Our model includes only the most relevant bacteria properties and functions such as movement, growth, division, gene transfer, and death. Simulation of our model suggests that resistance can increase by conjugation at the early growth stages of a floc and that the overall rate of gene transfer depends on floc size. Results indicate that our simple model can be a useful tool for examining how gene exchange and heterogeneity contribute to the spread of antibiotic resistance in bacterial flocs
Comparison of machine learning approaches for spectroscopy applications
Get PDFIn energy production the characterization of the fuel is a key aspect for modelling and optimizing the operation of a power plant. Near-infrared spectroscopy is a wellestablished method for characterization of different fuels and is widely used both in laboratory environments and in power plants for real-time results. It can provide a fast and accurate estimate of key parameters of the fuel, which for the case of biomass can include moisture content, heating value, and ash content. These instruments provide a chemical fingerprint of the samples and require a calibration model to relate that to the parameters of interest.
A near-infrared spectrometer can provide point data whereas a hyperspectral imaging camera allows the simultaneous acquisition of spatial and spectral information from an object. As a result, an installation above a conveyor belt can provide a distribution of the spectral data on a plane. This results in a large amount of data that is difficult to handle with traditional statistical analysis. Furthermore, storage of the data becomes a key issue, therefore a model to predict the parameters of interest should be able to be updated continuously in an automated way. This makes hyperspectral imaging data a prime candidate for the application of machine learning techniques. This paper discusses the modelling approach for hyperspectral imaging, focusing on data analysis and assessment of machine learning approaches for the development of calibration models
Dynamic modeling of diafiltration system for a biorefinery application
Get PDFApplication of membrane technologies in biorefinery processes has been studied for some time. The heterogenous nature of biorefinery steams, however, results in unideal performance of membrane systems and considerable fouling of membranes, which is decreasing the efficiency of separation. As a part of BioSPRINT project, this study focuses on application of separating monomeric sugars from the hemicelluloses fraction of lignocellulosic biomass, where pressure-driven nanofiltration with several diafiltration stages has been proposed for the separation task. Diafiltration is required to overcome the decreased separation efficiency when the retentate concentrations and viscosity increases. A lumped parameter dynamical model of the diafiltration plant is applied. The key model parameters are identified from experimental data from a laboratory membrane unit to reflect the considered biorefinery process. The model is then simulated to study the sensitivity of the uncertain model parameters (related to membrane fouling, solute concentrations, viscosity, and mass transfer coefficients) to the diafiltration plant performance (product purity, operation time). The model is implemented in the MATLAB®/Simulink environment. The simulation results are expected to identify potential sources of scale-up challenges in biorefinery-related membrane applications. The developed dynamic model also allows to investigate different operational strategies of diafiltration plants in the future
Simulation and optimization of screw feeder in a bubbling fluidized bed gasification reactor
Get PDFA fluidized bed biomass gasification reactor is used to produce syngas from biomass and municipal wastes. Gasification is a flexible technology where many different types of feedstocks can be used. The University of South-Eastern Norway has a 20kW gasification reactor which is used to investigate the quality and quantity of the syngas produced using different types of feedstocks. At the present, the reactor has the challenge to supply feedstock to the reactor via transport screws. The main challenge consists of achieving continuous feeding and reduction in the feed rate. Therefore, this work is focused on the optimization of the screw feeder in the gasification reactor to obtain a reduced feed rate while maintaining a continuous feeding rate. The aim is to reduce the feed rate from approximately 8 kg/h to 3-4 kg/h without missing continuity of the feeding.
A model of the screw feeder is developed using CAD software SolidWorks and the model is simulated using open-source simulation software LIGGGHTS to investigate feed rate and continuity using different combinations of transport screw parameters. The simulation results are processed using Excel and viewed graphically with the open-source visualization software ParaView. The simulation results are compared to the experimental measurements in the gasification reactor. The validated model is further used to investigate the feed rate with different combinations of transport screw parameters and the results are compared and discussed
Anaerobic Co-Digestion of Products from Biosolids Pyrolysis – Implementation in ADM1
Get PDFPyrolyzing biosolids can decrease volume and increase value of solids while anaerobic digestion of gas and liquids from the process could increase overall methane production. Prediction of process behavior and biogas yield through simulation is valuable when considering new substrates for anaerobic digestion. In this study, gas and liquids from biosolids pyrolysis were implemented in Anaerobic Digestion Model No 1 (ADM1) together with a stream of thermally hydrolyzed sludge/food waste used in an industrial biogas plant. Average operational data from the industrial plant was used to calibrate the base scenario in ADM1, achieving a good fit. Simulation scenarios evaluating two hydrolysis constants for the pyrolysis liquid showed minor differences at the load simulated and simulated variations in composition of the liquid showed minor differences. Simulation of adding a relevant stream of pyrolysis liquid and gas together increased methane production by 7 % but decreased overall methane yield from 63 % to 61 % compared to the base scenario
Towards Mapping of Information Technology-Induced Alterations in Online Physicians’ Professional Identities: A Conceptual Framework and Empirical Illustrations from Sweden
Get PDFDigital Patient Contact Technologies (DPCT), including telemedicine solutions and digital tools for text-based communication between patients and physicians, play a significant role in today’s healthcare. Professional identity defines norms, principles, and logic that guide one’s professional actions. Presently, little research is available regarding professional identity changes in the context of DPCT implementations. This work theoretically and empirically illustrates the nature of the possible DPCT’ impact on physicians’ professional identities. To this end, a conceptual framework was constructed, and the interviews with eight physicians operating an asynchronous healthcare-advice chat service (1177 Vårdguiden) in Uppsala, Sweden, were examined
Three Dimensional Ontological Perspective for Designing Healthcare Services
No full textSuccessful e-Health system engineering mainly depends on accurate and complete modelling of the HealthCare (HC) processes. These HC service processes are governed by a variety of regulations and rules enforced by many distinct authorities. Availability of these governance directives mostly on paper based-medium makes a bunch of information logistics and related issues in HC processes of e-Health systems. Further, even captured such directives are getting often buried in lower technical realizations making its impossible not only real-time adoption but also manipulation on long run by respective non-technical higher authorities. In order to rectify and to facilitate these stakeholders’ requirements for assistance with their access to these governing layers of e-Health solutions, in this work, we have proposed a three-dimensional ontological framework. This framework is expected to provide a complete and sound platform first to identify and then to develop eHealth solutions in compliance with those governing directives. In addition, it will ensure making convenient access with the non-technical higher healthcare authorities to monitoring and to governing HC processes. Proposed framework consists of three dimensions; 1) HC process activity dimension, 2) HC responsibility dimension and 3) HC directive enforcement dimension. The proposed approach facilitates the separation of concerns in HC governing perspectives in e-health solution development
CLARIN Knowledge Centre for Belarusian Text and Speech Processing (K-BLP)
Get PDFThis paper represents the CLARIN Knowledge Centre for Belarusian text and speech processing (K-BLP) which is based at the Speech synthesis and recognition laboratory, the United Institute of Informatics Problems of the National Academy of Sciences of Belarus, Minsk. The CLARIN Knowledge Centre for Belarusian text and speech processing is part of the CLARIN ERIC, which holds the European ESFRI (European Strategy Forum on Research Infrastructures) certification as a landmark research infrastructure. Services for text and speech processing, which were developed by the Laboratory, are presented in the article
Building of Parallel and Comparable Cybersecurity Corpora for Bilingual Terminology Extraction
Get PDFThe paper aims at presenting English-Lithuanian corpora for bilingual term extraction (BiTE) in the cybersecurity domain within the framework of the project DVITAS. It is argued that a system of parallel, comparable, and training corpora for BiTE is particularly useful for less-resourced languages, as it allows efficiently to combine strengths and avoid weaknesses of comparable and parallel resources. A special focus is given to the availability of sources in the cybersecurity domain and issues related to copyright-protected publications, as well as the data curation performed for building the corpora and depositing them to CLARIN-LT repository
Wrong Design of Cipher Keys: Analysis of Historical Cipher Keys From the Hessisches Staatsarchiv Marburg Used in the Thirty Years’ War
Get PDFNomenclator is a complex encryption system consisting of several different simpler encryption systems used together during the encryption. It is one of the main encryption systems used before the twentieth century. In some cases, there are large collections of historical ciphers preserved in archives. Those from a particular time period or geographic location are very valuable and can bring insights to the cipher design from a specific time/location. This paper provides the first detailed empirical analysis of historical cipher keys from the Thirty Years’War deposited in Hessisches Staatsarchiv Marburg. We describe a large variety of analyzed keys with a focus on those properties (poorly designed keys) that can decrease the security of the cipher. We further show that these properties alone do not imply a bad design, sometimes a combination of several properties is needed and at the same time a bad use of the encryption key