Search results for: models synthesis

Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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The utilization of Large Eddy Simulation (LES) has been extensive in turbulence research. LES concentrates on resolving the significant grid-scale motions while representing smaller scales through subfilter-scale (SFS) models. The deconvolution model, among the available SFS models, has proven successful in LES of engineering and geophysical flows. Nevertheless, the thorough investigation of how sub-filter scale dynamics and filter anisotropy affect SFS modeling accuracy remains lacking. The outcomes of LES are significantly influenced by filter selection and grid anisotropy, factors that have not been adequately addressed in earlier studies. This study examines two crucial aspects of LES: Firstly, the accuracy of direct deconvolution models (DDM) is evaluated concerning sub-filter scale (SFS) dynamics across varying filter-to-grid ratios (FGR) in isotropic turbulence. Various invertible filters are employed, including Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The importance of FGR becomes evident as it plays a critical role in controlling errors for precise SFS stress prediction. When FGR is set to 1, the DDM models struggle to faithfully reconstruct SFS stress due to inadequate resolution of SFS dynamics. Notably, prediction accuracy improves when FGR is set to 2, leading to accurate reconstruction of SFS stress, except for cases involving Helmholtz I and II filters. Remarkably high precision, nearly 100%, is achieved at an FGR of 4 for all DDM models. Furthermore, the study extends to filter anisotropy and its impact on SFS dynamics and LES accuracy. By utilizing the dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with anisotropic filters, aspect ratios (AR) ranging from 1 to 16 are examined in LES filters. The results emphasize the DDM’s proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. Notably high correlation coefficients exceeding 90% are observed in the a priori study for the DDM’s reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as filter anisotropy increases. In the a posteriori analysis, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, including velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strainrate tensors, and SFS stress. It is evident that as filter anisotropy intensifies, the results of DSM and DMM deteriorate, while the DDM consistently delivers satisfactory outcomes across all filter-anisotropy scenarios. These findings underscore the potential of the DDM framework as a valuable tool for advancing the development of sophisticated SFS models for LES in turbulence research.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Naman Solanki, Souraj Mondal

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With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

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Authors: A. Daftari, W. Kudla

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Liquefaction is a phenomenon in which the strength and stiffness of a soil is reduced by earthquake shaking or other rapid cyclic loading. Liquefaction and related phenomena have been responsible for huge amounts of damage in historical earthquakes around the world. Modelling of soil behaviour is the main step in soil liquefaction prediction process. Nowadays, several constitutive models for sand have been presented. Nevertheless, only some of them can satisfy this mechanism. One of the most useful models in this term is UBCSAND model. In this research, the capability of this model is considered by using PLAXIS software. The real data of superstition hills earthquake 1987 in the Imperial Valley was used. The results of the simulation have shown resembling trend of the UBC3D-PLM model.

Keywords: liquefaction, plaxis, pore-water pressure, UBC3D-PLM

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Authors: Lucie Jirotková, Daniel Macek, Andrea Palazzo, Veronika Malinová

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Currently, the implementation of 3D models in the construction industry is gaining popularity. Countries around the world are developing their own modelling standards and implement the use of 3D models into their individual permitting processes. Another theme that needs to be addressed are public building spaces and their subsequent maintenance, where the usage of BIM methodology is directly offered. The significant benefit of the implementation of Building Information Management is the information transfer. The 3D model contains not only the spatial representation of the item shapes but also various parameters that are assigned to the individual elements, which are easily traceable, mainly because they are all stored in one place in the BIM model. However, it is important to keep the data in the models up to date to achieve useability of the model throughout the life cycle of the building. It is now becoming standard practice to use BIM models in the construction of buildings, however, the building environment is very often neglected. Especially in large-scale development projects, the public space of buildings is often forwarded to municipalities, which obtains the ownership and are in charge of its maintenance. A 3D model of the building surroundings would include both the above-ground visible elements of the development as well as the underground parts, such as the technological facilities of water features, electricity lines for public lighting, etc. The paper shows the possibilities of a model in the field of information for the handover of premises, the following maintenance and decision making. The attributes and spatial representation of the individual elements make the model a reliable foundation for the creation of "Smart Cities". The paper analyses the current use of the BIM methodology and presents the state-of-the-art possibilities of development.

Keywords: BIM model, urban space, BIM methodology, facility management

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Authors: H. Dakhlaoui, D. Ruelland, Y. Tramblay, Z. Bargaoui

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To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that are able to be fairly reliable under changing climate conditions. This study aims at assessing the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in Northern Tunisia under long-term climate variability. Their robustness was evaluated according to a differential split sample test based on a climate classification of the observation period regarding simultaneously precipitation and temperature conditions. The studied catchments are situated in a region where climate change is likely to have significant impacts on runoff and they already suffer from scarcity of water resources. They cover the main hydrographical basins of Northern Tunisia (High Medjerda, Zouaraâ, Ichkeul and Cap bon), which produce the majority of surface water resources in Tunisia. The streamflow regime of the basins can be considered as natural since these basins are located upstream from storage-dams and in areas where withdrawals are negligible. A 30-year common period (1970‒2000) was considered to capture a large spread of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while the evaluation of model transferability is performed according to the Nash-Suttfliff efficiency criterion and volume error. The three hydrological models were shown to have similar behaviour under climate variability. Models prove a better ability to simulate the runoff pattern when transferred toward wetter periods compared to the case when transferred to drier periods. The limits of transferability are beyond -20% of precipitation and +1.5 °C of temperature in comparison with the calibration period. The deterioration of model robustness could in part be explained by the climate dependency of some parameters.

Keywords: rainfall-runoff modelling, hydro-climate variability, model robustness, uncertainty, Tunisia

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Authors: Jessica Carolina Hernandez Galeano, Juan Carlos Moreno Pirajan, Liliana Giraldo

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Carbon gels are materials whose structure and porous texture can be designed and controlled on a nanoscale. Among their characteristics it is found their low density, large surface area and high degree of porosity. These materials are produced by a sol-gel polymerization of organic monomers using basic or acid catalysts, followed by drying and controlled carbonization. In this work, the synthesis and characterization of carbon aerogels from resorcinol, phenol and formaldehyde in ethanol is described. The aim of this study is obtaining different carbonaceous materials in the form of spheres using the Stöber method to perform a further evaluation of CO₂ adsorption of each material. In general, the synthesis consisted of a sol-gel polymerization process that generates a cluster (cross-linked organic monomers) from the precursors in the presence of NH₃ as a catalyst. This cluster was subjected to specific conditions of gelling and curing (30°C for 24 hours and 100°C for 24 hours, respectively) and CO₂ supercritical drying. Finally, the dry material was subjected to a process of carbonization or pyrolysis, in N₂ atmosphere at 350°C (1° C / min) for 2 h and 600°C (1°C / min) for 4 hours, to obtain porous solids that retain the structure initially desired. For this work, both the concentrations of the precursors and the proportion of ammonia in the medium where modify to describe the effect of the use of phenol and the amount of catalyst in the resulting material. Carbon aerogels were characterized by Scanning Electron Microscope (SEM), N₂ isotherms, infrared spectroscopy (IR) and X-ray Powder Diffraction (XRD) showing the obtention of carbon spheres in the nanometric scale with BET areas around 500 m2g-1.

Keywords: carbon aerogels, carbon spheres, CO₂ adsorption, Stöber method

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Lori Lioce, Gary Maddux, Norven Goddard, Ishella Fogle, Bernard Schroer

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This paper presents the integration of technologies into nursing education. The collaborative effort includes the College of Nursing (CoN) at the University of Alabama in Huntsville (UAH) and the UAH Systems Management and Production Center (SMAP). The faculty at the CoN conducts needs assessments to identify education and training requirements. A team of CoN faculty and SMAP engineers then prioritize these requirements and establish improvement/development teams. The development teams consist of nurses to evaluate the models and to provide feedback and of undergraduate engineering students and their senior staff mentors from SMAP. The SMAP engineering staff develops and creates the physical models using 3D printing, silicone molds and specialized molding mixtures and techniques. The collaboration has focused on developing teaching and training, or clinical, simulators. In addition, the onset of the Covid-19 pandemic has intensified this relationship, as 3D modeling shifted to supplied personal protection equipment (PPE) to local health care providers. A secondary collaboration has been introducing students to clinical benchmarking through the UAH Center for Management and Economic Research. As a result of these successful collaborations the Model Exchange & Development of Nursing & Engineering Technology (MEDNET) has been established. MEDNET seeks to extend and expand the linkage between engineering and nursing to K-12 schools, technical schools and medical facilities in the region to the resources available from the CoN and SMAP. As an example, stereolithography (STL) files of the 3D printed models, along with the specifications to fabricate models, are available on the MEDNET website. Ten 3D printed models have been developed and are currently in use by the CoN. The following additional training simulators are currently under development:1) suture pads, 2) gelatin wound models and 3) printed wound tattoos. Specification sheets have been written for these simulations that describe the use, fabrication procedures and parts list. These specifications are available for viewing and download on MEDNET. Included in this paper are 1) descriptions of CoN, SMAP and MEDNET, 2) collaborative process used in product improvement/development, 3) 3D printed models of training and teaching simulators, 4) training simulators under development with specification sheets, 5) family care practice benchmarking, 6) integrating the simulators into the nursing curriculum, 7) utilizing MEDNET as a pandemic response, and 8) conclusions and lessons learned.

Keywords: 3D printing, nursing education, simulation, trainers

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, José J. Hernández-Flores, Edith Olaco Garcia

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The Project Scheduling Problem (PSP) is a generic name given to a whole class of problems in which the best form, time, resources and costs for project scheduling are necessary. The PSP is an application area related to the project management. This paper aims at being a guide to understand PSP by presenting a survey of the general parameters of PSP: the Resources (those elements that realize the activities of a project), and the Activities (set of operations or own tasks of a person or organization); the mathematical models of the main variants of PSP and the algorithms used to solve the variants of the PSP. The project scheduling is an important task in project management. This paper contains mathematical models, resources, activities, and algorithms of project scheduling problems. The project scheduling problem has attracted researchers of the automotive industry, steel manufacturer, medical research, pharmaceutical research, telecommunication, industry, aviation industry, development of the software, manufacturing management, innovation and technology management, construction industry, government project management, financial services, machine scheduling, transportation management, and others. The project managers need to finish a project with the minimum cost and the maximum quality.

Keywords: PSP, Combinatorial Optimization Problems, Project Management; Manufacturing Management, Technology Management.

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Authors: Aakash Chhunchha, Assma Begum

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The qualitative aspects of hypersonic flow over a range of blunt bodies have been extensively analyzed in the past. It is well known that the curvature of a body’s geometry in the sonic region predominantly dictates the bow shock shape and its standoff distance from the body, while the surface pressure distribution depends on both the sonic region and on the local body shape. The present study is an extension to analyze the hypersonic flow characteristics over several blunt-nosed bodies using modern Computational Fluid Dynamics (CFD) tools to determine the shock shape and its effect on the heat flux around the body. 4 blunt-nosed models with cylindrical afterbodies were analyzed for a flow at a Mach number of 10 corresponding to the standard atmospheric conditions at an altitude of 50 km. The nose radii of curvature of the models range from a hemispherical nose to a flat nose. Appropriate numerical models and the supplementary convergence techniques that were implemented for the CFD analysis are thoroughly described. The flow contours are presented highlighting the key characteristics of shock wave shape, shock standoff distance and the sonic point shift on the shock. The variation of heat flux, due to different shock detachments for various models is comprehensively discussed. It is observed that the more the bluntness of the nose radii, the farther the shock stands from the body; and consequently, the less the surface heating at the nose. The results obtained from the CFD analyses are compared with approximated theoretical engineering correlations. Overall, a satisfactory agreement is observed between the two.

Keywords: aero-thermodynamics, blunt-nosed bodies, computational fluid dynamics (CFD), hypersonic flow

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Authors: Leonardo C. Pacheco-Londoño, Nataly J. Galan-Freyle, Lisandro Pacheco-Lugo, Antonio Acosta, Elkin Navarro, Gustavo Aroca-Martínez, Karin Rondón-Payares, Samuel P. Hernández-Rivera

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In our Life Science Research Center of the University Simon Bolivar (LSRC), one of the focuses is the diagnosis and prognosis of different diseases; we have been implementing the use of gold nanoparticles (Au-NPs) for various biomedical applications. In this case, Au-NPs were used for Surface-Enhanced Raman Spectroscopy (SERS) in different diseases' diagnostics, such as Lupus Nephritis (LN), hypertension (H), preeclampsia (PC), and others. This methodology is proposed for the diagnosis of each disease. First, good signals of the different metabolites by SERS were obtained through a mixture of urine samples and Au-NPs. Second, PLS-DA models based on SERS spectra to discriminate each disease were able to differentiate between sick and healthy patients with different diseases. Finally, the sensibility and specificity for the different models were determined in the order of 0.9. On the other hand, a second methodology was developed using machine learning models from all data of the different diseases, and, as a result, a discriminant spectral map of the diseases was generated. These studies were possible thanks to joint research between two university research centers and two health sector entities, and the patient samples were treated with ethical rigor and their consent.

Keywords: SERS, Raman, PLS-DA, diseases

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Authors: Nesrine Benarous, Hassiba Bougueria, Nabila Moussa Slimane, Aouatef Cherouana

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Crystal polymorphism is important for the synthesis of more potent and bioactive pharmaceutical compounds, including their different properties, such as packing arrangement and conformation. In fact, polymorphism plays a vital role in drug development. Different parameters affect the crystallization and give their degree of freedom. Severalproperties affected polymorphism, like kinetics, thermodynamics, spectroscopy, and mechanical property. Various techniques are used for characterizing polymorphs, are crystallography, morphology, phase transitions, molecular motion, and chemical environment. In this work, crystal structures of two polymorphs (I and II) of the Schiff base (SB) title compound were prepared by condensation reaction. The crystal structures of both polymorphs were determined by single X-ray analysis. The two polymorphs crystallize in two different space groups: P21/c for I and Pbca for II. The dihedral angles between the two phenyl rings are 4.81º for I and 82.27º for II. Both crystal structures are built on the basis of moderate and weak hydrogen bonds, 𝜋-stacking, and halogen⋯halogeninteractions. On the other hand, Hirshfeld surface (HS) analysis indicates that the most important contributions to the crystal packing for the two polymorphs are from Cl⋯H/H⋯Cl, H⋯H, and N⋯H/H⋯N contacts. These are followed by C⋯H/H⋯C for compound I and C⋯C and by C⋯H/H⋯C contacts for compound II. Afterwards, the in vitro antibacterial activity revealed that the SB have been found effective against G- bacteria Klebsiella pneumonia andG+ bacteria Staphylococcus aureuswith MIC value of14.37μg/mL. Moreover, the SBexhibited moderate toxicity against Brine Shrimp with LC50 value of 44.19μg/mL.

Keywords: polymorph, crystal structure, hirshfeld surface analysis, in vitro antibacterial activity, toxicity

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Authors: Nader Ghareeb, Rüdiger Schmidt

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Minimizing the weight in flexible structures means reducing material and costs as well. However, these structures could become prone to vibrations. Attenuating these vibrations has become a pivotal engineering problem that shifted the focus of many research endeavors. One technique to do that is to design and implement an active control system. This system is mainly composed of a vibrating structure, a sensor to perceive the vibrations, an actuator to counteract the influence of disturbances, and finally a controller to generate the appropriate control signals. In this work, two different techniques are explored to create two different mathematical models of an active control system. The first model is a finite element model with a reduced number of nodes and it is called a super-element. The second model is in the form of state-space representation, i.e. a set of partial differential equations. The damping coefficients are calculated and incorporated into both models. The effectiveness of these models is demonstrated when the system is excited by its first natural frequency and an active control strategy is developed and implemented to attenuate the resulting vibrations. Results from both modeling techniques are presented and compared.

Keywords: damping coefficients, finite element analysis, super-element, state-space model

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Authors: Sze Shin Low, Michelle T. T. Tan, Poi Sim Khiew, Hwei-San Loh

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An efficient graphene/zinc oxide (PSE-G/ZnO) platform based on pi-pi stacking, non-covalent interactions for the development of aptamer-based biosensor was presented in this study. As a proof of concept, the DNA recognition capability of the as-developed PSE-G/ZnO enhanced aptamer-based biosensor was evaluated using Coconut Cadang-cadang viroid disease (CCCVd). The G/ZnO nanocomposite was synthesised via a simple, green and efficient approach. The pristine graphene was produced through a single step exfoliation of graphite in sonochemical alcohol-water treatment while the zinc nitrate hexahydrate was mixed with the graphene and subjected to low temperature hydrothermal growth. The developed facile, environmental friendly method provided safer synthesis procedure by eliminating the need of harsh reducing chemicals and high temperature. The as-prepared nanocomposite was characterised by X-ray diffractometry (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) to evaluate its crystallinity, morphology and purity. Electrochemical impedance spectroscopy (EIS) was employed for the detection of CCCVd sequence with the use of potassium ferricyanide (K3[Fe(CN)6]). Recognition of the RNA analytes was achieved via the significant increase in resistivity for the double stranded DNA, as compared to single-stranded DNA. The PSE-G/ZnO enhanced aptamer-based biosensor exhibited higher sensitivity than the bare biosensor, attributing to the synergistic effect of high electrical conductivity of graphene and good electroactive property of ZnO.

Keywords: aptamer-based biosensor, graphene/zinc oxide nanocomposite, green synthesis, screen printed carbon electrode

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Authors: Li Chen

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For an aerofoil or hydrofoil in high Reynolds number flows, broadband noise is generated efficiently as the result of the turbulence convecting over the trailing edge. This noise can be related to the surface pressure fluctuations, which can be predicted by either CFD or empirical models. However, in reality, the aerofoil or hydrofoil often operates at an angle of attack. Under this situation, the flow is subjected to an Adverse-Pressure-Gradient (APG), and as a result, a flow separation may occur. This study is to assess trailing-edge noise models for such flows. In the present work, the trailing-edge noise from a 2D airfoil at 6 degree of angle of attach is investigated. Under this condition, the flow is experiencing a strong APG, and the flow separation occurs. The flow over the airfoil with a chord of 300 mm, equivalent to a Reynold Number 4x10⁵, is simulated using RANS with the SST k-ɛ turbulent model. The predicted surface pressure fluctuations are compared with the published experimental data and empirical models, and show a good agreement with the experimental data. The effect of the APG on the trailing edge noise is discussed, and the associated trailing edge noise is calculated.

Keywords: aero-acoustics, adverse-pressure gradient, computational fluid dynamics, trailing-edge noise

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Authors: Pauline Bredy, Yves Schuurman, David Farrusseng

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To fulfill climate objectives, the production of synthetic e-fuels using CO₂ as a raw material appears as part of the solution. In particular, Power-to-Liquid (PtL) concept combines CO₂ with hydrogen supplied from water electrolysis, powered by renewable sources, which is currently gaining interest as it allows the production of sustainable fossil-free liquid fuels. The proposed process discussed here is an upgrading of the well-known Fischer-Tropsch synthesis. The concept deals with two cascade reactions in one pot, with first the conversion of CO₂ into CO via the reverse water gas shift (RWGS) reaction, which is then followed by the Fischer-Tropsch Synthesis (FTS). Instead of using a Fe-based catalyst, which can carry out both reactions, we have chosen the strategy to decouple the two functions (RWGS and FT) on two different catalysts within the same reactor. The FTS shall shift the equilibrium of the RWGS reaction (which alone would be limited to 15-20% of conversion at 250°C) by converting the CO into hydrocarbons. This strategy shall enable optimization of the catalyst pair and thus lower the temperature of the reaction thanks to the equilibrium shift to gain selectivity in the liquid fraction. The challenge lies in maximizing the activity of the RWGS catalyst but also in the ability of the FT catalyst to be highly selective. Methane production is the main concern as the energetic barrier of CH₄ formation is generally lower than that of the RWGS reaction, so the goal will be to minimize methane selectivity. Here we report the study of different combinations of copper-based RWGS catalysts with different cobalt-based FTS catalysts. We investigated their behaviors under mild process conditions by the use of high-throughput experimentation. Our results show that at 250°C and 20 bars, Cobalt catalysts mainly act as methanation catalysts. Indeed, CH₄ selectivity never drops under 80% despite the addition of various protomers (Nb, K, Pt, Cu) on the catalyst and its coupling with active RWGS catalysts. However, we show that the activity of the RWGS catalyst has an impact and can lead to longer hydrocarbons chains selectivities (C₂⁺) of about 10%. We studied the influence of the reduction temperature on the activity and selectivity of the tandem catalyst system. Similar selectivity and conversion were obtained at reduction temperatures between 250-400°C. This leads to the question of the active phase of the cobalt catalysts, which is currently investigated by magnetic measurements and DRIFTS. Thus, in coupling it with a more selective FT catalyst, better results are expected. This was achieved using a cobalt/iron FTS catalyst. The CH₄ selectivity dropped to 62% at 265°C, 20 bars, and a GHSV of 2500ml/h/gcat. We propose that the conditions used for the cobalt catalysts could have generated this methanation because these catalysts are known to have their best performance around 210°C in classical FTS, whereas the iron catalysts are more flexible but are also known to have an RWGS activity.

Keywords: cobalt-copper catalytic systems, CO₂-hydrogenation, Fischer-Tropsch synthesis, hydrocarbons, low-temperature process

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Authors: Samir K. Safi

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The purpose of this study was to compare the performance of two types of models, namely MIDAS and MIDAS-GARCH, in predicting the volatility of crude oil returns based on gold price returns and the COVID-19 pandemic. The study aimed to identify which model would provide more accurate short-term and long-term predictions and which model would perform better in handling the increased volatility caused by the pandemic. The findings of the study revealed that the MIDAS model performed better in predicting short-term and long-term volatility before the pandemic, while the MIDAS-GARCH model performed significantly better in handling the increased volatility caused by the pandemic. The study highlights the importance of selecting appropriate models to handle the complexities of real-world data and shows that the choice of model can significantly impact the accuracy of predictions. The practical implications of model selection and exploring potential methodological adjustments for future research will be highlighted and discussed.

Keywords: GARCH-MIDAS, MIDAS, crude oil, gold, COVID-19, volatility

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Authors: A. Kahil, A. Nekmouche, N. Khelil, I. Hamadou, M. Hamizi, Ne. Hannachi

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The objective of this work is to study the influence of the nonlinear behavior models of the concrete (concrete_BAEL and concrete_UNI) as well as the confinement brought by the transverse reinforcement on the seismic response of reinforced concrete frame (RC/frame). These models as well as the confinement are integrated in the Cast3m finite element calculation code. The consideration of confinement (TAC, taking into account the confinement) provided by the transverse reinforcement and the non-consideration of confinement (without consideration of containment, WCC) in the presence and absence of a vertical load is studied. The application was made on a reinforced concrete frame (RC/frame) with 3 levels and 2 spans. The results show that on the one hand, the concrete_BAEL model slightly underestimates the resistance of the RC/frame in the plastic field, whereas the concrete_uni model presents the best results compared to the simplified model "concrete_BAEL", on the other hand, for the concrete-uni model, taking into account the confinement has no influence on the behavior of the RC/frame under imposed displacement up to a vertical load of 500 KN.

Keywords: reinforced concrete, nonlinear calculation, behavior laws, fiber model confinement, numerical simulation

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Authors: M. A. Wanzala, L. A. Ogallo, F. J. Opijah, J. N. Mutemi

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The usefulness and limitations in climate information are due to uncertainty inherent in the climate system. For any given region to have sustainable development it is important to apply climate information into its socio-economic strategic plans. The overall objective of the study was to assess the performance of the Coupled Model Inter-comparison Project (CMIP5) over the Lake Victoria Basin. The datasets used included the observed point station data, gridded rainfall data from Climate Research Unit (CRU) and hindcast data from eight CMIP5. The methodology included trend analysis, spatial analysis, correlation analysis, Principal Component Analysis (PCA) regression analysis, and categorical statistical skill score. Analysis of the trends in the observed rainfall records indicated an increase in rainfall variability both in space and time for all the seasons. The spatial patterns of the individual models output from the models of MPI, MIROC, EC-EARTH and CNRM were closest to the observed rainfall patterns.

Keywords: categorical statistics, coupled model inter-comparison project, principal component analysis, statistical downscaling

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Authors: Ahmed Alqaoud

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This paper describes Publish/Subscribe Scientific Workflow Interoperability Framework (PS-SWIF) architecture and its components that collectively provide interoperability between heterogeneous scientific workflow systems. Requirements to achieve interoperability are identified. This paper also provides a detailed investigation and design of models and solutions for system requirements, and considers how workflow interoperability models provided by Workflow Management Coalition (WfMC) can be achieved using the PS-SWIF system.

Keywords: publish/subscribe, scientific workflow, web services, workflow interoperability

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Authors: Luciana Abednego, Cecilia Nugraheni

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There are many approaches proposed for solving Sudoku puzzles. One of them is by modelling the puzzles as block world problems. There have been three model for Sudoku solvers based on this approach. Each model expresses Sudoku solver as a parameterized multi agent systems. In this work, we propose a new model which is an improvement over the existing models. This paper presents the development of a Sudoku solver that implements all the proposed models. Some experiments have been conducted to determine the performance of each model.

Keywords: Sudoku puzzle, Sudoku solver, block world problem, parameterized multi agent systems

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Authors: Hunmin Jung, Michael Hawkins, Seongmin Lee

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The exocyclic amines of nucleobases can undergo deamination by various DNA damaging agents such as reactive oxygen species, nitric oxide, and water. The deamination of guanine and adenine generates the promutagenic xanthine and hypoxanthine, respectively. The exocyclic amines of bases in DNA are hydrogen bond donors, while the carbonyl moiety generated by the base deamination acts as hydrogen bond acceptors, which can alter base pairing properties of the purines. Xanthine is known to base pair with both cytosine and thymine, while hypoxanthine predominantly pairs with cytosine to promote A to G mutations. Despite the known promutagenicity of the major deaminated purines, structures of DNA polymerase bypassing these lesions have not been reported. To gain insights into the deaminated-induced mutagenesis, we solved crystal structures of human DNA polymerase η (polη) catalyzing across xanthine and hypoxanthine. In the catalytic site of polη, the deaminated guanine (i.e., xanthine) forms three Watson-Crick-like hydrogen bonds with an incoming dCTP, indicating the O2-enol tautomer of xanthine involves in the base pairing. The formation of the enol tautomer appears to be promoted by the minor groove contact by Gln38 of polη. When hypoxanthine is at the templating position, the deaminated adenine uses its O6-keto tautomer to form two Watson-Crick hydrogen bonds with an incoming dCTP, providing the structural basis for the high promutagenicity of hypoxanthine.

Keywords: DNA damage, DNA polymerase, deamination, mutagenesis, tautomerization, translesion synthesis

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Authors: Mukul R. Gupta, Rajkumar Gandhi, Rajitha Sachan, Naveen K. Khare

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The field of glycoscience has burgeoned in the last several decades, leading to the identification of many glycosides which could serve critical roles in a wide range of biological processes. This has prompted a resurgence in synthetic interest, with a particular focus on new approaches to construct the selective glycosidic bond. Despite the numerous elegant strategies and methods developed for the formation of glycosidic bonds, stereoselective construction of glycosides remains challenging. Here, we have recently developed the novel Hexafluoroisopropanol (HFIP) catalyzed stereoselective glycosylation methods by using KDN imidate glycosyl donor and a variety of alcohols in excellent yield. This method is broadly applicable to a wide range of substrates and with excellent selectivity of glycoside. Also, herein we are reporting the functionalization of the unbiased side of newly formed glycosides by dual-catalytic transition metal systems (Ru- or Fe-). We are using the innovative Reverse & Catalyst strategy, i.e., a reversible activation reaction by one catalyst with a functionalization reaction by another catalyst, together with enabling functionalization of substrates at their inherently unreactive sites. As well, we are targeting the diSia derivative synthesis by Wittig reaction. This synthetic method is applicable in mild conditions, functional group tolerance of the dual-catalytic systems and also highlights the potential of the multicatalytic approach to address challenging transformations to avoid multistep procedures in carbohydrate synthesis.

Keywords: KDN, stereoselective glycosylation, dual-catalytic functionalization, Wittig reaction

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Authors: M. Ahmadi, Sh. Damanabi, F. Sadoughi

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National Health Information System plays an important role in ensuring timely and reliable access to Health information which is essential for strategic and operational decisions that improve health, quality and effectiveness of health care. In other words, by using the National Health information system you can improve the quality of health data, information and knowledge used to support decision making at all levels and areas of the health sector. Since full identification of the components of this system for better planning and management influential factors of performance seems necessary, therefore, in this study, different attitudes towards components of this system are explored comparatively. Methods: This is a descriptive and comparative kind of study. The society includes printed and electronic documents containing components of the national health information system in three parts: input, process, and output. In this context, search for information using library resources and internet search were conducted and data analysis was expressed using comparative tables and qualitative data. Results: The findings showed that there are three different perspectives presenting the components of national health information system, Lippeveld, Sauerborn, and Bodart Model in 2000, Health Metrics Network (HMN) model from World Health Organization in 2008 and Gattini’s 2009 model. All three models outlined above in the input (resources and structure) require components of management and leadership, planning and design programs, supply of staff, software and hardware facilities, and equipment. In addition, in the ‘process’ section from three models, we pointed up the actions ensuring the quality of health information system and in output section, except Lippeveld Model, two other models consider information products, usage and distribution of information as components of the national health information system. Conclusion: The results showed that all the three models have had a brief discussion about the components of health information in input section. However, Lippeveld model has overlooked the components of national health information in process and output sections. Therefore, it seems that the health measurement model of network has a comprehensive presentation for the components of health system in all three sections-input, process, and output.

Keywords: National Health Information System, components of the NHIS, Lippeveld Model

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Authors: Linto Francis Kallukulangara

Abstract:

Although the Catholic and Reformed traditions share a common baptismal heritage, they differe considerably in their epistemic stance on whether a believer can legitimatly subscribe to a proposition of Christian Revelation without any evidence. Catholic tradition, which is essentially rooted in the internalist epistemology, posits that a theistic belief must be substantiated by a rational ground that is cognitively accessible to the believer. In contrast, Reformed thinkers have historically maintained a non-evidentialist stance, which has received strong criticism, including allegations of irrationality. However, recent developments in analytic philosophy, particularly the rise of externalist epistemology, have revitalized the non-evidentialist position within the Reformed tradition. The intellectual allure of this movement has led many contemporary thinkers to argue that the Catholic internalist/evidentialist position has not only been significantly challenged but has also been largely silenced by this externalism-based Reformed epistemological stance. Consequently, they argue that the non-cogntive Reformed currect has established itself as the dominant, or perhaps the only, epistemological position in the philosophy of religion. This paper counters the prevailing narrative, arguing that despite the ostensible challenge posed by Reformed non-evidentialism, a synthesis is possible. By analyzing various Reformed epistemological movements within the contemporary anaytic tradtion, we demonstrate that externalist-based Reformed epistemology does not fundamentally undermine Catholic evidentialism. Instead, it offers a new and more promising framework for a Christian epistemology that sythesizes elements from both traditions, offering a more comprehensive and nuanced understing of the justification of religion belief, incoperating both internalist and externalist perspective.

Keywords: reformed and catholic epistemology, evidentialism, non-evidentialism, internalism, externalism

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Authors: Ahmed R. Abdelaziz, Zaki M. I. Osha

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Solar radiation data are of great significance for solar energy system design. This study aims at developing and calibrating new empirical models for estimating monthly mean daily global solar radiation on a horizontal surface in Alexandria, Egypt. Day length hours, sun height, day number, and declination angle calculated data are used for this purpose. A comparison between measured and calculated values of solar radiation is carried out. It is shown that all the proposed correlations are able to predict the global solar radiation with excellent accuracy in Alexandria.

Keywords: solar energy, global solar radiation, model, regression coefficient

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Authors: Liang-Hsuan Chen, Sheng-Shing Nien

Abstract:

This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches.

Keywords: fuzzy sets, intuitionistic fuzzy number, intuitionistic fuzzy regression, mathematical programming method

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Authors: Rujira Jitrwung, Kuntima Krekkeitsakul, Weerawat Patthaveekongka, Chiraphat Kumpidet, Jarukit Tepkeaw, Krissana Jaikengdee, Anantachai Wannajampa

Abstract:

Flue gas discharging from coal fired or gas combustion power plant contains around 12% Carbon dioxide (CO₂), 6% Oxygen (O₂), and 82% Nitrogen (N₂).CO₂ is a greenhouse gas which has been concerned to the global warming. Carbon Capture, Utilization, and Storage (CCUS) is a topic which is a tool to deal with this CO₂ realization. Flue gas is drawn down from the chimney and filtered, then it is compressed to build up the pressure until 8 bar. This compressed flue gas is sent to three stages Pressure Swing Adsorption (PSA), which is filled with activated carbon. Experiments were showed the optimum adsorption pressure at 7bar, which CO₂ can be adsorbed step by step in 1st, 2nd, and 3rd stage, obtaining CO₂ concentration 29.8, 66.4, and 96.7 %, respectively. The mixed gas concentration from the last step is composed of 96.7% CO₂,2.7% N₂, and 0.6%O₂. This mixed CO₂product gas obtained from 3 stages PSA contained high concentration CO₂, which is ready to use for methanol synthesis. The mixed CO₂ was experimented in 5 Liter/Day of methanol synthesis reactor skid by 3 step processes as followed steam reforming, reverse water gas shift, and then hydrogenation. The result showed that proportional of mixed CO₂ and CH₄ 70/30, 50/50, 30/70 % (v/v), and 10/90 yielded methanol 2.4, 4.3, 5.6, and 6.0 Liter/day and save CO₂ 40, 30, 20, and 5 % respectively. The optimum condition resulted both methanol yield and CO₂ consumption using CO₂/CH₄ ratio 43/57 % (v/v), which yielded 4.8 Liter/day methanol and save CO₂ 27% comparing with traditional methanol production from methane steam reforming (5 Liter/day)and absent CO₂ consumption.

Keywords: carbon capture utilization and storage, pressure swing adsorption, reforming, reverse water gas shift, methanol

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Authors: Rebecca Owusu Coffie, Atakelty Hailu

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Variants of production frontier models have emerged, however, only a limited number of them are applied in empirical research. Hence the effects of these alternative frontier models are not well understood, particularly within sub-Saharan Africa. In this paper, we apply recent advances in the production frontier to examine levels of technical efficiency and efficiency drivers. Specifically, we compare the heteroscedastic parametric and the semiparametric stochastic smooth coefficient (SPSC) models. Using rice production data from Ghana, our empirical estimates reveal that alternative specification of efficiency estimators results in either downward or upward bias in the technical efficiency estimates. Methodologically, we find that the SPSC model is more suitable and generates high-efficiency estimates. Within the parametric framework, we find that parameterization of both the mean and variance of the pre-truncated function is the best model. For the drivers of technical efficiency, we observed that longer farm distances increase inefficiency through a reduction in labor productivity. High soil quality, however, increases productivity through increased land productivity.

Keywords: pre-truncated, rice production, smooth coefficient, technical efficiency

Procedia PDF Downloads 435