Search results for: molecular modeling of Cdk5/p25

Authors: Ahmed S. Eissa

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Whey represents about 85-95% of the milk volume and about 55% of milk nutrients. Whey proteins are of special importance in formulated foods due to their rich nutritional and functional benefits. Whey proteins form large polymers upon heating to a temperature greater than the denaturation temperature. Hydrophobic interactions play an important role in building whey protein polymers. In this study, dissociation of hydrophobic interactions of whey protein polymers was done by adding Sodium Dodecyl Sulphonate (SDS). At low SDS concentrations, protein polymers were dissociated to smaller chains, as revealed by dilution solution viscometry (DSV). Interestingly, at higher SDS concentrations, polymer molecules got larger in size. Intrinsic viscosity was increased to many folds when raising the SDS concentration from 0.5% to 2%. Complex molecular arrangement leads to the formation of larger macromolecules, due to micelle formation. The study opens a venue for manipulating and enhancing whey protein functional properties by manipulating the hydrophobic interactions.

Keywords: whey proteins, hydrophobic interactions, SDS

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Authors: Ghasem Sharifi, Hamed Shahmohamadi Ousaloo, Milad Azimi, Mehran Mirshams

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The ever-increasing use of satellites demands a search for increasingly accurate and reliable pointing systems. Reaction wheels are rotating devices used commonly for the attitude control of the spacecraft since provide a wide range of torque magnitude and high reliability. The numerical modeling of this device can significantly enhance the accuracy of the satellite control in space. Modeling the wheel rotation in the presence of the various frictions is one of the critical parts of this approach. This paper presents a Dynamic Model Control of a Reaction Wheel (DMCR) in the current control mode. In current-mode, the required current is delivered to the coils in order to achieve the desired torque. During this research, all the friction parameters as viscous and coulomb, motor coefficient, resistance and voltage constant are identified. In order to model identification of a reaction wheel, numerous varying current commands apply on the particular wheel to verify the estimated model. All the parameters of DMCR are identified by classical Levenberg-Marquardt (CLM) optimization method. The experimental results demonstrate that the developed model has an appropriate precise and can be used in the satellite control simulation.

Keywords: experimental modeling, friction parameters, model identification, reaction wheel

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Authors: Aneesh Joshi, Sagil James

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Cold Spray (CS) process is deposition of solid particles over a substrate above a certain critical impact velocity. Unlike thermal spray processes, CS process does not melt the particles thus retaining their original physical and chemical properties. These characteristics make CS process ideal for various engineering applications involving metals, polymers, ceramics and composites. The bonding mechanism involved in CS process is extremely complex considering the dynamic nature of the process. Though CS process offers great promise for several engineering applications, the realization of its full potential is limited by the lack of understanding of the complex mechanisms involved in this process and the effect of critical process parameters on the deposition efficiency. The goal of this research is to understand the complex nanoscale mechanisms involved in CS process. The study uses Molecular Dynamics (MD) simulation technique to understand the material deposition phenomenon during the CS process. Impact of a single crystalline copper nanoparticle on copper substrate is modelled under varying process conditions. The quantitative results of the impacts at different velocities, impact angle and size of the particles are evaluated using flattening ratio, von Mises stress distribution and local shear strain. The study finds that the flattening ratio and hence the quality of deposition was highest for an impact velocity of 700 m/s, particle size of 20 Å and an impact angle of 90°. The stress and strain analysis revealed regions of shear instabilities in the periphery of impact and also revealed plastic deformation of the particles after the impact. The results of this study can be used to augment our existing knowledge in the field of CS processes.

Keywords: cold spray process, molecular dynamics simulation, nanoparticles, particle impact

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Authors: Wayde Veldman, Ozlem T. Bishop, Igor Polikarpov

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In bacteria, mono and disaccharides are phosphorylated during uptake into the cell via the widely used phosphoenolpyruvate (PEP)-dependent phosphotransferase transport system. As an initial step in the phosphorylated disaccharide metabolism pathway, certain glycoside hydrolase family 1 (GH1) enzymes play a crucial role in releasing phosphorylated and non-phosphorylated monosaccharides. However, structural determinants for the specificity of these enzymes still need to be clarified. GH1 enzymes are known to have a wide array of functions. According to the CAZy database, there are twenty-one different enzymatic activities in the GH1 family. Here, the structure and substrate specificity of a GH1 enzyme from Bacillus licheniformis, hereafter known as BlBglH, was investigated. The sequence of the enzyme BlBglH was compared to the sequences of other characterized GH1 enzymes using sequence alignment, sequence identity calculations, phylogenetic analysis, and motif discovery. Through these various analyses, BlBglH was found to have sequence features characteristic of the 6-phospho-β-glucosidase activity enzymes. Additionally, motif and structure comparisons of the three most commonly studied GH1 enzyme-activities revealed a shared loop amongst the different structures that consist of different sequence motifs – this loop is thought to guide specific substrates (depending on activity) towards the active-site. To further affirm BlBglH enzyme activity, molecular docking and molecular dynamics simulations were performed. Docking was carried out using 6-phospho-β-glucosidase enzyme-activity positive (p-Nitrophenyl-beta-D-glucoside-6-phosphate) and negative (p-Nitrophenyl-beta-D-galactoside-6-phosphate) control ligands, followed by 400 ns molecular dynamics simulations. The positive-control ligand maintained favourable interactions within the active site until the end of the simulation. The negative-control ligand was observed exiting the enzyme at 287 ns. Binding free energy calculations showed that the positive-control complex had a substantially more favourable binding energy compared to the negative-control complex. Jointly, the findings of this study suggest that the BlBglH enzyme possesses 6-phospho-β-glucosidase enzymatic activity.

Keywords: 6-P-β-glucosidase, glycoside hydrolase 1, molecular dynamics, sequence analysis, substrate specificity

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Authors: Karla Cautivo, Thomas Riley, Daniel Knight

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Clostridium difficile infection (CDI) is the most common cause of infectious diarrhea in hospitalised humans. C. difficile colonises the gastrointestinal tract, causes disease in a variety of animal species and can persist as a spore in diverse environments. Genetic overlap between C. difficile strains from human, animal and environmental sources suggests CDI has a zoonotic or foodborne aetiology. In Australia, C. difficile PCR ribotype RT014 (MLST clade 1) and several ST11 (MLST clade 5) RTs are found commonly in livestock. The high prevalence and diversity of ST11 strains in Australian production animals indicates Australia might be the ancestral home for this lineage. This project describes for the first time the ecology of C. difficile in Australian native animals, providing insights into the prevalence, molecular epidemiology and evolution of C. difficile in this unique environment and a possible role in CDI in humans and animals in Australia. Faecal samples were collected from wild/captive reptiles (n=37), mammals (n=104) and birds (n=102) in Western Australia in 2020/21. Anaerobic enrichment culture was performed, and C. difficile isolates were characterised by PCR ribotyping and toxin gene profiling. Seventy isolates of C. difficile were recovered (prevalence of C. difficile in faecal samples 28%, n=68/243); 27 unique RTs were identified, 5 were novel. The prevalence of C. difficile was similar for reptiles and mammals, 46% (n=17/37) and 43%(n=45/104), respectively, but significantly lower in birds (7.8%, n=8/102; p<0.00001 for both reptiles and mammals). Of the 57 isolates available for typing, RT237 (clade 5) and RT002 (clade 2) were the most prevalent, 15.8% (n=9/57) and 14% (n=8/57), respectively. The high prevalence of C. difficile in reptiles and mammals, particularly clade 5 strains, supported by previous studies of C. difficile in Australian soils, suggest that Australia might be the ancestral home of MLST clade 5.

Keywords: Clostridium difficile, zoonosis, molecular epidemiology, ecology and evolution

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Authors: Donald G. Danmeier, Gian Marco Pizzo, Matthew Brennan

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Although wetlands have been proposed as a green alternative to manage coastal flood hazards because of their capacity to adapt to sea level rise and provision of multiple ecological and social co-benefits, they are often overlooked due to challenges in quantifying the uncertainty and naturally, variability of these systems. This objective of this study was to quantify wave attenuation provided by a natural marsh surrounding a large oil refinery along the US Gulf Coast that has experienced steady erosion along the shoreward edge. The vegetation module of the SWAN was activated and coupled with a hydrodynamic model (DELFT3D) to capture two-way interactions between the changing water level and wavefield over the course of a storm event. Since the marsh response to relative sea level rise is difficult to predict, a range of future marsh morphologies is explored. Numerical results were examined to determine the amount of wave attenuation as a function of marsh extent and the relative contributions from white-capping, depth-limited wave breaking, bottom friction, and flexing of vegetation. In addition to the coupled DELFT3D-SWAN modeling of a storm event, an uncoupled SWAN-VEG model was applied to a simplified bathymetry to explore a larger experimental design space. The wave modeling revealed that the rate of wave attenuation reduces for higher surge but was still significant over a wide range of water levels and outboard wave heights. The results also provide insights to the minimum marsh extent required to fully realize the potential wave attenuation so the changing coastal hazards can be managed.

Keywords: green infrastructure, wave attenuation, wave modeling, wetland

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Authors: Vladimir A. Vinnikov

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The paper proposes a model of an inhomogeneous rock mass with initially random distribution of microcracks on mineral grain boundaries. It describes the behavior of cracks in a medium under the effect of thermal field, the medium heated instantaneously to a predetermined temperature. Crack growth occurs according to the concept of fracture mechanics provided that the stress intensity factor K exceeds the critical value of Kc. The modeling of thermally induced acoustic emission memory effects is based on the assumption that every event of crack nucleation or crack growth caused by heating is accompanied by a single acoustic emission event. Parameters of the thermally induced acoustic emission memory effect produced by cyclic heating and cooling (with the temperature amplitude increasing from cycle to cycle) were calculated for several rock texture types (massive, banded, and disseminated). The study substantiates the adaptation of the proposed model to humidity interference with the thermally induced acoustic emission memory effect. The influence of humidity on the thermally induced acoustic emission memory effect in quasi-homogeneous and banded rocks is estimated. It is shown that such modeling allows the structure and texture of rocks to be taken into account and the influence of interference factors on the distinctness of the thermally induced acoustic emission memory effect to be estimated. The numerical modeling can be used to obtain information about the thermal impacts on rocks in the past and determine the degree of rock disturbance by means of non-destructive testing.

Keywords: degree of rock disturbance, non-destructive testing, thermally induced acoustic emission memory effects, structure and texture of rocks

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Authors: Cristian Patrascioiu, Loredana Negoita

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This paper is focused on modeling and simulation of the tubular heaters. The paper is structured in four parts: the structure of the tubular convection section, the heat transfer model, the adaptation of the mathematical model and the solving model. The main hypothesis of the heat transfer modeling is that the heat exchanger of the convective tubular heater is a lumped system. In the same time, the model uses the heat balance relations, Newton’s law and criteria relations. The numerical program achieved allows for the estimation of the burn gases outlet temperature and the heated flow outlet temperature.

Keywords: heat exchanger, mathematical modelling, nonlinear equation system, Newton-Raphson algorithm

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Authors: Miral Selim, May Haggag, Ibrahim Abotaleb

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The aging of transportation infrastructure presents significant challenges, particularly concerning the monitoring and maintenance of bridges. This study investigates the application of Random Forest algorithms for predictive modeling of bridge conditions, utilizing data from the US National Bridge Inventory (NBI). The research is significant as it aims to improve bridge management through data-driven insights that can enhance maintenance strategies and contribute to overall safety. Random Forest is chosen for its robustness, ability to handle complex, non-linear relationships among variables, and its effectiveness in feature importance evaluation. The study begins with comprehensive data collection and cleaning, followed by the identification of key variables influencing bridge condition ratings, including age, construction materials, environmental factors, and maintenance history. Random Forest is utilized to examine the relationships between these variables and the predicted bridge conditions. The dataset is divided into training and testing subsets to evaluate the model's performance. The findings demonstrate that the Random Forest model effectively enhances the understanding of factors affecting bridge conditions. By identifying bridges at greater risk of deterioration, the model facilitates proactive maintenance strategies, which can help avoid costly repairs and minimize service disruptions. Additionally, this research underscores the value of data-driven decision-making, enabling better resource allocation to prioritize maintenance efforts where they are most necessary. In summary, this study highlights the efficiency and applicability of Random Forest in predictive modeling for bridge management. Ultimately, these findings pave the way for more resilient and proactive management of bridge systems, ensuring their longevity and reliability for future use.

Keywords: data analysis, random forest, predictive modeling, bridge management

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Authors: Katerina H. Takova, Ivan N. Minkov, Gergana G. Zahmanova

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Molecular farming is the production of recombinant proteins in plants with the aim to use the protein as a purified product, crude extract or directly in the planta. Plants gain more attention as expression systems compared to other ones due to the cost effective production of pharmaceutically important proteins, appropriate post-translational modifications, assembly of complex proteins, absence of human pathogens to name a few. In addition, transient expression in plant leaves enables production of recombinant proteins within few weeks. Hepatitis E virus (HEV) is a causative agent of acute hepatitis. HEV causes epidemics in developing countries and is primarily transmitted through the fecal-oral route. Presently, all efforts for development of Hepatitis E vaccine are focused on the Open Read Frame 2 (ORF2) capsid protein as it contains epitopes that can induce neutralizing antibodies. For our purpose, we used the CMPV-based vector-pEAQ-HT for transient expression of HEV ORF2 in Nicotiana benthamina. Different molecular analysis (Western blot and ELISA) showed that HEV ORF2 capsid protein was expressed in plant tissue in high-yield up to 1g/kg of fresh leaf tissue. Electron microscopy showed that the capsid protein spontaneously assembled in low abundance virus-like particles (VLPs), which are highly immunogenic structures and suitable for vaccine development. The expressed protein was recognized by both human and swine HEV positive sera and can be used as a diagnostic reagent for the detection of HEV infection. Production of HEV capsid protein in plants is a promising technology for further HEV vaccine investigations. Here, we reported for a rapid high-yield transient expression of a recombinant protein in plants suitable for vaccine production as well as a diagnostic reagent. Acknowledgments -The authors’ research on HEV is supported with grants from the Project PlantaSYST under the Widening Program, H2020 as well as under the UK Biotechnological and Biological Sciences Research Council (BBSRC) Institute Strategic Programme Grant ‘Understanding and Exploiting Plant and Microbial Secondary Metabolism’ (BB/J004596/1). The authors want to thank Prof. George Lomonossoff (JIC, Norwich, UK) for his contribution.

Keywords: hepatitis E virus, plant molecular farming, transient expression, vaccines

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Authors: Mini P. Singh, Jagat Ram, Archit Kumar, Tripti Rungta, Jasmine Khurana, Amit Gupta, R. K. Ratho

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Introduction: Human adenovirus is the most common agent involved in viral conjunctivitis. The clinical manifestations vary with different serotypes. The identification of the circulating strains followed by phylogenetic analysis can be helpful in understanding the origin and transmission of the disease. The present study aimed to carry out molecular epidemiology of the adenovirus types in the patients with conjunctivitis presenting to the eye centre of a tertiary care hospital in North India. Materials and Methods: The conjunctival swabs were collected from 23 suspected adenoviral conjunctivitis patients between April-August, 2014 and transported in viral transport media. The samples were subjected to nested PCR targeting hexon gene of human adenovirus. The band size of 956bp was eluted and 8 representative positive samples were subjected to sequencing. The sequences were analyzed by using CLUSTALX2.1 and MEGA 5.1 software. Results: The male: female ratio was found to be 3.6:1. The mean age of presenting patients was 43.95 years (+17.2). Approximately 52.1% (12/23) of patients presented with bilateral involvement while 47.8% (11/23) with unilateral involvement of the eye. Human adenovirus DNA could be detected in 65.2% (15/23) of the patients. The phylogenetic analysis revealed presence of serotype 8 in 7 patients and serotype 4 in one patient. The serotype 8 sequences showed 99-100% identity with Tunisian, Indian and Japanese strains. The adenovirus serotype 4 strains had 100% identity with strains from Tunisia, China and USA. Conclusion: Human adenovirus was found be an important etiological agent for conjunctivitis in our set up. The phylogenetic analysis showed that the predominant circulating strains in our epidemic keratoconjunctivitis were serotypes 8 and 4.

Keywords: conjunctivitis, human adenovirus, molecular epidemiology, phylogenetics

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Authors: S. N. Harun, H. Ahmad

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A series of ruthenium(II) complexes, including two novel compounds [Ru(dppz)2(L)]2+ where dppz = dipyrido-[3,2-a:2’,3’-c]phenazine, and L = 2-phenylimidazo[4,5-f][1,10]phenanthroline (PIP) or 2-(4-hydroxyphenyl)imidazo[4,5-f][1,10]phenanthroline (p-HPIP) have been synthesized and characterized. The previously reported complexes [Ru(bpy)2L]2+ and [Ru(phen)2L]2+ were also prepared. All complexes were characterized by elemental analysis, 1H-NMR spectroscopy, ESI-Mass spectroscopy and FT-IR spectroscopy. The photophysical properties were analyzed by UV-Visible spectroscopy and fluorescence spectroscopy. [Ru(dppz)2(PIP)]2+ and [Ru(dppz)2(p-HPIP)]2+ displayed ‘molecular light-switch’ effect as they have high emission in acetonitrile but no emission in water. The cytotoxicity of all complexes against cancer cell lines Hela and MCF-7 were investigated through standard MTT assay. [Ru(dppz)2(PIP)]2+ showed moderate toxicity on both MCF-7 and Hela with IC50 of 37.64 µM and 28.02 µM, respectively. Interestingly, [Ru(dppz)2(p-HPIP)]2+ exhibited remarkable cytotoxicity results with IC50 of 13.52 µM on Hela and 11.63 µM on MCF-7 cell lines which are comparable to the infamous anti-cancer drug, cisplatin. The cytotoxicity of this complex series increased as the ligands size extended in order of [Ru(bpy)2(L)]2+ < [Ru(phen)2(L)]2+ < [Ru(dppz)2(L)]2+.

Keywords: ruthenium, cytotoxicity, molecular light-switch, anticancer

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Authors: Carolin Anna Joy, Rohith K. R, Rehin Sulay, Parvathy Santhoshkumar, G.Anil Kumar, Vibin Ipe Thomas

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Ullmann coupling reactions are gaining great relevance owing to their contribution in the synthesis of biologically and pharmaceutically important compounds. Palladium and many other heavy metals have proven their excellent ability in coupling reaction, but the toxicity matters. The first-row transition metal also possess toxicity, except in the case of iron and manganese. The suitability of manganese as a catalyst is achieving great interest in oxidation, reduction, C-H activation, coupling reaction etc. In this presentation, we discuss the thermo chemistry of ligand free manganese catalyzed C-O coupling reaction between phenol and aryl halide for the synthesis of biaryl ethers using Density functional theory techniques. The mechanism involves an oxidative addition-reductive elimination step. The transition state for both the step had been studied and confirmed using Intrinsic Reaction Coordinate (IRC) calculation. The barrier height for the reaction had also been calculated from the rate determining step. The possibility of other mechanistic way had also been studied. To achieve further insight into the mechanism, substrate having various functional groups is considered in our study to direct their effect on the feasibility of the reaction.

Keywords: Density functional theory, Molecular Modeling, ligand free, biaryl ethers, Ullmann coupling

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Authors: Saeed Zeinali, Nasser Talebbeydokhti, Mehdi Saeidian, Shahrad Vosough

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In this article, bathymetry changes have been studied as a case study for Larak Island, located in The South of Iran. The advanced 2D model of Mike21 has been used for this purpose. A simple procedure has been utilized in this model. First, the hydrodynamic (HD) module of Mike21 has been used to obtain the required output for sediment transport model (ST module). The ST module modeled the area for tidal currents only. Bed level changes are resulted by series of modeling for both HD and ST module in 3 months time step. The final bathymetry in each time step is used as the primary bathymetry for next time step. This consecutive procedure been continued until bathymetry for the year 2020 is obtained.

Keywords: bed level changes, Larak Island, hydrodynamic, sediment transport

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Authors: Jamel Boukhatem, Mouldi Djelassi

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Contrary to the existing literature generally focusing on the role played by Sukuk in enhancing investors' and shareholders' wealth, this paper sheds some light on the Sukuk wealth effect across all economic agents: households, government, and investors by implementing a two-period life-cycle model with overlapping generations to show whether Sukuk is net wealth. The main findings are threefold: i) the effect of a change in Sukuk issuances on the consumers’ utility level will be different from one generation to another, ii) an increase in taxes due to the increase in Sukuk and rents is covered by transfers made by the members of generation 1 in the form of inheritance, and iii) the existence of a positive relationship between the asset prices representative of Sukuk and the real activity.

Keywords: Sukuk, households, investors, overlapping generations model, wealth, modeling

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Authors: Nataša Kalajdžija, Strahinja Kovačević, Davor Lončar, Sanja Podunavac Kuzmanović, Lidija Jevrić

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In order to investigate the relationship between retention and structure, a quantitative Structure Retention Relationships (QSRRs) study was applied for the prediction of retention times of a set of 23 secoestrane derivatives in a reversed-phase thin-layer chromatography. After the calculation of molecular descriptors, a suitable set of molecular descriptors was selected by using step-wise multiple linear regressions. Artificial Neural Network (ANN) method was employed to model the nonlinear structure-activity relationships. The ANN technique resulted in 5-6-1 ANN model with the correlation coefficient of 0.98. We found that the following descriptors: Critical pressure, total energy, protease inhibition, distribution coefficient (LogD) and parameter of lipophilicity (miLogP) have a significant effect on the retention times. The prediction results are in very good agreement with the experimental ones. This approach provided a new and effective method for predicting the chromatographic retention index for the secoestrane derivatives investigated.

Keywords: lipophilicity, QSRR, RP TLC retention, secoestranes

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Authors: Mei-Chun Chang

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Due to digital transformation and social media development in recent years, various real-time interactive digital tools have been developed to meet the design demands for virtual reality avatars, which also promote digital content learners' active participation in the creation process. As a result, new social media design tools have the characteristics of intuitive operation with a simplified interface for fast production, from which works can be simply created. This study carried out observations, records, questionnaire surveys, and interviews on the creation and learning of visual avatars made by students of the National Taiwan University of Science and Technology (NTUST) with the VRoid Studio 3D modeling tool so as to explore their learning effectiveness on the design of visual avatars. According to the results of this study, the VRoid Studio 3D character modeling tool has a positive impact on the learners and helps to improve their learning effectiveness. Students with low academic achievements said that they could complete the conceived modeling with their own thinking by using the design tool, which increased their sense of accomplishment. Conclusions are drawn according to the results, and relevant future suggestions are put forward.

Keywords: virtual avatar, character design, social media, vroid studio, creation, digital learning

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Authors: Joseph E. Estevez, Mahdi Ghazizadeh, James G. Ryan, Ajit D. Kelkar

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Radiation shielding is an obstacle in long duration space exploration. Boron Nitride Nanotubes (BNNTs) have attracted attention as an additive to radiation shielding material due to B10’s large neutron capture cross section. The B10 has an effective neutron capture cross section suitable for low energy neutrons ranging from 10-5 to 104 eV and hydrogen is effective at slowing down high energy neutrons. Hydrogenated BNNTs are potentially an ideal nanofiller for radiation shielding composites. We use Molecular Dynamics (MD) Simulation via Material Studios Accelrys 6.0 to model the Young’s Modulus of Hydrogenated BNNTs. An extrapolation technique was employed to determine the Young’s Modulus due to the deformation of the nanostructure at its theoretical density. A linear regression was used to extrapolate the data to the theoretical density of 2.62g/cm3. Simulation data shows that the hydrogenated BNNTs will experience a 11% decrease in the Young’s Modulus for (6,6) BNNTs and 8.5% decrease for (8,8) BNNTs compared to non-hydrogenated BNNT’s. Hydrogenated BNNTs are a viable option as a nanofiller for radiation shielding nanocomposite materials for long range and long duration space exploration.

Keywords: boron nitride nanotube, radiation shielding, young modulus, atomistic modeling

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Authors: K. Passbakhsh

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Determination of reinforcement forces is one of the most important and main discussions in designing retaining walls. By determining these forces we refrain from conservative planning. By numerically modeling the reinforced soil retaining walls under dynamic loading reinforcement forces can be calculated. In this study we try to approach the gained forces by pseudo-static method according to FHWA code and gained forces from numerical modeling by finite element method, by selecting seismic horizontal coefficient for different wall height. PLAXIS software was used for numerical analysis. Then the effect of reinforcement stiffness and soil type on reinforcement forces is examined.

Keywords: reinforced soil, PLAXIS, reinforcement forces, retaining walls

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Authors: Rong Li, Brian D. Wirth, Bing Liu

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Graphite is the matrix, and structural material in the high temperature gas-cooled reactor exhibits an irradiation response. It is of significant importance to analyze the defect production and evaluate the role of graphite under irradiation. A vast experimental literature exists for graphite on the dimensional change, mechanical properties, and thermal behavior. However, simulations have not been applied to the atomistic perspective. Remarkably few molecular dynamics simulations have been performed to study the irradiation response in graphite. In this paper, irradiation-induced damage cascades in graphite were investigated with molecular dynamics simulation. Statistical results of the graphite defects were obtained by sampling a wide energy range (1–30 KeV) and 10 different runs for every cascade simulation with different random number generator seeds to the velocity scaling thermostat function. The chemical bonding in carbon was described using the adaptive intermolecular reactive empirical bond-order potential (AIREBO) potential coupled with the standard Ziegler–Biersack–Littmack (ZBL) potential to describe close-range pair interactions. This study focused on analyzing the number of defects, the final cascade morphology and the distribution of defect clusters in space, the length-scale cascade properties such as the cascade length and the range of primary knock-on atom (PKA), and graphite mechanical properties’ variation. It can be concluded that the number of surviving Frenkel pairs increased remarkably with the increasing initial PKA energy but did not exhibit a thermal spike at slightly lower energies in this paper. The PKA range and cascade length approximately linearly with energy which indicated that increasing the PKA initial energy will come at expensive computation cost such as 30KeV in this study. The cascade morphology and the distribution of defect clusters in space mainly related to the PKA energy meanwhile the temperature effect was relatively negligible. The simulations are in agreement with known experimental results and the Kinchin-Pease model, which can help to understand the graphite damage cascades and lifetime span under irradiation and provide a direction to the designs of these kinds of structural materials in the future reactors.

Keywords: graphite damage cascade, molecular dynamics, cascade morphology, cascade distribution

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Authors: Nour El Houda Bensiradj, Nafila Zouaghi, Taha Bensiradj

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The pollution of water resources is characterized by the presence of microorganisms, chemicals, or industrial waste. Generally, this waste generates effluents containing large quantities of heavy metals, making the water unsuitable for consumption and causing the death of aquatic life and associated biodiversity. Currently, it is very important to assess the impact of heavy metals in water pollution as well as the processes for treating and reducing them. Among the methods of water treatment and disinfection, we mention the complexation of metal ions using ligands which serve to precipitate and subsequently eliminate these ions. In this context, we are interested in the study of complexes containing heavy metals such as zinc, nickel, and cadmium, which are present in several industrial discharges and are discharged into water sources. We will use the ligands of triethanolamine (TEA) and nitrilotriacetic acid (NTA). The theoretical study is based on molecular modeling, using the density functional theory (DFT) implemented in the Gaussian 09 program. The geometric and energetic properties of the above complexes will be calculated. Spectral properties such as infrared, as well as reactivity descriptors, and thermodynamic properties such as enthalpy and free enthalpy will also be determined.

Keywords: heavy metals, NTA, TEA, DFT, IR, reactivity descriptors

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Authors: Rouaz Idriss, Bourahla Nour-Eddine, Kahlouche Farah, Rafa Sid Ali

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The stability of structures made of light-gauge steel depends highly on the contribution of Shear Wall Panel (SWP) systems under horizontal forces due to wind or earthquake loads. Steel plate sheathing is often used with these panels made of cold formed steel (CFS) to improve its shear strength. In order to predict the shear strength resistance, two methods are presented in this paper. In the first method, the steel plate sheathing is modeled with plats strip taking into account only the tension and compression force due to the horizontal load, where both track and stud are modeled according to the geometrical and mechanical characteristics of the specimen used in the experiments. The theoretical background and empirical formulations of this method are presented in this paper. However, the second method is based on a micro modeling of the cold formed steel Shear Wall Panel “CFS-SWP” using Abaqus software. A nonlinear analysis was carried out with an in-plan monotonic load. Finally, the comparison between these two methods shows that the micro modeling with Abaqus gives better prediction of shear resistance of SWP than strips method. However, the latter is easier and less time consuming than the micro modeling method.

Keywords: cold formed steel 'CFS', shear wall panel, strip method, finite elements

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Authors: Mthokozisi Simelane

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Background: Malaria remains a life-threatening disease in tropical regions despite the advances in the treatment of this disease, it still remains a significant burden as some parasites have become resistant to the currently available drugs. This has created a necessity for the development of alternative, more efficient antimalarial drugs. Warburgia salutaris is a traditional medicinal plant used in malaria treatment by Zulu traditional healers. Materials and methods: The W. salutaris stem-bark was extracted with dichloromethane and the compound was isolated through column chromatography. The compound was identified and characterized by spectroscopic analysis (1H NMR, 13C NMR, IR and MS) and the structure was also confirmed by x-ray crystallography. The anti-plasmodial activity (in vitro) was studied on NF54 Plasmodium falciparum strain (CQS). Cytotoxicity was measured using the MTT assay on HEK239 and HEPG2 cell lines. Docking of Mukaadial acetate was conducted in AutoDock Vina. Structural modifications were conducted in UCSF Chimera and molecular interactions examined in LigPlot. Results: The compound, Mukaadial Acetate showed appreciable inhibition (IC50 0.44±0.10 µg/ml) of the parasite growth and cytotoxicity activity of 0.124±0.109 and 0.199±0.083 (µg/ml) on HEK293 and HEPG2 cells respectively. Molecular docking revealed that Mukaadial Acetate binds to the purine, pyrophosphate and ribose binding sites of the PfHGXPRT with an optimum binding conformation and forms hydrogen bond, steric and hydrophobic interactions with the residues inhabiting the respective binding sites. Conclusion: It is apparent that W. salutaris contains components (including Mukaadial Acetate) that exhibit antimalarial activity. This study scientifically validates the use of this plant in folk medicine.

Keywords: plasmodium falciparum, molecular docking, antimalarial activity, PfHGXPRT, Warburgia salutaris, mukaadial acetate

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Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

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Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

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Authors: V. Pourmostaghimi, M. Zadshakoyan

Abstract:

Efficiency and productivity of the finish hard turning can be enhanced impressively by utilizing accurate predictive models for cutting tool wear. However, the ability of genetic programming in presenting an accurate analytical model is a notable characteristic which makes it more applicable than other predictive modeling methods. In this paper, the genetic equation for modeling of tool flank wear is developed with the use of the experimentally measured flank wear values and genetic programming during finish turning of hardened AISI D2. Series of tests were conducted over a range of cutting parameters and the values of tool flank wear were measured. On the basis of obtained results, genetic model presenting connection between cutting parameters and tool flank wear were extracted. The accuracy of the genetically obtained model was assessed by using two statistical measures, which were root mean square error (RMSE) and coefficient of determination (R²). Evaluation results revealed that presented genetic model predicted flank wear over the study area accurately (R² = 0.9902 and RMSE = 0.0102). These results allow concluding that the proposed genetic equation corresponds well with experimental data and can be implemented in real industrial applications.

Keywords: cutting parameters, flank wear, genetic programming, hard turning

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Authors: Soulayma Smirani, Mourad Aidi, Taoufik Aguili

Abstract:

Energy harvesting has arisen as a prominent research area for low power delivery to RF devices. Rectennas have become a key element in this technology. In this paper, electromagnetic modeling of a rectenna system is presented. In our approach, a hybrid technique was demonstrated to associate both the method of auxiliary sources (MAS) and MoM-GEC (the method of moments combined with the generalized equivalent circuit technique). Auxiliary sources were used in order to substitute specific electronic devices. Therefore, a simple and controllable model is obtained. Also, it can easily be interconnected to form different topologies of rectenna arrays for more energy harvesting. At last, simulation results show the feasibility and simplicity of the proposed rectenna model with high precision and computation efficiency.

Keywords: computational electromagnetics, MoM-GEC method, rectennas, RF energy harvesting

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Authors: Saeed Sayyad Hagh Shomar

Abstract:

Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using the users’ stated preference in questionnaire models users’ departure time choice affected by congestion pricing schemes in high traffic suburban entrance roads of Tehran. The results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.

Keywords: congestion pricing, departure time, modeling, travel timing, time of the day, transportation planning

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Authors: Dong Tran, Thanh Dac Van, Ly Le

Abstract:

Hemagglutinin (HA) and Neuraminidase (NA) play an important role in host immune evasion across influenza virus evolution process. The correlation between HA and NA evolution in respect to epitopic evolution and drug interaction has yet to be investigated. In this study, combining of sequence to structure evolution and statistical analysis on epitopic/binding site specificity, we identified potential therapeutic features of HA and NA that show specific antibody binding site of HA and specific binding distribution within NA active site of current inhibitors. Our approach introduces the use of sequence variation and molecular interaction to provide an effective strategy in establishing experimental based distributed representations of protein-protein/ligand complexes. The most important advantage of our method is that it does not require complete dataset of complexes but rather directly inferring feature interaction from sequence variation and molecular interaction. Using correlated sequence analysis, we additionally identified co-evolved mutations associated with maintaining HA/NA structural and functional variability toward immunity and therapeutic treatment. Our investigation on the HA binding specificity revealed unique conserved stalk domain interacts with unique loop domain of universal antibodies (CR9114, CT149, CR8043, CR8020, F16v3, CR6261, F10). On the other hand, NA inhibitors (Oseltamivir, Zaninamivir, Laninamivir) showed specific conserved residue contribution and similar to that of NA substrate (sialic acid) which can be exploited for drug design. Our study provides an important insight into rational design and identification of novel therapeutics targeting universally recognized feature of influenza HA/NA.

Keywords: influenza virus, hemagglutinin (HA), neuraminidase (NA), sequence evolution

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Authors: Moustafa Osman Mohammed

Abstract:

The modeling of a spatial-economic database is crucial in recitation economic network structure to social development. Sustainability within the spatial-economic model gives attention to green businesses to comply with Earth’s Systems. The natural exchange patterns of ecosystems have consistent and periodic cycles to preserve energy and materials flow in systems ecology. When network topology influences formal and informal communication to function in systems ecology, ecosystems are postulated to valence the basic level of spatial sustainable outcome (i.e., project compatibility success). These referred instrumentalities impact various aspects of the second level of spatial sustainable outcomes (i.e., participant social security satisfaction). The sustainability outcomes are modeling composite structure based on a network analysis model to calculate the prosperity of panel databases for efficiency value, from 2005 to 2025. The database is modeling spatial structure to represent state-of-the-art value-orientation impact and corresponding complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic-ecological model; develop a set of sustainability indicators associated with the model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate spatial structure reliability. The structure of spatial-ecological model is established for management schemes from the perspective pollutants of multiple sources through the input–output criteria. These criteria evaluate the spillover effect to conduct Monte Carlo simulations and sensitivity analysis in a unique spatial structure. The balance within “equilibrium patterns,” such as collective biosphere features, has a composite index of many distributed feedback flows. The following have a dynamic structure related to physical and chemical properties for gradual prolong to incremental patterns. While these spatial structures argue from ecological modeling of resource savings, static loads are not decisive from an artistic/architectural perspective. The model attempts to unify analytic and analogical spatial structure for the development of urban environments in a relational database setting, using optimization software to integrate spatial structure where the process is based on the engineering topology of systems ecology.

Keywords: ecological modeling, spatial structure, orientation impact, composite index, industrial ecology

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Authors: Sina Saadati, Mohammadreza Razzazi

Abstract:

In this article, we have tried to present an agent-based model of human muscle. A suitable model of muscle is necessary for the analysis of mankind's movements. It can be used by clinical researchers who study the influence of motion sicknesses, like Parkinson's disease. It is also useful in the development of a prosthesis that receives the electromyography signals and generates force as a reaction. Since we have focused on computational efficiency in this research, the model can compute the calculations very fast. As far as it concerns prostheses, the model can be known as a charge-efficient method. In this paper, we are about to illustrate an agent-based model. Then, we will use it to simulate the human gait cycle. This method can also be done reversely in the analysis of gait in motion sicknesses.

Keywords: agent-based modeling and simulation, human muscle, gait cycle, motion sickness

Procedia PDF Downloads 114