Search results for: Molecular Modeling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5878

Search results for: Molecular Modeling

5218 A Novel Combustion Engine, Design and Modeling

Authors: M. A. Effati, M. R. Hojjati, M. Razmdideh

Abstract:

Nowadays, engine developments have focused on internal combustion engine design call for increased engine power, reduced engine size and improved fuel economy, simultaneously. In this paper, a novel design for combustion engine is proposed. Two combustion chambers were designed in two sides of cylinder. Piston was designed in a way that two sides of piston would transfer heat energy due to combustion to linear motion. This motion would convert to rotary motion through the designed mechanism connected to connecting rod. Connecting rod operation was analyzed to evaluate applied stress in 3000, 4500 and 6000 rpm. Boundary conditions including generated pressure in each side of cylinder in these 3 situations was calculated.

Keywords: combustion engine, design, finite element method, modeling

Procedia PDF Downloads 509
5217 Application of Neural Network on the Loading of Copper onto Clinoptilolite

Authors: John Kabuba

Abstract:

The study investigated the implementation of the Neural Network (NN) techniques for prediction of the loading of Cu ions onto clinoptilolite. The experimental design using analysis of variance (ANOVA) was chosen for testing the adequacy of the Neural Network and for optimizing of the effective input parameters (pH, temperature and initial concentration). Feed forward, multi-layer perceptron (MLP) NN successfully tracked the non-linear behavior of the adsorption process versus the input parameters with mean squared error (MSE), correlation coefficient (R) and minimum squared error (MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed that NN modeling techniques could effectively predict and simulate the highly complex system and non-linear process such as ion-exchange.

Keywords: clinoptilolite, loading, modeling, neural network

Procedia PDF Downloads 413
5216 3D Modeling of Tunis Soft Soil Settlement Reinforced with Plastic Wastes

Authors: Aya Rezgui, Lasaad Ajam, Belgacem Jalleli

Abstract:

The Tunis soft soils present a difficult challenge as construction sites and for Geotechnical works. Currently, different techniques are used to improve such soil properties taking into account the environmental considerations. One of the recent methods is involving plastic wastes as a reinforcing materials. The present study pertains to the development of a numerical model for predicting the behavior of Tunis Soft soil (TSS) improved with recycled Monobloc chair wastes.3D numerical models for unreinforced TSS and reinforced TSS aims to evaluate settlement reduction and the values of consolidation times in oedometer conditions.

Keywords: Tunis soft soil, settlement, plastic wastes, finte -difference, FLAC3D modeling

Procedia PDF Downloads 130
5215 Modeling of Landslide-Generated Tsunamis in Georgia Strait, Southern British Columbia

Authors: Fatemeh Nemati, Lucinda Leonard, Gwyn Lintern, Richard Thomson

Abstract:

In this study, we will use modern numerical modeling approaches to estimate tsunami risks to the southern coast of British Columbia from landslides. Wave generation is to be simulated using the NHWAVE model, which solves the Navier-Stokes equations due to the more complex behavior of flow near the landslide source; far-field wave propagation will be simulated using the simpler model FUNWAVE_TVD with high-order Boussinesq-type wave equations, with a focus on the accurate simulation of wave propagation and regional- or coastal-scale inundation predictions.

Keywords: FUNWAVE-TVD, landslide-generated tsunami, NHWAVE, tsunami risk

Procedia PDF Downloads 149
5214 Association between Eating Behavior in Children Aged 7-10 Years Old and Their Mother’s Feeding Practice: A Study among the Families in Isfahan, Iran

Authors: Behnaz Farahani, Razieh Sotoudeh, Ali Vahdani, Hamed Abdi

Abstract:

Individual differences in eating behavior can cause underweight or overweight and obesity. Thus influencing factors on children’s eating behavior such as mothers’ feeding practices are needed to be more investigated. The goals of this survey are to evaluate the association of (i) parental pressure and children’s food avoidant tendency, (ii) parental restriction and children’s food approach tendency, (iii) modeling of healthy eating in front of children and their children’s eating behavior. 760 mothers of children aged 7-10 from schools in Isfahan were asked to complete questionnaires including Child Feeding Questionnaire, Children’s Eating Behavior Questionnaire, Modeling Questionnaire, and self-administered demographic questionnaire in which mothers reported their children’s height and weight as well. Of those mothers, 745 completed the questionnaires for the children’s index (mean age: 8.513±1.112) during the 2011-2012 school year. The results of this quantitative, descriptive, cross-sectional analysis indicated that “parental restriction” was positively associated with child food responsiveness (P,0.000) and food enjoyment (P,0.000) and surprisingly, it was positively associated with Food Fussiness(0.000) .Parental pressure to eat was positively associated with child satiety responsiveness (P,0.000), slowness (P,0.000), and fussiness (P,0.00) and negatively associated with Food responsiveness(p,0.000)and Enjoyment of food (p,0.002), modeling of healthy eating were positively associated with Enjoyment of food / q (p,0.000) and negatively with food fussiness (P,0.000). The results of this survey will improve interventions and maternal guidance on their feeding practices and their association with children’s eating behavior and weight.

Keywords: feeding practices, eating behavior, pressure to eat, restriction, modeling, satiety responsiveness, slowness in eating, food fussiness, food responsiveness, enjoyment of food

Procedia PDF Downloads 613
5213 Classification of Crisp Petri Nets

Authors: Riddhi Jangid, Gajendra Pratap Singh

Abstract:

Petri nets, a formalized modeling language that was introduced back around 50-60 years, have been widely used for modeling discrete event dynamic systems and simulating their behavior. Reachability analysis of Petri nets gives many insights into a modeled system. This idea leads us to study the reachability technique and use it in the reachability problem in the state space of reachable markings. With the same concept, Crisp Boolean Petri nets were defined in which the marking vectors that are boolean are distinct in the reachability analysis of the nets. We generalize the concept and define ‘Crisp’ Petri nets that generate the marking vectors exactly once in their reachability-based analysis, not necessarily Boolean.

Keywords: marking vector, n-vector, Petri nets, reachability

Procedia PDF Downloads 79
5212 Sequential Data Assimilation with High-Frequency (HF) Radar Surface Current

Authors: Lei Ren, Michael Hartnett, Stephen Nash

Abstract:

The abundant measured surface current from HF radar system in coastal area is assimilated into model to improve the modeling forecasting ability. A simple sequential data assimilation scheme, Direct Insertion (DI), is applied to update model forecast states. The influence of Direct Insertion data assimilation over time is analyzed at one reference point. Vector maps of surface current from models are compared with HF radar measurements. Root-Mean-Squared-Error (RMSE) between modeling results and HF radar measurements is calculated during the last four days with no data assimilation.

Keywords: data assimilation, CODAR, HF radar, surface current, direct insertion

Procedia PDF Downloads 567
5211 A Mathematical-Based Formulation of EEG Fluctuations

Authors: Razi Khalafi

Abstract:

Brain is the information processing center of the human body. Stimuli in form of information are transferred to the brain and then brain makes the decision on how to respond to them. In this research we propose a new partial differential equation which analyses the EEG signals and make a relationship between the incoming stimuli and the brain response to them. In order to test the proposed model, a set of external stimuli applied to the model and the model’s outputs were checked versus the real EEG data. The results show that this model can model the EEG signal well. The proposed model is useful not only for modeling of the EEG signal in case external stimuli but it can be used for the modeling of brain response in case of internal stimuli.

Keywords: Brain, stimuli, partial differential equation, response, eeg signal

Procedia PDF Downloads 428
5210 Computer Modeling and Plant-Wide Dynamic Simulation for Industrial Flare Minimization

Authors: Sujing Wang, Song Wang, Jian Zhang, Qiang Xu

Abstract:

Flaring emissions during abnormal operating conditions such as plant start-ups, shut-downs, and upsets in chemical process industries (CPI) are usually significant. Flare minimization can help to save raw material and energy for CPI plants, and to improve local environmental sustainability. In this paper, a systematic methodology based on plant-wide dynamic simulation is presented for CPI plant flare minimizations under abnormal operating conditions. Since off-specification emission sources are inevitable during abnormal operating conditions, to significantly reduce flaring emission in a CPI plant, they must be either recycled to the upstream process for online reuse, or stored somewhere temporarily for future reprocessing, when the CPI plant manufacturing returns to stable operation. Thus, the off-spec products could be reused instead of being flared. This can be achieved through the identification of viable design and operational strategies during normal and abnormal operations through plant-wide dynamic scheduling, simulation, and optimization. The proposed study includes three stages of simulation works: (i) developing and validating a steady-state model of a CPI plant; (ii) transiting the obtained steady-state plant model to the dynamic modeling environment; and refining and validating the plant dynamic model; and (iii) developing flare minimization strategies for abnormal operating conditions of a CPI plant via a validated plant-wide dynamic model. This cost-effective methodology has two main merits: (i) employing large-scale dynamic modeling and simulations for industrial flare minimization, which involves various unit models for modeling hundreds of CPI plant facilities; (ii) dealing with critical abnormal operating conditions of CPI plants such as plant start-up and shut-down. Two virtual case studies on flare minimizations for start-up operation (over 50% of emission savings) and shut-down operation (over 70% of emission savings) of an ethylene plant have been employed to demonstrate the efficacy of the proposed study.

Keywords: flare minimization, large-scale modeling and simulation, plant shut-down, plant start-up

Procedia PDF Downloads 316
5209 Bioeconomic Modeling for the Sustainable Exploitation of Three Key Marine Species in Morocco

Authors: I. Ait El Harch, K. Outaaoui, Y. El Foutayeni

Abstract:

This study aims to deepen the understanding and optimize fishing activity in Morocco by holistically integrating biological and economic aspects. We develop a biological equilibrium model in which these competing species present their natural growth by logistic equations, taking into account density and competition between them. The integration of human intervention adds a realistic dimension to our model. A company specifically targets the three species, thus influencing population dynamics according to their fishing activities. The aim of this work is to determine the fishing effort that maximizes the company’s profit, taking into account the constraints associated with conserving ecosystem equilibrium.

Keywords: bioeconomical modeling, optimization techniques, linear complementarity problem LCP, biological equilibrium, maximizing profits

Procedia PDF Downloads 15
5208 Resource Allocation Modeling and Simulation in Border Security Application

Authors: Kai Jin, Hua Li, Qing Song

Abstract:

Homeland security and border safety is an issue for any country. This paper takes the border security of US as an example to discuss the usage and efficiency of simulation tools in the homeland security application. In this study, available resources and different illegal infiltration parameters are defined, including their individual behavior and objective, in order to develop a model that describes border patrol system. A simulation model is created in Arena. This simulation model is used to study the dynamic activities in the border security. Possible factors that may affect the effectiveness of the border patrol system are proposed. Individual and factorial analysis of these factors is conducted and some suggestions are made.

Keywords: resource optimization, simulation, modeling, border security

Procedia PDF Downloads 511
5207 Investigation of the Mechanism, Régio and Sterioselectivity Using the 1,3-Dipolar Cycloaddition Reaction of Fused 1h-Pyrrole-2,3-Diones with Nitrones: Molecular Electron Density Theory Study

Authors: Ameur Soukaina, Zeroual Abdellah, Mazoir Noureddine

Abstract:

Molecular Electron Density Theory (MEDT) elucidates the regioselectivity of the [4+2] cycloaddition reaction between 3-aroylpyrrolo[1,2-α]quinoxaline-1,2,4(5H)-trione and butyl vinyl ether Regioselectivity and stereoselectivity. The regioselectivity mechanisms of these reactions were investigated by evaluating potential energy surfaces calculated for cycloaddition processes and DFT density-based reactivity indices. These methods have been successfully applied to predict preferred regioisomers for different method alternatives. Reactions were monitored by performing transition state optimizations, calculations of intrinsic reaction coordinates, and activation energies. The observed regioselectivity was rationalized using DFT-based reactivity descriptors such as the Parr function. Solvent effects were also investigated in 1,4-dioxane solvent using a field model for self-consistent reactions. The results were compared with experimental data to find good agreement.

Keywords: cycloaddition, DFT, ELF, MEDT, parr, stereoselectivité

Procedia PDF Downloads 105
5206 Implementing 3D Printing for 3D Digital Modeling in the Classroom

Authors: Saritdikhun Somasa

Abstract:

3D printing fabrication has empowered many artists in many fields. Artists who work in stop motion, 3D modeling, toy design, product design, sculpture, and fine arts become one-stop shop operations–where they can design, prototype, and distribute their designs for commercial or fine art purposes. The author has developed a digital sculpting course that fosters digital software, peripheral hardware, and 3D printing with traditional sculpting concept techniques to address the complexities of this multifaceted process, allowing the students to produce complex 3d-printed work. The author will detail the preparation and planning for pre- to post-process 3D printing elements, including software, materials, space, equipment, tools, and schedule consideration for small to medium figurine design statues in a semester-long class. In addition, the author provides insight into teaching challenges in the non-studio space that requires students to work intensively on post-printed models to assemble parts, finish, and refine the 3D printed surface. Even though this paper focuses on the 3D printing processes and techniques for small to medium design statue projects for the Digital Media program, the author hopes the paper will benefit other fields of study such as craft practices, product design, and fine-arts programs. Other schools that might implement 3D printing and fabrication in their programs will find helpful information in this paper, such as a teaching plan, choices of equipment and materials, adaptation for non-studio spaces, and putting together a complete and well-resolved project for students.

Keywords: 3D digital modeling, 3D digital sculpting, 3D modeling, 3D printing, 3D digital fabrication

Procedia PDF Downloads 100
5205 Modeling Jordan University of Science and Technology Parking Using Arena Program

Authors: T. Qasim, M. Alqawasmi, M. Hawash, M. Betar, W. Qasim

Abstract:

Over the last decade, the over population that has happened in urban areas has been reflecting on the services that various local institutions provide to car users in the form of car parks, which is becoming a daily necessity in our lives. This study focuses on car parks at Jordan University of Science and Technology, in Irbid, Jordan, to understand the university parking needs. Data regarding arrival and departure times of cars and the parking utilization were collected, to find various options that the university can implement to solve and develop an efficient car parking system. Arena software was used to simulate a parking model. This model allows measuring the different solutions that solve the parking problem at Jordan University of Science and Technology.

Keywords: car park, simulation, modeling, service time

Procedia PDF Downloads 174
5204 Traffic Congestions Modeling and Predictions by Social Networks

Authors: Bojan Najdenov, Danco Davcev

Abstract:

Reduction of traffic congestions and the effects of pollution and waste of resources that come with them has been a big challenge in the past decades. Having reliable systems to facilitate the process of modeling and prediction of traffic conditions would not only reduce the environmental pollution, but will also save people time and money. Social networks play big role of people’s lives nowadays providing them means of communicating and sharing thoughts and ideas, that way generating huge knowledge bases by crowdsourcing. In addition to that, crowdsourcing as a concept provides mechanisms for fast and relatively reliable data generation and also many services are being used on regular basis because they are mainly powered by the public as main content providers. In this paper we present the Social-NETS-Traffic-Control System (SNTCS) that should serve as a facilitator in the process of modeling and prediction of traffic congestions. The main contribution of our system is to integrate data from social networks as Twitter and also implements a custom created crowdsourcing subsystem with which users report traffic conditions using an android application. Our first experience of the usage of the system confirms that the integrated approach allows easy extension of the system with other social networks and represents a very useful tool for traffic control.

Keywords: traffic, congestion reduction, crowdsource, social networks, twitter, android

Procedia PDF Downloads 475
5203 Relationships between Financial, Cultural, Emotional, and General Wellbeing: A Structural Equation Modeling Study

Authors: Michael Alsop, Hannah Heitz, Prathiba Natesan Batley, Marion Hambrick, Jason Immekus

Abstract:

The impacts of cultural engagement on individuals’ health and well-being have been well documented. The purposes of this study were to create an instrument to measure wellbeing constructs, including cultural wellbeing, and explore the relationships between cultural wellbeing and other wellbeing constructs (e.g., emotional, social, physical, spiritual). A sample of 358 participants attending concerts performed by a civic orchestra in the southeastern United States completed a questionnaire designed to measure eight wellbeing constructs. Split-half exploratory, confirmatory factor analyses resulted in the retention of four wellbeing constructs: general, emotional, financial, and cultural. Structural equation modeling showed statistically significant relationships between cultural wellbeing and other wellbeing constructs. In addition to the indirect effect of financial wellbeing on emotional and general wellbeing through cultural wellbeing, there were also direct statistically significant relationships (i.e., moderator). This highlights the importance of removing financial barriers to cultural engagement and the relationship between cultural wellbeing on emotional and general wellbeing. Additionally, the retained cultural wellbeing items focused primarily on community features, indicating the value of community-based cultural engagement opportunities.

Keywords: cultural wellbeing, cultural engagement, factor analysis, structural equation modeling

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5202 Modeling and Validation of Microspheres Generation in the Modified T-Junction Device

Authors: Lei Lei, Hongbo Zhang, Donald J. Bergstrom, Bing Zhang, K. Y. Song, W. J. Zhang

Abstract:

This paper presents a model for a modified T-junction device for microspheres generation. The numerical model is developed using a commercial software package: COMSOL Multiphysics. In order to test the accuracy of the numerical model, multiple variables, such as the flow rate of cross-flow, fluid properties, structure, and geometry of the microdevice are applied. The results from the model are compared with the experimental results in the diameter of the microsphere generated. The comparison shows a good agreement. Therefore the model is useful in further optimization of the device and feedback control of microsphere generation if any.

Keywords: CFD modeling, validation, microsphere generation, modified T-junction

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5201 Atmospheric Transport Modeling of Radio-Xenon Detections Possibly Related to the Announced Nuclear Test in North Korea on February 12, 2013

Authors: Kobi Kutsher

Abstract:

On February 12th 2013, monitoring stations of the Preparatory Commission of the Comprehensive Nuclear Test-Ban Treaty Organization (CTBTO) detected a seismic event with explosion-like underground characteristics in the Democratic People’s Republic of Korea (DPRK). The location was found to be in the vicinity of the two previous announced nuclear tests in 2006 and 2009.The nuclear test was also announced by the government of the DPRK.After an underground nuclear explosion, radioactive fission products (mostly noble gases) can seep through layers of rock and sediment until they escape into the atmosphere. The fission products are dispersed in the atmosphere and may be detected thousands of kilometers downwind from the test site. Indeed, more than 7 weeks after the explosion, unusual detections of noble gases was reported at the radionuclide station in Takasaki, Japan. The radionuclide station is a part of the International Monitoring System, operated to verify the CTBT. This study provides an estimation of the possible source region and the total radioactivity of the release using Atmospheric Transport Modeling.

Keywords: atmospheric transport modeling, CTBTO, nuclear tests, radioactive fission products

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5200 E-Consumers’ Attribute Non-Attendance Switching Behavior: Effect of Providing Information on Attributes

Authors: Leonard Maaya, Michel Meulders, Martina Vandebroek

Abstract:

Discrete Choice Experiments (DCE) are used to investigate how product attributes affect decision-makers’ choices. In DCEs, choice situations consisting of several alternatives are presented from which choice-makers select the preferred alternative. Standard multinomial logit models based on random utility theory can be used to estimate the utilities for the attributes. The overarching principle in these models is that respondents understand and use all the attributes when making choices. However, studies suggest that respondents sometimes ignore some attributes (commonly referred to as Attribute Non-Attendance/ANA). The choice modeling literature presents ANA as a static process, i.e., respondents’ ANA behavior does not change throughout the experiment. However, respondents may ignore attributes due to changing factors like availability of information on attributes, learning/fatigue in experiments, etc. We develop a dynamic mixture latent Markov model to model changes in ANA when information on attributes is provided. The model is illustrated on e-consumers’ webshop choices. The results indicate that the dynamic ANA model describes the behavioral changes better than modeling the impact of information using changes in parameters. Further, we find that providing information on attributes leads to an increase in the attendance probabilities for the investigated attributes.

Keywords: choice models, discrete choice experiments, dynamic models, e-commerce, statistical modeling

Procedia PDF Downloads 134
5199 Role of Estrogen Receptor-alpha in Mammary Carcinoma by Single Nucleotide Polymorphisms and Molecular Docking: An In-silico Analysis

Authors: Asif Bilal, Fouzia Tanvir, Sibtain Ahmad

Abstract:

Estrogen receptor alpha, also known as estrogen receptor-1, is highly involved in risk of mammary carcinoma. The objectives of this study were to identify non-synonymous SNPs of estrogen receptor and their association with breast cancer and to identify the chemotherapeutic responses of phytochemicals against it via in-silico study design. For this purpose, different online tools. to identify pathogenic SNPs the tools were SIFT, Polyphen, Polyphen-2, fuNTRp, SNAP2, for finding disease associated SNPs the tools SNP&GO, PhD-SNP, PredictSNP, MAPP, SNAP, MetaSNP, PANTHER, and to check protein stability Mu-Pro, I-Mutant, and CONSURF were used. Post-translational modifications (PTMs) were detected by Musitedeep, Protein secondary structure by SOPMA, protein to protein interaction by STRING, molecular docking by PyRx. Seven SNPs having rsIDs (rs760766066, rs779180038, rs956399300, rs773683317, rs397509428, rs755020320, and rs1131692059) showing mutations on I229T, R243C, Y246H, P336R, Q375H, R394S, and R394H, respectively found to be completely deleterious. The PTMs found were 96 times Glycosylation; 30 times Ubiquitination, a single time Acetylation; and no Hydroxylation and Phosphorylation were found. The protein secondary structure consisted of Alpha helix (Hh) is (28%), Extended strand (Ee) is (21%), Beta turn (Tt) is 7.89% and Random coil (Cc) is (44.11%). Protein-protein interaction analysis revealed that it has strong interaction with Myeloperoxidase, Xanthine dehydrogenase, carboxylesterase 1, Glutathione S-transferase Mu 1, and with estrogen receptors. For molecular docking we used Asiaticoside, Ilekudinuside, Robustoflavone, Irinoticane, Withanolides, and 9-amin0-5 as ligands that extract from phytochemicals and docked with this protein. We found that there was great interaction (from -8.6 to -9.7) of these ligands of phytochemicals at ESR1 wild and two mutants (I229T and R394S). It is concluded that these SNPs found in ESR1 are involved in breast cancer and given phytochemicals are highly helpful against breast cancer as chemotherapeutic agents. Further in vitro and in vivo analysis should be performed to conduct these interactions.

Keywords: breast cancer, ESR1, phytochemicals, molecular docking

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5198 Transient Modeling of Velocity Profile and Heat Transfer of Electrohydrodynamically Augmented Micro Heat Pipe

Authors: H. Shokouhmand, M. Tajerian

Abstract:

At this paper velocity profile modeling and heat transfer in the micro heat pipes by using electrohydrodynamic (EHD) field at the transient regime have been studied. In the transient flow, one dimensional and two phase fluid flow and heat transfer for micro heat pipes with square cross section, have been studied. At this model Coulomb and dielectrophoretic forces are considered. Coupled, non-linear equations governed on the model (continuity, momentum, and energy equations) have been solved simultaneously by numerical methods. Transient behavior of affecting parameters e.g. substrate temperature, velocity of coolant liquid, radius of curvature and coolant liquid pressure, has been verified. By obtaining and plotting the mentioned parameters, it has been shown that the EHD field enhances the heat transfer process. So, the time required to reach the steady state regime decreases from 16 seconds to 2.4 seconds after applying EHD field. Another result has been observed implicitly that by increasing the heat input the effect of EHD field became more significant. The numerical results of model predict the experimental results available in the literature successfully, and it has been observed there is a good agreement between them.

Keywords: micro heat pipe, transient modeling, electrohydrodynamics, capillary, meniscus

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5197 Thermodynamic Modeling of Three Pressure Level Reheat HRSG, Parametric Analysis and Optimization Using PSO

Authors: Mahmoud Nadir, Adel Ghenaiet

Abstract:

The main purpose of this study is the thermodynamic modeling, the parametric analysis, and the optimization of three pressure level reheat HRSG (Heat Recovery Steam Generator) using PSO method (Particle Swarm Optimization). In this paper, a parametric analysis followed by a thermodynamic optimization is presented. The chosen objective function is the specific work of the steam cycle that may be, in the case of combined cycle (CC), a good criterion of thermodynamic performance analysis, contrary to the conventional steam turbines in which the thermal efficiency could be also an important criterion. The technologic constraints such as maximal steam cycle temperature, minimal steam fraction at steam turbine outlet, maximal steam pressure, minimal stack temperature, minimal pinch point, and maximal superheater effectiveness are also considered. The parametric analyses permitted to understand the effect of design parameters and the constraints on steam cycle specific work variation. PSO algorithm was used successfully in HRSG optimization, knowing that the achieved results are in accordance with those of the previous studies in which genetic algorithms were used. Moreover, this method is easy to implement comparing with the other methods.

Keywords: combined cycle, HRSG thermodynamic modeling, optimization, PSO, steam cycle specific work

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5196 Molecular Diagnosis of Influenza Strains Was Carried Out on Patients of the Social Security Clinic in Karaj Using the RT-PCR Technique

Authors: A. Ferasat, S. Rostampour Yasouri

Abstract:

Seasonal flu is a highly contagious infection caused by influenza viruses. These viruses undergo genetic changes that result in new epidemics across the globe. Medical attention is crucial in severe cases, particularly for the elderly, frail, and those with chronic illnesses, as their immune systems are often weaker. The purpose of this study was to detect new subtypes of the influenza A virus rapidly using a specific RT-PCR method based on the HA gene (hemagglutinin). In the winter and spring of 2022_2023, 120 embryonated egg samples were cultured, suspected of seasonal influenza. RNA synthesis, followed by cDNA synthesis, was performed. Finally, the PCR technique was applied using a pair of specific primers designed based on the HA gene. The PCR product was identified after purification, and the nucleotide sequence of purified PCR products was compared with the sequences in the gene bank. The results showed a high similarity between the sequence of the positive samples isolated from the patients and the sequence of the new strains isolated in recent years. This RT-PCR technique is entirely specific in this study, enabling the detection and multiplication of influenza and its subspecies from clinical samples. The RT-PCR technique based on the HA gene, along with sequencing, is a fast, specific, and sensitive diagnostic method for those infected with influenza viruses and its new subtypes. Rapid molecular diagnosis of influenza is essential for suspected people to control and prevent the spread of the disease to others. It also prevents the occurrence of secondary (sometimes fatal) pneumonia that results from influenza and pathogenic bacteria. The critical role of rapid diagnosis of new strains of influenza is to prepare a drug vaccine against the latest viruses that did not exist in the community last year and are entirely new viruses.

Keywords: influenza, molecular diagnosis, patients, RT-PCR technique

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5195 Stochastic Modeling for Parameters of Modified Car-Following Model in Area-Based Traffic Flow

Authors: N. C. Sarkar, A. Bhaskar, Z. Zheng

Abstract:

The driving behavior in area-based (i.e., non-lane based) traffic is induced by the presence of other individuals in the choice space from the driver’s visual perception area. The driving behavior of a subject vehicle is constrained by the potential leaders and leaders are frequently changed over time. This paper is to determine a stochastic model for a parameter of modified intelligent driver model (MIDM) in area-based traffic (as in developing countries). The parametric and non-parametric distributions are presented to fit the parameters of MIDM. The goodness of fit for each parameter is measured in two different ways such as graphically and statistically. The quantile-quantile (Q-Q) plot is used for a graphical representation of a theoretical distribution to model a parameter and the Kolmogorov-Smirnov (K-S) test is used for a statistical measure of fitness for a parameter with a theoretical distribution. The distributions are performed on a set of estimated parameters of MIDM. The parameters are estimated on the real vehicle trajectory data from India. The fitness of each parameter with a stochastic model is well represented. The results support the applicability of the proposed modeling for parameters of MIDM in area-based traffic flow simulation.

Keywords: area-based traffic, car-following model, micro-simulation, stochastic modeling

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5194 Multiple Negative-Differential Resistance Regions Based on AlN/GaN Resonant Tunneling Structures by the Vertical Growth of Molecular Beam Epitaxy

Authors: Yao Jiajia, Wu Guanlin, LIU Fang, Xue Junshuai, Zhang Jincheng, Hao Yue

Abstract:

Resonant tunneling diodes (RTDs) based on GaN have been extensively studied. However, no results of multiple logic states achieved by RTDs were reported by the methods of epitaxy in the GaN materials. In this paper, the multiple negative-differential resistance regions by combining two discrete double-barrier RTDs in series have been first demonstrated. Plasma-assisted molecular beam epitaxy (PA-MBE) was used to grow structures consisting of two vertical RTDs. The substrate was a GaN-on-sapphire template. Each resonant tunneling structure was composed of a double barrier of AlN and a single well of GaN with undoped 4-nm space layers of GaN on each side. The AlN barriers were 1.5 nm thick, and the GaN well was 2 nm thick. The resonant tunneling structures were separated from each other by 30-nm thick n+ GaN layers. The bottom and top layers of the structures, grown neighboring to the spacer layers that consist of 200-nm-thick n+ GaN. These devices with two tunneling structures exhibited uniform peaks and valleys current and also had two negative differential resistance NDR regions equally spaced in bias voltage. The current-voltage (I-V) characteristics of resonant tunneling structures with diameters of 1 and 2 μm were analyzed in this study. These structures exhibit three stable operating points, which are investigated in detail. This research demonstrates that using molecular beam epitaxy MBE to vertically grow multiple resonant tunneling structures is a promising method for achieving multiple negative differential resistance regions and stable logic states. These findings have significant implications for the development of digital circuits capable of multi-value logic, which can be achieved with a small number of devices.

Keywords: GaN, AlN, RTDs, MBE, logic state

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5193 Ultradrawing and Ultimate Tensile Properties of Ultrahigh Molecular Weight Polyethylene Composite Fibers Filled with Activated Nanocarbon Particles with Varying Specific Surface Areas

Authors: Wang-Xi Fan, Yi Ding, Zhong-Dan Tu, Kuo-Shien Huang, Chao-Ming Huang, Jen-Taut Yeh

Abstract:

Original and/or functionalized activated nanocarbon particles with a quoted specific surface area of 100, 500, 1000 and 1400 m2/g, respectively, were used to investigate the influence of specific surface areas of activated nanocarbon on ultra drawing and ultimate tensile properties of ultrahigh molecular weight polyethylene (UHMWPE), UHMWPE/activated nanocarbon and UHMWPE/ functionalized activated nanocarbon fibers. The specific surface areas of well dispersed functionalized activated nanocarbon in UHMWPE/functionalized activated nanocarbon fibers can positively affect their ultra drawing, orientation, ultimate tensile properties and “micro-fibril” characteristics. Excellent orientation and ultimate tensile properties of UHMWPE/nanofiller fibers can be prepared by ultra drawing the UHMWPE/functionalized activated nanocarbon as-prepared fibers with optimal contents and compositions of functionalized activated nanocarbon. The ultimate tensile strength value of the best prepared UHMWPE/functionalized activated nanocarbon drawn fiber reached 8.0 GPa, which was about 2.86 times of that of the best-prepared UHMWPE drawn fiber prepared in this study. Specific surface area, morphological and Fourier transform infrared analyses of original and functionalized activated nanocarbon and/or investigations of thermal, orientation factor and ultimate tensile properties of as-prepared and/or drawn UHMWPE/functionalized activated nanocarbon fibers were performed to understand the above-improved ultra drawing and ultimate tensile properties of the UHMWPE/functionalized activated nanocarbon fibers.

Keywords: activated nanocarbon, specific surface areas, ultradrawing, ultrahigh molecular weight polyethylene

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5192 Bioinformatic Approaches in Population Genetics and Phylogenetic Studies

Authors: Masoud Sheidai

Abstract:

Biologists with a special field of population genetics and phylogeny have different research tasks such as populations’ genetic variability and divergence, species relatedness, the evolution of genetic and morphological characters, and identification of DNA SNPs with adaptive potential. To tackle these problems and reach a concise conclusion, they must use the proper and efficient statistical and bioinformatic methods as well as suitable genetic and morphological characteristics. In recent years application of different bioinformatic and statistical methods, which are based on various well-documented assumptions, are the proper analytical tools in the hands of researchers. The species delineation is usually carried out with the use of different clustering methods like K-means clustering based on proper distance measures according to the studied features of organisms. A well-defined species are assumed to be separated from the other taxa by molecular barcodes. The species relationships are studied by using molecular markers, which are analyzed by different analytical methods like multidimensional scaling (MDS) and principal coordinate analysis (PCoA). The species population structuring and genetic divergence are usually investigated by PCoA and PCA methods and a network diagram. These are based on bootstrapping of data. The Association of different genes and DNA sequences to ecological and geographical variables is determined by LFMM (Latent factor mixed model) and redundancy analysis (RDA), which are based on Bayesian and distance methods. Molecular and morphological differentiating characters in the studied species may be identified by linear discriminant analysis (DA) and discriminant analysis of principal components (DAPC). We shall illustrate these methods and related conclusions by giving examples from different edible and medicinal plant species.

Keywords: GWAS analysis, K-Means clustering, LFMM, multidimensional scaling, redundancy analysis

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5191 Inhibitory Effects of Ambrosia trifida L. on the Development of Root Hairs and Protein Patterns of Radicles

Authors: Ji-Hyon Kil, Kew-Cheol Shim, Kyoung-Ae Park, Kyoungho Kim

Abstract:

Ambrosia trifida L. is designated as invasive alien species by the Act on the Conservation and Use of Biodiversity by the Ministry of Environment, Korea. The purpose of present paper was to investigate the inhibitory effects of aqueous extracts of A.trifida on the development of root hairs of Triticum aestivum L., and Allium tuberosum Rottler ex Spreng and the electrophoretic protein patterns of their radicles. The development of root hairs was inhibited by increasing of aqueous extract concentrations. Through SDS-PAGE, the electrophoretic protein bands of extracted proteins from their radicles were appeared in controls, but protein bands of specific molecular weight disappeared or weakened in treatments. In conclusion, inhibitory effects of A. trifida made two receptor species changed morphologically, and at the molecular level in early growth stage.

Keywords: Ambrosia trifida L., invasive alien species, inhibitory effect, root hair, electrophoretic protein, radicle

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5190 Comparison of Different Machine Learning Algorithms for Solubility Prediction

Authors: Muhammet Baldan, Emel Timuçin

Abstract:

Molecular solubility prediction plays a crucial role in various fields, such as drug discovery, environmental science, and material science. In this study, we compare the performance of five machine learning algorithms—linear regression, support vector machines (SVM), random forests, gradient boosting machines (GBM), and neural networks—for predicting molecular solubility using the AqSolDB dataset. The dataset consists of 9981 data points with their corresponding solubility values. MACCS keys (166 bits), RDKit properties (20 properties), and structural properties(3) features are extracted for every smile representation in the dataset. A total of 189 features were used for training and testing for every molecule. Each algorithm is trained on a subset of the dataset and evaluated using metrics accuracy scores. Additionally, computational time for training and testing is recorded to assess the efficiency of each algorithm. Our results demonstrate that random forest model outperformed other algorithms in terms of predictive accuracy, achieving an 0.93 accuracy score. Gradient boosting machines and neural networks also exhibit strong performance, closely followed by support vector machines. Linear regression, while simpler in nature, demonstrates competitive performance but with slightly higher errors compared to ensemble methods. Overall, this study provides valuable insights into the performance of machine learning algorithms for molecular solubility prediction, highlighting the importance of algorithm selection in achieving accurate and efficient predictions in practical applications.

Keywords: random forest, machine learning, comparison, feature extraction

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5189 Control-Oriented Enhanced Zero-Dimensional Two-Zone Combustion Modelling of Internal Combustion Engines

Authors: Razieh Arian, Hadi Adibi-Asl

Abstract:

This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine

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