Search results for: discrete events simulation

Authors: Wararit Panichkitkosolkul

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The unit root tests based on the robust estimator for the first-order autoregressive process are proposed and compared with the unit root tests based on the ordinary least squares (OLS) estimator. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of Type I error and powers of the unit root tests are estimated via Monte Carlo simulation. Simulation results show that all unit root tests can control the probability of Type I error for all situations. The empirical power of the unit root tests based on the robust estimator are higher than the unit root tests based on the OLS estimator.

Keywords: autoregressive, ordinary least squares, type i error, power of the test, Monte Carlo simulation

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Authors: Rama Bhargava

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In the current paper, numerical simulation has been performed for the two-dimensional time dependent Pennes’ heat transfer model which is solved for irregular diseased tumor cells. An elliptic cryoprobe of varying sizes is taken at the center of the computational domain in such a manner that the location of the probe is fixed throughout the computation. The phase transition occurs due to the effect of probe with infusion of different nanoparticles Au, Al₂O₃, Fe₃O₄. The cooling performance of these nanoparticles injected at very low temperature, has been studied by implementing a hybrid FEM/EFGM method in which the whole domain is decomposed into two subdomains. The results are shown in terms of temperature profile inside the computational domain. Rate of cooling is obtained for various nanoparticles and it is observed that infusion of Au nanoparticles is very much efficient in increasing the heating rate than other nanoparticles. Such numerical scheme has direct applications where the domain is irregular.

Keywords: cryosurgery, hybrid EFGM/FEM, nanoparticles, simulation

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Authors: Renalda El Samra, Elie Bou-Zeid, Hamza Kunhu Bangalath, Georgiy Stenchikov, Mutasem El Fadel

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The regional-scale impact of climate change over complex terrain was examined through high-resolution dynamic downscaling conducted using the Weather Research and Forecasting (WRF) model, with initial and boundary conditions from a High-Resolution Atmospheric Model (HiRAM). The analysis was conducted over the eastern Mediterranean, with a focus on the country of Lebanon, which is characterized by a challenging complex topography that magnifies the effect of orographic precipitation. Four year-long WRF simulations, selected based on HiRAM time series, were performed to generate future climate projections of extreme temperature and precipitation over the study area under the conditions of the Representative Concentration Pathway (RCP) 4.5. One past WRF simulation year, 2008, was selected as a baseline to capture dry extremes of the system. The results indicate that the study area might be exposed to a temperature increase between 1.0 and 3ºC in summer mean values by 2050, in comparison to 2008. For extreme years, the decrease in average annual precipitation may exceed 50% at certain locations in comparison to 2008.

Keywords: HiRAM, regional climate modeling, WRF, Representative Concentration Pathway (RCP)

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Authors: Kais Siala, Mohamed Kharrat, Mohamed Abid

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Exposure therapies encourage patients to gradually begin facing their painful memories of the trauma in order to reduce fear and anxiety. In this context, virtual reality techniques are widely used for treatment of different kinds of phobia. The particular case of fear of death phobia (thanataphobia) is addressed in this paper. For this purpose, we propose to make a simulation of Near Death Experience (NDE) using augmented reality techniques. We propose in particular to simulate the Out-of-Body experience (OBE) which is the first step of a Near-Death-Experience (NDE). In this paper, we present technical aspects of this simulation as well as short-term impact in terms of physiological measures. The non-linear Poincéré plot is used to describe the difference in Heart Rate Variability between In-Body and Out-Of-Body conditions.

Keywords: Out-of-Body simulation, physiological measure, augmented reality, phobia psychotherapy, HRV, Poincaré plot

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Authors: S. Yunus, A. Suratman, N. Mohamad Nor, M. Othman

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This paper presents the measurement and simulation results by Finite Element Method (FEM) for earth resistance (R_DC) for interconnected vertical ground rod configurations. The soil resistivity was measured using the Wenner four-pin Method, and R_DC was measured using the Fall of Potential (FOP) method, as outlined in the standard. Genetic Algorithm (GA) is employed to interpret the soil resistivity to that of a 2-layer soil model. The same soil resistivity data that were obtained by Wenner four-pin method were used in FEM for simulation. This paper compares the results of R_DC obtained by FEM simulation with the real measurement at field site. A good agreement was seen for R_DC obtained by measurements and FEM. This shows that FEM is a reliable software to be used for design of earthing systems. It is also found that the parallel rod system has a better performance compared to a similar setup using a grid layout.

Keywords: earthing system, earth electrodes, finite element method, genetic algorithm, earth resistances

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Authors: Do Chi Thanh, Dang Ngoc Huy

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Nowadays, there are more and more variable speed drive systems in small-scale and large-scale applications such as the electric vehicle industry, household appliances, medical equipment, and other industrial fields led to the development of BLDC (Brushless DC) motors. BLDC drive has many advantages, such as higher efficiency, better speed torque characteristics, high power density, and low maintenance cost compared to other conventional motors. Most BLDC motors use a proportional-integral (PI) controller and a pulse width modulation (PWM) scheme for speed control. This article describes the simulation model of BLDC motor drive control with the help of MATLAB - SIMULINK simulation software. The built simulation model includes a BLDC motor dynamic block, Hall sensor signal generation block, inverter converter block, and PI controller.

Keywords: brushless DC motor, BLDC, six-step inverter, PI speed

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Authors: Josef Novák, Alena Kohoutková, Vladimír Křístek, Jan Vodička

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Numerical analysis software belong to the main tools for simulating the real behavior of various concrete structures and elements. In comparison with experimental tests, they offer an affordable way to study the mechanical behavior of structures under various conditions. The contribution deals with a precast element of an innovative airfield pavement system which is being developed within an ongoing scientific project. The proposed system consists a two-layer surface course of precast concrete panels positioned on a two-layer base of fiber-reinforced concrete with recycled aggregate. As the panels are supposed to be installed directly on the hardened base course, imperfections at the interface between the base course and surface course are expected. Considering such circumstances, three various behavior patterns could be established and considered when designing the precast element. Enormous costs of full-scale experiments force to simulate the behavior of the element in a numerical analysis software using finite element method. The simulation was conducted on a nonlinear model in order to obtain such results which could fully compensate results from the experiments. First, several loading schemes were considered with the aim to observe the critical one which was used for the simulation later on. The main objective of the simulation was to optimize reinforcement of the element subject to quasi-static loading from airplanes. When running the simulation several parameters were considered. Namely, it concerns geometrical imperfections, manufacturing imperfections, stress state in reinforcement, stress state in concrete and crack width. The numerical simulation revealed that the precast element should be heavily reinforced to fulfill all the demands assumed. The main cause of using high amount of reinforcement is the size of the imperfections which could occur at real structure. Improving manufacturing quality, the installation of the precast panels on a fresh base course or using a bedding layer underneath the surface course belong to the main steps how to reduce the size of imperfections and consequently lower the consumption of reinforcement.

Keywords: nonlinear analysis, numerical simulation, precast concrete, pavement

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Authors: M. Dehestani, M. Ghasemi-Kooch

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In this work, adsorption of chlorophylls a and b pigments in aqueous solution on the inner and outer surfaces of single-walled carbon nanotube (SWCNT) has been studied using molecular dynamics simulation. The linear interaction energy algorithm has been used to calculate the binding free energy. The results show that the adsorption of two pigments is fine on the both positions. Although there is the close similarity between these two pigments, their interaction with the nanotube is different. This result is useful to separate these pigments from one another. According to interaction energy between the pigments and carbon nanotube, interaction between these pigments-SWCNT on the inner surface is stronger than the outer surface. The interaction of SWCNT with chlorophylls phytol tail is stronger than the interaction of SWCNT with porphyrin ring of chlorophylls.

Keywords: adsorption, chlorophyll, interaction, molecular dynamics simulation, nanotube

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Authors: Ali Raza, Shafiq Ur Rehman Khan, Raja Sher Afgun Usmani, Asif Raza, Basit Umair

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Detection of Fake news and missing information is gaining popularity, especially after the advancement in social media and online news platforms. Social media platforms are the main and speediest source of fake news propagation, whereas online news websites contribute to fake news dissipation. In this study, we propose a framework to detect fake news using the temporal features of text and consider user feedback to identify whether the news is fake or not. In recent studies, the temporal features in text documents gain valuable consideration from Natural Language Processing and user feedback and only try to classify the textual data as fake or true. This research article indicates the impact of recurring and non-recurring events on fake and true news. We use two models BERT and Bi-LSTM to investigate, and it is concluded from BERT we get better results and 70% of true news are recurring and rest of 30% are non-recurring.

Keywords: natural language processing, fake news detection, machine learning, Bi-LSTM

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Authors: Kamal Kumar Tanti, Nayan Moni Saikia, Markynti Swer

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This study aims to investigate and analyse the trends and variability of rainfall in Shillong and its nearby areas, located in Meghalaya hills of North-East India; which is geographically a neighbouring area to the wettest places of the Earth, i.e., Cherrapunji and Mawsynram. The analysis of variability and trends to annual, seasonal, monthly and daily rainfall was carried out, using the data collected from the IMD station at Shillong; thereby attempting to highlight whether rainfall in Shillong area has been increasing or decreasing over the years. Rainfall variability coefficient is utilized to compare the current rainfall trend of the area with its past rainfall trends. The present study also aims to analyse the frequency of occurrence of extreme rainfall events over the region. These studies will help us to establish a correlation between the current rainfall trend and climate change scenario of the study area.

Keywords: trends and variability of rainfall, annual, seasonal, monthly and daily rainfall, rainfall variability coefficient, extreme rainfall events, climate change, Shillong, Cherrapunji, Mawsynram

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Authors: Anil Kumar Pandey

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Power plane noise is the most significant source of signal integrity (SI) issues in a high-speed digital design. In this paper, power integrity (PI) analysis of multiple power planes in a power delivery system of a 12-layer high-speed FPGA board is presented. All 10 power planes of HSD board are analyzed separately by using 3D Electromagnetic based PI solver, then the transient simulation is performed on combined PI data of all planes along with voltage regulator modules (VRMs) and 70 current drawing chips to get the board level power noise coupling on different high-speed signals. De-coupling capacitors are placed between power planes and ground to reduce power noise coupling with signals.

Keywords: power integrity, power-aware signal integrity analysis, electromagnetic simulation, channel simulation

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Authors: Leila Khosravi

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A major part of the drinking water in North West of Iran is supplied from Mahabad reservoir 80 km northwest of Mahabad. This reservoir collects water from 750 km-catchment which is undergoing accelerated changes due to deforestation and urbanization. The main objective of this study is to develop a catchment modeling platform which translates ongoing land-use changes, soil data, precipitation and evaporation into surface runoff of the river discharging into the reservoir: Soil and Water Assessment Tool, SWAT, model along with hydro -meteorological records of 1997–2011. A variety of statistical indices were used to evaluate the simulation results for both calibration and validation periods; among them, the robust Nash–Sutcliffe coefficients were found to be 0.52 and 0.62 in the calibration and validation periods, respectively. This project has developed a reliable modeling platform with the benchmark land physical conditions of the Mahabad dam basin.

Keywords: simulation, surface runoff, Mahabad dam, SWAT model

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Authors: Joseph Bostick

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A method of decreasing the heating load of HVAC systems in a single-dwelling model of a multifamily building, by controlling movable insulation through the optimization of flux, time, surface incident solar radiation, and temperature thresholds. Simulations are completed using a co-simulation between EnergyPlus and MATLAB as an optimization tool to find optimal control thresholds. Optimization of the control thresholds leads to a significant decrease in total heating energy expenditure.

Keywords: energy plus, MATLAB, simulation, energy efficiency

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Authors: Omid Adibi, Nategheh Najafpour, Bijan Farhanieh, Hossein Afshin

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Gas release from the pipelines is one of the main factors in the gas industry accidents. Released gas ejects from the pipeline as a free jet and in the growth process, the fuel gets mixed with the ambient air. Accordingly, an accidental spark will release the chemical energy of the mixture with an explosion. Gas explosion damages the equipment and endangers the life of staffs. So due to importance of safety in gas industries, prevision of accident can reduce the number of the casualties. In this paper, natural gas leakages from the low pressure pipelines are studied in two steps: 1) the simulation of mixing process and identification of flammable zones and 2) the simulation of wind effects on the mixing process. The numerical simulations were performed by using the finite volume method and the pressure-based algorithm. Also, for the grid generation the structured method was used. The results show that, in just 6.4 s after accident, released natural gas could penetrate to 40 m in vertical and 20 m in horizontal direction. Moreover, the results show that the wind speed is a key factor in dispersion process. In fact, the wind transports the flammable zones into the downstream. Hence, to improve the safety of the people and human property, it is preferable to construct gas facilities and buildings in the opposite side of prevailing wind direction.

Keywords: flammable zones, gas pipelines, numerical simulation, wind effects

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Authors: Hadi Ardiny, Amir Mohammad Beigzadeh

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Through the utilization of a combination of various sensors and data fusion methods, the detection of potential nuclear threats can be significantly enhanced by extracting more information from different data. In this research, an experimental and modeling approach was employed to track a radioactive source by combining a surveillance camera and a radiation detector (NaI). To run this experiment, three mobile robots were utilized, with one of them equipped with a radioactive source. An algorithm was developed in identifying the contaminated robot through correlation between camera images and camera data. The computer vision method extracts the movements of all robots in the XY plane coordinate system, and the detector system records the gamma-ray count. The position of the robots and the corresponding count of the moving source were modeled using the MCNPX simulation code while considering the experimental geometry. The results demonstrated a high level of accuracy in finding and locating the target in both the simulation model and experimental measurement. The modeling techniques prove to be valuable in designing different scenarios and intelligent systems before initiating any experiments.

Keywords: nuclear threats, radiation detector, MCNPX simulation, modeling techniques, intelligent systems

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Authors: S. Kadiyala, M. Berzins, D. Juba, W. Keyrouz

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This paper describes the Material Point Method (MPM) for simulating a single-track laser melting process on an IN718 solid plate. MPM, known for simulating challenging multiphysics problems, is used to model the intricate thermal, mechanical, and fluid interactions during the laser sintering process. This study analyzes the formation of single tracks, exploring the impact of varying laser parameters such as speed, power, and spot diameter on the melt pool and track formation. The focus is on MPM’s ability to accurately simulate and capture the transient thermo-mechanical and phase change phenomena, which are critical in predicting the cooling rates before and after solidification of the laser track and the final melt pool geometry. The simulation results are rigorously compared with experimental data (AMB2022 benchmarks), demonstrating the effectiveness of MPM in replicating the physical processes in laser sintering. This research highlights the potential of MPM in advancing the understanding and simulation of melt pool physics in metal additive manufacturing, paving the way for optimized process parameters and improved material performance.

Keywords: dditive manufacturing simulation, material point method, phase change, melt pool physics

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Authors: Sujoy Anirudha Das, Albert Thomas

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Building sector is a major consumer of energy globally, and it has corresponding effects to the environment with respect to the carbon emissions. Given the fact that India is expected to add 40-billion square meter of new buildings till 2050, we need frameworks that help in reducing the overall energy consumption in the building sector. Even though several simulation-based frameworks that help in analyzing the building energy consumption are developed globally, in the Indian context, to the best of our knowledge, there is a lack of a comprehensive, yet user-friendly framework to simulate and optimize the effects of various energy influencing factors, specifically for Indian buildings. Therefore, this study is aimed at developing a simulation-based optimization framework to model the energy interactions in different types of Indian buildings by considering the dynamic nature of various energy influencing factors. This comprehensive framework can be used by various building stakeholders to test the energy effects of different factors such as, but not limited to, the various building materials, the orientation, the weather fluctuations, occupancy changes and the type of the building (e.g., office, residential). The results from the case study involving several building types would help us in gaining insights to build new energy-efficient buildings as well as retrofit the existing structures in a more convenient way to consume less energy, exclusively for an Indian scenario.

Keywords: building energy consumption, building energy simulations, energy efficient buildings, optimization framework

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Authors: N. Massoum, A. Guen. Bouazza, B. Bouazza, A. El Ouchdi

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The progress of industry integrated circuits in recent years has been pushed by continuous miniaturization of transistors. With the reduction of dimensions of components at 0.1 micron and below, new physical effects come into play as the standard simulators of two dimensions (2D) do not consider. In fact the third dimension comes into play because the transverse and longitudinal dimensions of the components are of the same order of magnitude. To describe the operation of such components with greater fidelity, we must refine simulation tools and adapted to take into account these phenomena. After an analytical study of the static characteristics of the component, according to the different operating modes, a numerical simulation is performed of field-effect transistor with submicron gate MESFET GaInP. The influence of the dimensions of the gate length is studied. The results are used to determine the optimal geometric and physical parameters of the component for their specific applications and uses.

Keywords: Monte Carlo simulation, transient electron transport, MESFET device, GaInP

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Authors: Elham Zamiri

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In this research, we have focused on numeral simulation of a fuel rod in order to examine distribution of heat temperature in components of fuel rod by Fluent software by providing steady state, single phase fluid flow, frequency heat flux in a fuel rod in nuclear reactor to numeral simulation. Results of examining different layers of a fuel rod consist of fuel layer, gap, pod, and fluid cooling flow, also examining thermal properties and fluids such as heat transition rate and pressure drop. The obtained results through analytical method and results of other sources have been compared and have appropriate correspondence. Results show that using heavy water as cooling fluid along with few layers of gas and pod have the ability of reducing the temperature from above 300 ^◦C to 70 ^◦C. This investigation is developable for any geometry and material used in the nuclear reactor.

Keywords: nuclear fuel fission, numberal simulation, fuel rod, reactor, Fluent software

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Authors: Rachid Benmoussa, Fatima Ezzahra Essaber, Roland De Guio, Fatima Zahra Ben Moussa

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Implementing green practices in supply chain management is a complex task mainly because ecological, economical and operational goals are usually in conflict. Green practices might thus face companies’ reluctance because managers can consider its implementation obviously as a performance lean degradation. To implement lean and green practices successfully, companies need relevant decision-making tools to highlight the correlation between them. To contribute to this issue, this work tries to answer the following research question: How to use simulation to assess correlation (antagonism or convergence) between lean and green goals? To answer this question, we propose in this paper a based simulation process that measures correlation generally between two variables. So as to prove its relevance, a logistics academic case study is used to illustrate all its stages. It shows, as for example, that Lean goal 'Stock' and Green goal 'CO₂ emission' are not conceptually correlated (linearly).

Keywords: simulation, lean, green, supply chain

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Authors: Sevilay Çankaya

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The detection of deception in children’s interviews is essential for statement veracity. The widely used method for deception detection is building cognitive load, which is the logic of the cognitive interview (CI), and its effectiveness for adults is approved. This meta-analysis delves into the effectiveness of inducing cognitive load as a means of enhancing veracity detection during interviews with children. Additionally, the effectiveness of cognitive load on children's total number of events recalled is assessed as a second part of the analysis. The current meta-analysis includes ten effect sizes from search using databases. For the effect size calculation, Hedge’s g was used with a random effect model by using CMA version 2. Heterogeneity analysis was conducted to detect potential moderators. The overall result indicated that cognitive load had no significant effect on veracity outcomes (g =0.052, 95% CI [-.006,1.25]). However, a high level of heterogeneity was found (I² = 92%). Age, participants’ characteristics, interview setting, and characteristics of the interviewer were coded as possible moderators to explain variance. Age was significant moderator (β = .021; p = .03, R2 = 75%) but the analysis did not reveal statistically significant effects for other potential moderators: participants’ characteristics (Q = 0.106, df = 1, p = .744), interview setting (Q = 2.04, df = 1, p = .154), and characteristics of interviewer (Q = 2.96, df = 1, p = .086). For the second outcome, the total number of events recalled, the overall effect was significant (g =4.121, 95% CI [2.256,5.985]). The cognitive load was effective in total recalled events when interviewing with children. All in all, while age plays a crucial role in determining the impact of cognitive load on veracity, the surrounding context, interviewer attributes, and inherent participant traits may not significantly alter the relationship. These findings throw light on the need for more focused, age-specific methods when using cognitive load measures. It may be possible to improve the precision and dependability of deceit detection in children's interviews with the help of more studies in this field.

Keywords: deceit detection, cognitive load, memory recall, children interviews, meta-analysis

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Authors: Alexander Zotov, Ilkin Osmanov, Emil Sakharov, Oleg Shelest, Aleksander Troitskiy, Robert Khabazov

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Objective: Thoracoscopic surgical ablation of atrial fibrillation (AF) includes two technologies in performing of operation. 1st strategy used is the AtriCure device (bipolar, nonirrigated, non clamping), 2nd strategy is- the Medtronic device (bipolar, irrigated, clamping). The study presents a comparative analysis of clinical outcomes of two strategies in thoracoscopic ablation of AF using AtriCure vs. Medtronic devices. Methods: In 2 center study, 123 patients underwent thoracoscopic ablation of AF for the period from 2016 to 2020. Patients were divided into two groups. The first group is represented by patients who applied the AtriCure device (N=63), and the second group is - the Medtronic device (N=60), respectively. Patients were comparable in age, gender, and initial severity of the condition. Among the patients, in group 1 were 65% males with a median age of 57 years, while in group 2 – 75% and 60 years, respectively. Group 1 included patients with paroxysmal form -14,3%, persistent form - 68,3%, long-standing persistent form – 17,5%, group 2 – 13,3%, 13,3% and 73,3% respectively. Median ejection fraction and indexed left atrial volume amounted in group 1 – 63% and 40,6 ml/m2, in group 2 - 56% and 40,5 ml/m2. In addition, group 1 consisted of 39,7% patients with chronic heart failure (NYHA Class II) and 4,8% with chronic heart failure (NYHA Class III), when in group 2 – 45% and 6,7%, respectively. Follow-up consisted of laboratory tests, chest Х-ray, ECG, 24-hour Holter monitor, and cardiopulmonary exercise test. Duration of freedom from AF, distant mortality rate, and prevalence of cerebrovascular events were compared between the two groups. Results: Exit block was achieved in all patients. According to the Clavien-Dindo classification of surgical complications fraction of adverse events was 14,3% and 16,7% (1st group and 2nd group, respectively). Mean follow-up period in the 1st group was 50,4 (31,8; 64,8) months, in 2nd group - 30,5 (14,1; 37,5) months (P=0,0001). In group 1 - total freedom of AF was in 73,3% of patients, among which 25% had additional antiarrhythmic drugs (AADs) therapy or catheter ablation (CA), in group 2 – 90% and 18,3%, respectively (for total freedom of AF P<0,02). At follow-up, the distant mortality rate in the 1st group was – 4,8%, and in the 2nd – no fatal events. Prevalence of cerebrovascular events was higher in the 1st group than in the 2nd (6,7% vs. 1,7% respectively). Conclusions: Despite the relatively shorter follow-up of the 2nd group in the study, applying the strategy using the Medtronic device showed quite encouraging results. Further research is needed to evaluate the effectiveness of this strategy in the long-term period.

Keywords: atrial fibrillation, clamping, ablation, thoracoscopic surgery

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Authors: Ridha Salhi, Mondher Labidi, Fethi Choubani

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Metamaterials have attracted much attention in recent years because of their electromagnetic exquisite proprieties. We will present, in this paper, the modeling of three metamaterial structures by equivalent circuit model. We begin by modeling the SRR (Split Ring Resonator), then we model the HIS (High Impedance Surfaces), and finally, we present the model of the CPW (Coplanar Wave Guide). In order to validate models, we compare the results obtained by an equivalent circuit models with numerical simulation.

Keywords: metamaterials, SRR, HIS, CPW, IDC

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Authors: K. Veluraja

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Glycan of glycolipids and glycoproteins is playing a significant role in living systems particularly in molecular recognition processes. Molecular recognition processes are attributed to their occurrence on the surface of the cell, sequential arrangement and type of sugar molecules present in the oligosaccharide structure and glyosidic linkage diversity (glycoinformatics) and conformational diversity (glycoconformatics). Molecular Dynamics Simulation study is a theoretical-cum-computational tool successfully utilized to establish glycoconformatics of glycan. The study on various oligosaccharides of glycan clearly indicates that oligosaccharides do exist in multiple conformational states and these conformational states arise due to the flexibility associated with a glycosidic torsional angle (φ,ψ) . As an example: a single disaccharide structure NeuNacα(2-3) Gal exists in three different conformational states due to the differences in the preferential value of glycosidic torsional angles (φ,ψ). Hence establishing three dimensional structural and conformational models for glycan (cartesian coordinates of every individual atoms of an oligosaccharide structure in a preferred conformation) is quite crucial to understand various molecular recognition processes such as glycan-toxin interaction and glycan-virus interaction. The gycoconformatics models obtained for various glycan through Molecular Dynamics Simulation stored in our 3DSDSCAR (3DSDSCAR.ORG) a public domain database and its utility value in understanding the molecular recognition processes and in drug design venture will be discussed.

Keywords: glycan, glycoconformatics, molecular dynamics simulation, oligosaccharide

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Ajay Kumar Choubey, Geeta Agnihotri, C. Sasikumar, Rashmi Dwivedi

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Deep-drawing operations are performed widely in industrial applications. It is very important for efficiency to achieve parts with no or minimum defects. Deep drawn parts are used in high performance, high strength and high reliability applications where tension, stress, load and human safety are critical considerations. Wrinkling is a kind of defect caused by stresses in the flange part of the blank during metal forming operations. To avoid wrinkling appropriate blank-holder pressure/force or drawbead can be applied. Now-a-day computer simulation plays a vital role in the field of manufacturing process. So computer simulation of manufacturing has much advantage over previous conventional process i.e. mass production, good quality of product, fast working etc. In this study, a two dimensional elasto-plastic Finite Element (F.E.) model for Mild Steel material blank has been developed to study the behavior of the flange wrinkling and deep drawing parameters under different Blank-Holder Pressure (B.H.P.). For this, commercially available Finite Element software ANSYS 14 has been used in this study. Simulation results are critically studied and salient conclusions have been drawn.

Keywords: ANSYS, deep drawing, BHP, finite element simulation, wrinkling

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Authors: Fadwa Haraka, Ahmad Elouatouati, Mourad Taha Janan

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In this study, we propose a neural network based method in order to calculate the heat source temperature of isotropic plate with lower surface forced cooling. To validate the proposed model, the heat source temperatures values will be compared to the analytical method -variables separation- and finite element model. The mathematical simulation is done through 3D numerical simulation by COMSOL software considering three different materials: Aluminum, Copper, and Graphite. The proposed method will lead to a formulation of the heat source temperature based on the thermal and geometric properties of the base plate.

Keywords: thermal model, thermal resistance, finite element simulation, neural network

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Authors: Andreas Ateke Njoh, Shalom Tchokfe Ndoula, Amani Adidja, Germain Nguessan Menan, Annie Mengue, Eric Mboke, Hassan Ben Bachir, Sangwe Clovis Nchinjoh, Yauba Saidu, Laurent Cleenewerck De Kiev

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Vaccines serve a great deal in protecting the population globally. Vaccine products are subject to rigorous quality control and approval before use to ensure safety. Even if all actors take the required precautions, some people could still have adverse events following immunization (AEFI) caused by the vaccine composition or an error in its administration. AEFI underreporting is pronounced in low-income settings like Cameroon. The Country introduced electronic platforms to strengthen surveillance. With the introduction of many novel vaccines, like COVID-19 and the novel Oral Polio Vaccine (nOPV) 2, there was a need to monitor AEFI in the Country. A cross-sectional study was conducted from July to December 2022. Data on AEFI per region of Cameroon were reviewed for the past five years. Data were analyzed with MS Excel, and the results were presented in proportions. AEFI reporting was uncommon in Cameroon. With the introduction of novel vaccines in 2021, the health authorities engaged in new tools and training to capture cases. AEFI detected almost doubled using the open data kit (ODK) compared to previous platforms, especially following the introduction of the nOPV2 and COVID-19 vaccines. The AEFI rate was 1.9 and 160 per administered 100 000 doses of nOPV2 and COVID-19 vaccines, respectively. This mobile tool captured individual information for people with AEFI from all regions. The platform helped to identify common AEFI following the use of these new vaccines. The ODK mobile technology was vital in improving AEFI reporting and providing data to monitor using new vaccines in Cameroon.

Keywords: adverse events following immunization, cameroon, COVID-19 vaccines, nOPV, ODK

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Authors: David C. Ni

Abstract:

Contemporary models for N-body systems are based on temporal, two-body, and mass point representation of Newtonian mechanics. Other mainstream models include 2D and 3D Ising models based on local neighborhood the lattice structures. In Quantum mechanics, the theories of collective modes are for superconductivity and for the long-range quantum entanglement. However, these models are still mainly for the specific phenomena with a set of designated parameters. We are therefore motivated to develop a new construction directly from the complex-variable N-body systems based on the extended Blaschke functions (EBF), which represent a non-temporal and nonlinear extension of Lorentz transformation on the complex plane – the normalized momentum spaces. A point on the complex plane represents a normalized state of particle momentums observed from a reference frame in the theory of special relativity. There are only two key parameters, normalized momentum and nonlinearity for modelling. An algorithm similar to Jenkins-Traub method is adopted for solving EBF iteratively. Through iteration, the solution sets show a form of σ + i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various distributions, such as 1-peak, 2-peak, and 3-peak etc. distributions and some of them are analog to the canonical distributions. The results of the numerical analysis demonstrate continuum-to-discreteness transitions, evolutional invariance of distributions, phase transitions with conjugate symmetry, etc., which manifest the construction as a potential candidate for the unification of statistics. We hereby classify the observed distributions on the finite convergent domains. Continuous and discrete distributions both exist and are predictable for given partitions in different regions of parameter-pair. We further compare these distributions with canonical distributions and address the impacts on the existing applications.

Keywords: blaschke, lorentz transformation, complex variables, continuous, discrete, canonical, classification

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Authors: M. Dehestani, F. Kamali, M. Klantari Pour, L. Zeidabadi-Nejad

Abstract:

Chemical bonding between polyethylene glycol (PEG) with pharmaceutical proteins called pegylation is one of the most effective methods of improving the pharmacological properties. The covalent attachment of polyethylene glycol (PEG) to proteins will increase their pharmacologic properties. For the formation of a combination of pegylated protein should first be activated PEG and connected to the protein. Interferons(IFNs) are a family of cytokines which show antiviral effects in front of the biological and are responsible for setting safety system. In this study, the nature and properties of the interaction between active positions of IFNs and polyethylene glycol have been investigated using molecular dynamics simulation. The main aspect of this theoretical work focuses on the achievement of valuable data on the reaction pathways of PEG-IFNs and the transition state energy. Our results provide a new perspective on the interactions, chemical properties and reaction pathways between IFNs and PEG.

Keywords: interaction, interferons, molecular dynamics simulation, polyethylene glycol

Procedia PDF Downloads 239