Search results for: Andre Di Carlo

Authors: Hamed Afrasiab, Saeed Khodaygan

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Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.

Keywords: process capability, machining error, dimensional and geometrical tolerances, uncertainty analysis

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Authors: Catherine Vasnetsov, Victor Vasnetsov

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Context: Thermo-responsive polymers are materials that undergo significant changes in their physical properties in response to temperature changes. These polymers have gained significant attention in research due to their potential applications in various industries and medicine. However, the molecular mechanisms underlying their behavior are not well understood, particularly in relation to cosolvency, which is crucial for practical applications. Research Aim: This study aimed to theoretically investigate the phenomenon of cosolvency in long-chain polymers using the Flory-Huggins statistical-mechanical framework. The main objective was to understand the interactions between the polymer, solvent, and cosolvent under different conditions. Methodology: The research employed a combination of Monte Carlo computer simulations and advanced machine-learning methods. The Flory-Huggins mean field theory was used as the basis for the simulations. Spinodal graphs and ternary plots were utilized to develop an initial computer model for predicting polymer behavior. Molecular dynamic simulations were conducted to mimic real-life polymer systems. Machine learning techniques were incorporated to enhance the accuracy and reliability of the simulations. Findings: The simulations revealed that the addition of very low or very high volumes of cosolvent molecules resulted in smaller radii of gyration for the polymer, indicating poor miscibility. However, intermediate volume fractions of cosolvent led to higher radii of gyration, suggesting improved miscibility. These findings provide a possible microscopic explanation for the cosolvency phenomenon in polymer systems. Theoretical Importance: This research contributes to a better understanding of the behavior of thermo-responsive polymers and the role of cosolvency. The findings provide insights into the molecular mechanisms underlying cosolvency and offer specific predictions for future experimental investigations. The study also presents a more rigorous analysis of the Flory-Huggins free energy theory in the context of polymer systems. Data Collection and Analysis Procedures: The data for this study was collected through Monte Carlo computer simulations and molecular dynamic simulations. The interactions between the polymer, solvent, and cosolvent were analyzed using the Flory-Huggins mean field theory. Machine learning techniques were employed to enhance the accuracy of the simulations. The collected data was then analyzed to determine the impact of cosolvent volume fractions on the radii of gyration of the polymer. Question Addressed: The research addressed the question of how cosolvency affects the behavior of long-chain polymers. Specifically, the study aimed to investigate the interactions between the polymer, solvent, and cosolvent under different volume fractions and understand the resulting changes in the radii of gyration. Conclusion: In conclusion, this study utilized theoretical modeling and computer simulations to investigate the phenomenon of cosolvency in long-chain polymers. The findings suggest that moderate cosolvent volume fractions can lead to improved miscibility, as indicated by higher radii of gyration. These insights contribute to a better understanding of the molecular mechanisms underlying cosolvency in polymer systems and provide predictions for future experimental studies. The research also enhances the theoretical analysis of the Flory-Huggins free energy theory.

Keywords: molecular modelling, flory-huggins, cosolvency, stimuli-responsive polymers

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Authors: Amir Moslehi, Gholamreza Raisali

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Microdosimetric detectors based on multiple-thick gas electron multiplier (multiple-THGEM) configurations are being used in various fields of radiation protection and dosimetry. In the present work, microdosimetric response of these detectors to fast neutrons has been investigated by Monte Carlo method. Three similar microdosimeters made of A-150 and rexolite as the wall materials are designed; the first based on single-THGEM, the second based on double-THGEM and the third is based on triple-THGEM. Sensitive volume of the three microdosimeters is a right cylinder of 5 mm height and diameter which is filled with the propane-based tissue-equivalent (TE) gas. The TE gas with 0.11 atm pressure at the room temperature simulates 1 µm of tissue. Lineal energy distributions for several neutron energies from 10 keV to 14 MeV including 241Am-Be neutrons are calculated by the Geant4 simulation toolkit. Also, mean quality factor and dose-equivalent value for any neutron energy has been determined by these distributions. Obtained data derived from the three microdosimeters are in agreement. Therefore, we conclude that the multiple-THGEM structures present similar microdosimetric responses to fast neutrons.

Keywords: fast neutrons, geant4, multiple-thick gas electron multiplier, microdosimeter

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Authors: Imen Dhaou

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This study examines conditional Value at Risk by applying the GJR-EVT-Copula model, and finds the optimal portfolio for eight Dow Jones Islamic-conventional pairs. Our methodology consists of modeling the data by a bivariate GJR-GARCH model in which we extract the filtered residuals and then apply the Peak over threshold model (POT) to fit the residual tails in order to model marginal distributions. After that, we use pair-copula to find the optimal portfolio risk dependence structure. Finally, with Monte Carlo simulations, we estimate the Value at Risk (VaR) and the conditional Value at Risk (CVaR). The empirical results show the VaR and CVaR values for an equally weighted portfolio of Dow Jones Islamic-conventional pairs. In sum, we found that the optimal investment focuses on Islamic-conventional US Market index pairs because of high investment proportion; however, all other index pairs have low investment proportion. These results deliver some real repercussions for portfolio managers and policymakers concerning to optimal asset allocations, portfolio risk management and the diversification advantages of these markets.

Keywords: CVaR, Dow Jones Islamic index, GJR-GARCH-EVT-pair copula, portfolio optimization

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Authors: Alexander de Tomás, Miquel Sierra, Stefan Pfenninger, Francesco Lombardi, Ines Campos, Cristina Madrid

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Environmental parameters are key in the definition of sustainable energy systems yet excluded from most energy system optimization models. Still, decision-making may be misleading without considering them. Environmental analyses of the energy transition are a key part of industrial ecology but often are performed without any input from the users of the information. This work assesses the systemic impacts of energy transition pathways in Portugal. Using the Calliope energy modeling framework, 250+ optimized energy system pathways are generated. A Delphi study helps to identify the relevant criteria for the stakeholders as regards the environmental assessment, which is performed with ENBIOS, a python package that integrates life cycle assessment (LCA) with a metabolic analysis based on complex relations. Furthermore, this study focuses on how the uncertainty propagates through the model’s consortium. With the aim of doing so, a soft link between the Calliope/ENBIOS cascade and Brightway’s data capabilities is built to perform Monte Carlo simulations. These findings highlight the relevance of including uncertainty analysis as a range of values rather than informing energy transition results with a single value.

Keywords: energy transition, energy modeling, uncertainty, sustainability

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Authors: Rajesh Singh, Kailash Kale

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In this paper, the Binomial process type occurrence of software failures is considered and failure intensity has been characterized by one parameter Rayleigh class Software Reliability Growth Model (SRGM). The proposed SRGM is mathematical function of parameters namely; total number of failures i.e. η-0 and scale parameter i.e. η-1. It is assumed that very little or no information is available about both these parameters and then considering non-informative priors for both these parameters, the Bayes estimators for the parameters η-0 and η-1 have been obtained under square error loss function. The proposed Bayes estimators are compared with their corresponding maximum likelihood estimators on the basis of risk efficiencies obtained by Monte Carlo simulation technique. It is concluded that both the proposed Bayes estimators of total number of failures and scale parameter perform well for proper choice of execution time.

Keywords: binomial process, non-informative prior, maximum likelihood estimator (MLE), rayleigh class, software reliability growth model (SRGM)

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Authors: Ashwani Kumar Aggarwal

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NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

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Authors: Mardi Falck, André Theron

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Traffic congestion on the Northern side of Table Bay is a major problem. In Gauteng, the implementation of the Gautrain between Pretoria and Johannesburg, solved their traffic congestion. In 2002 two entrepreneurs endeavoured to implement a hovercraft ferry service across the bay from Table View to the Port of Cape Town. However, the EIA process proved that disgruntled residents from the area did not agree with their location for a launch site. 17 years later the traffic problem has not gone away, but instead the congestion has increased. While property prices in the City Bowl of Cape Town are ever increasing, people tend to live more on the outskirts of the CBD and commute to work. This means more vehicles on the road every day and the public transport services cannot keep up with the demand. For this reason, the study area of the previous hovercraft plans is being extended further North. The study’s aim is thus to determine the feasibility of a launch site North of Bloubergstrand to launch and receive a public transport ferry across Table Bay. The feasibility is being established by researching ferry services across the world and on what makes them successful. Different types of ferries and their operational capacities in terms of weather and waves are researched and by establishing the offshore and nearshore wind and wave climate for the area, an appropriate protected launch site is determined. It was concluded that travel time could potentially be halved. A hovercraft proved to be the most feasible ferry type, because it does not require a conventional harbour. Other types of vessels require a protected launch site because of the wave climate. This means large breakwaters that influence the cost substantially. The Melkbos Cultural Centre proved to be the most viable option for the location of the launch site, because it already has buildings and infrastructure. It is recommended that, if a harbour is chosen for the proposed ferry service, it could be used for more services like fishing, eco-tourism and leisure. Further studies are recommended to optimise the feasibility of such a harbour.

Keywords: Cape Town, ferry, public, Table Bay

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Authors: Juan F. Muñoz-Rosas, Rosa M. García-Fernández, Encarnación Álvarez-Verdejo, Pablo J. Moya-Fernández

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Poverty measurement is a very important topic in many studies in social sciences. One of the most important indicators when measuring poverty is the low income proportion. This indicator gives the proportion of people of a population classified as poor. This indicator is generally unknown, and for this reason, it is estimated by using survey data, which are obtained by official surveys carried out by many statistical agencies such as Eurostat. The main feature of the mentioned survey data is the fact that they contain several variables. The variable used to estimate the low income proportion is called as the variable of interest. The survey data may contain several additional variables, also named as the auxiliary variables, related to the variable of interest, and if this is the situation, they could be used to improve the estimation of the low income proportion. In this paper, we use Monte Carlo simulation studies to analyze numerically the performance of estimators based on several auxiliary variables. In this simulation study, we considered real data sets obtained from the 2011 European Union Survey on Income and Living Condition. Results derived from this study indicate that the estimators based on auxiliary variables are more accurate than the naive estimator.

Keywords: inclusion probability, poverty, poverty line, survey sampling

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Authors: Fariba Azizi, Firoozeh Haghighi, Viliam Makis

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In this paper, we propose a method to model the relationship between failure time and degradation for a simple step stress test where underlying degradation path is linear and different causes of failure are possible. It is assumed that the intensity function depends only on the degradation value. No assumptions are made about the distribution of the failure times. A simple step-stress test is used to shorten failure time of products and a tampered failure rate (TFR) model is proposed to describe the effect of the changing stress on the intensities. We assume that some of the products that fail during the test have a cause of failure that is only known to belong to a certain subset of all possible failures. This case is known as masking. In the presence of masking, the maximum likelihood estimates (MLEs) of the model parameters are obtained through an expectation-maximization (EM) algorithm by treating the causes of failure as missing values. The effect of incomplete information on the estimation of parameters is studied through a Monte-Carlo simulation. Finally, a real example is analyzed to illustrate the application of the proposed methods.

Keywords: cause of failure, linear degradation path, reliability function, expectation-maximization algorithm, intensity, masked data

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Authors: Ridoy Das, Myriam Neaimeh, Yue Wang, Ghanim Putrus

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Electric vehicles are a popular transportation medium renowned for potential environmental benefits. However, large and uncontrolled charging volumes can impact distribution networks negatively. Smart charging is widely recognized as an efficient solution to achieve both improved renewable energy integration and grid relief. Nevertheless, different decision-makers may pursue diverse and conflicting objectives. In this context, this paper proposes a multi-objective optimization framework to control electric vehicle charging to achieve both energy cost reduction and peak shaving. A weighted-sum method is developed due to its intuitiveness and efficiency. Monte Carlo simulations are implemented to investigate the impact of uncertain electric vehicle driving patterns and provide decision-makers with a robust outcome in terms of prospective cost and network loading. The results demonstrate that there is a conflict between energy cost efficiency and peak shaving, with the decision-makers needing to make a collaborative decision.

Keywords: electric vehicles, multi-objective optimization, uncertainty, mixed integer linear programming

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Authors: Chau-Kuang Chen, John Hughes, Jr., A. Dexter Samuels

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The prediction models for the United States Medical Licensure Examination (USMLE) Steps 1 and 2 performances were constructed by the Monte Carlo simulation modeling approach via linear regression. The purpose of this study was to build robust simulation models to accurately identify the most important predictors and yield the valid range estimations of the Steps 1 and 2 scores. The application of simulation modeling approach was deemed an effective way in predicting student performances on licensure examinations. Also, sensitivity analysis (a/k/a what-if analysis) in the simulation models was used to predict the magnitudes of Steps 1 and 2 affected by changes in the National Board of Medical Examiners (NBME) Basic Science Subject Board scores. In addition, the study results indicated that the Medical College Admission Test (MCAT) Verbal Reasoning score and Step 1 score were significant predictors of the Step 2 performance. Hence, institutions could screen qualified student applicants for interviews and document the effectiveness of basic science education program based on the simulation results.

Keywords: prediction model, sensitivity analysis, simulation method, USMLE

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Authors: Armando A. Rodríguez, Emilio Salceda, Anoland Garateix, André J. Zaharenko, Steve Peigneur, Omar López, Tirso Pons, Michael Richardson, Maylín Díaz, Yasnay Hernández, Ludger Ständker, Jan Tytgat, Enrique Soto

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Acid-sensing ion channels are cation (Na+) channels activated by a pH drop. These proteins belong to the ENaC/degenerin superfamily of sodium channels. ASICs are involved in sensory perception, synaptic plasticity, learning, memory formation, cell migration and proliferation, nociception, and neurodegenerative disorders, among other processes; therefore those molecules that specifically target these channels are of growing pharmacological and biomedical interest. Sea anemones produce a large variety of ion channels peptide toxins; however, those acting on ligand-gated ion channels, such as Glu-gated, Ach-gated ion channels, and acid-sensing ion channels (ASICs), remain barely explored. The peptide PhcrTx1 is the first compound characterized from the sea anemone Phymanthus crucifer, and it constitutes a novel ASIC inhibitor. This peptide was purified by chromatographic techniques and pharmacologically characterized on acid-sensing ion channels of mammalian neurons using patch-clamp techniques. PhcrTx1 inhibited ASIC currents with an IC50 of 100 nM. Edman degradation yielded a sequence of 32 amino acids residues, with a molecular mass of 3477 Da by MALDI-TOF. No similarity to known sea anemone peptides was found in protein databases. The computational analysis of Cys-pattern and secondary structure arrangement suggested that this is a structurally ICK (Inhibitor Cystine Knot)-type peptide, a scaffold that had not been found in sea anemones but in other venomous organisms. These results show that PhcrTx1 represents the first member of a new structural group of sea anemones toxins acting on ASICs. Also, this peptide constitutes a novel template for the development of drugs against pathologies related to ASICs function.

Keywords: animal toxin, inhibitor cystine knot, ion channel, sea anemone

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Authors: Kernou Nassim

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The current study presents a vulnerability and a reliability-mechanical approach that focuses on evaluating the seismic performance of reinforced concrete structures to determine the probability of failure. In this case, the performance function reflecting the non-linear behavior of the structure is modeled by a response surface to establish an analytical relationship between the random variables (strength of concrete and yield strength of steel) and mechanical responses of the structure (inter-floor displacement) obtained by the pushover results of finite element simulations. The push over-analysis is executed by software SAP2000. The results acquired prove that properly designed frames will perform well under seismic loads. It is a comparative study of the behavior of the existing structure before and after reinforcement using the pushover method. The coupling indirect mechanical reliability by response surface avoids prohibitive calculation times. Finally, the results of the proposed approach are compared with Monte Carlo Simulation. The comparative study shows that the structure is more reliable after the introduction of new shear walls.

Keywords: finite element method, surface response, reliability, reliability mechanical coupling, vulnerability

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Authors: Benson Ade Eniola Afere

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Over the years, kernel density estimation has been extensively studied within the context of nonparametric density estimation. The fundamental components of kernel density estimation are the kernel function and the bandwidth. While the mathematical exploration of the kernel component has been relatively limited, its selection and development remain crucial. The Mean Integrated Squared Error (MISE), serving as a measure of discrepancy, provides a robust framework for assessing the effectiveness of any kernel function. A kernel function with a lower MISE is generally considered to perform better than one with a higher MISE. Hence, the primary aim of this article is to create kernels that exhibit significantly reduced MISE when compared to existing classical kernels. Consequently, this article introduces a cluster of hybrid polynomial kernel families. The construction of these proposed kernel functions is carried out heuristically by combining two kernels from the classical polynomial kernel family using probability axioms. We delve into the analysis of error propagation within these kernels. To assess their performance, simulation experiments, and real-life datasets are employed. The obtained results demonstrate that the proposed hybrid kernels surpass their classical kernel counterparts in terms of performance.

Keywords: classical polynomial kernels, cluster of families, global error, hybrid Kernels, Kernel density estimation, Monte Carlo simulation

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Authors: A. GuhaRay, C. V. S. P. Kiranmayi, S. Rudraraju

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The present study considers the effect of variation of different geotechnical random variables in the design of stone column-foundation systems for assessing the bearing capacity and consolidation settlement of highly compressible soil. The soil and stone column properties, spacing, diameter and arrangement of stone columns are considered as the random variables. Probability of failure (P_f) is computed for a target degree of consolidation and a target safe load by Monte Carlo Simulation (MCS). The study shows that the variation in coefficient of radial consolidation (c_r) and cohesion of soil (c_s) are two most important factors influencing Pf. If the coefficient of variation (COV) of c_r exceeds 20%, P_f exceeds 0.001, which is unsafe following the guidelines of US Army Corps of Engineers. The bearing capacity also exceeds its safe value for COV of c_s > 30%. It is also observed that as the spacing between the stone column increases, the probability of reaching a target degree of consolidation decreases. Accordingly, design guidelines, considering both consolidation and bearing capacity of improved ground, are proposed for different spacing and diameter of stone columns and geotechnical random variables.

Keywords: bearing capacity, consolidation, geotechnical random variables, probability of failure, stone columns

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Authors: Carlo Gadingan

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Swardspeak, as a language, highlights the exclusive identity of the Filipino gay men and the oppression they are confronted in the society. This paper presents a morphological analysis of swardspeak in the Philippines. Specifically, it aims to find out the common morphological processes involved in the construction of codes that may unmask the nature of swardspeak as a language. 30 purposively selected expert users of swardspeak from Luzon, Visayas, and Mindanao were asked to codify 30 natural words through the Facebook Messenger application. The results of the structural analysis affirm that swardspeak follows no specific rules revealing complicated combinations of clipping/stylized clipping, borrowing, connotation through images, connotation through actions, connotation through sounds, affixation, repetition, substitution, and simple reversal. Moreover, it was also found out that most of these word formation processes occur in all word classes which indicate that swardspeak is very unpredictable. Although different codes are used for the same words, there are still codes that are really common to all homosexuals and these are Chaka (ugly), Crayola (cry), and Aida (referring to a person with AIDS). Hence, the prevailing word formation processes explored may be termed as observed time-specific patterns because the codes documented in this study may turn obsolete and may be replaced with novel ones in a matter of weeks to month, knowing the creativity of homosexuals and the multiplicity of societal resources which can be used to make the codes more opaque and more confusing for non-homosexuals.

Keywords: codes, homosexuals, morphological processes, swardspeak

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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: Jefferson Hernandez, Juan Padilla

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Estimation of price elasticity of demand is a valuable tool for the task of price settling. Given its relevance, it is an active field for microeconomic and statistical research. Price elasticity in the industry of oil and gas, in particular for fuels sold in gas stations, has shown to be a challenging topic given the market and state restrictions, and underlying correlations structures between the types of fuels sold by the same gas station. This paper explores the Lotka-Volterra model for the problem for price elasticity estimation in the context of fuels; in addition, it is introduced multivariate random effects with the purpose of dealing with errors, e.g., measurement or missing data errors. In order to model the underlying correlation structures, the Inverse-Wishart, Hierarchical Half-t and LKJ distributions are studied. Here, the Bayesian paradigm through Markov Chain Monte Carlo (MCMC) algorithms for model estimation is considered. Simulation studies covering a wide range of situations were performed in order to evaluate parameter recovery for the proposed models and algorithms. Results revealed that the proposed algorithms recovered quite well all model parameters. Also, a real data set analysis was performed in order to illustrate the proposed approach.

Keywords: price elasticity, volume, correlation structures, Bayesian models

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Authors: Hiba Dakroub, Danilo Russo, Luca Cistrone, Francesco Serra, Giovanna Fusco, Esterina De Carlo, Maria Grazia Amoroso

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The question of the origin of SARS-CoV-2 and the cycle of transmission between humans and animals is still unanswered. One serious concern associated with the SARS-CoV-2 pandemic is that the virus might spill back from humans to wildlife, which would render some animal species reservoirs of the human virus. The aim of the present study is to monitor the potential risk of SARS-CoV-2 reverse infection from humans to bats, by performing bat surveillance from different sites in Central-Southern Italy. We collected 240 droppings or saliva from 129 bats and tested them using specific and general primers of SARS-COV-2 and coronaviruses respectively. All samples, including 127 nasal swabs and 113 fecal droppings resulted negative for SARS-COV-2, and these results were confirmed by testing the samples with the Droplet Digital PCR. Also, an end-point RT-PCR was performed and no sample showed specific bands. The absence of SARS-CoV-2 in the bats we surveyed is a first step towards a better understanding of reverse transmission to bats of this virus. We hope our first contribution will encourage the establishment of systematic surveillance of wildlife, and specifically bats, to help prevent reverse zoonotic episodes that would jeopardize human health as well as biodiversity conservation and management.

Keywords: coronaviruses, bats, zoonotic viruses, spillback, SARS-CoV-2

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Authors: N. Zandi, M. Sitarz, J. Jastrzebski, M. Vagheian, J. Choinski, A. Stolarz, A. Trzcinska

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¹³⁵La with the half-life of 19.5 h can be considered as a good candidate for Auger therapy. ¹³⁵La decays almost 100% by electron capture to the stable ¹³⁵Ba. In this study, all important possible reactions leading to ¹³⁵La production are investigated in details, and the corresponding theoretical yield for each reaction using the Monte-Carlo method (MCNPX code) are presented. Among them, the best reaction based on the cost-effectiveness and production yield regarding Poland facilities equipped with medical cyclotron has been selected. ¹³⁵La is produced using 16.5 MeV proton beam of general electric PET trace cyclotron through the ¹³⁵Ba(p,n)¹³⁵La reaction. Moreover, for a consistent facilitating comparison between the theoretical calculations and the experimental measurements, the beam current and also the proton beam energy is measured experimentally. Then, the obtained proton energy is considered as the entrance energy for the theoretical calculations. The production yield finally is measured and compared with the results obtained using the MCNPX code. The results show the experimental measurement and the theoretical calculations are in good agreement.

Keywords: efficient ¹³⁵La production, proton cyclotron energy measurement, MCNPX code, theoretical and experimental production yield

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Authors: Khaled Soliman, Abdullah Alrushoud, Abdulrahman Alkhalifah, Raed Albathi, Salman Altymiat

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Radiation dose received by patients undergoing Computed Tomography (CT) examination of the cervical spine was evaluated using Gafchromic XR-QA2 films and CT-EXPO software (ver. 2.3), in order to document our clinical dose values and to compare our results with other benchmarks reported in the current literature. Radiochromic films were recently used as practical dosimetry tool that provides dose profile information not available using the standard ionisation chamber routinely used in CT dosimetry. We have developed an in-house program to use the films in order to calculate the Entrance Dose Length Product (EDLP) in (mGy.cm) and to relate the EDLP to various organ doses calculated using the CT-EXPO software. We also calculated conversion factor in (mSv/mGy.cm) relating the EDLP to the effective dose (ED) from the examination using CT-EXPO software. Variability among different types of CT scanners and dose modulation methods are reported from at least three major CT brands available at our medical institution. Our work describes the dosimetry method and results are reported. The method can be used as in-vivo dosimetry method. But this work only reports results obtained from adult female anthropomorphic Phantom studies.

Keywords: CT dosimetry, gafchromic films, XR-QA2, CT-Expo software

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Authors: Laribi-Habchi Hasiba, Bouanane-Darenfed Amel, Drouiche Nadjib, Pausse André, Mameri Nabil

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Chitin, a linear 1, 4-linked N-acetyl-d-glucosamine (GlcNAc) polysaccharide is the major structural component of fungal cell walls, insect exoskeletons and shells of crustaceans. It is one of the most abundant naturally occurring polysaccharides and has attracted tremendous attention in the fields of agriculture, pharmacology and biotechnology. Each year, a vast amount of chitin waste is released from the aquatic food industry, where crustaceans (prawn, crab, Shrimp and lobster) constitute one of the main agricultural products. This creates a serious environmental problem. This linear polymer can be hydrolyzed by bases, acids or enzymes such as chitinase. In this context an extracellular chitinase (ChiA-65) was produced and purified from a newly isolated LHH100. Pure protein was obtained after heat treatment and ammonium sulphate precipitation followed by Sephacryl S-200 chromatography. Based on matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF/MS) analysis, the purified enzyme is a monomer with a molecular mass of 65,195.13 Da. The sequence of the 27 N-terminal residues of the mature ChiA-65 showed high homology with family-18 chitinases. Optimal activity was achieved at pH 4 and 75◦C. Among the inhibitors and metals tested p-chloromercuribenzoic acid, N-ethylmaleimide, Hg2+ and Hg + completelyinhibited enzyme activity. Chitinase activity was high on colloidal chitin, glycol chitin, glycol chitosane, chitotriose and chitooligosaccharide. Chitinase activity towards synthetic substrates in the order of p-NP-(GlcNAc) n (n = 2–4) was p-NP-(GlcNAc)2> p-NP-(GlcNAc)4> p-NP-(GlcNAc)3. Our results suggest that ChiA-65 preferentially hydrolyzed the second glycosidic link from the non-reducing end of (GlcNAc) n. ChiA-65 obeyed Michaelis Menten kinetics the Km and kcat values being 0.385 mg, colloidal chitin/ml and5000 s−1, respectively. ChiA-65 exhibited remarkable biochemical properties suggesting that this enzyme is suitable for bioconversion of chitin waste.

Keywords: Bacillus licheniformis LHH100, characterization, extracellular chitinase, purification

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Authors: Yanjie Zhu, André Jesus, Irwanda Laory

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Structural Health Monitoring (SHM), involving data acquisition, data interpretation and decision-making system aim to continuously monitor the structural performance of civil infrastructures under various in-service circumstances. The main value and purpose of SHM is identifying damages through data interpretation system. Research on SHM has been expanded in the last decades and a large volume of data is recorded every day owing to the dramatic development in sensor techniques and certain progress in signal processing techniques. However, efficient and reliable data interpretation for damage detection under environmental variations is still a big challenge. Structural damages might be masked because variations in measured data can be the result of environmental variations. This research reports a novel method based on single-channel Blind Signal Separation (BSS), which extracts environmental effects from measured data directly without any prior knowledge of the structure loading and environmental conditions. Despite the successful application in audio processing and bio-medical research fields, BSS has never been used to detect damage under varying environmental conditions. This proposed method optimizes and combines Ensemble Empirical Mode Decomposition (EEMD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) together to separate structural responses due to different loading conditions respectively from a single channel input signal. The ICA is applying on dimension-reduced output of EEMD. Numerical simulation of a truss bridge, inspired from New Joban Line Arakawa Railway Bridge, is used to validate this method. All results demonstrate that the single-channel BSS-based method can recover temperature effects from mixed structural response recorded by a single sensor with a convincing accuracy. This will be the foundation of further research on direct damage detection under varying environment.

Keywords: damage detection, ensemble empirical mode decomposition (EEMD), environmental variations, independent component analysis (ICA), principal component analysis (PCA), structural health monitoring (SHM)

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Authors: Bu Seog Ju, Ho Young Son, Yong Hee Ryu

Abstract:

This study is focused on the evaluation of seismic fragility of multi-story piping system installed in critical structures, isolated with triple friction pendulum bearing. The concept of this study is to isolate the critical building structure as well as nonstructural component, especially piping system in order to mitigate the earthquake damage and achieve the reliable seismic design. Then, the building system and multi-story piping system was modeled in OpenSees. In particular, the triple friction pendulum isolator was accounted for the vertical and horizontal coupling behavior in the building system subjected to seismic ground motions. Consequently, in order to generate the seismic fragility of base-isolated multi-story piping system, 21 selected seismic ground motions were carried out, by using Monte Carlo Simulation accounted for the uncertainties in demand. Finally, the system-level fragility curves corresponding to the limit state of the piping system was conducted at each T-joint system, which was commonly failure points in piping systems during and after an earthquake. Additionally, the system-level fragilities were performed to the first floor and second floor level in critical structures.

Keywords: fragility, friction pendulum bearing, nonstructural component, seismic

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Authors: M. Manohari, Himanshu Gupta, S. Priyadharshini, R. Santhanam, S. Chandrasekaran, B. Venkatraman

Abstract:

Injection is one of the potential routes of intake in a radioactive facility. The internal dose due to this intake is monitored at the radiation emergency medical centre, IGCAR using a portable planar HPGe detector. The contaminated wound may be having different shapes. In a reprocessing potential of wound contamination with actinide is more. Efficiency is one of the input parameters for estimation of internal dose. Estimating these efficiencies experimentally would be tedious and cumbersome. Numerical estimation can be a supplement to experiment. As an initial step in this study 241Am contamination of different shapes are studied. In this study portable planar HPGe detector was modeled using Monte Carlo code FLUKA and the effect of different parameters like distance of the contamination from the detector, radius of the circular contamination were studied. Efficiency values for point and surface contamination located at different distances were estimated. The effect of efficiency on the radius of the surface source was more predominant when the source is at 1 cm distance compared to when the source to detector distance is 10 cm. At 1 cm the efficiency decreased quadratically as the radius increased and at 10 cm it decreased linearly. The point source efficiency varied exponentially with source to detector distance.

Keywords: Planar HPGe, efficiency value, injection, surface source

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Authors: Mohammed Mahmood, Walid Tizani, Carlo Sansour

Abstract:

In this paper, experimental testing and numerical analysis were used to investigate the effect of tube thickness on the face bending for concrete filled hollow sections connected to other structural members using Extended Hollobolts. Six samples were tested experimentally by applying pull-out load on the bolts. These samples were designed to fail by column face bending. The main variable in all tests is the column face thickness. Finite element analyses were also performed using ABAQUS 6.11 to extend the experimental results and to quantify the effect of column face thickness. Results show that, the column face thickness has a clear impact on the connection strength and stiffness. However, the amount of improvement in the connection stiffness by changing the column face thickness from 5 mm to 6.3 mm seems to be higher than that when increasing it from 6.3 mm to 8 mm. The displacement at which the bolts start pulling-out from their holes increased with the use of thinner column face due to the high flexibility of the section. At the ultimate strength, the yielding of the column face propagated to the column corner and there was no yielding in its walls. After the ultimate resistance is reached, the propagation of the yielding was mainly in the column face with a miner yielding in the walls.

Keywords: anchored bolted connection, Extended Hollobolt, column faces bending, concrete filled hollow sections

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Authors: Victoria Siriaki Jorry, I. S. Mbalawata, Hayong Shin

Abstract:

The main objective in a change detection problem is to develop algorithms for efficient detection of gradual and/or abrupt changes in the parameter distribution of a process or time series data. In this paper, we present a modified cumulative (MCUSUM) algorithm to detect the start and end of a time-varying linear drift in mean value of a time series data based on likelihood ratio test procedure. The design, implementation and performance of the proposed algorithm for a linear drift detection is evaluated and compared to the existing CUSUM algorithm using different performance measures. An approach to accurately approximate the threshold of the MCUSUM is also provided. Performance of the MCUSUM for gradual change-point detection is compared to that of standard cumulative sum (CUSUM) control chart designed for abrupt shift detection using Monte Carlo Simulations. In terms of the expected time for detection, the MCUSUM procedure is found to have a better performance than a standard CUSUM chart for detection of the gradual change in mean. The algorithm is then applied and tested to a randomly generated time series data with a gradual linear trend in mean to demonstrate its usefulness.

Keywords: average run length, CUSUM control chart, gradual change detection, likelihood ratio test

Procedia PDF Downloads 278

Authors: F. Murilo T. Luna, Vanessa F. Oliveira, Alysson Rocha, Expedito J. S. Parente, Andre V. Bueno, Matheus C. M. Farias, Celio L. Cavalcante Jr.

Abstract:

Aviation jetfuel used in aircraft gas-turbine engines is customarily obtained from the kerosene distillation fraction of petroleum (150-275°C). Mineral jetfuel consists of a hydrocarbon mixture containing paraffins, naphthenes and aromatics, with low olefins content. In order to ensure their safety, several stringent requirements must be met by jetfuels, such as: high energy density, low risk of explosion, physicochemical stability and low pour point. In this context, aviation fuels eventually obtained from biofeedstocks (which have been coined as ‘biojetfuel’), must be used as ‘drop in’, since adaptations in aircraft engines are not desirable, to avoid problems with their operation reliability. Thus, potential aviation biofuels must present the same composition and physicochemical properties of conventional jetfuel. Among the potential feedtstocks for aviation biofuel, the babaçu oil, extracted from a palm tree extensively found in some regions of Brazil, contains expressive quantities of short chain saturated fatty acids and may be an interesting choice for biojetfuel production. In this study, biojetfuel was synthesized through homogeneous transesterification of babaçu oil using methanol and its properties were compared with petroleum-based jetfuel through measurements of oxidative stability, physicochemical properties and low temperature properties. The transesterification reactions were carried out using methanol and after decantation/wash procedures, the methyl esters were purified by molecular distillation under high vacuum at different temperatures. The results indicate significant improvement in oxidative stability and pour point of the products when compared to the fresh oil. After optimization of operational conditions, potential biojetfuel samples were obtained, consisting mainly of C8 esters, showing low pour point and high oxidative stability. Jet engine tests are being conducted in an automated test bed equipped with pollutant emissions analysers to study the operational performance of the biojetfuel that was obtained and compare with a mineral commercial jetfuel.

Keywords: biojetfuel, babaçu oil, oxidative stability, engine tests

Procedia PDF Downloads 247

Authors: Kyra Kannen, Sonja D. Roelen, Sebastian Schnieder, Jarek Krajewski, Steffen Holsteg, André Karger, Johanna Askeridis, Celina Slawik, Philip Mildner, Jens Piesk, Ruslan David, Holger Kürten, Benjamin Oster, Robert Malzan, Mike Ludemann

Abstract:

Virtual Reality (VR) is increasingly recognized for its potential in transforming mental disorder treatment, offering advantages such as cost-effectiveness, time efficiency, accessibility, reduced stigma, and scalability. While the application of VR in the context of anxiety disorders has been extensively evaluated and demonstrated to be effective, the utilization of VR as a therapeutic treatment for depression remains under-investigated. Our goal is to pioneer immersive VR therapy modules for treating major depression, alongside a web-based system for home use. We develop a modular digital therapy platform grounded in psychodynamic therapy interventions which addresses stress reduction, exploration of social situations and relationship support, social skill training, avoidance behavior analysis, and psychoeducation. In addition, an automated depression monitoring system, based on acoustic voice analysis, is implemented in the form of a speech-based diary to track the affective state of the user and depression severity. The use of immersive VR facilitates patient immersion into complex and realistic interpersonal interactions with high emotional engagement, which may contribute to positive treatment acceptance and satisfaction. In a proof-of-concept study, 45 depressed patients were assigned to VR or web-platform modules, evaluating user experience, usability and additional metrics including depression severity, mindfulness, interpersonal problems, and treatment satisfaction. The findings provide valuable insights into the effectiveness and user-friendliness of VR and web modules for depression therapy and contribute to the refinement of more tailored digital interventions to improve mental health.

Keywords: virtual reality therapy, digital health, depression, psychotherapy

Procedia PDF Downloads 48