Search results for: structural equation modeling semiparametric

Authors: Randa Alharbi, Vladislav Vyshemirsky

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Systems biology is an important field in science which focuses on studying behaviour of biological systems. Modelling is required to produce detailed description of the elements of a biological system, their function, and their interactions. A well-designed model requires selecting a suitable mechanism which can capture the main features of the system, define the essential components of the system and represent an appropriate law that can define the interactions between its components. Complex biological systems exhibit stochastic behaviour. Thus, using probabilistic models are suitable to describe and analyse biological systems. Continuous-Time Markov Chain (CTMC) is one of the probabilistic models that describe the system as a set of discrete states with continuous time transitions between them. The system is then characterised by a set of probability distributions that describe the transition from one state to another at a given time. The evolution of these probabilities through time can be obtained by chemical master equation which is analytically intractable but it can be simulated. Uncertain parameters of such a model can be inferred using methods of Bayesian inference. Yet, inference in such a complex system is challenging as it requires the evaluation of the likelihood which is intractable in most cases. There are different statistical methods that allow simulating from the model despite intractability of the likelihood. Approximate Bayesian computation is a common approach for tackling inference which relies on simulation of the model to approximate the intractable likelihood. Particle Markov chain Monte Carlo (PMCMC) is another approach which is based on using sequential Monte Carlo to estimate intractable likelihood. However, both methods are computationally expensive. In this paper we discuss the efficiency and possible practical issues for each method, taking into account the computational time for these methods. We demonstrate likelihood-free inference by performing analysing a model of the Repressilator using both methods. Detailed investigation is performed to quantify the difference between these methods in terms of efficiency and computational cost.

Keywords: Approximate Bayesian computation(ABC), Continuous-Time Markov Chains, Sequential Monte Carlo, Particle Markov chain Monte Carlo (PMCMC)

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Authors: Tytus Tulwin, Adam Majczak

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In aviation most important systems that impact the aircraft flight safety are duplicated. The ASz-62IR aircraft radial engine consists of two spark plugs powered by two separate magnetos. The relative difference in spark timing has an influence on the combustion process. The retardation of the second spark relative to the first spark was analyzed. The CFD simulation was developed as a multicycle transient model. Two independent spark sources imitate two flame fronts after an ignition period. It makes the combustion process shorter but only for certain range of second spark retardation. The model was validated by the in-cylinder pressure comparison. Combustion parameters were analyzed for different second spark retardation values. It was found that the most advantageous ignition timing in means of performance is simultaneous ignition. Nevertheless, for this engine the ignition time of the second spark plug is greatly retarded eliminating the advantageous performance influence. The reason behind this is maintaining high ignition certainty for all engine running conditions and for whole operating rpm range. In aviation the engine reliability is more important than its performance. Introducing electronic ignition system can yield from simultaneous ignition timing by increasing the engine performance and providing good reliability for all flight conditions. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: CFD, combustion, ignition, simulation, timing

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Authors: Martial Pouzet, Marc Dubois, Karine Charlet, Alexis Béakou

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The availability, the ecologic and economic characteristics of wood are advantages which explain the very wide scope of applications of this material, in several domains such as paper industry, furniture, carpentry and building. However, wood is a hygroscopic material highly sensitive to ambient humidity and temperature. The swelling and the shrinking caused by water absorption and desorption cycles lead to crack and deformation in the wood volume, making it incompatible for such applications. In this study, dynamic fluorination using F2 gas was applied to wood samples (douglas and silver fir species) to decrease their hydrophilic character. The covalent grafting of fluorine atoms onto wood surface through a conversion of C-OH group into C-F was validated by Fourier-Transform infrared spectroscopy and 19F solid state Nuclear Magnetic Resonance. It revealed that the wood, which is initially hydrophilic, acquired a hydrophobic character comparable to that of the Teflon, thanks to fluorination. A good durability of this treatment was also determined by aging tests under ambient atmosphere and under UV irradiation. Moreover, this treatment allowed obtaining hydrophobic character without major structural (morphology, density and colour) or mechanical changes. The maintaining of these properties after fluorination, which requires neither toxic solvent nor heating, appears as a remarkable advantage over other more traditional physical and chemical wood treatments.

Keywords: cellulose, spectroscopy, surface treatment, water absorption

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Authors: Alparslan A. Balta, Hilmi Yurdakul, Orkun Tunckan, Servet Turan, Arife Yurdakul

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A silicon oxynitride (Si2N2O), the mineralogical name is “Sinoite”, reveals the outstanding physical, mechanical and thermal properties, e.g., good oxidation resistance at high temperatures, high fracture toughness with rod shape, high hardness, low theoretical density, good thermal shock resistance by low thermal expansion coefficient and high thermal conductivity. In addition, the orthorhombic crystal structure of Si2N2O allows accommodating the rare earth (RE) element atoms along the “c” axis due to existing large structural interstitial sites. Here, 0.02 to 0.12 wt. % Nd3+ doped Si2N2O samples were successfully synthesized by spark plasma sintering (SPS) method at 30MPa pressure and 1650oC temperature. Li2O was also utilized as a sintering additive to take advantage of low eutectic point during synthesizing. The specimens were characterized in detail by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and cathodoluminescence (CL) in SEM and photoluminescence (PL) spectroscopy. Based on the overall results, the Si2N2O phase was obtained above 90% by the SPS route. Furthermore, Nd3+: Si2N2O samples showed a very broad intense emission peak between 400-700 nm, which corresponds to white color. Therefore, this material can be considered as a promising candidate for white light-emitting diodes (WLEDs) purposes. This study was supported by TUBITAK under project number 217M667.

Keywords: neodymium, oxynitride, Si₂N₂O, WLEDs

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Authors: Selvan Bellan, Koji Matsubara, Nobuyuki Gokon, Tatsuya Kodama, Hyun Seok-Cho

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In concentrated solar thermal industry, fluidized-bed technology has been used to produce hydrogen by thermochemical two step water splitting cycles, and synthetic gas by gasification of coal coke. Recently, couple of fluidized bed reactors have been developed and tested at Niigata University, Japan, for two-step thermochemical water splitting cycles and coal coke gasification using Xe light, solar simulator. The hydrodynamic behavior of the gas-solid flow plays a vital role in the aforementioned fluidized bed reactors. Thus, in order to study the dynamics of dense gas-solid flow, a CFD-DEM model has been developed; in which the contact forces between the particles have been calculated by the spring-dashpot model, based on the soft-sphere method. Heat transfer and hydrodynamics of a solar thermochemical fluidized bed reactor filled with ceria particles have been studied numerically and experimentally for beam-down solar concentrating system. An experimental visualization of particles circulation pattern and mixing of two-tower fluidized bed system has been presented. Simulation results have been compared with experimental data to validate the CFD-DEM model. Results indicate that the model can predict the particle-fluid flow of the two-tower fluidized bed reactor. Using this model, the key operating parameters can be optimized.

Keywords: solar reactor, CFD-DEM modeling, fluidized bed, beam-down solar concentrating system

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Authors: Masato Saeki

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Presented herein is a novel algorithms for calculating the damping performance of particle dampers. The particle damper is a passive vibration control technique and has many practical applications due to simple design. It consists of granular materials constrained to move between two ends in the cavity of a primary vibrating system. The damping effect results from the exchange of momentum during the impact of granular materials against the wall of the cavity. This damping has the advantage of being independent of the environment. Therefore, particle damping can be applied in extreme temperature environments, where most conventional dampers would fail. It was shown experimentally in many papers that the efficiency of the particle dampers is high in the case of resonant vibration. In order to use the particle dampers effectively, it is necessary to solve the equations of motion for each particle, considering the granularity. The discrete element method (DEM) has been found to be effective for revealing the dynamics of particle damping. In this method, individual particles are assumed as rigid body and interparticle collisions are modeled by mechanical elements as springs and dashpots. However, the computational cost is significant since the equation of motion for each particle must be solved at each time step. In order to improve the computational efficiency of the DEM, the new algorithms are needed. In this study, new algorithms are proposed for implementing the high performance DEM. On the assumption that behaviors of the granular particles in the each divided area of the damper container are the same, the contact force of the primary system with all particles can be considered to be equal to the product of the divided number of the damper area and the contact force of the primary system with granular materials per divided area. This convenience makes it possible to considerably reduce the calculation time. The validity of this calculation method was investigated and the calculated results were compared with the experimental ones. This paper also presents the results of experimental studies of the performance of particle dampers. It is shown that the particle radius affect the noise level. It is also shown that the particle size and the particle material influence the damper performance.

Keywords: particle damping, discrete element method (DEM), granular materials, numerical analysis, equivalent noise level

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Authors: Debashree Ghosh, Preethi Sridhar, Shloka Atul Dhavle

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The judicious and economic consumption of energy for sustainable growth and development is nowadays a thing of primary importance; Phase Change Materials (PCM) provide an ingenious option of storing energy in the form of Latent Heat. Energy storing mechanism incorporating phase change material increases the efficiency of the process by minimizing the difference between supply and demand; PCM heat exchangers are used to storing the heat or non-convectional energy within the PCM as the heat of fusion. The experimental study evaluates the effect of thermo-physical properties, variation in inlet temperature, and flow rate on charging period of a coiled heat exchanger. Secondly, a numerical study is performed on a PCM double pipe heat exchanger packed with two different PCMs, namely, RT50 and Fatty Acid, in the annular region. In this work, the simulation of charging of paraffin wax (RT50) using water as high-temperature fluid (HTF) is performed. Commercial software Ansys-Fluent 15 is used for simulation, and hence charging of PCM is studied. In the Enthalpy-porosity model, a single momentum equation is applicable to describe the motion of both solid and liquid phases. The details of the progress of phase change with time are presented through the contours of melt-fraction, temperature. The velocity contour is shown to describe the motion of the liquid phase. The experimental study revealed that paraffin wax melts with almost the same temperature variation at the two Intermediate positions. Fatty acid, on the other hand, melts faster owing to greater thermal conductivity and low melting temperature. It was also observed that an increase in flow rate leads to a reduction in the charging period. The numerical study also supports some of the observations found in the experimental study like the significant dependence of driving force on the process of melting. The numerical study also clarifies the melting pattern of the PCM, which cannot be observed in the experimental study.

Keywords: latent heat storage, charging period, discharging period, coiled heat exchanger

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Authors: Nyussupova Gulnara, Kenespayeva Laura, Kelinbayeva Roza, Aubakirova Gaukhar, Zhumagulov Chingiz, Aidarkhanova Gaukhar

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The article analyzes the development of demographic processes in four regions of the Western region of the Republic of Kazakhstan (Aktobe, Atyrau, West Kazakhstan, and Mangystau) for the period from 2000 to 2022. This study uses theoretical and methodological analysis of scientific literature, methods of comparative, statistical analysis, GIS methods, grouping and systematization, index method and structural analysis. The research identified regional characteristics, development trends, and disproportions in the population of the studied areas within the framework of sustainable demographic development. The population dynamics, the age-sex structure of the population, life expectancy, natural movement of the population, including maternal and infant mortality, are considered as important indicators of the region’s sustainability. The features of migration processes in the Western region of Kazakhstan and the factors that determine them are identified. Conclusions are drawn about the level of sustainable development of the population of the studied region based on demographic processes. The results obtained will provide scientific, methodological and information support in the sectors of economics and science, including the preparation of socio-economic development programs and the development of scientific research using GIS.

Keywords: sustainable development, demographic processes, Western Region, Republic of Kazakhstan, population structure, natural population movement, migration

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Authors: Sara Mercedes Barroso Pinzón, Álvaro Jesús Caicedo Castro, Antonio Javer Sánchez Herencia

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In recent years there has been increased academic and industrial research into the development of orthopaedic implants with structural properties and functionality similar to mechanical strength, osseointegration, thermal stability and antibacterial capacity similar to bone structure. Hydroxyapatite has been considered for decades as an ideal biomaterial for bone regeneration due to its chemical and crystallographic similarity to the mineral structure bioapatites. However, the lack of trace elements in the hydroxyapatite structure confers very low mechanical and biological properties. Under this scenario, the objective of the research is the synthesis of hydroxyapatite with Mg from the francolite mineral present in phosphate rock from the central-eastern region of Colombia, taking advantage of the extraction of mineral species as natural precursors of Ca, P and Mg. The minerals present were studied, fluorapatite as the mineral of interest associated with magnesium carbonates and quartz. The chemical and mineralogical composition was determined by X-ray fluorescence (XRF) and X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX); the optimum conditions were established using the acid leaching mechanism in the wet concentration process. From the products obtained and characterised by XRD, XRF, SEM, FTIR, RAMAN, HAp-Mg biocomposite scaffolds are fabricated and the influence of Mg on morphometric parameters, mechanical and biological properties in the formed materials is evaluated.

Keywords: phosphate rock, hydroxyapatite, magnesium, biomaterials

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Authors: Saeed Javaherzadeh, Babak Dindar Safa

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Structure, given its ductility, can depreciate significant amount of seismic energy in the form of hysteresis behavior; the amount of energy depreciation depends on the structure ductility rate. So in seismic guidelines such as ASCE7-10 code, to reduce the number of design forces and using the seismic energy dissipation capacity of structure, when entering non-linear behavior range of the materials, the response modification factor is used. Various parameters such as ductility modification factor, overstrength factor and reliability factor, are effective in determining the value of this factor. Also, gradually, energy dissipation systems, especially added dampers, have become an inseparable part of the seismic design. In this paper, in addition to reviewing of previous studies, using the response modification factor caused by using more added viscoelastic dampers, a new design method has introduced for steel moment-frame with added dampers installed. To do this, in addition to using bilinear behavior models and quick ways such as using the equivalent lateral force method and capacity spectrum method for the proposed design methodology, the results has been controlled with non-linear time history analysis for a number of structural. The analysis is done by Opensees Software.

Keywords: added viscoelastic damper, design base shear, response modification factor, non-linear time history

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Authors: Levan Sabauri

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In this paper, we discuss the deteriorated standing of engineering companies, some of the reasons behind it and the problems facing engineering enterprises during the financial crisis. We show the part that financial analysis plays in the detection of the main factors affecting the standing of a company, classify internal problems and the reasons influencing efficiency thereof. The publication contains the analysis of municipal engineering companies in post-Soviet transitional economies. In the wake of the 2008 world financial crisis the issue became even more poignant. It should be said though that even before the problem had been no less acute for some post-Soviet states caught up in a lengthy transitional period. The paper highlights shortcomings in the management of transportation companies, with new, more appropriate methods suggested. In analyzing the financial stability of a company, three elements need to be considered: current assets, investment policy and structural management of the funding sources leveraging the stability, should be focused on. Inappropriate management of the three may create certain financial problems, with timely and accurate detection thereof being an issue in terms of improved standing of an enterprise. In this connection, the publication contains a diagram reflecting the reasons behind the deteriorated financial standing of a company, as well as a flow chart thereof. The main reasons behind low profitability are also discussed.

Keywords: efficiency, financial management, financial analysis funding structure, financial sustainability, investment policy, profitability, solvency, working capital

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Authors: Wardatutthoyyibah, Satyawan Pudyatmoko, Sena Adi Subrata, Muhammad Ali Imron

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The proboscis monkey is an endemic species to the island of Borneo with conservation status IUCN (The International Union for Conservation of Nature) of endangered. The population of the monkey has a specific habitat and sensitive to habitat disturbances. As a consequence of increasing rates of land-use change in the last four decades, its population was reported significantly decreased. We quantified the effect of land use change on the proboscis monkey’s habitat through the species distribution modeling (SDM) approach with Maxent Software. We collected presence data and environmental variables, i.e., land cover, topography, bioclimate, distance to the river, distance to the road, and distance to the anthropogenic disturbance to generate predictive distribution maps of the monkeys. We compared two prediction maps for 2000 and 2015 data to represent the current habitat of the monkey. We overlaid the monkey’s predictive distribution map with the existing protected areas to investigate whether the habitat of the monkey is protected under the protected areas networks. The results showed that almost 50% of the monkey’s habitat reduced as the effect of land use change. And only 9% of the current proboscis monkey’s habitat within protected areas. These results are important for the master plan of conservation of the endangered proboscis monkey and provide scientific guidance for the future development incorporating biodiversity issue.

Keywords: endemic species, land use change, maximum entropy, spatial distribution

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Authors: M. Arunachalam, M. Pandey

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Nacre, a biological material that forms the inner-layer of sea shells can achieve high toughness and strength by way of staggered arrangement of strong tablets with soft and weak organic interface. Under applied loads the tablets slide over the adjacent tablets, thus generating inelastic deformation and toughness on macroscopic scale. A two dimensional finite element based homogenization methodology is adopted for obtaining the effective material properties of Nacre using a representative volume element (RVE) at finite deformations. In this work, the material behaviour for tablet and interface are assumed to be Isotropic elastic and Isotropic elastic-perfectly plastic with strain softening respectively. Numerical experiments such as uniaxial tension test along X, Y directions and simple shear test are performed on the RVE with uniform displacement and periodic constraints applied at the RVE boundaries to obtain the anisotropic homogenized response and maximum local stresses within each constituents of Nacre. Homogenized material model is then tested for macroscopic structure under three point bending condition and the results obtained are comparable with the results obtained for detailed microstructure based structure, thus homogenization provides a bridge between macroscopic scale and microscopic scale and homogenized material properties obtained from microstructural (RVE) analysis could be used in large scale structural analysis.

Keywords: finite element, homogenization, inelastic deformation, staggered arrangement

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Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

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Authors: Muqdad Al-Juboori, Bithin Datta

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Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis

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Authors: Asmae Tafraouti, Yasmina Layouni, Pascal Kleimann

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The growing market for Microsystems (MST) and Micro-Electromechanical Systems (MEMS) is driving the research for alternative manufacturing techniques to microelectronics-based technologies, which are generally expensive and time-consuming. Hot-embossing and micro-injection modeling of thermoplastics appear to be industrially viable processes. However, both require the use of master models, usually made in hard materials such as steel. These master models cannot be fabricated using standard microelectronics processes. Thus, other micromachining processes are used, as laser machining or micro-electrical discharge machining (µEDM). In this work, µEDM has been used. The principle of µEDM is based on the use of a thin cylindrical micro-tool that erodes the workpiece surface. The two electrodes are immersed in a dielectric with a distance of a few micrometers (gap). When an electrical voltage is applied between the two electrodes, electrical discharges are generated, which cause material machining. In order to produce master models with high resolution and smooth surfaces, it is necessary to well control the discharge mechanism. However, several problems are encountered, such as a random electrical discharge process, the fluctuation of the discharge energy, the electrodes' polarity inversion, and the wear of the micro-tool. The effect of different parameters, such as the applied voltage, the working capacitor, the micro-tool diameter, the initial gap, has been studied. This analysis helps to improve the machining performances, such: the workpiece surface condition and the lateral crater's gap.

Keywords: craters, electrical discharges, micro-electrical discharge machining (µEDM), microsystems

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Authors: Tawfiq Chekifi, Brahim Dennai, Rachid Khelfaoui

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Over the last few decades, modeling immiscible fluids such as oil and water have been a classical research topic. Droplet-based microfluidics presents a unique platform for mixing, reaction, separation, dispersion of drops, and numerous other functions. For this purpose, several devices were studied, as well as microfluidic oscillator. The latter was obtained from wall attachment microfluidic amplifiers using a feedback loop from the outputs to the control inputs, nevertheless this device have not well used for microdrops applications. In this paper, we suggest a numerical CFD study of a microfluidic oscillator with two different lengths of feedback loop. In order to produce simultaneous microdrops of gasoil on water, a typical geometry that includes double T-junction is connected to the fluidic oscillator. The generation of microdrops is computed by volume-of-fluid method (VOF). Flow oscillations of microdrops were triggered by the Coanda effect of jet flow. The aim of work is to obtain a high oscillation frequency in output of this passive device, the influence of hydrodynamics and physics parameters on the microdrops frequency in the output of our microsystem is also analyzed, The computational results show that, the length of feedback loop, applied pressure on T-junction and interfacial tension have a significant effect on the dispersion of microdrops and its oscillation frequency. Across the range of low Reynold number, the microdrops generation and its dynamics have been accurately controlled by adjusting applying pressure ratio of two phases.

Keywords: fluidic oscillator, microdrops manipulation, VOF (volume of fluid method), microfluidic oscillator

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Authors: Peter K. Galenko, Stefanie Koch, Markus Rettenmayr, Robert Wonneberger, Evgeny V. Kharanzhevskiy, Maria Zamoryanskaya, Vladimir Ankudinov

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We analyze the structure of undercooled melts, crystal growth kinetics and amorphous/crystalline microstructure of rapidly solidifying glass-forming Pd-based and CuZr-based alloys. A dendrite growth model is developed using a combination of the kinetic phase-field model and mesoscopic sharp interface model. The model predicts features of crystallization kinetics in alloys from thermodynamically controlled growth (governed by the Gibbs free energy change on solidification) to the kinetically limited regime (governed by atomic attachment-detachment processes at the solid/liquid interface). Comparing critical undercoolings observed in the crystallization kinetics with experimental data on melt viscosity, atomistic simulation's data on liquid microstructure and theoretically predicted dendrite growth velocity allows us to conclude that the dendrite growth kinetics strongly depends on the cluster structure changes of the melt. The obtained data of theoretical and experimental investigations are used for interpretation of microstructure of samples processed in electro-magnetic levitator on board International Space Station in the frame of the project "MULTIPHAS" (European Space Agency and German Aerospace Center, 50WM1941) and "KINETIKA" (ROSKOSMOS).

Keywords: dendrite, kinetics, model, solidification

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Authors: Ruangdech Sirikit

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The purposes of this research were to study the variables affecting the quality assessment of mathematics subject in Thailand by using value-added analysis on TIMSS 2011. The data used in this research is the secondary data from the 2011 Trends in International Mathematics and Science Study (TIMSS), collected from 6,124 students in 172 schools from Thailand, studying only mathematics subjects. The data were based on 14 assessment tests of knowledge in mathematics. There were 3 steps of data analysis: 1) To analyze descriptive statistics 2) To estimate competency of students from the assessment of their mathematics proficiency by using MULTILOG program; 3) analyze value added in the model of quality assessment using Value-Added Model with Hierarchical Linear Modeling (HLM) and 2 levels of analysis. The research results were as follows: 1. Student level variables that had significant effects on the competency of students at .01 levels were Parental care, Resources at home, Enjoyment of learning mathematics and Extrinsic motivation in learning mathematics. Variable that had significant effects on the competency of students at .05 levels were Education of parents and self-confident in learning mathematics. 2. School level variable that had significant effects on competency of students at .01 levels was Extra large school. Variable that had significant effects on competency of students at .05 levels was medium school.

Keywords: quality assessment, value-added model, TIMSS, mathematics, Thailand

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Authors: Kimberly McCabe

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The trafficking of women and children for abuse and exploitation is not a new problem under the umbrella of human trafficking; however, over the last decade, the problem has attracted increased attention from international governments and non-profits attempting to reduce victimization and provide services for survivors. Research on human trafficking suggests that the trafficking of human beings is, largely, a symptom of poverty. As the trafficking of human beings may be viewed as a response to the demand for people for various forms of exploitation, a product of poverty, and a consequence of the subordinate positions of women and children in society, it reaches beyond randomized victimization. Hence, human trafficking, and especially the trafficking of women and children, goes beyond the realm of poorness. Therefore, to begin to understand the reasons for the existence of human trafficking, one must identify and consider not only the immediate causes but also those underlying structural determinants that facilitate this form of victimization. Specifically, one must acknowledge the economic, social, and cultural factors that support human trafficking. This research attempts to study human trafficking at the country level by focusing on economic, social, and cultural characteristics. This study focuses on inequality and, in particular, gender inequality as related to legislative attempts to address human trafficking. Within the design of this project is the use of the US State Department’s tier classification system for Trafficking in Persons (TIP) and the USA CIA Fact Sheet of country characteristics for over 150 countries in an attempt to model legal outcomes as related to human trafficking. Results of this research demonstrate the significance of characteristics beyond poverty as related to country-level responses to human trafficking.

Keywords: child trafficking, gender inequality, human trafficking, inequality

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Authors: Yurdum Cokadar

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The United States is the country where the majority of highly skilled immigrants are hosted. Two-thirds of foreign-born migrants from Turkey - an underrepresented and understudied immigrant group in the United States - are highly skilled. Generated by the aim of filling this gap in the literature, the motivation of this research is to understand highly skilled Turkish immigrant women’s integration into the U.S. labor market, including barriers that they face and strategies they develop to rebuild their career after relocation. The in-depth interviews of 20 highly skilled Turkish women residing in the U.S. revealed that the majority of women participants are either not integrated into the labor market, occupy positions below their skill, or cannot reach the same upper segments of the labor market in the host country, arising from a range of structural and personal barriers interplaying in their career trajectories. Furthermore, many of them cannot transfer their social and cultural capital gained in their home country into the United States. The labor market participation process of these women is analyzed in the light of Bourdieu’s theory of capital and the intersectional approach of gender, class and ethnicity in order to understand the positions of highly skilled immigrant women in the host country labor market.

Keywords: deskilling, gender, class and ethnicity, highly skilled women immigrants, integration into the U.S. the labor market, labor market participation, skilled migration, theory of capital

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Authors: S. Palaniyappan, P. K. Chennam, M. Trautmann, H. Ahmad, T. Mehner, T. Lampke, G. Wagner

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In structural-health monitoring of fiber reinforced plastics (FRPs), every single inorganic fiber sensor that are integrated into the bulk material requires an electrical insulation around itself, when the surrounding reinforcing fibers are electrically conductive. This results in a more accurate data acquisition only from the sensor fiber without any electrical interventions. For this purpose, thin nano-films of aluminium oxide (Al₂O₃)-based electrical-insulation coatings have been fabricated around the Silicon Carbide (SiC) single fiber sensors through reactive DC magnetron sputtering technique. The sputtered coatings were amorphous in nature and the thickness of the coatings increased with an increase in the sputter time. Microstructural characterization of the coated fibers performed using scanning electron microscopy (SEM) confirmed a homogeneous circumferential coating with no detectable defects or cracks on the surface. X-ray diffraction (XRD) analyses of the as-sputtered and 2 hours annealed coatings (825 & 1125 ˚C) revealed the amorphous and crystalline phases of Al₂O₃ respectively. Raman spectroscopic analyses produced no characteristic bands of Al₂O₃, as the thickness of the films was in the nanometer (nm) range, which is too small to overcome the actual penetration depth of the laser used. In addition, the influence of the insulation coatings on the mechanical properties of the SiC sensor fibers has been analyzed.

Keywords: Al₂O₃ thin film, electrical insulation coating, PVD process, SiC fibre, single fibre tensile test

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Authors: Khurram Munir, Cuie Wen, Yuncang Li

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Magnesium (Mg) metal matrix composites (MMCs) reinforced with graphene nanoplatelets (GNPs) have been developed by powder metallurgy (PM). In this study, GNPs with different concentrations (0.1-0.3 wt.%) were dispersed into Mg powders by high-energy ball-milling processes. The microstructure and resultant mechanical properties of the fabricated nanocomposites were characterized using transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), Raman spectroscopy (RS), compression and nano-wear tests. The corrosion resistance of the fabricated composites was evaluated by electrochemical tests and hydrogen evolution measurements. Finally, the biological response of Mg-GNPs composites was assessed using osteoblast-like SaOS2 cells. The results indicate that GNPs are excellent candidates as reinforcements in Mg matrices for the manufacture of biodegradable Mg-based composite implants. GNP addition improved the mechanical properties of Mg via synergetic strengthening modes. Moreover, retaining the structural integrity of GNPs during PM processing improved the ductility, compressive strength, and corrosion resistance of the Mg-GNP composites as compared to monolithic Mg. Cytotoxicity assessments did not reveal any significant toxicity with the addition of GNPs to Mg matrices. This study demonstrates that Mg-xGNPs with x < 0.3 wt.%, may constitute novel biodegradable implant materials for load-bearing applications.

Keywords: magnesium-graphene composites, strengthening mechanisms, In vitro cytotoxicity, biocorrosion

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Authors: Mohieldin Elmashad, Salwa Yassin

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Expansive soils regarded as one of the most problematic unsaturated formations in the Egyptian arid zones and present a great challenge in civil engineering, in general, and geotechnical engineering, in particular. Severe geotechnical complications and consequent structural damages have been arising due to an excessive and differential volumetric change upon wetting and change in water content. Different studies have been carried out concerning the swelling performance of the expansive soils using different additives including phospho-gypsum as an industrial waste product. However, this paper describes the results of a comprehensive testing programme that was carried out to investigate the effect of phospho-gypsum (PG) and sodium chloride (NaCl), as an additive mixture, on the swelling performance of constituent samples of swelling soils. The constituent samples comprise commercial bentonite collected from a natural site, mixed with different percentages of PG-NaCl mixture. The testing programme had been scoped to cover the physical and chemical properties of the constituent samples. In addition, a mineralogical study using x-ray diffraction (XRD) was performed on the collected bentonite and the mixed bentonite with PG-NaCl mixture samples. The obtained results of this study showed significant improvement in the swelling performance of the tested samples with the increase of the proposed PG-NaCl mixture content.

Keywords: expansive soils, industrial waste, mineralogical study, swelling performance, X-ray diffraction

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Authors: Delaram Ghodsi, Nasrin Omidvar, Hassan Eini-Zinab, Arash Rashidian, Hossein Raghfar

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Food supplementary programs are policy approaches that aim to reduce financial barriers to healthy diets and tackle food insecurity. This study aimed to evaluate the effect of the supportive section of Multidisciplinary Supplementary Program for Improvement of Nutritional Status of Children (MuPINSC) on households’ food security status and nutritional status of mothers. MuPINSC is a national integrative program in Iran that distributes supplementary food basket to malnourished or growth retarded children living in low-income families in addition to providing health services, including sanitation, growth monitoring, and empowerment of families. This longitudinal study is part of a comprehensive evaluation of the program. The study participants included 359 mothers of children aged 6 to 72 month under coverage of the supportive section of the program in two provinces of Iran (Semnan and Qazvin). Demographic and economic characteristics of families were assessed by a questionnaire. Data on food security of family was collected by locally adapted Household Food Insecurity Access Scale (HFIAS) at the baseline of the study and six month thereafter. Weight and height of mothers were measured at the baseline and end of the study and mother’s BMI was calculated. Data were analysed, using paired t-test, GEE (Generalized Estimating Equation), and Chi-square tests. Based on the findings, at the baseline, only 4.7% of families were food-secure, while 13.1%, 38.7% and, 43.5% were categorized as mild, moderate and severe food insecure. After six months follow up, the distribution of different levels of food security changed significantly (P<0.001) to 7.9%, 11.6%, 42.6%, and 38%, respectively. At the end of the study, the chance of food insecurity was significantly 20% lower than the beginning (OR=0.796; 0.653-0.971). No significant difference was observed in maternal BMI based on food security (P>0.05). The findings show that the food supplementary program for children improved household food security status in the studied households. Further research is needed to assess other factors that affect the effectiveness of this large scale program on nutritional status and household’s food security.

Keywords: food security, food supplementary program, household, malnourished children

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Authors: Ajai Singh

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Simulation of hydrological processes at the watershed outlet through modelling approach is essential for proper planning and implementation of appropriate soil conservation measures in Damodar Barakar catchment, Hazaribagh, India where soil erosion is a dominant problem. This study quantifies the parametric uncertainty involved in simulation of stream flow using Soil and Water Assessment Tool (SWAT), a watershed scale model and Radial Basis Neural Network (RBNN), an artificial neural network model. Both the models were calibrated and validated based on measured stream flow and quantification of the uncertainty in SWAT model output was assessed using ‘‘Sequential Uncertainty Fitting Algorithm’’ (SUFI-2). Though both the model predicted satisfactorily, but RBNN model performed better than SWAT with R2 and NSE values of 0.92 and 0.92 during training, and 0.71 and 0.70 during validation period, respectively. Comparison of the results of the two models also indicates a wider prediction interval for the results of the SWAT model. The values of P-factor related to each model shows that the percentage of observed stream flow values bracketed by the 95PPU in the RBNN model as 91% is higher than the P-factor in SWAT as 87%. In other words the RBNN model estimates the stream flow values more accurately and with less uncertainty. It could be stated that RBNN model based on simple input could be used for estimation of monthly stream flow, missing data, and testing the accuracy and performance of other models.

Keywords: SWAT, RBNN, SUFI 2, bootstrap technique, stream flow, simulation

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Authors: Pooja Rani, G. S. Mahapatra, S. K. Pandey

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In this paper, we propose a novel approach of Neural Network and Particle Swarm Optimization methods for software reliability prediction. We first explain how to apply compound function in neural network so that we can derive a Flexible Logistic (S-shaped) Growth Curve (FLGC) model. This model mathematically represents software failure as a random process and can be used to evaluate software development status during testing. To avoid trapping in local minima, we have applied Particle Swarm Optimization method to train proposed model using failure test data sets. We drive our proposed model using computational based intelligence modeling. Thus, proposed model becomes Neuro-Particle Swarm Optimization (NPSO) model. We do test result with different inertia weight to update particle and update velocity. We obtain result based on best inertia weight compare along with Personal based oriented PSO (pPSO) help to choose local best in network neighborhood. The applicability of proposed model is demonstrated through real time test data failure set. The results obtained from experiments show that the proposed model has a fairly accurate prediction capability in software reliability.

Keywords: software reliability, flexible logistic growth curve model, software cumulative failure prediction, neural network, particle swarm optimization

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Authors: Zhaojun Wang, Zongdi Sun, Qinqin Cui, Xingwan Ren

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Based on multivariate statistical analysis theory, this paper uses the principal component analysis method, Mahalanobis distance analysis method and fitting method to establish the photovoltaic health model to evaluate the health of photovoltaic panels. First of all, according to weather conditions, the photovoltaic panel variable data are classified into five categories: sunny, cloudy, rainy, foggy, overcast. The health of photovoltaic panels in these five types of weather is studied. Secondly, a scatterplot of the relationship between the amount of electricity produced by each kind of weather and other variables was plotted. It was found that the amount of electricity generated by photovoltaic panels has a significant nonlinear relationship with time. The fitting method was used to fit the relationship between the amount of weather generated and the time, and the nonlinear equation was obtained. Then, using the principal component analysis method to analyze the independent variables under five kinds of weather conditions, according to the Kaiser-Meyer-Olkin test, it was found that three types of weather such as overcast, foggy, and sunny meet the conditions for factor analysis, while cloudy and rainy weather do not satisfy the conditions for factor analysis. Therefore, through the principal component analysis method, the main components of overcast weather are temperature, AQI, and pm2.5. The main component of foggy weather is temperature, and the main components of sunny weather are temperature, AQI, and pm2.5. Cloudy and rainy weather require analysis of all of their variables, namely temperature, AQI, pm2.5, solar radiation intensity and time. Finally, taking the variable values in sunny weather as observed values, taking the main components of cloudy, foggy, overcast and rainy weather as sample data, the Mahalanobis distances between observed value and these sample values are obtained. A comparative analysis was carried out to compare the degree of deviation of the Mahalanobis distance to determine the health of the photovoltaic panels under different weather conditions. It was found that the weather conditions in which the Mahalanobis distance fluctuations ranged from small to large were: foggy, cloudy, overcast and rainy.

Keywords: fitting, principal component analysis, Mahalanobis distance, SPSS, MATLAB

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Authors: S. Rostami, S. H. Hosseini, A. A. Torabi, M. Bekhradi

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Introduction: Interest in the use of caffeine as an ergogenic aid has increased since the International Olympic Committee lifted the partial ban on its use. Caffeine has beneficial effects on various aspects of athletic performance, but its effects on training have been neglected. The purpose of this study was to investigate the acute effect of caffeine on testosterone and cortisole in young futsal players. Methods: Twenty-four professional futsal players with 18.3± 1.9 years ingested caffeine doses of 0, 200 and 800 mg in random order 1 hr before an anaerobic-exercise session (RAST test). Samples were taken at the time of caffeine ingestion and 30 min after the session. Data were log-transformed to estimate percent effects with mixed modeling, and effects were standardized to assess magnitudes. fects on training have been neglected. Results: Testosterone concentration showed a small increase of 15% (90% confidence limits, ± 19%) during exercise. Caffeine raised this concentration in a dose-dependent manner by a further small 21% (± 24%) at the highest dose. The 800-mg dose also produced a moderate 52% (± 44%) increase in cortisol. The effect of caffeine on the testosterone: cortisol ratio was a small decline (14%; ± 21%). Discussion and Conclusion: Caffeine has some potential to benefit training outcomes via the anabolic effects of the increase in testosterone concentration, but this benefit might be counteracted by the opposing catabolic effects of the increase in cortisol and resultant decline in the testosterone: cortisol ratio.

Keywords: anabolic, catabolic, performance, testosterone, cortisol ratio, RAST test

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Authors: Humphrey Agevi, Harrison Tsingalia, Richard Onwonga, Shem Kuyah

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Most of the world ecosystems have been affected by the effects of climate change. Efforts have been made to mitigate against climate change effects. While most studies have been done in forest ecosystems and pure plant plantations, trees on farms including agroforestry have only received attention recently. Agroforestry systems and tree cover on agricultural lands make an important contribution to climate change mitigation but are not systematically accounted for in the global carbon budgets. This study sought to: (i) determine tree diversity in different agroforestry practices; (ii) determine tree biomass in different agroforestry practices. Study area was determined according to the Land degradation surveillance framework (LSDF). Two study sites were established. At each of the site, a 5km x 10km block was established on a map using Google maps and satellite images. Way points were then uploaded in a GPS helped locate the blocks on the ground. In each of the blocks, Nine (8) sentinel clusters measuring 1km x 1km were randomized. Randomization was done in a common spreadsheet program and later be downloaded to a Global Positioning System (GPS) so that during surveys the researchers were able to navigate to the sampling points. In each of the sentinel cluster, two farm boundaries were randomly identified for convenience and to avoid bias. This led to 16 farms in Kakamega South and 16 farms in Kakamega North totalling to 32 farms in Kakamega Site. Species diversity was determined using Shannon wiener index. Tree biomass was determined using allometric equation. Two agroforestry practices were found; homegarden and hedgerow. Species diversity ranged from 0.25-2.7 with a mean of 1.8 ± 0.10. Species diversity in homegarden ranged from 1-2.7 with a mean of 1.98± 0.14. Hedgerow species diversity ranged from 0.25-2.52 with a mean of 1.74± 0.11. Total Aboveground Biomass (AGB) determined was 13.96±0.37 Mgha-1. Homegarden with the highest abundance of trees had higher above ground biomass (AGB) compared to hedgerow agroforestry. This study is timely as carbon budgets in the agroforestry can be incorporated in the global carbon budgets and improve the accuracy of national reporting of greenhouse gases.

Keywords: agroforestry, allometric equations, biomass, climate change

Procedia PDF Downloads 347