Search results for: chemical transport modeling

Authors: Aleksander Ostrowski, Hugh J. Byrne, Roland Sanctuary

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Investigation of the polymer interphases is an emerging field nowadays. In many cases interphases determine the functionality of a system. There is a great demand for exploration of fundamental understanding of the interphases and elucidation of their formation, dimensions dependent on various influencing factors, change of functional properties, etc. The epoxy applied on porous glass penetrates its pores with an extent dependent on the pore size, temperature and epoxy components mixing ratio. Developed over the recent time challenging sample preparation procedure allowed to produce very smooth epoxy-porous glass cross-sections. In this study, Raman spectroscopy was used to investigate the epoxy-porous glass interphases. It allowed for chemical differentiation between different regions at the cross-section and determination of the degree of cure of epoxy system in the porous glass.

Keywords: interphases, Raman spectroscopy, epoxy, porous glass

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Authors: A. Pourahmad, Sh. Gharipour

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The present work describes the preparation and characterization of nanosized SiO₂@PbS core-shell particles by using a simple wet chemical route. This method utilizes silica spheres formation followed by successive ionic layer adsorption and reaction method assisted lead sulphide shell layer formation. The final product was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), UV–vis spectroscopic, infrared spectroscopy (IR) and transmission electron microscopy (TEM) experiments. The morphological studies revealed the uniformity in size distribution with core size of 250 nm and shell thickness of 18 nm. The electron microscopic images also indicate the irregular morphology of lead sulphide shell layer. The structural studies indicate the face-centered cubic system of PbS shell with no other trace for impurities in the crystal structure.

Keywords: core-shell, nanostructure, semiconductor, optical property, XRD

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Authors: Shah Md. Imran Kabir, Md. Mostafa Ali

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Karnafuli is one of the most important rivers of Bangladesh which is playing a vital role in our national economy. The major sea port of Bangladesh is the Chittagong port located on the right bank of Karnafuli River Bangladesh. Karnafuli river port is considered as the lifeline of the economic activities of the country. Therefore, it is always necessary to keep the river active and live in terms of its navigability. Due to man-made intervention, the river flow becomes interrupted and thereby may cause the change in the river morphology. The specific objective of this study is the application of 2D model to assess different hydrodynamic and morphological characteristics of the river due to normal flow condition and sea level rise condition. The model has been set with the recent bathymetry data collected from CPA hydrography division. For model setup, the river reach is selected between Kalurghat and Khal no-18. Time series discharge and water level data are used as boundary condition at upstream and downstream. Calibration and validation have been carried out with the recent water level data at Khal no-10 and Sadarghat. The total reach length of the river has been divided into four parts to determine different hydrodynamic and morphological assessments like variation of velocity, sediment erosion and deposition and bed level changes also have been studied. This model has been used for the assessment of river response due sediment transport and sea level rise. Model result shows slight increase in velocity. It also changes the rate of erosion and deposition at some location of the selected reach. It is hoped that the result of the model simulation will be helpful to suggest the effect of possible future development work to be implemented on this river.

Keywords: CCHE 2D, hydrodynamic, morphology, sea level rise

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Authors: K. Jarmkom, P. Eakwaropas, W. Khobjai, S. Techaeoi

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Ancient Thai perfumed powder was used as a fragrance for clothing, food, and the body. Plant-based natural Thai perfume products are known as Pang-Rum. The objective of this study was to evaluate the stability of essential oils after six months of incubation. The chemical compositions were determined by gas chromatography-mass spectrometry (GC-MS), in terms of the qualitative composition of the isolated essential oil. The isolation of the essential oil of natural products by incubate sample for 5 min at 40 ºC is described. The volatile components were identified by percentage of total peak areas comparing their retention times of GC chromatograph with NIST mass spectral library. The results show no significant difference in the seven chromatograms of perfumed powder (Pang-Rum) both with binder and without binder. Further identification was done by GC-MS. Some components of Pang-Rum with/without binder were changed by temperature and time.

Keywords: GC-MS analysis, essential oils, stability, Pang-Rum

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Authors: Kumar Neeraj, Ranjan Haldar, Ashok Srivastava

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Polyaniline used as light-emitting devices (LEDs), televisions, cellular telephones, automotive, Corrosion-resistant coatings, actuators and ability to have micro- and nano-devices. the electrical conductivity properties can be increased by introduction of metal nano particles. In the present study, platinum nano particles have been utilized to achieve the improved properties. Polyaniline and Pt-polyaniline composite are synthesized by chemical routes. The samples characterized by X-ray diffractometer show the amorphous nature of polyaniline and Pt-polyaniline composite. The Bragg’s diffraction peaks correspond to platinum nano particles and thermogravimetric analyzer predicts its decomposition at certain temperature. The current-potential characteristics of the samples are also studied which indicate a significant increasing the value of conductivity after introduction of pt nanoparticles in the matrix of polyaniline (PANI).

Keywords: polyaniline, XRD and platinum nanoparticles, characterization, pharmaceutical sciences

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Authors: Atousa Ataieyan, Salvador A. Gomez-Lopera, Gennaro Sepede

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Today, due to the growing urban population and consequently, the increasing water demand in cities, the amount of contaminants entering the water resources is increasing. This can impose harmful effects on the quality of the downstream water. Therefore, predicting the concentration of discharged pollutants at different times and distances of the interested area is of high importance in order to carry out preventative and controlling measures, as well as to avoid consuming the contaminated water. In this paper, the concentration distribution of an injected conservative pollutant in a square reservoir containing four symmetric blocks and three sources using Finite Volume Method (FVM) is simulated. For this purpose, after estimating the flow velocity, classical Advection-Diffusion Equation (ADE) has been discretized over the studying domain by Backward Time- Backward Space (BTBS) scheme. Then, the discretized equations for each node have been derived according to the initial condition, boundary conditions and point contaminant sources. Finally, taking into account the appropriate time step and space step, a computational code was set up in MATLAB. Contaminant concentration was then obtained at different times and distances. Simulation results show how using BTBS differentiating scheme and FVM as a numerical method for solving the partial differential equation of transport is an appropriate approach in the case of two-dimensional contaminant transfer in an advective-diffusive flow.

Keywords: BTBS differentiating scheme, contaminant concentration, finite volume, mass transfer, water pollution

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Authors: Javad Khazaei, Rick Blum

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Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: consensus tracking, distributed control, model-free control, sparse identification of dynamical systems

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Authors: Eddegdag Nasser, Naamane Azzeddine, Radouani Mohammed, Ensam Meknes

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In this study, we are interested in the asymptotic modeling of the two-dimensional stationary supersonic flow of a viscous compressible fluid around wing airfoil. The aim of this article is to solve the partial differential equations of the flow far from the leading edge and near the wall using the triple-deck technique is what brought again in precision according to the principle of least degeneration. In order to validate our theoretical model, these obtained results will be compared with the experimental results. The comparison of the results of our model with experimentation has shown that they are quantitatively acceptable compared to the obtained experimental results. The experimental study was conducted using the AF300 supersonic wind tunnel and a NACA Reduced airfoil model with two pressure Taps on extrados. In this experiment, we have considered the incident upstream supersonic Mach number over a dissymmetric NACA airfoil wing. The validation and the accuracy of the results support our model.

Keywords: supersonic, viscous, triple deck technique, asymptotic methods, AF300 supersonic wind tunnel, reduced airfoil model

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Authors: Sun-Jin Han, Deuck Hang Lee, Hyo-Eun Joo, Hyun Kang, Kang Su Kim

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In pretensioned concrete members, the transfer length region is existed, in which the stress in prestressing strand is developed due to the bond mechanism with surrounding concrete. The stress of strands in the transfer length zone is smaller than that in the strain plateau zone, so-called effective prestress, therefore the web-shear strength in transfer length region is smaller than that in the strain plateau zone. Although the transfer length is main key factor in the shear design, a few analytical researches have been conducted to investigate the transfer length. Therefore, in this study, a theoretical approach was used to estimate the transfer length. The bond stress developed between the strands and the surrounding concrete was quantitatively calculated by using the Thick-Walled Cylinder Model (TWCM), based on this, the transfer length of strands was calculated. To verify the proposed model, a total of 209 test results were collected from the previous studies. Consequently, the analysis results showed that the main influencing factors on the transfer length are the compressive strength of concrete, the cover thickness of concrete, the diameter of prestressing strand, and the magnitude of initial prestress. In addition, the proposed model predicted the transfer length of collected test specimens with high accuracy. Acknowledgement: This research was supported by a grant(17TBIP-C125047-01) from Technology Business Innovation Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Keywords: bond, Hoyer effect, prestressed concrete, prestressing strand, transfer length

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Authors: Jiandong Ren, Lijun Zhao, Peng Chen

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Nafamostat (NA), a synthetic broad-spectrum serine protease inhibitor, has been routinely employed for the treatment of acute pancreatitis (AP) and other inflammatory-associated diseases in some East Asia countries. Although the potent inhibitory activity against inflammation-related proteases such as thrombin, trypsin, kallikrein, plasmin, coagulation factors and complement factors is generally considered to be responsible for the anti-inflammatory effects of NA, precise target and molecular mechanism underlying the anti-inflammatory activity in the treatment of AP remain largely unknown yet. As an intracellular inflammatory signaling platform, the NOD-like receptor protein 3 (NLRP3) inflammasome is recently identified to be involved in the development of AP. In present study, we have revealed that NA alleviated pancreatic injury in a caerulein-induced AP model by inhibiting the NLRP3 inflammasome activation in pancreas. Mechanistically, NA interacted with HDAC6, a cytoplasmic deacetylase implicated in the NLRP3 inflammasome pathway, and efficiently abrogated the function of HDAC6. This property enabled NA to influence HDAC6 dependent NF-κB transcriptional activity and thus block NF-κB-driven transcriptional priming of NLRP3 inflammasome. Moreover, NA exerted the potential to interfere HDAC6-mediated intracellular transport of NLRP3, thereby leading to the failure of NLRP3 inflammasome activation. Our current work has provided valuable insight into the molecular mechanism underlying the immunomodulatory effect of NA in treatment of AP, highlighting its promising application in prevention of NLRP3 inflammasome-associated inflammatory pathological damage.

Keywords: acute pancreatitis, HDAC6, nafamostat, NLRP3 inflammasome

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Authors: Zahid Ullah, Atlas Khan

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The presented research is dedicated to an extensive examination of the regularity properties associated with a specific class of equations, namely extremely degenerate elliptic equations. This study holds significance in unraveling the complexities inherent in these equations and understanding the smoothness of their solutions. The focus is on analyzing the regularity of results, aiming to contribute to the broader field of mathematical theory. By delving into the intricacies of extremely degenerate elliptic equations, the research seeks to advance our understanding beyond conventional analyses, addressing challenges posed by degeneracy and pushing the boundaries of classical analytical methods. The motivation for this exploration lies in the practical applicability of mathematical models, particularly in real-world scenarios where physical phenomena exhibit characteristics that challenge traditional mathematical modeling. The research aspires to fill gaps in the current understanding of regularity properties within solutions to extremely degenerate elliptic equations, ultimately contributing to both theoretical foundations and practical applications in diverse scientific fields.

Keywords: investigating smoothness, extremely degenerate elliptic equations, regularity properties, mathematical analysis, complexity solutions

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Authors: Şebnem Aslan, Demet Akarçay

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The objective of this study is to investigate the feelings of health employees occurred by bullying and the relationships between these feelings at work place. In this context, the relationships between bullying and the feelings of self-esteem, employee silence, anger, self- blame and shame. This study was conducted among 512 health employees in three hospitals in Konya by using survey method and simple random sampling. The scales of bullying, self-esteem, employee silence, anger, self-blame, and shame were performed within the study. The obtained data were analyzed with descriptive analysis, correlation, confirmative factor analysis, structural equation modeling and path analysis. The results of the study showed that while bullying had a positive effect on self-esteem (.61), employee silence (.41), anger (.18), a negative effect on self-blame and shame (-.26) was observed. Employee silence affected self-blame and shame (.83) as positively. Besides, self-esteem impacted on self- blame and shame (.18), employee silence (.62) positively and self-blame and shame was observed as negatively affecting on anger (-.20). Similarly, self-esteem was found as negatively affected on anger (-.13).

Keywords: bullying, self-esteem, employee silence, anger, shame and guilt, healthcare employee

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Authors: M. Djekoun, H. Berrebah, M. R. Djebar

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Fusarium wilt is destructive disease of cereal crops with small grains. It affects yields but also the quality of the crop and economic losses arising are often very heavy. Chemical control is currently one of the most effective ways to fight against these diseases. In this study, the efficacy of three fungicides (tebuconazole, thiram, and fludioxonil-difenoconazole mixture) was tested. In vitro, on the phytopathogenic Fusarium spp. isolated from seeds of wheat. The active ingredients were tested at different concentrations: 0.06, 1.39, 2.79, 5.58, and 11.16 mg/l for tebuconazole, 0.035, 0.052, 0.105, 0.21, and 0.42 mg/l for thiram and finally, for the mixture fludioxonil-difenoconazole 4 concentrations were tested: 0.05, 0.1, 0.5 and 1 mg/l. Toxicity responses were expressed as effective concentration, which inhibits mycelial growth by 50%, (EC50). Of the three selected fungicides, thirame proved to be the most effective with EC50 value of the order of 0,15 mg/l followed by the mixture of fludioxonil-difenoconazole with 0,27mg/l and finally tebuconazole with a value of 3.79 mg/l.

Keywords: Fusarium spp., thiram, tebuconazole, fludioxonil, difenoconazole, percentage of inhibition, EC50

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Authors: Hasan Keshavarzian, Tayebeh Nesari

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Bolted rail joint is one of the most vulnerable areas in railway track. A comprehensive approach was developed for studying the reliability of fatigue crack initiation of railroad bolt hole under random axle loads and random material properties. The operation condition was also considered as stochastic variables. In order to obtain the comprehensive probability model of fatigue crack initiation life prediction in railroad bolt hole, we used FEM, response surface method (RSM), and reliability analysis. Combined energy-density based and critical plane based fatigue concept is used for the fatigue crack prediction. The dynamic loads were calculated according to the axle load, speed, and track properties. The results show that axle load is most sensitive parameter compared to Poisson’s ratio in fatigue crack initiation life. Also, the reliability index decreases slowly due to high cycle fatigue regime in this area.

Keywords: rail-wheel tribology, rolling contact mechanic, finite element modeling, reliability analysis

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Authors: Tahir Nawaz Cheema, Dumitru Baleanu, Ali Raza

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In this research work, we design intelligent computing through Bayesian Regularization artificial neural networks (BRANNs) introduced to solve the mathematical modeling of infectious diseases (Covid-19). The dynamical transmission is due to the interaction of people and its mathematical representation based on the system's nonlinear differential equations. The generation of the dataset of the Covid-19 model is exploited by the power of the explicit Runge Kutta method for different countries of the world like India, Pakistan, Italy, and many more. The generated dataset is approximately used for training, testing, and validation processes for every frequent update in Bayesian Regularization backpropagation for numerical behavior of the dynamics of the Covid-19 model. The performance and effectiveness of designed methodology BRANNs are checked through mean squared error, error histograms, numerical solutions, absolute error, and regression analysis.

Keywords: mathematical models, beysian regularization, bayesian-regularization backpropagation networks, regression analysis, numerical computing

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Authors: Alain Kusmoko, Druce Dunne, Huijun Li

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Stellite 6 was deposited by laser cladding on a chromium bearing substrate (P91) with energy inputs of 1 kW (P91-1) and 1.8 kW (P91-1.8). The chemical compositions and microstructures of these coatings were characterized by atomic absorption spectroscopy, optical microscopy and scanning electron microscopy. The microhardness of the coatings was measured and the wear mechanism of the coatings was assessed using a pin-on-plate (reciprocating) wear testing machine. The results showed less cracking and pore development for Stellite 6 coatings applied to the P91 steel substrate with the lower heat input (P91-1). Further, the Stellite coating for P91-1 was significantly harder than that obtained for P91-1.8. The wear test results indicated that the weight loss for P91-1 was much lower than for P91-1.8. It is concluded that the lower hardness of the coating for P91-1.8, together with the softer underlying substrate structure, markedly reduced the wear resistance of the Stellite 6 coating.

Keywords: friction and wear, laser cladding, P91 steel, Stellite 6 coating

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Authors: I. F. Ejim, F. L. Kamen

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Aims: In this experiment, algae oil extraction with a combination of n-hexane and ethanol was investigated. The effects of extraction solvent concentration, extraction time and temperature on the yield and quality of oil were studied using Response Surface Methodology (RSM). Experimental Design: Optimization of algae oil extraction using Box-Behnken design was used to generate 17 experimental runs in a three-factor-three-level design where oil yield, specific gravity, acid value and saponification value were evaluated as the response. Result: In this result, a minimum oil yield of 17% and maximum of 44% was realized. The optimum values for yield, specific gravity, acid value and saponification value from the overlay plot were 40.79%, 0.8788, 0.5056 mg KOH/g and 180.78 mg KOH/g respectively with desirability of 0.801. The maximum point prediction was yield 40.79% at solvent concentration 66.68 n-hexane, temperature of 40.0°C and extraction time of 4 hrs. Analysis of Variance (ANOVA) results showed that the linear and quadratic coefficient were all significant at p<0.05. The experiment was validated and results obtained were with the predicted values. Conclusion: Algae oil extraction was successfully optimized using RSM and its quality indicated it is suitable for many industrial uses.

Keywords: algae oil, response surface methodology, optimization, Box-Bohnken, extraction

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Muthana Abdul Mjed Jamel Al-gburi

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The present paper introduces the methane-air flame and its main chemical reaction, the mass burning rate, the burning velocity, and the most important parameter, the adiabatic and its evaluation. Those major important flame parameters will be mathematically formulated and computerized using the MATLAB program. The present program established a new technique to decide the true adiabatic flame temperature. The new technique implements the trial and error procedure to obtained the calculated total internal energy of the product species then evaluate of the reactants ones, from both, we can draw two energy lines their intersection will decide the true required temperature. The obtained results show accurate evaluation for the atmospheric Stoichiometric (Φ=1.05) methane-air flame, and the value was 2136.36 K.

Keywords: 1- methane-air flame, 2-, adiabatic flame temperature, 3-, reaction model, 4- matlab program, 5-, new technique

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Authors: Ada Garus

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This paper presents the outcomes of the sustainability assessment of food delivery with a last-mile delivery service introduced in a real-world case study. The methodology used in the sustainability assessment integrates multi-criteria decision-making analysis, sustainability pillars, and scenario analysis to best reflect the conflicting needs of stakeholders involved in the last mile delivery system. The case study provides an application of the framework to the food delivery system of the Joint Research Centre of the European Commission where three alternative solutions were analyzed I) the existent state in which individuals frequent the local cantine or pick up their food, using their preferred mode of transport II) the hypothetical scenario in which individuals can only order their food using the delivery droid system III) a scenario in which the food delivery droid based system is introduced as a supplement to the current system. The environmental indices are calculated using a simulation study in which decision regarding the food delivery is predicted using a multinomial logit model. The vehicle dynamics model is used to predict the fuel consumption of the regular combustion engines vehicles used by the cantine goers and the electricity consumption of the droid. The sustainability assessment allows for the evaluation of the economic, environmental, and social aspects of food delivery, making it an apt input for policymakers. Moreover, the assessment is one of the first studies to investigate automated delivery droids, which could become a frequent addition to the urban landscape in the near future.

Keywords: innovations in transportation technologies, behavioural change and mobility, urban freight logistics, innovative transportation systems

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Authors: Wooyoung Jung, Ghang Lee

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This paper paper reports the worldwide status of building information modeling (BIM) adoption from the perspectives of the engagement level, the Hype Cycle model, the technology diffusion model, and BIM-uses. An online survey was distributed, and 156 experts from six continents responded. Overall, North America was the most advanced continent, followed by Oceania and Europe. Countries in Asia perceived their phase mainly as slope of enlightenment (mature) in the Hype Cycle model. In the technology diffusion model, the main BIM-users worldwide were “early majority” (third phase), but those in the Middle East/Africa and South America were “early adopters” (second phase). In addition, the more advanced the country, the more number of BIM services employed in general. In summary, North America, Europe, Oceania, and Asia were advancing rapidly toward the mature stage of BIM, whereas the Middle East/Africa and South America were still in the early phase. The simple indexes used in this study may be used to track the worldwide status of BIM adoption in long-term surveys.

Keywords: BIM adoption, BIM services, hype cycle model, technology diffusion model

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Authors: Elham Mansouri, Asghar Mesbahi

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Purpose: In the current study, we aimed to investigate the macroscopic and microscopic dose enhancement effect of metallic nanoparticles in interstitial brachytherapy of uterus cancer by Iodin-125 source using a nano-lattice model in MCNPX (5) and MCNP6.1 codes. Materials and methods: Based on a nano-lattice simulation model containing a radiation source and a tumor tissue with cellular compartments loaded with 7mg/g spherical nanoparticles (bismuth, gold, and gadolinium), the energy deposited by the secondary electrons in microscopic and macroscopic level was estimated. Results: The results show that the values of macroscopic DEF is higher than microscopic DEF values and the macroscopic DEF values decreases as a function of distance from the brachytherapy source surface. Also, the results revealed a remarkable discrepancy between the DEF and secondary electron spectra calculated by MCNPX (5) and MCNP6.1 codes, which could be justified by the difference in energy cut-off and electron transport algorithms of two codes. Conclusion: According to the both MCNPX (5) and MCNP6.1 outputs, it could be concluded that the presence of metallic nanoparticles in the tumor tissue of uteruscancer increases the physical effectiveness of brachytherapy by I-125 source. The results presented herein give a physical view of radiosensitization potential of different metallic nanoparticles and could be considered in design of analytical and experimental radiosensitization studies in tumor regions using various radiotherapy modalities in the presence of heavy nanomaterials.

Keywords: MCNPX, MCNP6, nanoparticle, brachytherapy

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Authors: Yoonsuh Jung

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As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an "optimal" value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: cross validation, parameter averaging, parameter selection, regularization parameter search

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Authors: Aniedi A. Udo, Magnus U. Igboekwe, Rasaaq Bello, Francis D. Eyenaka, Michael C. Ohakwere-Eze

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Groundwater vulnerability to pollution was assessed in Akwa Ibom State, Southern Nigeria, with the aim of locating areas with high potentials for resource contamination, especially due to anthropogenic influence. The electrical resistivity method was utilized in the collection of the initial field data. Additional data input, which included depth to static water level, drilled well log data, aquifer recharge data, percentage slope, as well as soil information, were sourced from secondary sources. The initial field data were interpreted both manually and with computer modeling to provide information on the geoelectric properties of the subsurface. Interpreted results together with the secondary data were used to develop the DRASTIC thematic maps. A vulnerability assessment was performed using the DRASTIC model in a GIS environment and areas with high vulnerability which needed immediate attention was clearly mapped out and presented using an aquifer vulnerability map. The model was subjected to validation and the rate of validity was 73% within the area of study.

Keywords: groundwater, vulnerability, DRASTIC model, pollution

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Authors: Zhongyang Sun, Shu Zhang

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In osteoblasts, L-type voltage sensitive calcium channels (LTCCs), especially the Cav1.2 LTCCs, play fundamental roles in cellular responses to external stimuli including both mechanical forces and hormonal signals. Several lines of evidence have revealed that the density of bone is increased and the resorption of bone is decreased when these calcium channels in osteoblasts are activated. And numerous studies have shown that mechanical loading promotes bone formation in the modeling skeleton, whereas removal of this stimulus in microgravity results in a reduction in bone mass. However, the effect of microgravity on LTCCs in osteoblasts is still unknown. The aim of this study was to determine whether microgravity exerts influence on LTCCs in osteoblasts and the possible mechanisms underlying. In this study, we demonstrate that simulated microgravity substantially inhibits LTCCs in osteoblast by suppressing the expression of Cav1.2. Then we show that the up-regulation of miR-103 is involved in the down-regulation of Cav1.2 expression and inhibition of LTCCs by simulated microgravity in osteoblasts. Our study provides a novel mechanism of simulated microgravity-induced adverse effects on osteoblasts, offering a new avenue to further investigate the bone loss caused by microgravity.

Keywords: L-type voltage sensitive calcium channels, Cav1.2, osteoblasts, microgravity

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Haozhe Xiang

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With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

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Authors: Maddumage Don Sandeepa Lakshad Wimalananda, Jae-Kwan Kim, Ji-Myon Lee

Abstract:

Graphene is an extraordinary 2D material that shows superior electrical, optical, and mechanical properties for the applications such as transparent contacts. Further, chemical vapor deposition (CVD) technique facilitates to synthesizing of large-area graphene, including transferability. The abstract is describing the use of high surface free energy (SFE) and nano-scale high-density surface kinks (rough) existing Cu foil for CVD graphene growth, which is an opposite approach to modern use of catalytic surfaces for high-quality graphene growth, but the controllable rough morphological nature opens new era to fast synthesis (less than the 50s with a short annealing process) of graphene as a continuous film over conventional longer process (30 min growth). The experiments were shown that high SFE condition and surface kinks on Cu(100) crystal plane existing Cu catalytic surface facilitated to synthesize graphene with high monolayer and continuous nature because it can influence the adsorption of C species with high concentration and which can be facilitated by faster nucleation and growth of graphene. The fast nucleation and growth are lowering the diffusion of C atoms to Cu-graphene interface, which is resulting in no or negligible formation of bilayer patches. High energy (500W) Ar plasma treatment (inductively Coupled plasma) was facilitated to form rough and high SFE existing (54.92 mJm-2) Cu foil. This surface was used to grow the graphene by using CVD technique at 1000C for 50s. The introduced kink-like high SFE existing point on Cu(100) crystal plane facilitated to faster nucleation of graphene with a high monolayer ratio (I2D/IG is 2.42) compared to another different kind of smooth morphological and low SFE existing Cu surfaces such as Smoother surface, which is prepared by the redeposit of Cu evaporating atoms during the annealing (RRMS is 13.3nm). Even high SFE condition was favorable to synthesize graphene with monolayer and continuous nature; It fails to maintain clean (surface contains amorphous C clusters) and defect-free condition (ID/IG is 0.46) because of high SFE of Cu foil at the graphene growth stage. A post annealing process was used to heal and overcome previously mentioned problems. Different CVD atmospheres such as CH4 and H2 were used, and it was observed that there is a negligible change in graphene nature (number of layers and continuous condition) but it was observed that there is a significant difference in graphene quality because the ID/IG ratio of the graphene was reduced to 0.21 after the post-annealing with H2 gas. Addition to the change of graphene defectiveness the FE-SEM images show there was a reduction of C cluster contamination of the surface. High SFE conditions are favorable to form graphene as a monolayer and continuous film, but it fails to provide defect-free graphene. Further, plasma modified high SFE existing surface can be used to synthesize graphene within 50s, and a post annealing process can be used to reduce the defectiveness.

Keywords: chemical vapor deposition, graphene, morphology, plasma, surface free energy

Procedia PDF Downloads 232

Authors: Jikhil Joseph, S. R. Satish Kumar

Abstract:

Steel Structures are commonly used for rapid erections and multistory constructions due to its inherent advantages. However, the high accuracy required in detailing and heavier sections, make it difficult to erect in place and transport. Cold Formed steel which are specially made by reducing carbon and other alloys are used nowadays to make thin-walled structures. Various types of connections are being reported as well as practiced for the thin-walled members such as bolting, riveting, welding and other mechanical connections. Commonly self-drilling screw connections are used for cold-formed purlin sheeting connection. In this paper an attempt is made to develop a moment resting frame which can be rapidly and remotely constructed with thin walled sections and self-drilling screws. Semi-rigid Moment connections are developed with Rectangular thin-walled tubes and the screws. The Finite Element Analysis programme ABAQUS is used for modelling the screwed connections. The various modelling procedures for simulating the connection behavior such as tie-constraint model, oriented spring model and solid interaction modelling are compared and are critically reviewed. From the experimental validations the solid-interaction modelling identified to be the most accurate one and are used for predicting the connection behaviors. From the finite element analysis, hysteresis curves and the modes of failure were identified. Parametric studies were done on the connection model to optimize the connection configurations to get desired connection characteristics.

Keywords: buckling, cold formed steel, finite element analysis, screwed connections

Procedia PDF Downloads 169

Authors: Zita Šereš, Dragana Šoronja Simović, Ljubica Dokić, Lidietta Giorno, Biljana Pajin, Cecilia Hodur, Nikola Maravić

Abstract:

Membrane technology is convenient for separation of suspended solids, colloids and high molecular weight materials that are present. The idea is that the waste stream from edible oil industry, after the separation of oil by using skimmers is subjected to microfiltration and the obtained permeate can be used again in the production process. The wastewater from edible oil industry was used for the microfiltration. For the microfiltration of this effluent a tubular membrane was used with a pore size of 200 nm at transmembrane pressure in range up to 3 bar and in range of flow rate up to 300 L/h. Box–Behnken design was selected for the experimental work and the responses considered were permeate flux and chemical oxygen demand (COD) reduction. The reduction of the permeate COD was in the range 40-60% according to the feed. The highest permeate flux achieved during the process of microfiltration was 160 L/m²h.

Keywords: ceramic membrane, edible oil, microfiltration, wastewater

Procedia PDF Downloads 278