Search results for: currents and potentials matrix

Authors: S. Tunmee, P. Wongpanya, I. Toda, X. L. Zhou, Y. Nakaya, N. Konkhunthot, S. Arakawa, H. Saitoh

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The hydrogenated amorphous carbon films (a-C:H) were deposited on p-type Si (100) substrates at different thicknesses by radio frequency plasma enhanced chemical vapor deposition technique (rf-PECVD). Raman spectra display asymmetric diamond-like peaks, representative of the a-C:H films. The decrease of intensity ID/IG ratios revealed the sp3 content arise at different thicknesses of the a-C:H films. In terms of mechanical properties, the high hardness and elastic modulus values show the elastic and plastic deformation behaviors related to sp3 content in amorphous carbon films. Electro chemical properties showed that the a-C:H films exhibited excellent corrosion resistance in air-saturated 3.5 wt% NaCl solution for pH 2 at room temperature. Thickness increasing affected the small sp2 clusters in matrix, restricting the velocity transfer and exchange of electrons. The deposited a-C:H films exhibited excellent mechanical properties and corrosion resistance.

Keywords: thickness, mechanical properties, electrochemical corrosion properties, a-C:H film

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Authors: Soltani Amir, Hu Jiaxin

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Determination of optimal parameters of a passive control system device is the primary objective of this study. Expanding upon the use of control devices in wind and earthquake hazard reduction has led to development of various control systems. The advantage of non-linearity characteristics in a passive control device and the optimal control method using LQR algorithm are explained in this study. Finally, this paper introduces a simple approach to determine optimum parameters of a nonlinear viscous damper for vibration control of structures. A MATLAB program is used to produce the dynamic motion of the structure considering the stiffness matrix of the SDOF frame and the non-linear damping effect. This study concluded that the proposed system (variable damping system) has better performance in system response control than a linear damping system. Also, according to the energy dissipation graph, the total energy loss is greater in non-linear damping system than other systems.

Keywords: passive control system, damping devices, viscous dampers, control algorithm

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Authors: Clarissa D. M. O. Guimaraes, Mariza C. M. Fernandes, Francisco R. V. Diaz, Juliana R. Souza

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The use of mineral fillers in the preparation of organic matrix composites can be an efficient alternative in minimizing the environmental damage generated in passive mineral beneficiation processes. In addition, it may represent a new material option for wind, construction, and aeronautical industries, for example. In this sense, epoxy resin composites with Tailings of Scheelite (TS) were developed. The composites were manufactured with 5%, 10% and 20% of TS in volume percentage, homogenized by mechanical mixing and molded in a silicon mold. In order to make the tribological evaluation, pin on disk tests were performed to analyze coefficient of friction and wear. The wear mechanisms were identified by SEM (scanning electron microscope) images. The coefficient of friction had a tendency to decrease with increasing amount of filler. The wear tends to increase with increasing amount of filler, although it exhibits a similar wear behavior. The results suggest characteristics that are potential used in many tribological applications.

Keywords: composites, mineral filler, tailings of scheelite, tribology

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Authors: Subodh Chandra Shakya, Badal Shrestha, Suni Thapa, Ashutosh Chauhan, Saugat Adhikari

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To tackle our problem of clothes identification, we used different architectures of Convolutional Neural Networks. Among different architectures, the outcome from Inception ResNet V2 and MobileNet V2 seemed promising. On comparison of the metrices, we observed that the Inception ResNet V2 slightly outperforms MobileNet V2 for this purpose. So this paper of ours proposes the cloth identifier using Inception ResNet V2 and also contains the comparison between the outcome of ResNet V2 and MobileNet V2. The document here contains the results and findings of the research that we performed on the DeepFashion Dataset. To improve the dataset, we used different image preprocessing techniques like image shearing, image rotation, and denoising. The whole experiment was conducted with the intention of testing the efficiency of convolutional neural networks on cloth identification so that we could develop a reliable system that is good enough in identifying the clothes worn by the users. The whole system can be integrated with some kind of recommendation system.

Keywords: inception ResNet, convolutional neural net, deep learning, confusion matrix, data augmentation, data preprocessing

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Authors: Hanna Abbo, Siyasanga Noganta, Salam Titinchi

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The global lack of clean water for human sanitation and other purposes has become an emerging dilemma for human beings. The presence of organic pollutants in wastewater produced by textile industries, leather manufacturing and chemical industries is an alarming matter for a safe environment and human health. For the last decades, conventional methods have been applied for the purification of water but due to industrialization these methods fall short. Advanced oxidation processes and their reliable application in degradation of many contaminants have been reported as a potential method to reduce and/or alleviate this problem. Lately it has been assumed that incorporation of some metal nanoparticles such as magnetite nanoparticles as photocatalyst for Fenton reaction which could improve the degradation efficiency of contaminants. Core/shell nanoparticles, are extensively studied because of their wide applications in the biomedical, drug delivery, electronics fields and water treatment. The current study is centred on the synthesis of silver-doped Fe3O4/SiO2/TiO2 photocatalyst. Magnetically separable Fe3O4@SiO2@TiO2 composite with core–shell structure were synthesized by the deposition of uniform anatase TiO2 NPs on Fe3O4@SiO2 by using titanium butoxide (TBOT) as titanium source. Then, the silver is doped on SiO2 layer by hydrothermal method. Integration of magnetic nanoparticles was suggested to avoid the post separation difficulties associated with the powder form of the TiO2 catalyst, increase of the surface area and adsorption properties. The morphology, structure, composition, and magnetism of the resulting composites were characterized and their photocatalytic activities were also evaluated. The results demonstrate that TiO2 NPs were uniformly deposited on the Fe3O4@SiO2 surface. The silver nanoparticles were also uniformly distributed on the surface of TiO2 nanoparticles. The aim of this work is to study the suitability of photocatalysis for the treatment of aqueous streams containing organic pollutants such as methylene blue which is selected as a model compound to represent one of the pollutants existing in wastewaters. Various factors such as initial pollutant concentration, photocatalyst dose and wastewater matrix were studied for their effect on the photocatalytic degradation of the organic model pollutants using the as synthesized catalysts and compared with the commercial titanium dioxide (Aeroxide P25). Photocatalysis was found to be a potential purification method for the studied pollutant also in an industrial wastewater matrix with the removal percentages of over 81 % within 15 minutes. Methylene blue was removed most efficiently and its removal consumed the least of energy in terms of the specific applied energy. The magnetic Ag/SiO2/TiO2 composites show high photocatalytic performance and can be recycled three times by magnetic separation without major loss of activity, which meant that they can be used as efficient and conveniently renewable photocatalyst.

Keywords: Magnetite nanoparticles, Titanium, Photocatalyst, Organic pollutant, Water treatment

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Authors: Krisada Lekdee, Sunee Sammatat, Nittaya Boonsit

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This paper proposes a GLMM with spatial and temporal effects for malaria data in Thailand. A Bayesian method is used for parameter estimation via Gibbs sampling MCMC. A conditional autoregressive (CAR) model is assumed to present the spatial effects. The temporal correlation is presented through the covariance matrix of the random effects. The malaria quarterly data have been extracted from the Bureau of Epidemiology, Ministry of Public Health of Thailand. The factors considered are rainfall and temperature. The result shows that rainfall and temperature are positively related to the malaria morbidity rate. The posterior means of the estimated morbidity rates are used to construct the malaria maps. The top 5 highest morbidity rates (per 100,000 population) are in Trat (Q3, 111.70), Chiang Mai (Q3, 104.70), Narathiwat (Q4, 97.69), Chiang Mai (Q2, 88.51), and Chanthaburi (Q3, 86.82). According to the DIC criterion, the proposed model has a better performance than the GLMM with spatial effects but without temporal terms.

Keywords: Bayesian method, generalized linear mixed model (GLMM), malaria, spatial effects, temporal correlation

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Authors: Brahmanage S. Rangika, Dinithi C. Peiris

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Boiled Aqueous Flower Extract (AFE) of Nyctanthes arbor-tristis L. (Family: Oleaceae) is used in traditional Sri Lankan medicinal system to treat diabetes. However, this is not scientifically proven and the mechanisms by which the flowers reduce diabetes have not been investigated. The present study was carried out to examine the hypoglycemic potential and toxicity effects of aqueous flower extract of N. arbor-tristis. AFE was prepared and mice were treated orally either with 250, 500, and 750 mg/kg of AFE or distilled water (Control). Fasting and random blood glucose levels were determined. In addition, the toxicity of AFE was determined using chronic oral administration. In normoglycemic mice, mid dose (500mg/kg) of AFE significantly (p < 0.01) reduced fasting blood glucose levels by 49% at 4h post treatment. Further, 500mg/kg of AFE significantly (p < 0.01) lowered random blood glucose level of non-fasted normoglycemic mice. AFE significantly lowered total cholesterol and triglyceride levels while increasing the HDL levels in the serum. Further, AFE significantly inhibited the glucose absorption from the lumen of the intestine and it increases the diaphragm uptake of glucose. Alpha-amylase inhibitory activity was also evident. However, AFE did not induce any overt signs of toxicity or hepatotoxicity. There were no adverse effects on food and water intake and body weight of mice during the experimental period. It can be concluded that AFE of N. arbor-tristis posses safe oral anti diabetic potentials mediated via multiple mechanisms. Results of the present study scientifically proved the claims made about the uses of N. arbor-tristis in the treatment of diabetes mellitus in traditional Sri Lankan medicinal system. Further, flowers can also be used for as a remedy to improve blood lipid profile.

Keywords: aqueous extract, hypoglycemic hypolipidemic, Nyctanthes arbor-tristis flowers, hepatotoxicity

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Authors: Alvarez Barrantes, Robert Dorrell, Christopher Hackney, Anne Baar, Roberto Fernandez, Daniel Parsons

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Microplastic particles entering fluvial environments are deposited with natural sediments. Their settling properties can change by the absorption or adsorption of contaminants, organic matter, and organisms. These deposits include positively, neutrally, and negatively buoyant particles. This study aims to understand how plastic particles of different densities interact with natural sediments as they settle and how they are stored within the sediment deposit. The results of this study contribute to a better understanding of the deposition of microplastic particles and associated pollution in rivers. A set of 48 experiments was designed to investigate the settling process of microplastic particles in freshwater. The experimental work describes the vertical variation of cohesive and/or non-cohesive sediment versus microplastic densities in deposited sediment. The experiment consisted of adding microplastic particles, sediment, and water in a waterproof carton tube of a height of 24 cm and a diameter of 5 cm. The plastic selected is positively, neutrally, and negatively buoyant. The sediments consist of sand and clay with four different concentrations. The mixture of materials was shaken until is thoroughly mixed and left to settle for 24 hours. After the settlement, the tubes were frozen at -20 °C to be able to cut them and measure the thickness of the deposits and analyze the sediment and plastic distribution. The most representative experiments were repeated in a glass tube of the same size; to analyse the influences of current flows and depositional process. Finally, the glass tube experiments were used to study organic materials adsorption in plastic, settling the sample for four months. Defined microplastic layers were identified as the density of the plastic change. Preliminary results show that most of the positive buoyancy particles floated, neutral buoyancy particles form a layer above the sediment and negative buoyancy particles mixed with the sediment. The vertical grain size distribution of the deposits was analysed to determine deposition variation with and without plastic. It is expected that the positively buoyant particles are trapped in the sediment by the currents flows and sink due to organic material adsorption. Finally, the experiments will explain how microplastic particles, including positively buoyant ones, are stored in natural sediment deposits.

Keywords: microplastic adsorption process, microplastic deposition in natural sediment, microplastic pollution in rivers, storages of positive buoyancy microplastic particles

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Authors: Rachid Belhachemi, Pierre Rostan, Alexandra Rostan

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This paper develops a discrete-time option pricing model for index options. The model consists of two key ingredients. First, daily stock return innovations are driven by a continuous hidden threshold mixed skew-normal (HTSN) distribution which generates conditional non-normality that is needed to fit daily index return. The most important feature of the HTSN is the inclusion of a latent state variable with a continuum of states, unlike the traditional mixture distributions where the state variable is discrete with little number of states. The HTSN distribution belongs to the class of univariate probability distributions where parameters of the distribution capture the dependence between the variable of interest and the continuous latent state variable (the regime). The distribution has an interpretation in terms of a mixture distribution with time-varying mixing probabilities. It has been shown empirically that this distribution outperforms its main competitor, the mixed normal (MN) distribution, in terms of capturing the stylized facts known for stock returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence. Second, heteroscedasticity in the model is captured by a threeexogenous-factor GARCH model (GARCHX), where the factors are taken from the principal components analysis of various world indices and presents an application to option pricing. The factors of the GARCHX model are extracted from a matrix of world indices applying principal component analysis (PCA). The empirically determined factors are uncorrelated and represent truly different common components driving the returns. Both factors and the eight parameters inherent to the HTSN distribution aim at capturing the impact of the state of the economy on price levels since distribution parameters have economic interpretations in terms of conditional volatilities and correlations of the returns with the hidden continuous state. The PCA identifies statistically independent factors affecting the random evolution of a given pool of assets -in our paper a pool of international stock indices- and sorting them by order of relative importance. The PCA computes a historical cross asset covariance matrix and identifies principal components representing independent factors. In our paper, factors are used to calibrate the HTSN-GARCHX model and are ultimately responsible for the nature of the distribution of random variables being generated. We benchmark our model to the MN-GARCHX model following the same PCA methodology and the standard Black-Scholes model. We show that our model outperforms the benchmark in terms of RMSE in dollar losses for put and call options, which in turn outperforms the analytical Black-Scholes by capturing the stylized facts known for index returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence.

Keywords: continuous hidden threshold, factor models, GARCHX models, option pricing, risk-premium

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Authors: Pooria Pasbakhsh, Rangika T. De Silva, Vahdat Vahedi, Hanafi Ismail

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The influence of three different types of halloysite nanotubes (HNTs) with different dimensions, namely as camel lake (CLA), Jarrahdale (JA) and Matauri Bay (MB), on their reinforcing ability of ethylene propylene dine monomer (EPDM) were investigated by varying the HNTs loading (from 0-15 phr). Mechanical properties of the nanocomposites improved with addition of all three HNTs, but CLA based nanocomposites exhibited a significant enhancement compared to the other HNTs. For instance, tensile properties of EPDM nanocomposites increased by 120%, 256% and 340% for MB, JA, and CLA, respectively with addition of 15 phr of HNTs. This could be due to the higher aspect ratio and higher surface area of CLA compared to others. Scanning electron microscopy (SEM) of nanocomposites at 15 phr of HNT loadings showed low amounts of pulled-out nanotubes which confirmed the presence of more embedded nanotubes inside the EPDM matrix, as well as aggregates within the fracture surface of EPDM/HNT nanocomposites.

Keywords: aspect ratio, halloysite nanotubes (HNTs), mechanical properties, rubber/clay nanocomposites

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Authors: Samar Aoujia, Théo Guérineaub, Rayan Zaitera, Evelyne Fargina, Younès Messaddeqb, Thierry Cardinala

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Two barium gallo-germanate glass series were elaborated to investigate the effect of the yttrium introduction on the glass physicochemical properties and crystallization behavior. One to twenty mol% of YO3/2 were either added into the glass matrix or substituted for gallium oxide. The glass structure was studied by Raman spectroscopy, and the thermal, optical, thermo-mechanical and physical properties are examined. The introduction of yttrium ions in both glass series increases the glass transition temperature, crystallization temperature, softening temperature, coefficient of linear thermal expansion and density. Through differential scanning calorimetry and X-ray diffraction analyses, it was found that competition occurs between the gallo-germanate zeolite-type phase and the yttrium-containing phase. From 13 mol% of YO3/2, the yttrium introduction impedes the formation of surface crystallization in these glasses.

Keywords: photonic, heavy-metal oxide, glass, crystallization

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Authors: John A. Morales, Guillermo Guidi, B. M. Keune

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Electric Power supply is a crucial topic for economic and social development. Power outages statistics show that discharges atmospherics are imperative phenomena to produce those outages. In this context, it is necessary to correctly detect when overhead line insulators are faulted. In this paper, an algorithm to detect if a lightning stroke generates or not permanent fault on insulator strings is proposed. On top of that, lightning stroke simulations developed by using the Alternative Transients Program, are used. Based on these insights, a novel approach is designed that depends on mother functions analysis corresponding to the given variance-covariance matrix. Signals registered at the insulator string are projected on corresponding axes by the means of Principal Component Analysis. By exploiting these new axes, it is possible to determine a flashover characteristic zone useful to a good insulation design. The proposed methodology for flashover detection extends the existing approaches for the analysis and study of lightning performance on transmission lines.

Keywords: mother function, outages, lightning, sensitivity analysis

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Authors: Esther Lorrayne M. Pereira, Adriana S. M. Batista, Fabíola A. S. Ribeiro, Adelina P. Santos, Luiz O. Faria

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In this work we have prepared nanocomposites made by mixing Poli (vinilidene fluoride) (PVDF), zirconium oxide (ZrO₂) and multi–walled carbon nanotubes (MWCNTs) aiming to find dosimetric properties for applications in high dose dosimetry. The samples were irradiated with a Co-60 source at constant dose rate (16.7 kGy/h), with doses ranging from 100 to 2750 kGy. The UV-Vis and FTIR spectrophotometry have been used to monitor the appearing of C=C conjugated bonds and radio-oxidation of carbon (C=O). FTIR spectrometry has that the absorbance intensities at 1715 cm⁻¹ and 1730 cm⁻¹ can be used for high dosimetry purposes for gamma doses ranging from 500 to 2750 kGy. In this range, it is possible to observe a linear relationship between Abs & Dose. Fading of signal was evaluated for one month and reproducibility in 2000 kGy dose. Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDX) was used for evaluated the dispersion ZrO₂ and MWCNT in the matrix of the PVDF.

Keywords: polymer, composite, high dose dosimetry, PVDF/ZrO₂/MWCNT

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Authors: Preeti Makkar, R. C. Agarwala, Vijaya Agarwala

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The present study focuses on the preparation of Al2O3 nanoparticles by top down approach i.e. mechanical milling using high energy planetary ball mill at 250 rpm for 40h. The milled Al2O3 nanoparticles are then used as the second phase to develop electroless (EL) Ni-P- Al2O3 nanocomposite coatings on mild steel substrate. An alkaline bath was used with a suspension of Al2O3 particles (4 g/L) for the synthesis of Ni-P-Al2O3 nanocomposite coating. The surface morphology, size range and phase analysis of as-prepared Al2O3 particles and the coatings were characterized using X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM). The coatings were heat treated at 400°C for 1h in argon atmosphere and the hardness of the nanocomposite coatings was investigated with respect to Ni-P before and after heat treatment. The results showed that as milled Al2O3 nanoparticles exhibit irregular shaped and size ranges around 40-45 nm. The Al2O3 particles are uniformly distributed in Ni-P matrix. The microhardness of the coatings is found to be significantly improved after heat treatment (1126 VHN).

Keywords: Electroless (EL), Ni-P-Al2O3, nanocomposite, mechanical milling, microhardness

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Authors: Hamioud Saida, Khalfallah Salah

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In this study, a spectral element method is employed to predict the free vibration of a Euler-Bernoulli beam resting on a Winkler foundation with elastically restrained ends. The formulation of the dynamic stiffness matrix has been established by solving the differential equation of motion, which was transformed to frequency domain. Non-dimensional natural frequencies and shape modes are obtained by solving the partial differential equations, numerically. Numerical comparisons and examples are performed to show the effectiveness of the SEM and to investigate the effects of various parameters, such as the springs at the boundaries and the elastic foundation parameter on the vibration frequencies. The obtained results demonstrate that the present method can also be applied to solve the more general problem of the dynamic analysis of structures with higher order precision.

Keywords: elastically supported Euler-Bernoulli beam, free-vibration, spectral element method, Winkler foundation

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Authors: Nilgun Becenen

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In this study, the structural properties of composite materials with the plastic matrix, which are used in body parts of urban furniture were investigated. Surfaces of the specimens were observed by scanning electron microscopy (SEM: JSM-5200, JEOL) and Climatic environmental test analyses in laboratory conditions were used to analyze the performance of the composite samples. Climate conditions were determined as follow; 3 hour working under the conditions of -10 ºC heat and 20 % moisture, Heating until 45 ºC for 4 hours, 3 hour work at 45 ºC, 3 hour work under the conditions of 45 ºC heat and 80 % moisture, Cooling at -10 ºC for 4 hours. In this cycle, the atmospheric conditions that urban furniture would be exposed to in the open air were taken into consideration. Particularly, sudden heat changes and humidity effect were investigated. The climate conditions show that performance in Low Temperatures: The endurance isn’t affected, hardness does not change, tensile, bending and impact resistance does not change, the view isn’t affected. It has a high environmental performance.

Keywords: fibre-reinforced material, glass fiber, textile science, polymer composites

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Authors: Ananya Govindarajan

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Tetrahymena thermophila is a single-cell, eukaryotic organism that belongs to the Protozoa Kingdom. Tetrahymena thermophila is often used in signal transduction pathway studies because of its ability to model sensory input and the effects of environmental conditions such as chemicals and temperature. The recently discovered G37 chemorepellent receptor showed increased responsiveness to all chemorepellents. Investigating the mutant G37 Tetrahymena gene in various test solutions, including ferric chloride, ferrous sulfate, hydrogen peroxide, tetrazolium blue, potassium chloride, and dithiothreitol were performed to determine the role of oxidants and reducing agents with the mutant and wild-type cells (CU427) to assess the role of the receptor. Behavioral assays and recordings processed by ImageJ indicated that ferric chloride, hydrogen peroxide, and tetrazolium blue yielded little to no chemorepellent responses from G37 cells (<20% ARs). CU427 cells were over-responsive based on the mean percent of cells (>50% ARs). Reducing agents elicited chemorepellent responses from both G37 and CU427, in addition to potassium chloride. Cell responses were classified as over-responsive (>50% ARs). Dithiothreitol yielded unexpected results as G37 (37.0% ARs) and CU427 (38.1% ARs) had relatively similar responses and were only responsive and not over-responsive to the reducing agent test chemical solution. Ultimately, this indicates that the G37 receptor is more interactive with molecules that are reducing agents or non-oxidant compounds; G37 may be unable to sense and respond to oxidants effectively, further elucidating the pathways of the G37 strain and nature of this receptor. Results also indicate that the CSF most likely contained an oxidant, like ferric chloride. This research can be further applied to neuronal influences and how specific compounds may affect human neurons individually and their excitability as the responses model action potentials and membrane potential.

Keywords: tetrahymena thermophila, signal transduction, chemosensory, oxidant, reducing agent

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Authors: Juraj Belan, Lenka Hurtalová, Eva Tillová, Alan Vaško, Milan Uhríčik

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High-pressure turbine (HPT) blades of DV–2 jet engines are made from Ni–base superalloy, a former Soviet Union production, specified as ŽS6K. For improving its high-temperature resistance are blades covered with Al–Si diffusion layer. A regular operation temperature of HPT blades vary from 705°C to 750°C depending on jet engine regime. An over-crossing working temperature range causes degradation of protective alitize layer as well as base material–gamma matrix and gamma prime particles what decreases turbine blade lifetime. High-temperature degradation has mainly diffusion mechanism and causes coarsening of strengthening phase gamma prime and protective alitize layer thickness growing. All changes have a significant influence on high-temperature properties of base material.

Keywords: alitize layer, gamma prime phase, high-temperature degradation, Ni–base superalloy ŽS6K, turbine blade

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Authors: A. Adetutu, T. M. Awodugba, O. A. Owoade

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The development of resistance to currently known conventional anti-typhoid drugs has necessitated search into cheap, more potent and less toxic anti-typhoid drugs of plant origin. Therefore, this study investigated the anti-typhoid activity of fractions of A. indica in Salmonella typhi infected rats. Leaves of A. indica were extracted in methanol and fractionated into n-hexane, chloroform, ethyl-acetate, and aqueous fractions. The anti-salmonella potentials of fractions of A. indica were assessed via in-vitro inhibition of S. typhi using agar well diffusion, Minimum Inhibitory Concentration (MIC), Minimum Bactericidal Concentration (MBC) and biofilm assays. The biochemical and haematological parameters were determined by spectrophotometric methods. The histological analysis was performed using Haematoxylin and Eosin staining methods. Data analysis was performed by one-way ANOVA. Results of this study showed that S. typhi was sensitive to aqueous and chloroform fractions of A. indica, and the fractions showed biofilm inhibition at concentrations of 12.50, 1.562, and 0.39 mg/mL. In the in-vivo study, the extract and chloroform fraction had significant (p < 0.05) effects on the number of viable S. typhi recovered from the blood and stopped salmonellosis after 6 days of treatment of rats at 500 mg/kg b.w. Treatments of infected rats with chloroform and aqueous fractions of A. indica normalized the haematological parameters in the animals. Similarly, treatment with fractions of the plants sustained a normal antioxidant status when compared with the normal control group. Chloroform and ethyl-acetate fractions of A. indica reversed the liver and intestinal degeneration induced by S. typhi infection in rats. The present investigation indicated that the aqueous and chloroform fractions of A. indica showed the potential to provide an effective treatment for salmonellosis, including typhoid fever. The results of the study may justify the ethno-medicinal use of the extract in traditional medicine for the treatment of typhoid and salmonella infections.

Keywords: Azadirachta indica L, salmonella, typhoid, leave fractions

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Authors: Mehrangiz Rezaee, Zabih Charrahi

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In the last decade, with increasing tourism destinations and tourism growth, we are witnessing the widespread impacts of tourism on the economy, environment and society. Tourism and its related economy are now undergoing a transformation and as one of the key pillars of business economics, it plays a vital role in the world economy. Activities related to tourism and providing services appropriate to it in an area, like many economic sectors, require the necessary context on its origin. Given the importance of tourism industry and tourism potentials of Yazd province in Iran, it is necessary to use a proper procedure for prioritizing different areas for proper and efficient planning. One of the most important goals of planning is foresight and creating balanced development in different geographical areas. This process requires an accurate study of the areas and potential and actual talents, as well as evaluation and understanding of the relationship between the indicators affecting the development of the region. At the global and regional level, the development of tourist resorts and the proper distribution of tourism destinations are needed to counter environmental impacts and risks. The main objective of this study is the sustainable development of suitable tourism areas. Given that tourism activities in different territorial areas require operational zoning, this study deals with the evaluation of territorial tourism using concepts such as land use, fitness and sustainable development. It is essential to understand the structure of tourism development and the spatial development of tourism using land use patterns, spatial planning and sustainable development. Tourism spatial planning implements different approaches. However, the development of tourism as well as the spatial development of tourism is complex, since tourist activities can be carried out in different areas with different purposes. Multipurpose areas have great important for tourism because it determines the flow of tourism. Therefore, in this paper, by studying the development and determination of tourism suitability that is related to spatial development, it is possible to plan tourism spatial development by developing a model that describes the characteristics of tourism. The results of this research determine the suitability of multi-functional territorial tourism development in line with spatial planning of tourism.

Keywords: land use change, spatial planning, sustainability, territorial tourist, Yazd

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Authors: Omer Yeni

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Ground strata failure or fall-of-ground is one of the underground mines' most prominent catastrophic risks. Mining companies use various methods/technics to prevent and critically control the associated risks. Some of those are safety by design, excavation methods, ground support, training, and competency, which all require quality control and assurance activities to confirm their efficiencies and performances and identify improvement opportunities through monitoring. However, many mining companies use quality control (QC) methods without quality assurance (QA), and they call it QA/QC together as a habit. From a simple definition, QC is a method of detecting defects, and QA is a method of preventing defects. Testing the final products at the end of the production line is not the way of proper QA/QC application but testing every component before assembly and the final product once completed. The installed ground support elements are some final products mining companies use to prevent ground strata failure. Testing the final product (i.e., rock bolt pull testing, shotcrete strength test, etc.) with QC methods only while those areas are already accessible; is not like testing an airplane full of passengers right after the production line or testing a car after the sale. Can only QC methods be called QA/QC? Can QA/QC activities be numerically scored for each critical control implemented to assess ground strata failure potential? Can numerical scores be used to identify Geotechnical Risk Rating (GRR) to determine the ground strata failure risk and its probability? This paper sets out to provide a specific QA/QC methodology to manage and confirm efficiencies and performances of the implemented critical controls and a numerical approach through the Geotechnical Risk Rating (GRR) process to assess ground strata failure risk to determine the gaps where proactive action is required to evaluate the probability of ground strata failures in underground mines.

Keywords: fall of ground, ground strata failure, QA/QC, underground

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Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

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Authors: Vincent Liu

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Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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Authors: Afshin Kadri

Abstract:

Using Renewable Energy Resources (RES) as a type of DG unit is developing in distribution systems. The connection of these generation units to existing AC distribution systems changes the structure and some of the operational aspects of these grids. Most of the RES requires to power electronic-based interfaces for connection to AC systems. These interfaces consist of at least one DC/AC conversion unit. Nowadays, grid-connected inverters must have the required feature to support the grid under sag voltage conditions. There are two curves in these conditions that show the magnitude of the reactive component of current as a function of voltage drop value and the required minimum time value, which must be connected to the grid. This feature is named low voltage ride-through (LVRT). Implementing this feature causes problems in the operation of the inverter that increases the amplitude of high-frequency components of the injected current and working out of maximum power point in the photovoltaic panel connected inverters are some of them. The important phenomenon in these conditions is ripples in the DC bus voltage that affects the operation of the inverter directly and indirectly. The losses of DC bus capacitors which are electrolytic capacitors, cause increasing their temperature and decreasing its lifespan. In addition, if the inverter is connected to the photovoltaic panels directly and has the duty of maximum power point tracking, these ripples cause oscillations around the operating point and decrease the generating energy. Using a bidirectional converter in the DC bus, which works as a buck and boost converter and transfers the ripples to its DC bus, is the traditional method to eliminate these ripples. In spite of eliminating the ripples in the DC bus, this method cannot solve the problem of reliability because it uses an electrolytic capacitor in its DC bus. In this work, a control method is proposed which uses the bidirectional converter as the fourth leg of the inverter and eliminates the DC bus ripples using an injection of unbalanced currents into the grid. Moreover, the proposed method works based on constant power control. In this way, in addition, to supporting the amplitude of grid voltage, it stabilizes its frequency by injecting active power. Also, the proposed method can eliminate the DC bus ripples in deep voltage drops, which cause increasing the amplitude of the reference current more than the nominal current of the inverter. The amplitude of the injected current for the faulty phases in these conditions is kept at the nominal value and its phase, together with the phase and amplitude of the other phases, are adjusted, which at the end, the ripples in the DC bus are eliminated, however, the generated power decreases.

Keywords: renewable energy resources, voltage drop value, DC bus ripples, bidirectional converter

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Authors: Smail Tigani, Mohamed Ouzzif

Abstract:

This work presents a discrete quantitative state prediction algorithm with intelligent behavior making it able to self-improve some performance aspects. The specificity of this algorithm is the capacity of self-rectification of the prediction strategy before the final decision. The auto-rectification mechanism is based on two parallel mathematical models. In one hand, the algorithm predicts the next state based on event transition matrix updated after each observation. In the other hand, the algorithm extracts its residues trend with a linear regression representing historical residues data-points in order to rectify the first decision if needs. For a normal distribution, the interactivity between the two models allows the algorithm to self-optimize its performance and then make better prediction. Designed key performance indicator, computed during a Monte Carlo simulation, shows the advantages of the proposed approach compared with traditional one.

Keywords: discrete state, Markov Chains, linear regression, auto-adaptive systems, decision making, Monte Carlo Simulation

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Authors: Haniye Dehestani, Yadollah Ordokhani

Abstract:

In this work, we present an efficient approach for solving variable-order time-fractional partial differential equations, which are based on Legendre and Laguerre polynomials. First, we introduced the pseudo-operational matrices of integer and variable fractional order of integration by use of some properties of Riemann-Liouville fractional integral. Then, applied together with collocation method and Legendre-Laguerre functions for solving variable-order time-fractional partial differential equations. Also, an estimation of the error is presented. At last, we investigate numerical examples which arise in physics to demonstrate the accuracy of the present method. In comparison results obtained by the present method with the exact solution and the other methods reveals that the method is very effective.

Keywords: collocation method, fractional partial differential equations, legendre-laguerre functions, pseudo-operational matrix of integration

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Authors: Hua Jin, Il Kim

Abstract:

The biocompatible tadpole-shaped polypeptides with one cyclic polypeptides ring and two alkyl chain tails were synthesized by N-heterocyclic carbine (NHC)-mediated ring-opening polymerization (ROP) of α-amino acid N-carboxyanhydrides (NCAs). First, the NHC precursor, denoted as [NHC(H)][HCO₃], with two alkyl chains at the nitrogen was prepared by a simple anion metathesis of imidazole(in)ium chlorides with KHCO₃. Then NHC releasing from the [NHC(H)][HCO₃] directly initiated the ROP of NCA to produce the cyclic polypeptides. Finally, the tadpole-shaped polypeptides with two regulable tails were obtained. The target polypeptides were characterized by nuclear magnetic resonance spectrum (1H NMR), Fourier transform infrared spectroscopy (FT-IR), gel permeation chromatography (GPC) and matrix-assisted laser desorption ionization-time of flight mass spectra (MALDI-TOF MS). This pioneering approach simplifies the synthesis procedures of tadpole-shaped polypeptides compared to other methods, which usually requires specific intramolecular ring-closure reaction.

Keywords: cyclic polypeptides, α-amino acid N-carboxyanhydrides, N-heterocyclic carbene, ring-opening polymerization, tadpole-shaped

Procedia PDF Downloads 187

Authors: Meng-Fei Cheng, Wei-Lun Chen, Han-Chang Ma, Chi-Che Tsai

Abstract:

Recent K–12 Taiwan Science Education Curriculum Guideline emphasize the essential role of modeling curriculum in science learning; however, few modeling curricula have been designed and adopted in current science teaching. Therefore, this study aims to develop modeling curriculum on electric circuits to investigate any learning difficulties students have with modeling curriculum and further enhance modeling teaching. This study was conducted with 44 10th-grade students in Central Taiwan. Data collection included a students’ understanding of models in science (SUMS) survey that explored the students' epistemology of scientific models and modeling and a complex circuit problem to investigate the students’ modeling abilities. Data analysis included the following: (1) Paired sample t-tests were used to examine the improvement of students’ modeling abilities and conceptual understanding before and after the curriculum was taught. (2) Paired sample t-tests were also utilized to determine the students’ modeling abilities before and after the modeling activities, and a Pearson correlation was used to understand the relationship between students’ modeling abilities during the activities and on the posttest. (3) ANOVA analysis was used during different stages of the modeling curriculum to investigate the differences between the students’ who developed microscopic models and macroscopic models after the modeling curriculum was taught. (4) Independent sample t-tests were employed to determine whether the students who changed their models had significantly different understandings of scientific models than the students who did not change their models. The results revealed the following: (1) After the modeling curriculum was taught, the students had made significant progress in both their understanding of the science concept and their modeling abilities. In terms of science concepts, this modeling curriculum helped the students overcome the misconception that electric currents reduce after flowing through light bulbs. In terms of modeling abilities, this modeling curriculum helped students employ macroscopic or microscopic models to explain their observed phenomena. (2) Encouraging the students to explain scientific phenomena in different context prompts during the modeling process allowed them to convert their models to microscopic models, but it did not help them continuously employ microscopic models throughout the whole curriculum. The students finally consistently employed microscopic models when they had help visualizing the microscopic models. (3) During the modeling process, the students who revised their own models better understood that models can be changed than the students who did not revise their own models. Also, the students who revised their models to explain different scientific phenomena tended to regard models as explanatory tools. In short, this study explored different strategies to facilitate students’ modeling processes as well as their difficulties with the modeling process. The findings can be used to design and teach modeling curricula and help students enhance their modeling abilities.

Keywords: electric circuits, modeling curriculum, science learning, scientific model

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Authors: Valentina Futoryanova, Hugh Hunt

Abstract:

One of the common failure modes of the diesel engine turbochargers is high cycle fatigue of the turbine wheel blades. Mistuning of the blades due to the casting process is believed to contribute to the failure mode. Laser vibrometer is used to characterize mistuning for a population of turbine wheels through the analysis of the blade response to piezo speaker induced noise. The turbine wheel design under investigation is radial and is typically used in 6-12 L diesel engine applications. Amplitudes and resonance frequencies are reviewed and summarized. The study also includes test results for a paddle wheel that represents a perfectly tuned system and acts as a reference. Mass spring model is developed for the paddle wheel and the model suitability is tested against the actual data. Randomization is applied to the stiffness matrix to model the mistuning effect in the turbine wheels. Experimental data is shown to have good agreement with the model.

Keywords: vibration, radial turbines, mistuning, turbine blades, modal analysis, periodic structures, finite element

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Authors: Khader S. Al-Aidmat, Venus W. Samawi

Abstract:

Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

Procedia PDF Downloads 371