Search results for: spectroscopy data analysis

Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

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Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: big data, big data analytics, Hadoop, cloud

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Authors: Afrah E. Mohammed, Mudawi M. Nour

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Environmentally friendly green synthesis of nanomaterial has a very significant part in nanotechnology. In the present research, the synthesis of silver nanoparticles (AgNPs) was established by treating silver ions with the aqueous extract of Calligonum comosum green shoots at room temperature. AgNPs formation was firstly detected by the colour change of mixed extract (plant extract and AgNO3). Further characterization was done by ultraviolet (UV)-Vis spectrophotometer, transmission electron microscopy (TEM), scanning electron microscopy (SEM), zeta potential and fourier transform infrared spectroscopy (FTIR). The peak values for UV-VIS- spectroscopy were in the range of 440 nm, TEM micrograph showed a spherical shape for the particles and zeta potential showed the formation of negative charged nanoparticles with an average size of about 105.8 nm. 1635.41 and 3249.83 cm−1 are the peaks detected from the FTIR analysis. In this study, biosynthesized silver nanoparticles mediated by C. comosum were tested for their antimycotic activity using a well diffusion method against fungal species; Aspergillus flavus, Penicillium sp, Fusarium oxysporum. Our findings indicated that biosynthesized AgNPs showed an efficient antimycotic activity against tested species. The antimycotic action of AgNPs varied according to different fungal species. Results confirmed the ability of C. comosum green shoot extract to act as an reducing and stabilizing agent during the synthesis of AgNPs.

Keywords: AGNPS, zeta potential, TEM, SEM

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Authors: Ayman M. M. Abdelhaleem, Mustafa Gamal Sadek, Kamal Reyad, Montasser M. Dewidar

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The main objective of this research is to study the effect of adding polycarbonate (PC) to pure Acrylonitrile Butadiene Styrene (ABS) using the injection moulding process. The PC was mixed mechanically with ABS in 10%, 20%, 30%, 40%, and 50% by weight. The mechanical properties of pure ABS reinforced with PC were investigated using tensile, impact, hardness, and wear tests. The results showed that, by adding 10%, 20%, 30%, 40%, and 50% wt. of PC to the pure ABS, the ultimate tensile strength increased from 55 N/mm2 for neat ABS to 57 N/mm2 (i.e. 3.63%), 60 N/mm2 (i.e. 9.09%), 63 N/mm2 (i.e. 14.54%), 66 N/mm2 (i.e. 20%), 69 N/mm2 (i.e. 25.45%) respectively. Test results also revealed nearly 5.72% improvement in young's modulus by adding 10% of PC to ABS, 16.74% improvement by adding 20%, 23.34% improvement by adding 30%, 27.75% improvement by adding 40%, and no other increase in case of 50%. The impact test results showed that with the increase of the PC content, first, the impact strength decreased and then increased gradually. The impact strength decreased rapidly when the content of PC was 0% to 10% range. As well as, in the case of 20%, 30%, 40%, and 50% PC, the impact strength is increased. The hardness test results, using the Shore D tester, showed that, as the PC particles contents increased, the hardness increased from 76 for the ABS to 80 for 10% PC, and decreased to 79 for 20% PC, and then increased to 80 in case of 30%, 40%, and 50% PC. Wear test results showed that PC improves the wear resistance of ABS/PC blends. Positron annihilation lifetime spectroscopy showed that with an increase of PC in ABS/PC blends, a slight decrease in free volume size and an increase in the tensile strength due to good adhesion between PC and ABS matrix, which acted as an advantage in the polymer matrix.

Keywords: ABS, PC, injection molding process, mechanical properties, lifetime spectroscopy

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Authors: Kheira Hamaida, Mohamed Salah Halati

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In this current paper, our aim work is to link as possible the obtained simulation results and the other experimental ones, just focusing on the electronic and optical properties of ZnSe. The predictive spectra of the total and partial densities of states using the Full Potential Linearized/Augmented Plane Wave method with the newly Tran-Blaha (TB) modified Becke-Johnson (mBJ) exchange-correlation potential (EXC). So the upper valence energy (UVE) levels contain the relative contribution of Se-(4p and 3d) states with considerable contribution from the electrons of Zn-2s orbital. The dielectric function of w-ZnSe, with its two parts, appears with a noticeable anisotropy character. The microscopic origins of the electronic states that are responsible for the observed peaks in the spectrum are determined through the decomposition of the spectrum to the individual contributions of the electronic transitions between the pairs of bands, where Vi is an occupied state in the valence band, and Ci is an unoccupied state in the conduction band. X-PES (X Ray-Photo Electron Spectroscopy) is an important technique used to probe the homogeneity, stoichiometry, and purity state of the title compound. In order to check the electron transitions derived from simulations and the others from Reflected Electron Energy Loss Spectroscopy (REELS) technique which was of great sensitivity, is used to determine the interband electronic transitions. In the optical window (Eg), all the electron energy states created were also determined through the specific gaussian deconvolution of the photoluminescence spectrum (PLS) that probed under a room temperature (RT).

Keywords: spectroscopy, WIEN2K, IIB-VIA semiconductors, dielectric function

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Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

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There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

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Authors: Raghvendra Singh Yadav, Ivo Kuritka, Jarmila Vilcakova, Pavel Urbanek, Michal Machovsky, David Skoda, Milan Masar

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The elastomer nanocomposites were synthesized by solution mixing method with an elastomer as a matrix and in situ thermally reduced graphene oxide (RGO) and spinel ferrite NiFe₂O₄ nanoparticles as filler. Spinel ferrite NiFe₂O₄ nanoparticles were prepared by the starch-assisted sol-gel auto-combustion method. The influence of filler on the microstructure, morphology, dielectric, electrical and magnetic properties of Reduced Graphene Oxide-Nickel Ferrite-Elastomer nanocomposite was characterized by X-ray diffraction, Raman spectroscopy, Fourier transform infrared spectroscopy, field emission scanning electron microscopy, X-ray photoelectron spectroscopy, the Dielectric Impedance analyzer, and vibrating sample magnetometer. Scanning electron microscopy study revealed that the fillers were incorporated in elastomer matrix homogeneously. The dielectric constant and dielectric tangent loss of nanocomposites was decreased with the increase of frequency, whereas, the dielectric constant increases with the addition of filler. Further, AC conductivity was increased with the increase of frequency and addition of fillers. Furthermore, the prepared nanocomposites exhibited ferromagnetic behavior. This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic – Program NPU I (LO1504).

Keywords: polymer-matrix composites, nanoparticles as filler, dielectric property, magnetic property

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Authors: Arpan Bera, Rini Ganguly, Raja Chakraborty, Amlan J. Pal

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To deal with the increasing demands for the high-density non-volatile memory devices, we need nano-sites with efficient and stable charge storage capabilities. We prepared nanocrystals (NCs) of inorganic perovskite, CsPbCl₃ coated with Cs₄PbCl₆, by colloidal synthesis. Due to the type-I band alignment at the junction, this core-shell composite is expected to behave as a charge trapping site. Using Scanning Tunneling Spectroscopy (STS), we investigated voltage-controlled resistive switching in this heterostructure by tracking the change in its current-voltage (I-V) characteristics. By applying voltage pulse of appropriate magnitude on the NCs through this non-invasive method, different resistive states of this system were systematically accessed. For suitable pulse-magnitude, the response jumped to a branch with enhanced current indicating a high-resistance state (HRS) to low-resistance state (LRS) switching in the core-shell NCs. We could reverse this process by using a pulse of opposite polarity. These two distinct resistive states can be considered as two logic states, 0 and 1, which are accessible by varying voltage magnitude and polarity. STS being a local probe in space enabled us to capture this switching at individual NC site. Hence, we claim a bright prospect of these core-shell NCs made of inorganic halide perovskites in future high density memory application.

Keywords: Core-shell perovskite, CsPbCl₃-Cs₄PbCl₆, resistive switching, Scanning Tunneling Spectroscopy

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Authors: S. S. Pati, L. Herojit Singh, A. C. Oliveira, V. K. Garg

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Chitosan functionalized Fe3O4-Au core shell nanoparticles have been prepared using a two step wet chemical approach using NaBH4 as reducing agent for formation of Au inethylene glycol. X-ray diffraction studies shows individual phases of Fe3O4 and Au in the as prepared samples with crystallite size of 5.9 and 11.4 nm respectively. The functionalization of the core-shell nanostructure with Chitosan has been confirmed using Fourier transform infrared spectroscopy along with signatures of octahedral and tetrahedral sites of Fe3O4 below 600cm-1. Mössbauer spectroscopy shows decrease in particle-particle interaction in presence of Au shell (72% sextet) than pure oleic coated Fe3O4 nanoparticles (88% sextet) at room temperature. At 80K, oleic acid coated Fe3O4 shows only sextets whereas the Chitosan functionalized Fe3O4 and Chitosan functionalized Fe3O4@Au core shell show presence of 5 and 11% doublet, respectively.

Keywords: core shell, drug delivery, gold nanoparticles, magnetic nanoparticles

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Authors: Yi-Chun Wu, Nai-Yun Chang, Chuan LI

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This study investigates a feasible range of composition for the mixture of gelatin and polyvinyl alcohol to form nanofibers by electrospinning. Gelatin, one of the most available naturally derived hydrogels of amino acids, is a popular choice for food additives, cosmetic ingredients, biomedical implants, or dressing of its non-toxic and biodegradable nature. Nevertheless, synthetic hydrogel polyvinyl alcohol has long been used as a thickening agent for adhesion purposes. Many biomedical devices are also containing polyvinyl-alcohol as a major content, such as eye drops and contact lenses. To discover appropriate compositions of gelatin and polyvinyl-alcohol for electrospun nanofibers, polymer solutions of different volumetric ratios between gelatin and polyvinyl alcohol were prepared for electrospinning. The viscosity, surface tension, pH value, and electrical conductance of polymer solutions were measured. On the nanofibers, the vibrational modes of molecular structures in nanofibers were investigated by Fourier-transform infrared spectroscopy. The morphologies and surface chemical elements of fibers were examined by the scanning electron microscope and the energy-dispersive X-ray spectroscopy. The hydrophilicity of nanofiberswas evaluated by the water contact angles on the surface of the fibers. To further test the biotoxicity of nanofibers, an in-vitro 3T3 fibroblasts culture further tested the biotoxicity of the electrospun nanofibers. Throughstatistical analyses of the experimental data, it is found that the polyvinyl-alcohol rich composition (the volumetric ratio of gelatin/polyvinyl-alcohol < 1) would be a preferable choice for the formation of nanofibers by the current setup of electrospinning. These electrospun nanofibers tend to be hydrophilic with no biotoxicity threat to the 3T3 fibroblasts.

Keywords: gelatin, polyvinyl-alcohol, nanofibers, electrospinning, spin coating

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Authors: J. R. Wang, H. C. Chen, C. Shih, S. W. Chen, J. H. Yang, Y. Chiang

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In this study, we focus on the establishment of the analysis model for Maanshan PWR nuclear power plant (NPP) by using RADTRAD and SNAP codes with the FSAR, manuals, and other data. In order to evaluate the cumulative dose at the Exclusion Area Boundary (EAB) and Low Population Zone (LPZ) outer boundary, Maanshan NPP RADTRAD/SNAP model was used to perform the analysis of the DBA LOCA case. The analysis results of RADTRAD were similar to FSAR data. These analysis results were lower than the failure criteria of 10 CFR 100.11 (a total radiation dose to the whole body, 250 mSv; a total radiation dose to the thyroid from iodine exposure, 3000 mSv).

Keywords: RADionuclide, transport, removal, and dose estimation (RADTRAD), symbolic nuclear analysis package (SNAP), dose, PWR

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Authors: Leila Samiee, Amir Yadegari, Saeedeh Tasharrofi

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In the work presented here, nitrogen-doped graphene materials were synthesized and used as metal-free electrocatalysts for oxygen reduction reaction (ORR) under alkaline conditions. Paraphenylenediamine was used as N precursor. The N-doped graphene was synthesized under hydrothermal treatment at 200°C. All the materials have been characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Transmission electron microscopy (TEM) and X-ray photo-electron spectroscopy (XPS). Moreover, for electrochemical evaluation of samples, Rotating Disk electrode (RDE) and Cyclic Voltammetry techniques (CV) were employed. The resulting material exhibits an outstanding catalytic activity for the oxygen reduction reaction (ORR) as well as excellent resistance towards methanol crossover effects, indicating their promising potential as ORR electrocatalysts for alkaline fuel cells.

Keywords: alkaline fuel cell, graphene, metal-free catalyst, paraphenylen diamine

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Authors: Hemant Kumar

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Brahmaputra River is known according to the Hindu mythology the son of the Lord Brahma. According to this name, the river Brahmaputra creates mass destruction during the monsoon season in Assam, India. It is a state situated in North-East part of India. This is one of the essential states out of the seven countries of eastern India, where almost all entire Brahmaputra flow carried out. The other states carry their tributaries. In the present case study, the spatial analysis performed in this specific case the number of MODIS data are acquired. In the method of detecting the change, the spray content was found during heavy rainfall and in the flooded monsoon season. By this method, particularly the analysis over the Brahmaputra outflow determines the flooded season. The charged particle-associated in aerosol content genuinely verifies the heavy water content below the ground surface, which is validated by trend analysis through rainfall spectrum data. This is confirmed by in-situ sampled view data from a different position of Brahmaputra River. Further, a Hyperion Hyperspectral 30 m resolution data were used to scan the sediment deposits, which is also confirmed by in-situ sampled view data from a different position.

Keywords: aerosol, change detection, spatial analysis, trend analysis

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Authors: Iveta Řepková

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The aim of this paper is to estimate the efficiency of the Slovak commercial banks employing the Data Envelopment Analysis (DEA) window analysis approach during the period 2003-2012. The research is based on unbalanced panel data of the Slovak commercial banks. Undesirable output was included into analysis of banking efficiency. It was found that most efficient banks were Postovabanka, UniCredit Bank and Istrobanka in CCR model and the most efficient banks were Slovenskasporitelna, Istrobanka and UniCredit Bank in BCC model. On contrary, the lowest efficient banks were found Privatbanka and CitiBank. We found that the largest banks in the Slovak banking market were lower efficient than medium-size and small banks. Results of the paper is that during the period 2003-2008 the average efficiency was increasing and then during the period 2010-2011 the average efficiency decreased as a result of financial crisis.

Keywords: data envelopment analysis, efficiency, Slovak banking sector, window analysis

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Authors: Hironori Karachi, Haruka Yamashita

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Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: data science, non-negative matrix factorization, missing data, quality of services

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Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

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This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

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Authors: L. Cesari, L. Canabady-Rochelle, F. Mutelet

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The thermal conversion of lignin produces bio-oils that contain many compounds with high added-value such as phenolic compounds. In order to efficiently extract these compounds, the possible use of choline bis(trifluoromethylsulfonyl)imide [Choline][NTf2] ionic liquid was explored. To this end, a multistep approach was implemented. First, binary (phenolic compound and solvent) and ternary (phenolic compound and solvent and ionic liquid) solutions were investigated. Eight binary systems of phenolic compound and water were investigated at atmospheric pressure. These systems were quantified using the turbidity method and UV-spectroscopy. Ternary systems (phenolic compound and water and [Choline][NTf2]) were investigated at room temperature and atmospheric pressure. After stirring, the solutions were let to settle down, and a sample of each phase was collected. The analysis of the phases was performed using gas chromatography with an internal standard. These results were used to quantify the values of the interaction parameters of thermodynamic models. Then, extractions were performed on synthetic solutions to determine the influence of several operating conditions (temperature, kinetics, amount of [Choline][NTf2]). With this knowledge, it has been possible to design and simulate an extraction process composed of one extraction column and one flash. Finally, the extraction efficiency of [Choline][NTf2] was quantified with real bio-oils from lignin pyrolysis. Qualitative and quantitative analysis were performed using gas chromatographic connected to mass spectroscopy and flame ionization detector. The experimental measurements show that the extraction of phenolic compounds is efficient at room temperature, quick and does not require a high amount of [Choline][NTf2]. Moreover, the simulations of the extraction process demonstrate that [Choline][NTf2] process requires less energy than an organic one. Finally, the efficiency of [Choline][NTf2] was confirmed in real situations with the experiments on lignin pyrolysis bio-oils.

Keywords: bio-oils, extraction, lignin, phenolic compounds

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Authors: Usman Qamar, Younus Javed

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Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and rough-sets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

Keywords: rough-sets, classification, feature selection, entropy, outliers, frequent itemset mining

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Authors: Marie Kudrnova, Jana Petru

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This study is part of the international research - Materials for Molten Salt Reactors (MSR) and addresses the part of the project dealing with the corrosion behavior of candidate construction materials. Inconel 625 was characterized by x-ray photoelectron spectroscopy (XPS) before and after high–temperature experiment in molten salt. The experiment was performed in a horizontal tube furnace molten salt reactor, at 450 °C in argon, at atmospheric pressure, for 150 hours. Industrially produced HITEC salt was used (NaNO3, KNO3, NaNO2). The XPS study was carried out using the ESCAProbe P apparatus (Omicron Nanotechnology Ltd.) equipped with a monochromatic Al Kα (1486.6 eV) X-ray source. The surface layer on alloy 625 after exposure contains only Na, C, O, and Ni (as NiOx) and Nb (as NbOx BE 206.8 eV). Ni was detected in the metallic state (Ni0 – Ni 2p BE-852.7 eV, NiOx - Ni 2p BE-854.7 eV) after a short Ar sputtering because the oxide layer on the surface was very thin. Nickel oxides can form a protective layer in the molten salt, but only future long-term exposures can determine the suitability of Inconel 625 for MSR.

Keywords: Inconel 625, molten salt, oxide layer, XPS

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Authors: Ali Asheibi

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The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

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Authors: Javiera Poblete, Fernando Gajardo, Katherina Fernandez

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Graphene, and its derivatives such as graphene oxide (GO), are emerging nanoscopic materials, with interesting physical and chemical properties. From them, it is possible to develop three-dimensional macrostructures, such as aerogels, which are characterized by a low density, high porosity, and large surface area, having a promising structure for the development of materials. The use of GO as a precursor of these structures provides a wide variety of materials, which can be developed as a result of the functionalization of their oxygenated groups, with specific compounds such as polyethylene glycol (PEG). The synthesis of aerogels of GO-PEG for non-covalent interactions has not yet been widely reported, being of interest due to its feasible escalation and economic viability. Thus, this work aims to develop a non-covalently functionalized GO-PEG aerogels and characterize them physicochemically. In order to get this, the GO was synthesized from the modified hummers method and it was functionalized with the PEG by polymer-assisted GO gelation (crosslinker). The gelation was obtained for GO solutions (10 mg/mL) with the incorporation of PEG in different proportions by weight. The hydrogel resulting from the reaction was subsequently lyophilized, to obtain the respective aerogel. The material obtained was chemically characterized by analysis of Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy and X-ray diffraction (XRD), and its morphology by scanning electron microscopy (SEM) images; as well as water absorption tests. The results obtained showed the formation of a non-covalent aerogel (FTIR), whose structure was highly porous (SEM) and with a water absorption values greater than 50% g/g. Thus, a methodology of synthesis for GO-PEG was developed and validated.

Keywords: aerogel, graphene oxide, polyethylene glycol, synthesis

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Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

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In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: simulation data, data summarization, spatial histograms, exploration, visualization

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Authors: Peter Thissen

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In this work, we report about the influence of the chemical potential of water on the carbonation reaction of wollastonite (CaSiO3) as model surface of cement and concrete. Total energy calculations based on density functional theory (DFT) combined with kinetic barrier predictions based on nudge elastic band (NEB) method show that the exposure of the water-free wollastonite surface to CO2 results in a barrier-less carbonation. CO2 reacts with the surface oxygen and forms carbonate (CO32-) complexes together with a major reconstruction of the surface. The reaction comes to a standstill after one carbonate monolayer has been formed. In case one water monolayer is covering the wollastonite surface, the carbonation is no more barrier-less, yet ending in a localized monolayer. Covered with multilayers of water, the thermodynamic ground state of the wollastonite completely changes due to a metal-proton exchange reaction (MPER, also called early stage hydration) and Ca2+ ions are partially removed from solid phase into the H2O/wollastonite interface. Mobile Ca2+ react again with CO2 and form carbonate complexes, ending in a delocalized layer. By means of high resolution time-of-flight secondary-ion mass-spectroscopy images (ToF-SIMS), we confirm that hydration can lead to a partially delocalization of Ca2+ ions on wollastonite surfaces. Finally, we evaluate the impact of our model surface results by means of Low Energy Ion Scattering (LEIS) spectroscopy combined with careful discussion about the competing reactions of carbonation vs. hydration.

Keywords: Calcium-silicate, carbonation, hydration, metal-proton exchange reaction

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Authors: Mehrnaz Mostafavi, Jalaledin Ghanavi

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This research investigates the production of nanoring structures through a chemical reduction approach, exploring gradual reduction processes assisted by reductant agents, leading to the formation of these specialized nanorings. The study focuses on the controlled reduction of metal atoms within these agents, crucial for shaping these nanoring structures over time. The paper commences by highlighting the wide-ranging applications of metal nanostructures across fields like Nanomedicine, Nanobiotechnology, and advanced spectroscopy methods such as Surface Enhanced Raman Spectroscopy (SERS) and Surface Enhanced Infrared Absorption Spectroscopy (SEIRA). Particularly, gold nanoparticles, especially in the nanoring configuration, have gained significant attention due to their distinctive properties, offering accessible spaces suitable for sensing and spectroscopic applications. The methodology involves utilizing human serum albumin as a reducing agent to create gold nanoparticles through a chemical reduction process. This process involves the transfer of electrons from albumin's carboxylic groups, converting them into carbonyl, while AuCl4− acquires electrons to form gold nanoparticles. Various characterization techniques like Ultraviolet–visible spectroscopy (UV-Vis), Atomic-force microscopy (AFM), and Transmission electron microscopy (TEM) were employed to examine and validate the creation and properties of the gold nanoparticles and nanorings. The findings suggest that precise and gradual reduction processes, in conjunction with optimal pH conditions, play a pivotal role in generating nanoring structures. Experiments manipulating optical properties revealed distinct responses in the visible and infrared spectrums, demonstrating the tunability of these nanorings. Detailed examinations of the morphology confirmed the formation of gold nanorings, elucidating their size, distribution, and structural characteristics. These nanorings, characterized by an empty volume enclosed by uniform walls, exhibit promising potential in the realms of Nanomedicine and Nanobiotechnology. In summary, this study presents a chemical synthesis approach using organic reducing agents to produce gold nanorings. The results underscore the significance of controlled and gradual reduction processes in crafting nanoring structures with unique optical traits, offering considerable value across diverse nanotechnological applications.

Keywords: nanoring structures, chemical reduction approach, gold nanoparticles, spectroscopy methods, nano medicine applications

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Authors: Rami Al Jafar, Paul Elliott, Konstantinos K. Tsilidis, Abbas Dehghan

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Although Ramadan fasting is a ritual that is practiced every year by millions of Muslims, studies on Ramadan fasting are still scarce. To the best of our knowledge, none of the previous studies comprehensively explored the effect on the metabolic profile. In London Ramadan Fasting Study, blood samples were collected from 81 participants before and 10-14 days after Ramadan. Blood samples were analysed using nuclear magnetic resonance (NMR) spectroscopy which covers 249 metabolites. Mixed-effects models were used to analyse collected data and assess the effect of Ramadan fasting on the metabolic profile. Our observational study involved 85 individuals with a mean age of 45.2 years, and 53.1% of them were males. After Ramadan, forty metabolites were affected significantly by Ramadan fasting. Most of these metabolites were metabolites ratios (24), and the rest were three Glycolysis, three ketone bodies, nine Lipoprotein subclasses and one inflammation marker. This study suggests that Ramadan fasting is significantly associated with changes in the metabolic profile. However, the changes are assumed to be temporary, and the long-term effect of these changes is unknown.

Keywords: metabolic profile, Ramadan fasting, metabolites, intermittent fasting

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Authors: Nadia Hammouda, Kamel Belmokre

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Organic coatings are widely employed in the corrosion protection of most metal surfaces, particularly steel. They provide a barrier against corrosive species present in the environment, due to their high resistance to oxygen, water and ions transport. This study focuses on the evaluation of corrosion protection performance of epoxy paint on the carbon steel surface in sea water by Electrochemical Impedance Spectroscopy (EIS). The electrochemical behavior of painted surface was estimated by EIS parameters that contained paint film resistance, paint film capacitance and double layer capacitance. On the basis of calculation using EIS spectrums it was observed that pore resistance (Rpore) decreased with the appearance of doubled layer capacitance (Cdl) due to the electrolyte penetration through the film. This was further confirmed by the decrease of diffusion resistance (Rd) which was also the indicator of the deterioration of paint film protectiveness.

Keywords: epoxy paints, carbon steel, electrochemical impedance spectroscopy, corrosion mechanisms, seawater

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Authors: Ubeyd Toçoğlu, Miraç Alaf, Hatem Akbulut

Abstract:

We present a work which was conducted in order to improve the cycle life of silicon based lithium ion battery anodes by utilizing novel composite structure. In this study, carbon coated nano sized (50-100 nm) silicon particles were embedded into Graphene/MWCNT silicon matrix to produce free standing silicon based electrodes. Also, conventional Si powder anodes were produced from Si powder slurry on copper current collectors in order to make comparison of composite and conventional anode structures. Free –standing composite anodes (binder-free) were produced via vacuum filtration from a well dispersion of Graphene, MWCNT and carbon coated silicon powders. Carbon coating process of silicon powders was carried out via microwave reaction system. The certain amount of silicon powder and glucose was mixed under ultrasonication and then coating was conducted at 200 °C for two hours in Teflon lined autoclave reaction chamber. Graphene which was used in this study was synthesized from well-known Hummers method and hydrazine reduction of graphene oxide. X-Ray diffraction analysis and RAMAN spectroscopy techniques were used for phase characterization of anodes. Scanning electron microscopy analyses were conducted for morphological characterization. The electrochemical performance tests were carried out by means of galvanostatic charge/discharge, cyclic voltammetry and electrochemical impedance spectroscopy.

Keywords: graphene, Li-Ion, MWCNT, silicon

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Authors: Nungki Rositaningsih, Emil Budianto

Abstract:

Starch has been widely used as an encapsulation material for drug delivery system. However, starch hydrogel is very easily degraded during metabolism in human stomach. Modification of this material is needed to improve the encapsulation process in drug delivery system, especially for gastrointestinal drug. In this research, three modified starch-based hydrogels are synthesized i.e. Crosslinked starch hydrogel, Semi- and Full- Interpenetrating Polymer Network (IPN) starch hydrogel using Poly(N-Vinyl-Pyrrolidone). Non-modified starch hydrogel was also synthesized as a control. All of those samples were compared as biomaterials, floating drug delivery, and their ability in loading drug test. Biomaterial characterizations were swelling test, stereomicroscopy observation, Differential Scanning Calorimetry (DSC), and Fourier Transform Infrared Spectroscopy (FTIR). Buoyancy test and stereomicroscopy scanning were done for floating drug delivery characterizations. Lastly, amoxicillin was used as test drug, and characterized with UV-Vis spectroscopy for loading drug observation. Preliminary observation showed that Full-IPN has the most dense and elastic texture, followed by Semi-IPN, Crosslinked, and Non-modified in the last position. Semi-IPN and Crosslinked starch hydrogel have the most ideal properties and will not be degraded easily during metabolism. Therefore, both hydrogels could be considered as promising candidates for encapsulation material. Further analysis and issues will be discussed in the paper.

Keywords: biomaterial, drug delivery system, interpenetrating polymer network, poly(N-vinyl-pyrrolidone), starch hydrogel

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Authors: M. Al Azri, M. Elzain, K. Bouziane, S. M. Chérif

Abstract:

n-Type 6H-SiC(0001) substrates were implanted with three fluencies of Mn+ 5x1015 Mn/cm2 (Mn content: 0.7%), 1x1016 (~2 %), and 5x1016 cm–2 (7%) with implantation energy of 80 keV and substrate temperature of 365ºC. The samples were characterized using Rutherford Backscattering and Channeling Spectroscopy (RBS/C), High-Resolution X-Ray Diffraction technique (HRXRD), micro-Raman Spectroscopy (μRS), and Superconducting Quantum Interference Device (SQUID) techniques. The aim of our work is to investigate implantation induced defects with dose and to study any correlation between disorder-composition and magnetic properties. In addition, ab-initio calculations were used to investigate the structural and magnetic properties of Mn-doped 6H-SiC. Various configurations of Mn sites and vacancy types were considered. The calculations showed that a substitutional Mn atom at Si site possesses larger magnetic moment than Mn atom at C site. A model is introduced to explain the dependence of the magnetic structure on site occupation. The magnetic properties of ferromagnetically (FM) and antiferromagnetically (AFM) coupled pairs of Mn atoms with and without neighboring vacancies have also been explored.

Keywords: ab-initio calculations, diluted magnetic semiconductors, magnetic properties, silicon carbide

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Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

Abstract:

The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

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Authors: Adji Achmad Rinaldo Fernandes

Abstract:

SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.

Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model

Procedia PDF Downloads 41