Search results for: features extraction

Authors: Wided Bakari, Patrice Bellot, Omar Trigui, Mahmoud Neji

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This article constitutes an opening to think of the modeling and analysis of Arabic texts in the context of a question-answer system. It is a question of exceeding the traditional approaches focused on morphosyntactic approaches. Furthermore, we present a new approach that analyze a text in order to extract correct answers then transform it to logical predicates. In addition, we would like to represent different levels of information within a text to answer a question and choose an answer among several proposed. To do so, we transform both the question and the text into logical forms. Then, we try to recognize all entailment between them. The results of recognizing the entailment are a set of text sentences that can implicate the user’s question. Our work is now concentrated on an implementation step in order to develop a system of question-answering in Arabic using techniques to recognize textual implications. In this context, the extraction of text features (keywords, named entities, and relationships that link them) is actually considered the first step in our process of text modeling. The second one is the use of techniques of textual implication that relies on the notion of inference and logic representation to extract candidate answers. The last step is the extraction and selection of the desired answer.

Keywords: NLP, Arabic language, question-answering, recognition text entailment, logic forms

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Authors: Velasco-Rendón María Del Carmen, Cuéllar-Bermúdez Sara Paulina, Parra-Saldívar Roberto

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Phycocyanin is a blue pigment protein with fluorescent activity produced by cyanobacteria. It has been recently studied to determine its anticancer, antioxidant and antiinflamatory potential. Since 2014 it was approved as a Generally Recognized As Safe (GRAS) proteic pigment for the food industry. Therefore, phycocyanin shows potential for the food, nutraceutical, pharmaceutical and diagnostics industry. Conventional phycocyanin extraction includes buffer solutions and ammonium sulphate followed by chromatography or ATPS for protein separation. Therefore, further purification steps are time-requiring, energy intensive and not suitable for scale-up processing. This work presents an alternative to conventional methods that also allows large scale application with commercially available equipment. The extraction was performed by exposing the dry biomass to mechanical cavitation and salting out with NaCl to use an edible reagent. Also, isoelectric point precipitation was used by addition of HCl and neutralization with NaOH. The results were measured and compared in phycocyanin concentration, purity and extraction yield. Results showed that the best extraction condition was the extraction by salting out with 0.20 M NaCl after 30 minutes cavitation, with a concentration in the supernatant of 2.22 mg/ml, a purity of 3.28 and recovery from crude extract of 81.27%. Mechanical cavitation presumably increased the solvent-biomass contact, making the crude extract visibly dark blue after centrifugation. Compared to other systems, our process has less purification steps, similar concentrations in the phycocyanin-rich fraction and higher purity. The contaminants present in our process edible NaCl or low pHs that can be neutralized. It also can be adapted to a semi-continuous process with commercially available equipment. This characteristics make this process an appealing alternative for phycocyanin extraction as a pigment for the food industry.

Keywords: extraction, phycocyanin, precipitation, scale-up

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Authors: Kolela J Nyembwe, Darlington C. Ashiegbu, Herman J. Potgieter

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Over the past few decades, the demand for metals has increased significantly. This has led to a decrease and decline of high-grade ore over time and an increase in mineral complexity and matrix heterogeneity. In addition to that, there are rising concerns about greener processes and a sustainable environment. Due to these challenges, the mining and metal industry has been forced to develop new technologies that are able to economically process and recover metallic values from low-grade ores, materials having a metal content locked up in industrially processed residues (tailings and slag), and complex matrix mineral deposits. Several methods to address these issues have been developed, among which are ionic liquids (IL), heap leaching, and bioleaching. Recently, the gas phase extraction technique has been gaining interest because it eliminates many of the problems encountered in conventional mineral processing methods. The technique relies on the formation of volatile metal complexes, which can be removed from the residual solids by a carrier gas. The complexes can then be reduced using the appropriate method to obtain the metal and regenerate-recover the organic extractant. Laboratory work on the gas phase have been conducted for the extraction and recovery of aluminium (Al), iron (Fe), copper (Cu), chrome (Cr), nickel (Ni), lead (Pb), and vanadium V. In all cases the extraction revealed to depend of temperature and mineral surface area. The process technology appears very promising, offers the feasibility of recirculation, organic reagent regeneration, and has the potential to deliver on all promises of a “greener” process.

Keywords: gas-phase extraction, hydrometallurgy, low-grade ore, sustainable environment

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Authors: Beata Pospiech

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Separation of metal ions from aqueous solutions is important as well as difficult process in hydrometallurgical technology. This process is necessary for obtaining of clean metals. Solvent extraction and membrane processes are well known as separation methods. Recently, ionic liquids (ILs) are very often applied and studied as extractants and carriers of metal ions from aqueous solutions due to their good extractability properties for various metals. This work discusses a method to separate copper(II) and iron(III) from hydrochloric acid solutions by solvent extraction and transport across polymer inclusion membranes (PIM) with the selected ionic liquids as extractants/ion carriers. Cyphos IL 101 (trihexyl(tetradecyl)phosphonium chloride), Cyphos IL 104 (trihexyl(tetradecyl)phosphonium bis(2,4,4 trimethylpentyl)phosphi-nate), trioctylmethylammonium thiosalicylate [A336][TS] and trihexyl(tetradecyl)phosphonium thiosalicylate [PR4][TS] were used for the investigations. Effect of different parameters such as hydrochloric acid concentration in aqueous phase on iron(III) and copper(II) extraction has been investigated. Cellulose triacetate membranes with the selected ionic liquids as carriers have been prepared and applied for transport of iron(IIII) and copper(II) from hydrochloric acid solutions.

Keywords: copper, iron, ionic liquids, solvent extraction

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Authors: Aghoutane Basma, Naama Amal, Talbi Hayat, El Manfalouti Hanae, Kartah Badreddine

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Aromatic and medicinal plants are used by man for different needs, including food and medicinal needs for their biological properties attributed mainly to phenolic compounds and for their antioxidant capacity. In our study, the aim is to compare three extraction solvents by evaluating the contents of phenolic compounds, the contents of flavonoids, and the antioxidant activities of extracts from different methods of extracting the aerial part of an endemic medicinal plant from Morocco. This activity was also confirmed by three methods (2,2-diphenyl-1-picrylhydrazyl (DPPH), antioxidant reducing power of iron (FRAP), and total antioxidant capacity (CAT)). The results showed that this plant is rich in polyphenols and flavonoids, as well as it has a very important antioxidant capacity in whatever the solvent or the extraction method. This suggests the importance of using extracts from this plant as a new natural source of food additives and potent antioxidants in the food industry.

Keywords: endemic plant of Morocco, phenolic compound, solvent, extraction technique, antioxidant activity

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Authors: I. Ahumada, L. Ascar, C. Pedraza, J. Montecino

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It has been found that the addition of biosolids to soil is beneficial to soil health, enriching soil with essential nutrient elements. Although this sludge has properties that allow for the improvement of the physical features and productivity of agricultural and forest soils and the recovery of degraded soils, they also contain trace elements, organic trace and pathogens that can cause damage to the environment. The application of these biosolids to land without the total reclamation and the treated wastewater can transfer these compounds into terrestrial and aquatic environments, giving rise to potential accumulation in plants. The general aim of this study was to evaluate the bioavailability of bisphenol A (BPA), and 17 α-ethynyl estradiol (EE2) in a soil-biosolid system using wheat (Triticum aestivum) plant assays and a predictive extraction method using a solution of hydroxypropyl-β-cyclodextrin (HPCD) to determine if it is a reliable surrogate for this bioassay. Two soils were obtained from the central region of Chile (Lo Prado and Chicauma). Biosolids were obtained from a regional wastewater treatment plant. The soils were amended with biosolids at 90 Mg ha-1. Soils treated with biosolids, spiked with 10 mgkg-1 of the EE2 and 15 mgkg-1 and 30 mgkg-1of BPA were also included. The BPA, and EE2 concentration were determined in biosolids, soils and plant samples through ultrasound assisted extraction, solid phase extraction (SPE) and gas chromatography coupled to mass spectrometry determination (GC/MS). The bioavailable fraction found of each one of soils cultivated with wheat plants was compared with results obtained through a cyclodextrin biosimulator method. The total concentration found in biosolid from a treatment plant was 0.150 ± 0.064 mgkg-1 and 12.8±2.9 mgkg-1 of EE2 and BPA respectively. BPA and EE2 bioavailability is affected by the organic matter content and the physical and chemical properties of the soil. The bioavailability response of both compounds in the two soils varied with the EE2 and BPA concentration. It was observed in the case of EE2, the bioavailability in wheat plant crops contained higher concentrations in the roots than in the shoots. The concentration of EE2 increased with increasing biosolids rate. On the other hand, for BPA, a higher concentration was found in the shoot than the roots of the plants. The predictive capability the HPCD extraction was assessed using a simple linear correlation test, for both compounds in wheat plants. The correlation coefficients for the EE2 obtained from the HPCD extraction with those obtained from the wheat plants were r= 0.99 and p-value ≤ 0.05. On the other hand, in the case of BPA a correlation was not found. Therefore, the methodology was validated with respect to wheat plants bioassays, only in the EE2 case. Acknowledgments: The authors thank FONDECYT 1150502.

Keywords: emerging compounds, bioavailability, biosolids, endocrine disruptors

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Authors: Mustapha Bouhoun Ali, Ahmed Yacine Badjah Hadj Ahmed, Mouloud Attou, Abdel Hamid Elias, Mohamed Amine Didi

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The extraction of uranium(VI) from aqueous solutions has been investigated using 1-hydroxyhexadecylidene-1,1-diphosphonic acid (HHDPA) and 1-hydroxydodecylidene-1,1-diphosphonic acid (HDDPA), which were synthesized and characterized by elemental analysis and by FT-IR, 1H NMR, 31P NMR spectroscopy. In this paper, we propose a tentative assignment for the shifts of those two ligands and their specific complexes with uranium(VI). We carried out the extraction of uranium(VI) by HHDPA and HDDPA from [carbon tetrachloride + 2-octanol (v/v: 90%/10%)] solutions. Various factors such as contact time, pH, organic/aqueous phase ratio and extractant concentration were considered. The optimum conditions obtained were: contact time = 20 min, organic/aqueous phase ratio = 1, pH value = 3.0 and extractant concentration = 0.3M. The extraction yields are more significant in the case of the HHDPA which is equipped with a hydrocarbon chain, longer than that of the HDDPA. Logarithmic plots of the uranium(VI) distribution ratio vs. pHeq and the extractant concentration showed that the ratio of extractant to extracted uranium(VI) (ligand/metal) is 2:1. The formula of the complex of uranium(VI) with the HHDPA and the DHDPA is UO2(H3L)2 (HHDPA and DHDPA are denoted as H4L). A spectroscopic analysis has showed that coordination of uranium(VI) takes place via oxygen atoms.

Keywords: liquid-liquid extraction, uranium(VI), 1-hydroxyalkylidene-1, 1-diphosphonic acids, HHDPA, HDDPA, aqueous solution

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Authors: Dmitry Yu. Korulkin, Raissa A. Muzychkina

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In review the generalized data about different methods of extraction, separation and purification of natural and modify anthraquinones is presented. The basic regularity of an isolation process is analyzed. Action of temperature, pH, and polarity of extragent, catalysts and other factors on an isolation process is revealed.

Keywords: anthraquinones; isolation; extraction; polarity; chromatography; precipitation; bioactivity; phytopreparation; chrysophanol; aloe-emodin; emodin; physcion.

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Ola A. Younis, Said Ghoul

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Systems running these days are huge, complex and exist in many versions. Controlling these versions and tracking their changes became a very hard process as some versions are created using meaningless names or specifications. Many versions of a system are created with no clear difference between them. This leads to mismatching between a user’s request and the version he gets. In this paper, we present a system versions meta-modeling approach that produces versions based on system’s features. This model reduced the number of steps needed to configure a release and gave each version its unique specifications. This approach is applicable for systems that use features in its specification.

Keywords: features, meta-modeling, semantic modeling, SPL, VCS, versioning

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Authors: T. Yılmaz, Ş. Tavman

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In this study, optimization of ultrasound assisted extraction (UAE) of hemicellulose based polysaccharides from plant waste material has been studied. Selected material is hazelnut skin. Extraction variables for the operation are extraction time, amplitude and application temperature. Optimum conditions have been evaluated depending on responses such as amount of wet crude polysaccharide, total carbohydrate content and dried sample. Pretreated hazelnut skin powders were used for the experiments. 10 grams of samples were suspended in 100 ml water in a jacketed vessel with additional magnetic stirring. Mixture was sonicated by immersing ultrasonic probe processor. After the extraction procedures, ethanol soluble and insoluble sides were separated for further examinations. The obtained experimental data were analyzed by analysis of variance (ANOVA). Second order polynomial models were developed using multiple regression analysis. The individual and interactive effects of applied variables were evaluated by Box Behnken Design. The models developed from the experimental design were predictive and good fit with the experimental data with high correlation coefficient value (R2 more than 0.95). Extracted polysaccharides from hazelnut skin are assumed to be pectic polysaccharides according to the literature survey of Fourier Transform Spectrometry (FTIR) analysis results. No more change can be observed between spectrums of different sonication times. Application of UAE at optimized condition has an important effect on extraction of hemicellulose from plant material by satisfying partial hydrolysis to break the bounds with other components in plant cell wall material. This effect can be summarized by varied intensity of microjets and microstreaming at varied sonication conditions.

Keywords: hazelnut skin, optimization, polysaccharide, ultrasound assisted extraction

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Authors: E. E. Tereshatov, M. Yu. Boltoeva, V. Mazan, M. F. Volia, C. M. Folden III

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Room temperature ionic liquids (RTILs) are a class of liquid organic salts with melting points below 20 °C that are considered to be environmentally friendly ‘designers’ solvents. Pure hydrophobic ILs are known to extract metallic species from aqueous solutions. The closest analogues of ionic liquids are deep eutectic solvents (DESs), which are a eutectic mixture of at least two compounds with a melting point lower than that of each individual component. DESs are acknowledged to be attractive for organic synthesis and metal processing. Thus, these non-volatile and less toxic compounds are of interest for critical metal extraction. The US Department of Energy and the European Commission consider indium as a key metal. Its chemical homologue, thallium, is also an important material for some applications and environmental safety. The aim of this work is to systematically investigate In and Tl extraction from aqueous solutions into pure fluorinated ILs and hydrophobic DESs. The dependence of the Tl extraction efficiency on the structure and composition of the ionic liquid ions, metal oxidation state, and initial metal and aqueous acid concentrations have been studied. The extraction efficiency of the TlXz3–z anionic species (where X = Cl– and/or Br–) is greater for ionic liquids with more hydrophobic cations. Unexpectedly high distribution ratios (> 103) of Tl(III) were determined even by applying a pure ionic liquid as receiving phase. An improved mathematical model based on ion exchange and ion pair formation mechanisms has been developed to describe the co-extraction of two different anionic species, and the relative contributions of each mechanism have been determined. The first evidence of indium extraction into new quaternary ammonium- and menthol-based hydrophobic DESs from hydrochloric and oxalic acid solutions with distribution ratios up to 103 will be provided. Data obtained allow us to interpret the mechanism of thallium and indium extraction into ILs and DESs media. The understanding of Tl and In chemical behavior in these new media is imperative for the further improvement of separation and purification of these elements.

Keywords: deep eutectic solvents, indium, ionic liquids, thallium

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, Rebecca K. Rossi, Yanmin Yuan, Xianpei Li

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The fiscal growth of any country hinges on the prudent administration of water resources. The river Yamuna and Ganga are measured as the life line of India as it affords the needs for life to endure. Earth observation over remote sensing images permits the precise description and identification of ingredients on the superficial from space and airborne platforms. Multiple and heterogeneous image sources are accessible for the same geographical section; multispectral, hyperspectral, radar, multitemporal, and multiangular images. In this paper, a taxonomical learning of the fluvial geomorphological features of river Yamuna and Ganga over doon valley using color fusion of multispectral remote sensing images was performed. Experimental results exhibited that the segmentation based colorization technique stranded on pattern recognition, and color mapping fashioned more colorful and truthful colorized images for geomorphological feature extraction.

Keywords: color fusion, geomorphology, fluvial processes, multispectral images, pattern recognition

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Authors: Stylianos Kampakis

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This paper presents a new algorithm for neural networks called “Input Dropout with Aggressive Re-weighting” (IDAR) aimed specifically at datasets with many useless features. IDAR combines two techniques (dropout of input neurons and aggressive re weighting) in order to eliminate the influence of noisy features. The technique can be seen as a generalization of dropout. The algorithm is tested on two different benchmark data sets: a noisy version of the iris dataset and the MADELON data set. Its performance is compared against three other popular techniques for dealing with useless features: L2 regularization, LASSO and random forests. The results demonstrate that IDAR can be an effective technique for handling data sets with many useless features.

Keywords: neural networks, feature selection, regularization, aggressive reweighting

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Authors: Jawad Alzeer

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Natural products are well recognized as sources of drugs in several human ailments. To investigate the impact of variable extraction techniques on the cytotoxic effects of medicinal plant extracts, 5 well-known medicinal plants from Palestine were extracted with 90% ethanol, 80% methanol, acetone, coconut water, apple vinegar, grape vinegar or 5% acetic acid. The resulting extracts were screened for cytotoxic activities against three different cancer cell lines (B16F10, MCF-7, and HeLa) using a standard resazurin-based cytotoxicity assay and Nile Blue A as the positive control. Highly variable toxicities and tissue sensitivity were observed, depending upon the solvent used for extraction. Acetone consistently gave lower extraction yields but higher cytotoxicity, whereas other solvent systems gave much higher extraction yields with lower cytotoxicity. Interestingly, coconut water was found to offer a potential alternative to classical organic solvents; it gave consistently highest extraction yields, and in the case of S. officinalis L., highly toxic extracts towards MCF-7 cells derived from human breast cancer. These results demonstrate how the cytotoxicity of plant extracts can be inversely proportional to the yield, and that solvent selection plays an important role in both factors.

Keywords: plant extract, natural products, anti cancer drug, cytotoxicity

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Authors: Gracious Tendai Matayaya

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The world is facing problems in finding alternative resources to offset the decline in global petroleum reserves. The use of fossil fuels has prompted biofuel development, particularly in the transportation sector. In these circumstances, looking for alternative renewable energy sources makes sense. Petroleum-based fuels also result in a lot of carbon dioxide being released into the environment causing global warming. Replacing petroleum and fossil fuel-based fuels with biofuels has the advantage of reducing undesirable aspects of these fuels, which are mostly the production of greenhouse gas and dependence on unstable foreign suppliers. Algae refer to a group of aquatic microorganisms that produce a lot of lipids up to 60% of their total weight. This project aims to exploit the large amounts of oil produced by these microorganisms in the Soxhlet extraction to make biodiesel. Experiments were conducted to establish the cultivability of algae, harvesting methods, the oil extraction process, and the transesterification process. Although there are various methods for producing algal oil, the Soxhlet extraction method was employed for this particular research. After extraction, the oil was characterized before being used in the transesterification process that used methanol and hydrochloric acid as the process reactants. The properties of the resulting biodiesel were then determined. Because there is a requirement to dry wet algae, the experimental findings showed that Soxhlet extraction was the optimum way to produce a higher yield of microalgal oil. Upon cultivating algae, Compound D fertilizer was added as a source of nutrients (Phosphorous and Nitrogen), and the highest growth of algae was observed at 6 days (using 2 g of fertilizer), after which it started to decrease. Butanol, hexane, heptane and acetone have been experimented with as solvents, and heptane gave the highest amount of oil (89ml of oil) when 300 ml of solvent was used. This was compared to 73.21ml produced by butanol, 81.90 produced by hexane and 69.57ml produced by acetone, and as a result, heptane was used for the rest of the experiments, which included a variation of the mass of dried algae and time of extraction. This meant that the oil composition of algae was higher than other oil sources like peanuts, soybean etc. Algal oil was heated at 150℃ for 150 minutes in the presence of methanol (reactant) and hydrochloric acid (HCl), which was used as a catalyst. A temperature of 200℃ produced 93.64%, and a temperature of 250℃ produced 92.13 of biodiesel at 150 minutes.

Keywords: microalgae, algal oil, biodiesel, soxhlet extraction

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Authors: Hossein Tavallali, Mohammad Ali Karimi, Gohar Deilamy-Rad

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The proposed method for speciation, preconcentration and determination of Fe(II) and Fe(III) in pharmaceutical products was developed using of alumina-coated magnetite nanoparticles (Fe₃O₄/Al₂O₃ NPs) as solid phase extraction (SPE) sorbent in magnetic mixed hemimicell solid phase extraction (MMHSPE) technique followed by flame atomic absorption spectrometry analysis. The procedure is based on complexation of Fe(II) with 1, 10-phenanthroline (OP) as complexing reagent for Fe(II) that immobilized on the modified Fe₃O₄/Al₂O₃ NPs. The extraction and concentration process for pharmaceutical sample was carried out in a single step by mixing the extraction solvent, magnetic adsorbents under ultrasonic action. Then, the adsorbents were isolated from the complicated matrix easily with an external magnetic field. Fe(III) ions determined after facility reduced to Fe(II) by added a proper reduction agent to sample solutions. Compared with traditional methods, the MMHSPE method simplified the operation procedure and reduced the analysis time. Various influencing parameters on the speciation and preconcentration of trace iron, such as pH, sample volume, amount of sorbent, type and concentration of eluent, were studied. Under the optimized operating conditions, the preconcentration factor of the modified nano magnetite for Fe(II) 167 sample was obtained. The detection limits and linear range of this method for iron were 1.0 and 9.0 - 175 ng.mL⁻¹, respectively. Also the relative standard deviation for five replicate determinations of 30.00 ng.mL^-1 Fe²⁺ was 2.3%.

Keywords: Alumina-Coated magnetite nanoparticles, Magnetic Mixed Hemimicell Solid-Phase Extraction, Fe(ΙΙ) and Fe(ΙΙΙ), pharmaceutical sample

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Authors: Hossein Tavallali, Mohammad Ali Karimi, Gohar Deilamy-Rad

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In this study, a new type of alumina-coated magnetite nanoparticles (Fe3O4/Al2O3 NPs) with sodium dodecyl sulfate- 1-(2-pyridylazo)-2-naphthol (SDS-PAN) as a new sorbent solid phase extraction (SPE) has been successfully synthesized and applied for preconcentration and separation of Cd and Pb in environmental samples. Compared with conventional SPE methods, the advantages of this new magnetic Mixed Hemimicelles Solid-Phase Extraction Procedure (MMHSPE) still include easy preparation and regeneration of sorbents, short times of sample pretreatment, high extraction yields, and high breakthrough volumes. It shows great analytical potential in preconcentration of Cd and Pb compounds from large volume water samples. Due to the high surface area of these new sorbents and the excellent adsorption capacity after surface modification by SDS-PAN, satisfactory concentration factor and extraction recoveries can be produced with only 0.05 g Fe3O4/Al2O3 NPs. The metals were eluted with 3mL HNO3 2 mol L-1 directly and detected with the detection system Flame Atomic Absorption Spectrometry (FAAS). Various influencing parameters on the separation and preconcentration of trace metals, such as the amount of PAN, pH value, sample volume, standing time, desorption solvent and maximal extraction volume, amount of sorbent and concentration of eluent, were studied. The detection limits of this method for Cd and Pb were 0.3 and 0.7 ng mL−1 and the R.S.D.s were 3.4 and 2.8% (C = 28.00 ng mL-1, n = 6), respectively. The preconcentration factor of the modified nanoparticles was 166.6. The proposed method has been applied to the determination of these metal ions at trace levels in soil, river, tap, mineral, spring and wastewater samples with satisfactory results.

Keywords: Alumina-coated magnetite nanoparticles, Magnetic Mixed Hemimicell Solid-Phase Extraction, Cd and Pb, soil sample

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Khaled Alshamari

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Synthesized partially phosphorylated polyvinyl phosphate derivative (PPVP) was functionalized to extract Zirconium (IV) from Egyptian zircon sand. The specifications for the PPVP composite were approved effectively via different techniques, namely, FT-IR, XPS, BET, EDX, TGA, HNMR, C-NMR, GC-MS, XRD and ICP-OES analyses, which demonstrated a satisfactory synthesis of PPVP and zircon dissolution from Egyptian zircon sand. Factors controlling parameters, such as pH values, shaking time, initial zirconium concentration, PPVP dose, nitrate ions concentration, co-ions, temperature and eluting agents, have been optimized. At 25 ◦C, pH 0, 20 min shaking, 0.05 mol/L zirconium ions and 0.5 mol/L nitrate ions, PPVP has an exciting preservation potential of 195 mg/g, equivalent to 390 mg/L zirconium ions. From the extraction–distribution isotherm, the practical outcomes of Langmuir’s modeling are better than the Freundlich model, with a theoretical value of 196.07 mg/g, which is more in line with the experimental results of 195 mg/g. The zirconium ions adsorption onto the PPVP composite follows the pseudo-second-order kinetics with a theoretical capacity value of 204.08 mg/g. According to thermodynamic potential, the extraction process was expected to be an exothermic, spontaneous and beneficial extraction at low temperatures. The thermodynamic parameters ∆S (−0.03 kJ/mol), ∆H (−12.22 kJ/mol) and ∆G were also considered. As the temperature grows, ∆G values increase from −2.948 kJ/mol at 298 K to −1.941 kJ/mol at 338 K. Zirconium ions may be eluted from the working loaded PPVP by 0.025M HNO₃, with a 99% efficiency rate. It was found that zirconium ions revealed good separation factors towards some co-ions such as Hf⁴+ (28.82), Fe³+ (10.64), Ti⁴+ (28.82), V⁵+ (86.46) and U⁶+ (68.17). A successful alkali fusion technique with NaOH flux followed by the extraction with PPVP is used to obtain a high-purity zirconia concentrate with a zircon content of 72.77 % and a purity of 98.29%. As a result of this, the improved factors could finally be used.

Keywords: zirconium extraction, partially phosphorylated polyvinyl phosphate (PPVP), acidic medium, zircon

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Authors: Hajer Rahali, Zied Hajaiej, Noureddine Ellouze

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The goal of speech parameterization is to extract the relevant information about what is being spoken from the audio signal. In speech recognition systems Mel-Frequency Cepstral Coefficients (MFCC) and Relative Spectral Mel-Frequency Cepstral Coefficients (RASTA-MFCC) are the two main techniques used. It will be shown in this paper that it presents some modifications to the original MFCC method. In our work the effectiveness of proposed changes to MFCC called Modified Function Cepstral Coefficients (MODFCC) were tested and compared against the original MFCC and RASTA-MFCC features. The prosodic features such as jitter and shimmer are added to baseline spectral features. The above-mentioned techniques were tested with impulsive signals under various noisy conditions within AURORA databases.

Keywords: auditory filter, impulsive noise, MFCC, prosodic features, RASTA filter

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Authors: Michal Krčál

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Since their introduction in 1990’s, Enterprise Information Portals (EIPs) were investigated from different perspectives (e.g. project management, technology acceptance, IS success). However, no systematic literature review was produced to systematize both the research efforts and the technology itself. This paper reports first results of an extent systematic literature review study focused on research of EIPs and its categorization, specifically it reports a conceptual model of EIP features. The previous attempt to categorize EIP features was published in 2002. For the purpose of the literature review, content of 89 articles was analyzed in order to identify and categorize features of EIPs. The methodology of the literature review was as follows. Firstly, search queries in major indexing databases (Web of Science and SCOPUS) were used. The results of queries were analyzed according to their usability for the goal of the study. Then, full-texts were coded in Atlas.ti according to previously established coding scheme. The codes were categorized and the conceptual model of EIP features was created.

Keywords: enterprise information portal, content analysis, features, systematic literature review

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Authors: Abdulfattah M. Alkherraz, Zaineb I. Lusta, Ahmed E. Zubi

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The environmental pollution by heavy metals became more problematic nowadays. To solve the problem of Cadmium accumulation in human organs which lead to dangerous effects on human health, and to determine its concentration, the organic legand 1-phenyl-3-benzoyl-2-thiourea was used to extract the cadmium ions from its solution. This legand as one of thiourea derivatives was successfully synthesized. The legand was characterized by NMR and CHN elemental analysis, and used to extract the cadmium from its solutions by formation of a stable complex at neutral pH. The complex was characterized by elemental analysis and melting point. The concentrations of cadmium ions before and after the extraction were determined by Atomic Absorption Spectrophotometer (AAS). The data show the percentage of the extract was more than 98.7% of the concentration of cadmium used in the study.

Keywords: thiourea derivatives, cadmium extraction, water, environment

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Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis

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Authors: Hamed Qazanfari, Hamid Hassanpour, Kazem Qazanfari

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In this paper, a method is provided for content-based image retrieval. Content-based image retrieval system searches query an image based on its visual content in an image database to retrieve similar images. In this paper, with the aim of simulating the human visual system sensitivity to image's edges and color features, the concept of color difference histogram (CDH) is used. CDH includes the perceptually color difference between two neighboring pixels with regard to colors and edge orientations. Since the HSV color space is close to the human visual system, the CDH is calculated in this color space. In addition, to improve the color features, the color histogram in HSV color space is also used as a feature. Among the extracted features, efficient features are selected using entropy and correlation criteria. The final features extract the content of images most efficiently. The proposed method has been evaluated on three standard databases Corel 5k, Corel 10k and UKBench. Experimental results show that the accuracy of the proposed image retrieval method is significantly improved compared to the recently developed methods.

Keywords: content-based image retrieval, color difference histogram, efficient features selection, entropy, correlation

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Authors: Saeid Jafari, Khursheed Ahmad Sheikh, Randy W. Worobo, Kitipong Assatarakul

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In this study, the extraction of cocoa shell powder (CSP) was optimized, and the optimized extracts were spray-dried for encapsulation purposes. Temperature (45-65 ◦C), extraction time (30–60 min), and ethanol concentration (60–100%) were the extraction parameters. The response surface methodology analysis revealed that the model was significant (p ≤ 0.05) in interactions between all variables (total phenolic compound, total flavonoid content, and antioxidant activity as measured by 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP assays), with a lack of fit test for the model being insignificant (p > 0.05). Temperature (55 ◦C), time (45 min), and ethanol concentration (60%) were found to be the optimal extraction conditions. For spray-drying encapsulation, some quality metrics (e.g., water solubility, water activity) were insignificant (p > 0.05). The microcapsules were found to be spherical in shape using a scanning electron microscope. Thermogravimetric and differential thermogravimetric measurements of the microcapsules revealed nearly identical results. The gum arabic + maltodextrin microcapsule (GMM) showed potential antibacterial (zone of inhibition: 11.50 mm; lower minimum inhibitory concentration: 1.50 mg/mL) and antioxidant (DPPH: 1063 mM trolox/100g dry wt.) activities (p ≤ 0.05). In conclusion, the microcapsules in this study, particularly GMM, are promising antioxidant and antibacterial agents to be fortified as functional food ingredients for the production of nutraceutical foods with health-promoting properties.

Keywords: functional foods, coco shell powder, antioxidant activity, encapsulation, extraction

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Authors: Md. Sakinul Islam, Nhol Kao, Sati Bhattacharya, Rahul Gupta

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The objective of the study is to produce naocrystalline cellulose (NCC) from rice husk by chemical extraction process. The chemical extraction processes of this production are delignification, bleaching and hydrolysis. In order to produce NCC, raw rice husk (RRH) was grinded and converted to powder form. Powder rice husk was obtained by sieving and the particles in the 75-710 μm size range was used for experimental work. The production of NCC was conducted into the jacketed glass reactor at 80 ˚C temperature under predetermined experimental conditions. In this work NaOH (4M) solution was used for delignification process. After certain experimental time delignified powder RH was collected from the reactor then washed, bleached and finally hydrolyzed in order to degrade cellulose to nanocrystalline cellulose (NCC). For bleaching and hydrolysis processes NaOCl (20%) and H2SO4 (4M) solutions were used, respectively. The resultant products from hydrolysis was neutralized by buffer solution and analyzed by FTIR, XRD, SEM, AFM and TEM. From the analysis, NCC has been identified successfully and the particle dimension has been confirmed to be in the range of 20-50 nm. From XRD results, the crystallinity of NCC was found to be approximately 45%.

Keywords: nanocrystalline cellulose, NCC, rice husk, biomass, chemical extraction

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Authors: Smita Pallavi, Raj Ratn Pranesh, Sumit Kumar

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Information representation as tables is compact and concise method that eases searching, indexing, and storage requirements. Extracting and cloning tables from parsable documents is easier and widely used; however, industry still faces challenges in detecting and extracting tables from OCR (Optical Character Recognition) documents or images. This paper proposes an algorithm that detects and extracts multiple tables from OCR document. The algorithm uses a combination of image processing techniques, text recognition, and procedural coding to identify distinct tables in the same image and map the text to appropriate the corresponding cell in dataframe, which can be stored as comma-separated values, database, excel, and multiple other usable formats.

Keywords: table extraction, optical character recognition, image processing, text extraction, morphological transformation

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Authors: T. Zaki, Fathi S. Soliman

Abstract:

Desulfurization process is required by most, if not all refineries, to achieve ultra-low sulfur fuel, that contains less than 10 ppm sulfur. A lot of research works and many effective technologies have been studied to achieve deep desulfurization process in moderate reaction environment, such as adsorption desulfurization (ADS), oxidative desulfurization (ODS), biodesulfurization and extraction desulfurization (EDS). Extraction desulfurization using deep eutectic solvents (DESs) is considered as simple, cheap, highly efficient and environmentally friend process. In this work, four DESs were designed and synthesized. Choline chloride (ChCl) was selected as typical hydrogen bond acceptors (HBA), and ethylene glycol (EG), glycerol (Gl), urea (Ur) and thiourea (Tu) were selected as hydrogen bond donors (HBD), from which a series of deep eutectic solvents were synthesized. The experimental data showed that the synthesized DESs showed desulfurization affinities towards the thiophene species in cyclohexane solvent. Ethylene glycol molecules showed more affinity to create hydrogen bond with thiophene instead of choline chloride. Accordingly, ethylene glycol choline chloride DES has the highest extraction efficiency.

Keywords: DES, desulfurization, green solvent, extraction

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Authors: Asma Ben Abdallah

Abstract:

Language has a powerful influence over people and their actions. The language of advertising has a very great impact on the consumer. It makes use of different features from the linguistic continuum. The present paper attempts to apply the theories of stylistics to the analysis of advertising texts. In order to decipher the stylistic features of the advertising discourse, 30 advertising text samples designed by MA Business students have been selected. These samples have been analyzed at the level of design and content. The study brings insights into the use of stylistic devices in advertising, and it reveals that both linguistic and non-linguistic features of advertisements are frequently employed to develop a well-thought-out design and content. The practical significance of the study is to highlight the specificities of the advertising genre so that people interested in the language of advertising (Business students and ESP teachers) will have a better understanding of the nature of the language used and the techniques of writing and designing ads. Similarly, those working in the advertising sphere (ad designers) will appreciate the specificities of the advertising discourse.

Keywords: the language of advertising, advertising discourse, ad design, stylistic features

Procedia PDF Downloads 198