Search results for: inference extraction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2244

Search results for: inference extraction

2154 Oil Extraction from Sunflower Seed Using Green Solvent 2-Methyltetrahydrofuran and Isoamyl Alcohol

Authors: Sergio S. De Jesus, Aline Santana, Rubens Maciel Filho

Abstract:

The objective of this study was to choose and determine a green solvent system with similar extraction efficiencies as the traditional Bligh and Dyer method. Sunflower seed oil was extracted using Bligh and Dyer method with 2-methyltetrahydrofuran and isoamyl using alcohol ratios of 1:1; 2:1; 3:1; 1:2; 3:1. At the same time comparative experiments was performed with chloroform and methanol ratios of 1:1; 2:1; 3:1; 1:2; 3:1. Comparison study was done using 5 replicates (n=5). Statistical analysis was performed using Microsoft Office Excel (Microsoft, USA) to determine means and Tukey’s Honestly Significant Difference test for comparison between treatments (α = 0.05). The results showed that using classic method with methanol and chloroform presented the extraction oil yield with the values of 31-44% (w/w) and values of 36-45% (w/w) using green solvents for extractions. Among the two extraction methods, 2 methyltetrahydrofuran and isoamyl alcohol ratio 2:1 provided the best results (45% w/w), while the classic method using chloroform and methanol with ratio of 3:1 presented a extraction oil yield of 44% (w/w). It was concluded that the proposed extraction method using 2-methyltetrahydrofuran and isoamyl alcohol in this work allowed the same efficiency level as chloroform and methanol.

Keywords: extraction, green solvent, lipids, sugarcane

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2153 Oil Extraction from Microalgae Dunalliela sp. by Polar and Non-Polar Solvents

Authors: A. Zonouzi, M. Auli, M. Javanmard Dakheli, M. A. Hejazi

Abstract:

Microalgae are tiny photosynthetic plants. Nowadays, microalgae are being used as nutrient-dense foods and sources of fine chemicals. They have significant amounts of lipid, carotenoids, vitamins, protein, minerals, chlorophyll, and pigments. Oil extraction from algae is a hotly debated topic currently because introducing an efficient method could decrease the process cost. This can determine the sustainability of algae-based foods. Scientific research works show that solvent extraction using chloroform/methanol (2:1) mixture is one of the efficient methods for oil extraction from algal cells, but both methanol and chloroform are toxic solvents, and therefore, the extracted oil will not be suitable for food application. In this paper, the effect of two food grade solvents (hexane and hexane/ isopropanol) on oil extraction yield from microalgae Dunaliella sp. was investigated and the results were compared with chloroform/methanol (2:1) extraction yield. It was observed that the oil extraction yield using hexane, hexane/isopropanol (3:2) and chloroform/methanol (2:1) mixture were 5.4, 13.93, and 17.5 (% w/w, dry basis), respectively. The fatty acid profile derived from GC illustrated that the palmitic (36.62%), oleic (18.62%), and stearic acids (19.08%) form the main portion of fatty acid composition of microalgae Dunalliela sp. oil. It was concluded that, the addition of isopropanol as polar solvent could increase the extraction yield significantly. Isopropanol solves cell wall phospholipids and enhances the release of intercellular lipids, which improves accessing of hexane to fatty acids.

Keywords: fatty acid profile‎, microalgae‎, oil extraction‎, polar solvent‎

Procedia PDF Downloads 357
2152 Green Extraction of Patchoulol from Patchouli Leaves Using Ultrasound-Assisted Ionic Liquids

Authors: G. C. Jadeja, M. A. Desai, D. R. Bhatt, J. K. Parikh

Abstract:

Green extraction techniques are fast paving ways into various industrial sectors due to the stringent governmental regulations leading to the banning of toxic chemicals’ usage and also due to the increasing health/environmental awareness. The present work describes the ionic liquids based sonication method for selectively extracting patchoulol from the leaves of patchouli. 1-Butyl-3-methylimidazolium tetrafluoroborate ([Bmim]BF4) and N,N,N,N’,N’,N’-Hexaethyl-butane-1,4-diammonium dibromide (dicationic ionic liquid - DIL) were selected for extraction. Ultrasound assisted ionic liquid extraction was employed considering concentration of ionic liquid (4–8 %, w/w), ultrasound power (50–150 W for [Bmim]BF4 and 20–80 W for DIL), temperature (30–50 oC) and extraction time (30–50 min) as major parameters influencing the yield of patchoulol. Using the Taguchi method, the parameters were optimized and analysis of variance (ANOVA) was performed to find the most influential factor in the selected extraction method. In case of [Bmim]BF4, the optimum conditions were found to be: 4 % (w/w) ionic liquid concentration, 50 W power, 30 oC temperature and extraction time of 30 min. The yield obtained under the optimum conditions was 3.99 mg/g. In case of DIL, the optimum conditions were obtained as 6 % (w/w) ionic liquid concentration, 80 W power, 30 oC temperature and extraction time of 40 min, for which the yield obtained was 4.03 mg/g. Temperature was found to be the most significant factor in both the cases. Extraction time was the insignificant parameter while extracting the product using [Bmim]BF4 and in case of DIL, power was found to be the least significant factor affecting the process. Thus, a green method of recovering patchoulol is proposed.

Keywords: green extraction, ultrasound, patchoulol, ionic liquids

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2151 Literature Review: Microalgae as Functional Foods with Solvent Free Extraction

Authors: Angela Justina Kumalaputri

Abstract:

Indonesia, as a maritime country, has abundant marine living resources yet has not been optimally utilized. So far, we only focusing on fisheries. In the other hand, Indonesia, as the country with the fourth longest coastline, is a very good cultivation place for microalgae. Microalgae can be diversified to many important products, such as food, fuel, pharmaceutical products, functional food, and cosmetics.This research is focusing on the literature study about types of microalgae as sources for functional foods (such as antioxidants), including the contents and the separation methods. The research methods which we use are: (1) Literature study about various microalgaes (2) Literature study about extractions using supercritical fluid of CO₂, which are free from toxic organic solvents, environmentally friendly, and safe for food products. Supercritical fluid extraction using CO₂ (low critical points: temperature at 31.1 oC and pressure at 72.9 bars) could be done at a low temperature which are suitable for temperature labile compounds, low energy, and faster extraction time compared with conventional method of extraction.

Keywords: antioxidants, supercritical fluid extraction, solvent-free extraction, microalgae

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2150 An Automatic Feature Extraction Technique for 2D Punch Shapes

Authors: Awais Ahmad Khan, Emad Abouel Nasr, H. M. A. Hussein, Abdulrahman Al-Ahmari

Abstract:

Sheet-metal parts have been widely applied in electronics, communication and mechanical industries in recent decades; but the advancement in sheet-metal part design and manufacturing is still behind in comparison with the increasing importance of sheet-metal parts in modern industry. This paper presents a methodology for automatic extraction of some common 2D internal sheet metal features. The features used in this study are taken from Unipunch ™ catalogue. The extraction process starts with the data extraction from STEP file using an object oriented approach and with the application of suitable algorithms and rules, all features contained in the catalogue are automatically extracted. Since the extracted features include geometry and engineering information, they will be effective for downstream application such as feature rebuilding and process planning.

Keywords: feature extraction, internal features, punch shapes, sheet metal

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2149 Combination of Electrochemical Impedance Spectroscopy and Electromembrane Extraction for the Determination of Zolpidem Using Modified Screen-Printed Electrode

Authors: Ali Naeemy, Mir Ghasem Hoseini

Abstract:

In this study, for the first time, an analytical method developed and validated by combining electrochemical impedance spectroscopy and electromembrane extraction (EIS-EME) by Vulcan/poly pyrrole nanocomposite modified screen-printed electrode (PPY–VU/SPE) for accurately quantifying zolpidem. EME parameters optimized, including solvent composition, voltage, pH adjustments and extraction time. Zolpidem was transferred from a donor solution (pH 5) to an acceptor solution (pH 13) using a hollow fiber in 1-octanol as a membrane, driven by a 60 V voltage for 25 minutes, ensuring precise and selective extraction. In comparison with SPE, VU/SPE and PPY/SPE, the PPY–VU/SPE was much more efficient for ZP oxidation. Calibration curves with good linearity were obtained in the concentration range of 2-75 µmol L-1 using the EIS-EME with the detection limit of 0.5 µmol L-1 . Finally, the EIS-EME by using the PPY– VU/SPE was successfully used to determine ZP in tablet dosage form, urine and plasma samples. Keywords: Electrochemical impedance spectroscopy, Electromembrane extraction, Zolpidem, Vulcan, poly pyrrole, Screen printed electrode

Keywords: electrochemical impedance spectroscopy, electromembrane extraction, screen printed electrode, zolpidem

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2148 Improvement of Protein Extraction From Shrimp by Product Used for Electrospinning by Applying Emerging Technologies

Authors: Mario Pérez-Won, Vilbett Briones L., Guido Trautmann, María José Bugueño, Gipsy Tabilo-Munizaga, Luis Gonzalez-Cavieres

Abstract:

The fishing industry generates a significant amount of shrimp byproducts, which often result in environmental contamination. Protein extraction from these by-products is a potential solution to minimize waste and revalue the by-products. To improve the extraction of proteins (by chemical method) from shrimp (Pleuroncodes monodon) by-products, the emerging technologies of ohmic heating (OH), microwaves (MW) and pulsed electric fields (PEF) were used. The results show that microwaves, electrical pulses, and ohmic heating improved performance by 28.19%, 19.25%, and 3.65%, respectively. Furthermore, conformational changes were studied by DSC and FTIR. Subsequently, the use of these proteins in electrospinning technology was evaluated. In conclusion, this study demonstrates that the application of emerging technologies, can significantly improve the extraction yield of proteins from shrimp by-products.

Keywords: electrospinning, emerging technologies, improving extraction, shrimp by-products

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2147 Drinking Water Quality Assessment Using Fuzzy Inference System Method: A Case Study of Rome, Italy

Authors: Yas Barzegar, Atrin Barzegar

Abstract:

Drinking water quality assessment is a major issue today; technology and practices are continuously improving; Artificial Intelligence (AI) methods prove their efficiency in this domain. The current research seeks a hierarchical fuzzy model for predicting drinking water quality in Rome (Italy). The Mamdani fuzzy inference system (FIS) is applied with different defuzzification methods. The Proposed Model includes three fuzzy intermediate models and one fuzzy final model. Each fuzzy model consists of three input parameters and 27 fuzzy rules. The model is developed for water quality assessment with a dataset considering nine parameters (Alkalinity, Hardness, pH, Ca, Mg, Fluoride, Sulphate, Nitrates, and Iron). Fuzzy-logic-based methods have been demonstrated to be appropriate to address uncertainty and subjectivity in drinking water quality assessment; it is an effective method for managing complicated, uncertain water systems and predicting drinking water quality. The FIS method can provide an effective solution to complex systems; this method can be modified easily to improve performance.

Keywords: water quality, fuzzy logic, smart cities, water attribute, fuzzy inference system, membership function

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2146 N-Type GaN Thinning for Enhancing Light Extraction Efficiency in GaN-Based Thin-Film Flip-Chip Ultraviolet (UV) Light Emitting Diodes (LED)

Authors: Anil Kawan, Soon Jae Yu, Jong Min Park

Abstract:

GaN-based 365 nm wavelength ultraviolet (UV) light emitting diodes (LED) have various applications: curing, molding, purification, deodorization, and disinfection etc. However, their usage is limited by very low output power, because of the light absorption in the GaN layers. In this study, we demonstrate a method utilizing removal of 365 nm absorption layer buffer GaN and thinning the n-type GaN so as to improve the light extraction efficiency of the GaN-based 365 nm UV LED. The UV flip chip LEDs of chip size 1.3 mm x 1.3 mm were fabricated using GaN epilayers on a sapphire substrate. Via-hole n-type contacts and highly reflective Ag metal were used for efficient light extraction. LED wafer was aligned and bonded to AlN carrier wafer. To improve the extraction efficiency of the flip chip LED, sapphire substrate and absorption layer buffer GaN were removed by using laser lift-off and dry etching, respectively. To further increase the extraction efficiency of the LED, exposed n-type GaN thickness was reduced by using inductively coupled plasma etching.

Keywords: extraction efficiency, light emitting diodes, n-GaN thinning, ultraviolet

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2145 Optimization of Ultrasonic Assisted Extraction of Antioxidants and Phenolic Compounds from Coleus Using Response Surface Methodology

Authors: Reihaneh Ahmadzadeh Ghavidel

Abstract:

Free radicals such as reactive oxygen species (ROS) have detrimental effects on human health through several mechanisms. On the other hand, antioxidant molecules reduce free radical generation in biologic systems. Synthetic antioxidants, which are used in food industry, have also negative impact on human health. Therefore recognition of natural antioxidants such as anthocyanins can solve these problems simultaneously. Coleus (Solenostemon scutellarioides) with red leaves is a rich source of anthocyanins compounds. In this study we evaluated the effect of time (10, 20 and 30 min) and temperature (40, 50 and 60° C) on optimization of anthocyanin extraction using surface response method. In addition, the study was aimed to determine maximum extraction for anthocyanin from coleus plant using ultrasound method. The results indicated that the optimum conditions for extraction were 39.84 min at 69.25° C. At this point, total compounds were achieved 3.7451 mg 100 ml⁻¹. Furthermore, under optimum conditions, anthocyanin concentration, extraction efficiency, ferric reducing ability, total phenolic compounds and EC50 were registered 3.221931, 6.692765, 223.062, 3355.605 and 2.614045, respectively.

Keywords: anthocyanin, antioxidant, coleus, extraction, sonication

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2144 Moderate Electric Field Influence on Carotenoids Extraction Time from Heterochlorella luteoviridis

Authors: Débora P. Jaeschke, Eduardo A. Merlo, Rosane Rech, Giovana D. Mercali, Ligia D. F. Marczak

Abstract:

Carotenoids are high value added pigments that can be alternatively extracted from some microalgae species. However, the application of carotenoids synthetized by microalgae is still limited due to the utilization of organic toxic solvents. In this context, studies involving alternative extraction methods have been conducted with more sustainable solvents to replace and reduce the solvent volume and the extraction time. The aim of the present work was to evaluate the extraction time of carotenoids from the microalgae Heterochlorella luteoviridis using moderate electric field (MEF) as a pre-treatment to the extraction. The extraction methodology consisted of a pre-treatment in the presence of MEF (180 V) and ethanol (25 %, v/v) for 10 min, followed by a diffusive step performed for 50 min using a higher ethanol concentration (75 %, v/v). The extraction experiments were conducted at 30 °C and, to keep the temperature at this value, it was used an extraction cell with a water jacket that was connected to a water bath. Also, to enable the evaluation of MEF effect on the extraction, control experiments were performed using the same cell and conditions without voltage application. During the extraction experiments, samples were withdrawn at 1, 5 and 10 min of the pre-treatment and at 1, 5, 30, 40 and 50 min of the diffusive step. Samples were, then, centrifuged and carotenoids analyses were performed in the supernatant. Furthermore, an exhaustive extraction with ethyl acetate and methanol was performed, and the carotenoids content found for this analyses was considered as the total carotenoids content of the microalgae. The results showed that the application of MEF as a pre-treatment to the extraction influenced the extraction yield and the extraction time during the diffusive step; after the MEF pre-treatment and 50 min of the diffusive step, it was possible to extract up to 60 % of the total carotenoids content. Also, results found for carotenoids concentration of the extracts withdrawn at 5 and 30 min of the diffusive step did not presented statistical difference, meaning that carotenoids diffusion occurs mainly in the very beginning of the extraction. On the other hand, the results for control experiments showed that carotenoids diffusion occurs mostly during 30 min of the diffusive step, which evidenced MEF effect on the extraction time. Moreover, carotenoids concentration on samples withdrawn during the pre-treatment (1, 5 and 10 min) were below the quantification limit of the analyses, indicating that the extraction occurred in the diffusive step, when ethanol (75 %, v/v) was added to the medium. It is possible that MEF promoted cell membrane permeabilization and, when ethanol (75 %) was added, carotenoids interacted with the solvent and the diffusion occurred easily. Based on the results, it is possible to infer that MEF promoted the decrease of carotenoids extraction time due to the increasing of the permeability of the cell membrane which facilitates the diffusion from the cell to the medium.

Keywords: moderate electric field (MEF), pigments, microalgae, ethanol

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2143 Optimizing Microwave Assisted Extraction of Anti-Diabetic Plant Tinospora cordifolia Used in Ayush System for Estimation of Berberine Using Taguchi L-9 Orthogonal Design

Authors: Saurabh Satija, Munish Garg

Abstract:

Present work reports an efficient extraction method using microwaves based solvent–sample duo-heating mechanism, for the extraction of an important anti-diabetic plant Tinospora cordifolia from AYUSH system for estimation of berberine content. The process is based on simultaneous heating of sample matrix and extracting solvent under microwave energy. Methanol was used as the extracting solvent, which has excellent berberine solubilizing power and warms up under microwave attributable to its great dispersal factor. Extraction conditions like time of irradition, microwave power, solute-solvent ratio and temperature were optimized using Taguchi design and berberine was quantified using high performance thin layer chromatography. The ranked optimized parameters were microwave power (rank 1), irradiation time (rank 2) and temperature (rank 3). This kind of extraction mechanism under dual heating provided choice of extraction parameters for better precision and higher yield with significant reduction in extraction time under optimum extraction conditions. This developed extraction protocol will lead to extract higher amounts of berberine which is a major anti-diabetic moiety in Tinospora cordifolia which can lead to development of cheaper formulations of the plant Tinospora cordifolia and can help in rapid prevention of diabetes in the world.

Keywords: berberine, microwave, optimization, Taguchi

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2142 The Quotation-Based Algorithm for Distributed Decision Making

Authors: Gennady P. Ginkul, Sergey Yu. Soloviov

Abstract:

The article proposes to use so-called "quotation-based algorithm" for simulation of decision making process in distributed expert systems and multi-agent systems. The idea was adopted from the techniques for group decision-making. It is based on the assumption that one expert system to perform its logical inference may use rules from another expert system. The application of the algorithm was demonstrated on the example in which the consolidated decision is the decision that requires minimal quotation.

Keywords: backward chaining inference, distributed expert systems, group decision making, multi-agent systems

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2141 Response Surface Modeling of Lactic Acid Extraction by Emulsion Liquid Membrane: Box-Behnken Experimental Design

Authors: A. Thakur, P. S. Panesar, M. S. Saini

Abstract:

Extraction of lactic acid by emulsion liquid membrane technology (ELM) using n-trioctyl amine (TOA) in n-heptane as carrier within the organic membrane along with sodium carbonate as acceptor phase was optimized by using response surface methodology (RSM). A three level Box-Behnken design was employed for experimental design, analysis of the results and to depict the combined effect of five independent variables, vizlactic acid concentration in aqueous phase (cl), sodium carbonate concentration in stripping phase (cs), carrier concentration in membrane phase (ψ), treat ratio (φ), and batch extraction time (τ) with equal volume of organic and external aqueous phase on lactic acid extraction efficiency. The maximum lactic acid extraction efficiency (ηext) of 98.21%from aqueous phase in a batch reactor using ELM was found at the optimized values for test variables, cl, cs,, ψ, φ and τ as 0.06 [M], 0.18 [M], 4.72 (%,v/v), 1.98 (v/v) and 13.36 min respectively.

Keywords: emulsion liquid membrane, extraction, lactic acid, n-trioctylamine, response surface methodology

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2140 Surfactant-Assisted Aqueous Extraction of Residual Oil from Palm-Pressed Mesocarp Fibre

Authors: Rabitah Zakaria, Chan M. Luan, Nor Hakimah Ramly

Abstract:

The extraction of vegetable oil using aqueous extraction process assisted by ionic extended surfactant has been investigated as an alternative to hexane extraction. However, the ionic extended surfactant has not been commercialised and its safety with respect to food processing is uncertain. Hence, food-grade non-ionic surfactants (Tween 20, Span 20, and Span 80) were proposed for the extraction of residual oil from palm-pressed mesocarp fibre. Palm-pressed mesocarp fibre contains a significant amount of residual oil ( 5-10 wt %) and its recovery is beneficial as the oil contains much higher content of vitamin E, carotenoids, and sterols compared to crude palm oil. In this study, the formulation of food-grade surfactants using a combination of high hydrophilic-lipophilic balance (HLB) surfactants and low HLB surfactants to produce micro-emulsion with very low interfacial tension (IFT) was investigated. The suitable surfactant formulation was used in the oil extraction process and the efficiency of the extraction was correlated with the IFT, droplet size and viscosity. It was found that a ternary surfactant mixture with a HLB value of 15 (82% Tween 20, 12% Span 20 and 6% Span 80) was able to produce micro-emulsion with very low IFT compared to other HLB combinations. Results suggested that the IFT and droplet size highly affect the oil recovery efficiency. Finally, optimization of the operating parameters shows that the highest extraction efficiency of 78% was achieved at 1:31 solid to liquid ratio, 2 wt % surfactant solution, temperature of 50˚C, and 50 minutes contact time.

Keywords: food-grade surfactants, aqueous extraction of residual oil, palm-pressed mesocarp fibre, interfacial tension

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2139 Application of Adaptive Neuro Fuzzy Inference Systems Technique for Modeling of Postweld Heat Treatment Process of Pressure Vessel Steel AASTM A516 Grade 70

Authors: Omar Al Denali, Abdelaziz Badi

Abstract:

The ASTM A516 Grade 70 steel is a suitable material used for the fabrication of boiler pressure vessels working in moderate and lower temperature services, and it has good weldability and excellent notch toughness. The post-weld heat treatment (PWHT) or stress-relieving heat treatment has significant effects on avoiding the martensite transformation and resulting in high hardness, which can lead to cracking in the heat-affected zone (HAZ). An adaptive neuro-fuzzy inference system (ANFIS) was implemented to predict the material tensile strength of post-weld heat treatment (PWHT) experiments. The ANFIS models presented excellent predictions, and the comparison was carried out based on the mean absolute percentage error between the predicted values and the experimental values. The ANFIS model gave a Mean Absolute Percentage Error of 0.556 %, which confirms the high accuracy of the model.

Keywords: prediction, post-weld heat treatment, adaptive neuro-fuzzy inference system, mean absolute percentage error

Procedia PDF Downloads 142
2138 Determination of Benzatropine in Hair by GC/MS after Liquid-Liquid Extraction (LLE)

Authors: Abdulsallam A. Bakdash, Aiyshah M. Alshehri, Hind M. Alenzi

Abstract:

Benzatropine (benztropine) is used to treat symptoms of Parkinson's disease or involuntary movements due to the side effects of certain psychiatric drugs. We report in this study, results of a procedure for the determination of benzatropine in hair using LLE, once with methanol and second with phosphate buffer (pH 6.0), followed by filtration and then re-extraction with dichloromethane. A GC/MS method was developed and validated for this determination using selected ion monitoring (SIM) detection without derivatization. Linearity established over the concentration range 0.1-20.0 ng/mg hair, and the correlation coefficients were greater than 0.99. Recoveries were 52.2% and 21.1% using methanol and phosphate buffer extraction, respectively. Detection limits of benzatropine in hair were between 0.65 and 3.0 ng/mg hair, while the accuracy were 10.4% and 18.5% (RSD), respectively. We also applied this method to the analysis of soaked hair samples and demonstrated that the LLE using methanol meets the requirement for the analysis of benzatropine in hair.

Keywords: hair analysis, benzatropine, liquid-liquid extraction, GC/MS

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2137 Solvent Free Microwave Extraction of Essential Oils: A Clean Chemical Processing in the Teaching and Research Laboratory

Authors: M. A. Ferhat, M. N. Boukhatem, F. Chemat

Abstract:

Microwave Clevenger or microwave accelerated distillation (MAD) is a combination of microwave heating and distillation, performed at atmospheric pressure without added any solvent or water. Isolation and concentration of volatile compounds are performed by a single stage. MAD extraction of orange essential oil was studied using fresh orange peel from Valencia late cultivar oranges as the raw material. MAD has been compared with a conventional technique, which used a Clevenger apparatus with hydro-distillation (HD). MAD and HD were compared in term of extraction time, yields, chemical composition and quality of the essential oil, efficiency and costs of the process. Extraction of essential oils from orange peels with MAD was better in terms of energy saving, extraction time (30 min versus 3 h), oxygenated fraction (11.7% versus 7.9%), product yield (0.42% versus 0.39%) and product quality. Orange peels treated by MAD and HD were observed by scanning electronic microscopy (SEM). Micrographs provide evidence of more rapid opening of essential oil glands treated by MAD, in contrast to conventional hydro-distillation.

Keywords: clevenger, microwave, extraction; hydro-distillation, essential oil, orange peel

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2136 A Sentence-to-Sentence Relation Network for Recognizing Textual Entailment

Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

Abstract:

Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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2135 Membranes for Direct Lithium Extraction (DLE)

Authors: Amir Razmjou, Elika Karbassi Yazdi

Abstract:

Several direct lithium extraction (DLE) technologies have been developed for Li extraction from different brines. Although laboratory studies showed that they can technically recover Li to 90%, challenges still remain in developing a sustainable process that can serve as a foundation for the lithium dependent low-carbon economy. There is a continuing quest for DLE technologies that do not need extensive pre-treatments, fewer materials, and have simplified extraction processes with high Li selectivity. Here, an overview of DLE technologies will be provided with an emphasis on the basic principles of the materials’ design for the development of membranes with nanochannels and nanopores with Li ion selectivity. We have used a variety of building blocks such as nano-clay, organic frameworks, Graphene/oxide, MXene, etc., to fabricate the membranes. Molecular dynamic simulation (MD) and density functional theory (DFT) were used to reveal new mechanisms by which high Li selectivity was obtained.

Keywords: lithium recovery, membrane, lithium selectivity, decarbonization

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2134 Risk Assessment of Natural Gas Pipelines in Coal Mined Gobs Based on Bow-Tie Model and Cloud Inference

Authors: Xiaobin Liang, Wei Liang, Laibin Zhang, Xiaoyan Guo

Abstract:

Pipelines pass through coal mined gobs inevitably in the mining area, the stability of which has great influence on the safety of pipelines. After extensive literature study and field research, it was found that there are a few risk assessment methods for coal mined gob pipelines, and there is a lack of data on the gob sites. Therefore, the fuzzy comprehensive evaluation method is widely used based on expert opinions. However, the subjective opinions or lack of experience of individual experts may lead to inaccurate evaluation results. Hence the accuracy of the results needs to be further improved. This paper presents a comprehensive approach to achieve this purpose by combining bow-tie model and cloud inference. The specific evaluation process is as follows: First, a bow-tie model composed of a fault tree and an event tree is established to graphically illustrate the probability and consequence indicators of pipeline failure. Second, the interval estimation method can be scored in the form of intervals to improve the accuracy of the results, and the censored mean algorithm is used to remove the maximum and minimum values of the score to improve the stability of the results. The golden section method is used to determine the weight of the indicators and reduce the subjectivity of index weights. Third, the failure probability and failure consequence scores of the pipeline are converted into three numerical features by using cloud inference. The cloud inference can better describe the ambiguity and volatility of the results which can better describe the volatility of the risk level. Finally, the cloud drop graphs of failure probability and failure consequences can be expressed, which intuitively and accurately illustrate the ambiguity and randomness of the results. A case study of a coal mine gob pipeline carrying natural gas has been investigated to validate the utility of the proposed method. The evaluation results of this case show that the probability of failure of the pipeline is very low, the consequences of failure are more serious, which is consistent with the reality.

Keywords: bow-tie model, natural gas pipeline, coal mine gob, cloud inference

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2133 Prediction of Compressive Strength in Geopolymer Composites by Adaptive Neuro Fuzzy Inference System

Authors: Mehrzad Mohabbi Yadollahi, Ramazan Demirboğa, Majid Atashafrazeh

Abstract:

Geopolymers are highly complex materials which involve many variables which makes modeling its properties very difficult. There is no systematic approach in mix design for Geopolymers. Since the amounts of silica modulus, Na2O content, w/b ratios and curing time have a great influence on the compressive strength an ANFIS (Adaptive neuro fuzzy inference system) method has been established for predicting compressive strength of ground pumice based Geopolymers and the possibilities of ANFIS for predicting the compressive strength has been studied. Consequently, ANFIS can be used for geopolymer compressive strength prediction with acceptable accuracy.

Keywords: geopolymer, ANFIS, compressive strength, mix design

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2132 Fuzzy Inference System for Determining Collision Risk of Ship in Madura Strait Using Automatic Identification System

Authors: Emmy Pratiwi, Ketut B. Artana, A. A. B. Dinariyana

Abstract:

Madura Strait is considered as one of the busiest shipping channels in Indonesia. High vessel traffic density in Madura Strait gives serious threat due to navigational safety in this area, i.e. ship collision. This study is necessary as an attempt to enhance the safety of marine traffic. Fuzzy inference system (FIS) is proposed to calculate risk collision of ships. Collision risk is evaluated based on ship domain, Distance to Closest Point of Approach (DCPA), and Time to Closest Point of Approach (TCPA). Data were collected by utilizing Automatic Identification System (AIS). This study considers several ships’ domain models to give the characteristic of marine traffic in the waterways. Each encounter in the ship domain is analyzed to obtain the level of collision risk. Risk level of ships, as the result in this study, can be used as guidance to avoid the accident, providing brief description about safety traffic in Madura Strait and improving the navigational safety in the area.

Keywords: automatic identification system, collision risk, DCPA, fuzzy inference system, TCPA

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2131 Optimization of Process Parameters using Response Surface Methodology for the Removal of Zinc(II) by Solvent Extraction

Authors: B. Guezzen, M.A. Didi, B. Medjahed

Abstract:

A factorial design of experiments and a response surface methodology were implemented to investigate the liquid-liquid extraction process of zinc (II) from acetate medium using the 1-Butyl-imidazolium di(2-ethylhexyl) phosphate [BIm+][D2EHP-]. The optimization process of extraction parameters such as the initial pH effect (2.5, 4.5, and 6.6), ionic liquid concentration (1, 5.5, and 10 mM) and salt effect (0.01, 5, and 10 mM) was carried out using a three-level full factorial design (33). The results of the factorial design demonstrate that all these factors are statistically significant, including the square effects of pH and ionic liquid concentration. The results showed that the order of significance: IL concentration > salt effect > initial pH. Analysis of variance (ANOVA) showing high coefficient of determination (R2 = 0.91) and low probability values (P < 0.05) signifies the validity of the predicted second-order quadratic model for Zn (II) extraction. The optimum conditions for the extraction of zinc (II) at the constant temperature (20 °C), initial Zn (II) concentration (1mM) and A/O ratio of unity were: initial pH (4.8), extractant concentration (9.9 mM), and NaCl concentration (8.2 mM). At the optimized condition, the metal ion could be quantitatively extracted.

Keywords: ionic liquid, response surface methodology, solvent extraction, zinc acetate

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2130 The Effect of Supercritical Fluid on the Extraction Efficiency of Heavy Metal from Soil

Authors: Haifa El-Sadi, Maria Elektorowicz, Reed Rushing, Ammar Badawieh, Asif Chaudry

Abstract:

Clay soils have particular properties that affect the assessment and remediation of contaminated sites. In clay soils, electro-kinetic transport of heavy metals has been carried out. The transport of these metals is predicated on maintaining a low pH throughout the cell, which, in turn, keeps the metals in the pore water phase where they are accessible to electro-kinetic transport. Supercritical fluid extraction and acid digestion were used for the analysis of heavy metals concentrations after the completion of electro-kinetic experimentation. Supercritical fluid (carbon dioxide) extraction is a new technique used to extract the heavy metal (lead, nickel, calcium and potassium) from clayey soil. The comparison between supercritical extraction and acid digestion of different metals was carried out. Supercritical fluid extraction, using ethylenediaminetetraacetic acid (EDTA) as a modifier, proved to be efficient and a safer technique than acid digestion technique in extracting metals from clayey soil. Mixing time of soil with EDTA before extracting heavy metals from clayey soil was investigated. The optimum and most practical shaking time for the extraction of lead, nickel, calcium and potassium was two hours.

Keywords: clay soil, heavy metals, supercritical fluid extraction, acid digestion

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2129 Optimization of a Method of Total RNA Extraction from Mentha piperita

Authors: Soheila Afkar

Abstract:

Mentha piperita is a medicinal plant that contains a large amount of secondary metabolite that has adverse effect on RNA extraction. Since high quality of RNA is the first step to real time-PCR, in this study optimization of total RNA isolation from leaf tissues of Mentha piperita was evaluated. From this point of view, we researched two different total RNA extraction methods on leaves of Mentha piperita to find the best one that contributes the high quality. The methods tested are RNX-plus, modified RNX-plus (1-5 numbers). RNA quality was analyzed by agarose gel 1.5%. The RNA integrity was also assessed by visualization of ribosomal RNA bands on 1.5% agarose gels. In the modified RNX-plus method (number 2), the integrity of 28S and 18S rRNA was highly satisfactory when analyzed in agarose denaturing gel, so this method is suitable for RNA isolation from Mentha piperita.

Keywords: Mentha piperita, polyphenol, polysaccharide, RNA extraction

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2128 Different Methods Anthocyanins Extracted from Saffron

Authors: Hashem Barati, Afshin Farahbakhsh

Abstract:

The flowers of saffron contain anthocyanins. Generally, extraction of anthocyanins takes place at low temperatures (below 30 °C), preferably under vacuum (to minimize degradation) and in an acidic environment. In order to extract anthocyanins, the dried petals were added to 30 ml of acidic ethanol (pH=2). Amount of petals, extraction time, temperature, and ethanol percentage which were selected. Total anthocyanin content was a function of both variables of ethanol percent and extraction time.To prepare SW with pH of 3.5, different concentrations of 100, 400, 700, 1,000, and 2,000 ppm of sodium metabisulfite were added to aqueous sodium citrate. At this selected concentration, different extraction times of 20, 40, 60, 120, 180 min were tested to determine the optimum extraction time. When the extraction time was extended from 20 to 60 min, the total recovered anthocyanins of sulfur method changed from 650 to 710 mg/100 g. In the EW method Cellubrix and Pectinex enzymes were added separately to the buffer solution at different concentrations of 1%, 2.5%, 5%, 7%, 10%, and 12.5% and held for 2 hours reaction time at an ambient temperature of 40 °C. There was a considerable and significant difference in trends of Acys content of tepals extracted by pectinex enzymes at 5% concentration and AE solution.

Keywords: saffron, anthocyanins, acidic environment, acidic ethanol, pectinex enzymes, Cellubrix enzymes, sodium metabisulfite

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2127 Optimal Classifying and Extracting Fuzzy Relationship from Query Using Text Mining Techniques

Authors: Faisal Alshuwaier, Ali Areshey

Abstract:

Text mining techniques are generally applied for classifying the text, finding fuzzy relations and structures in data sets. This research provides plenty text mining capabilities. One common application is text classification and event extraction, which encompass deducing specific knowledge concerning incidents referred to in texts. The main contribution of this paper is the clarification of a concept graph generation mechanism, which is based on a text classification and optimal fuzzy relationship extraction. Furthermore, the work presented in this paper explains the application of fuzzy relationship extraction and branch and bound method to simplify the texts.

Keywords: extraction, max-prod, fuzzy relations, text mining, memberships, classification, memberships, classification

Procedia PDF Downloads 563
2126 Optimizing Communications Overhead in Heterogeneous Distributed Data Streams

Authors: Rashi Bhalla, Russel Pears, M. Asif Naeem

Abstract:

In this 'Information Explosion Era' analyzing data 'a critical commodity' and mining knowledge from vertically distributed data stream incurs huge communication cost. However, an effort to decrease the communication in the distributed environment has an adverse influence on the classification accuracy; therefore, a research challenge lies in maintaining a balance between transmission cost and accuracy. This paper proposes a method based on Bayesian inference to reduce the communication volume in a heterogeneous distributed environment while retaining prediction accuracy. Our experimental evaluation reveals that a significant reduction in communication can be achieved across a diverse range of dataset types.

Keywords: big data, bayesian inference, distributed data stream mining, heterogeneous-distributed data

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2125 Bayesian Parameter Inference for Continuous Time Markov Chains with Intractable Likelihood

Authors: Randa Alharbi, Vladislav Vyshemirsky

Abstract:

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

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

Procedia PDF Downloads 194