Search results for: DNA extraction methods

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: Dalvir Kataria, Khushminder Kaur Chahal, Amit Kumar

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The carrot seed essential oil was obtained by hydrodistillation. Hexane, dichloromethane, and methanol solvents were used for extraction of carrot seed by Soxhlet extraction methods. The major and minor compounds identified in carrot seed essential oil were carotol (52.73), daucol (5.10), daucene (5.68), (E)-β-farnesene (5.40), β-cubebene (3.19), longifolenaldehyde (3.23), β-elimene (3.23), (E)-caryophyllene (1.22), β-bisabolene (2.95) etc. The chemical composition of hexane, dichloromethane, and methanol extracts was different. Carotol was the common compound present. Major compounds isolated were from the carrot seed essential oil by column chromatography. Chemical transformations of carotol (2) with mercuric acetate/sodium borohydride, dry hydrochloric acid gas, acetonitrile/sulfuric acid, selenium dioxide/t-butyl hydrogen peroxide, N-bromosuccinimide, hydrogen iodide, and phenol were carried out. The derivatives of carotol were designed to explore the significance of some structural modifications in relation to antioxidant activities. The structures of major compounds and derivatives were confirmed on the basis of FT-IR, 1HNMR and 13CNMR spectroscopy. Antioxidant activity of carrot seed essential oil, various extracts and isolated compounds were tested by in vitro models involving 2, 2-diphenyl-1-picrylhydrazyl (DPPH•), hydroxyl (OH•), nitric oxide (NO•), superoxide radical scavenging methods and ferric reducing antioxidant power assay (FRAP). Chemical transformations of major isolated compound carotol were carried out, and antioxidant activity of all compounds was undertaken. The major sesquiterpenoidcarotol isolated from carrot seed essential oil showed the highest antioxidant activity in all the methods. The methanol extract showed higher antioxidant potential as compared to carrot seed essential oil, hexane, and dichloromethane extracts.

Keywords: antioxidant, carotol, carrot, DPPH

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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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

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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: Shweta Kumari, Parmjit S. Panesar, Manab B. Bera

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The hydrolysis of lactose using β-galactosidase is one of the most promising biotechnological applications, which has wide range of potential applications in food processing industries. However, due to intracellular location of the yeast enzyme, and expensive extraction methods, the industrial applications of enzymatic hydrolysis processes are being hampered. The use of permeabilization technique can help to overcome the problems associated with enzyme extraction and purification of yeast cells and to develop the economically viable process for the utilization of whole cell biocatalysts in food industries. In the present investigation, standardization of permeabilization process of novel yeast isolate was carried out using a statistical model approach known as Response Surface Methodology (RSM) to achieve maximal b-galactosidase activity. The optimum operating conditions for permeabilization process for optimal β-galactosidase activity obtained by RSM were 1:1 ratio of toluene (25%, v/v) and ethanol (50%, v/v), 25.0 oC temperature and treatment time of 12 min, which displayed enzyme activity of 1.71 IU /mg DW.

Keywords: β-galactosidase, optimization, permeabilization, response surface methodology, yeast

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Authors: Jinlu Ruan, Liang Chen, Bo Liu, Xiaoping Ouyang, Zhichao Zhu, Zhongbing Zhang, Shiyi He, Mengxuan Xu

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Plastic scintillators play an important role in the measurement of a mixed neutron/gamma pulsed radiation, neutron radiography and pulse shape discrimination technology. In some research, these luminescent properties are necessary that photons produced by the interactions between a plastic scintillator and radiations can be detected as much as possible by the photoelectric detectors and more photons can be emitted from the scintillators along a specific direction where detectors are located. Unfortunately, a majority of these photons produced are trapped in the plastic scintillators due to the total internal reflection (TIR), because there is a significant light-trapping effect when the incident angle of internal scintillation light is larger than the critical angle. Some of these photons trapped in the scintillator may be absorbed by the scintillator itself and the others are emitted from the edges of the scintillator. This makes the light extraction of plastic scintillators very low. Moreover, only a small portion of the photons emitted from the scintillator easily can be detected by detectors effectively, because the distribution of the emission directions of this portion of photons exhibits approximate Lambertian angular profile following a cosine emission law. Therefore, enhancing the light extraction efficiency and adjusting the emission angular profile become the keys for improving the number of photons detected by the detectors. In recent years, photonic crystal structures have been covered on inorganic scintillators to enhance the light extraction efficiency and adjust the angular profile of scintillation light successfully. However, that, preparation methods of photonic crystals will deteriorate performance of plastic scintillators and even destroy the plastic scintillators, makes the investigation on preparation methods of photonic crystals for plastic scintillators and luminescent properties of plastic scintillators with photonic crystal structures inadequate. Although we have successfully made photonic crystal structures covered on the surface of plastic scintillators by a modified self-assembly technique and achieved a great enhance of light extraction efficiency without evident angular-dependence for the angular profile of scintillation light, the preparation of photonic crystal structures with large area (the diameter is larger than 6cm) and perfect periodic structure is still difficult. In this paper, large area photonic crystals on the surface of scintillators were prepared by nanoimprint lithography firstly, and then a conformal layer with material of high refractive index on the surface of photonic crystal by atomic layer deposition technique in order to enhance the stability of photonic crystal structures and increase the number of leaky modes for improving the light extraction efficiency. The luminescent properties of the plastic scintillator with photonic crystals prepared by the mentioned method are compared with those of the plastic scintillator without photonic crystal. The results indicate that the number of photons detected by detectors is increased by the enhanced light extraction efficiency and the angular profile of scintillation light exhibits evident angular-dependence for the scintillator with photonic crystals. The mentioned preparation of photonic crystals is beneficial to scintillation detection applications and lays an important technique foundation for the plastic scintillators to meet special requirements under different application backgrounds.

Keywords: angular profile, atomic layer deposition, light extraction efficiency, plastic scintillator, photonic crystal

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Authors: Harshit Mahandra, Rashmi Singh, Bina Gupta

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Molybdenum is widely used in thermocouples, anticathode of X-ray tubes and in the production of alloys of steels. Molybdenum compounds are extensively used as a catalyst in petroleum-refining industries for hydrodesulphurization. Activity of the catalysts decreases gradually with time and are dumped as hazardous waste due to contamination with toxic materials during the process. These spent catalysts can serve as a secondary source for metal recovery and help to sort out environmental and economical issues. In present study, extraction and separation of molybdenum from a Mo-Co spent catalyst leach liquor containing 0.870 g L⁻¹ Mo, 0.341 g L⁻¹ Co, 0.422 ×10⁻¹ g L⁻¹ Fe and 0.508 g L⁻¹ Al in 3 mol L⁻¹ HCl has been investigated using solvent extraction technique. The extracted molybdenum has been finally recovered as molybdenum trioxide. Leaching conditions used were- 3 mol L⁻¹ HCl, 90°C temperature, solid to liquid ratio (w/v) of 1.25% and reaction time of 60 minutes. 96.45% molybdenum was leached under these conditions. For the extraction of molybdenum from leach liquor, Cyphos IL 104 [trihexyl(tetradecyl)phosphonium bis(2,4,4-trimethylpentyl)phosphinate] in toluene was used as an extractant. Around 91% molybdenum was extracted with 0.02 mol L⁻¹ Cyphos IL 104, and 75% of molybdenum was stripped from the loaded organic phase with 2 mol L⁻¹ HNO₃ at A/O=1/1. McCabe Thiele diagrams were drawn to determine the number of stages required for the extraction and stripping of molybdenum. According to McCabe Thiele plots, two stages are required for both extraction and stripping of molybdenum at A/O=1/1 which were also confirmed by countercurrent simulation studies. Around 98% molybdenum was extracted in two countercurrent extraction stages with no co-extraction of cobalt and aluminum. Iron was removed from the loaded organic phase by scrubbing with 0.01 mol L⁻¹ HCl. Quantitative recovery of molybdenum is achieved in three countercurrent stripping stages at A/O=1/1. Trioxide of molybdenum was obtained from strip solution and was characterized by XRD, FE-SEM and EDX techniques. Molybdenum trioxide due to its distinctive electrochromic, thermochromic and photochromic properties is used as a smart material for sensors, lubricants, and Li-ion batteries. Molybdenum trioxide finds application in various processes such as methanol oxidation, metathesis, propane oxidation and in hydrodesulphurization. It can also be used as a precursor for the synthesis of MoS₂ and MoSe₂.

Keywords: Cyphos IL 104, molybdenum, spent Mo-Co catalyst, recovery

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Authors: Mihai-Alexandru Florea, Veronica Drumea, Roxana Nita, Cerasela Gird, Laura Olariu

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The aim of this study was to investigate the residues of pesticide found in tea water infusions. A multi-residues method to determine 147 pesticides has been developed using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged, Safe) procedure and dispersive solid phase extraction (d-SPE) for the cleanup the pesticides from complex matrices such as plants and tea. Sample preparation was carefully optimized for the efficient removal of coextracted matrix components by testing more solvent systems. Determination of pesticides was performed using GC-MS/MS (100 of pesticides) and LC-MS/MS (47 of pesticides). The selected reaction monitoring (SRM) mode was chosen to achieve low detection limits and high compounds selectivity and sensitivity. Overall performance was evaluated and validated according to DG-SANTE Guidelines. To assess the pesticide residue transfer rate (qualitative) from dried tea in infusions the samples (tea) were spiked with a mixture of pesticides at the maximum residues level accepted for teas and herbal infusions. In order to investigate the release of the pesticides in tea preparations, the medicinal plants were prepared in four ways by variation of water temperature and the infusion time. The pesticides from infusions were extracted using two methods: QuEChERS versus solid-phase extraction (SPE). More that 90 % of the pesticides studied was identified in infusion.

Keywords: tea, solid-phase extraction (SPE), selected reaction monitoring (SRM), QuEChERS

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

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

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

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Authors: Mário Silva, Filipa Gomes, Filipa Oliveira, Simone Morais, Cristina Delerue-Matos

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Brown seaweeds are abundant in Portuguese coastline and represent an almost unexploited marine economic resource. One of the most common species, easily available for harvesting in the northwest coast, is Saccorhiza polyschides grows in the lowest shore and costal rocky reefs. It is almost exclusively used by local farmers as natural fertilizer, but contains a substantial amount of valuable compounds, particularly alginates, natural biopolymers of high interest for many industrial applications. Alginates are natural polysaccharides present in cell walls of brown seaweed, highly biocompatible, with particular properties that make them of high interest for the food, biotechnology, cosmetics and pharmaceutical industries. Conventional extraction processes are based on thermal treatment. They are lengthy and consume high amounts of energy and solvents. In recent years, microwave-assisted extraction (MAE) has shown enormous potential to overcome major drawbacks that outcome from conventional plant material extraction (thermal and/or solvent based) techniques, being also successfully applied to the extraction of agar, fucoidans and alginates. In the present study, acid pretreatment of brown seaweed Saccorhiza polyschides for subsequent microwave-assisted extraction (MAE) of alginate was optimized. Seaweeds were collected in Northwest Portuguese coastal waters of the Atlantic Ocean between May and August, 2014. Experimental design was used to assess the effect of temperature and acid pretreatment time in alginate extraction. Response surface methodology allowed the determination of the optimum MAE conditions: 40 mL of HCl 0.1 M per g of dried seaweed with constant stirring at 20ºC during 14h. Optimal acid pretreatment conditions have enhanced significantly MAE of alginates from Saccorhiza polyschides, thus contributing for the development of a viable, more environmental friendly alternative to conventional processes.

Keywords: acid pretreatment, alginate, brown seaweed, microwave-assisted extraction, response surface methodology

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Authors: Khaled Khaladi, Rafika Bibi, Hind Mokrane, Boubekeur Nadjemi

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Sorghum (Sorghum bicolor (L.) Moench) is an important cereal crop grown in the semi-arid tropics of Africa and Asia due to its drought tolerance. Sorghum grain has protein content varying from 6 to 18%, with an average of 11%, Sorghum proteins can be broadly classified into prolamin and non-prolamin proteins. Kafirins, the major storage proteins, are classified as prolamins, and as such, they contain high levels of proline and glutamine and are soluble in non-polar solvents such as aqueous alcohols. Kafirins account for 77 to 82% of the protein in the endosperm, whereas non-prolamin proteins (namely, albumins, globulins, and glutelins) make up about 30% of the proteins. To optimize the extraction of sorghum proteins, several variables were examined: detergent type and concentration, reducing agent type and concentration, and buffer pH and concentration. Samples were quantified and characterized by RP-HPLC.

Keywords: sorghum, protein extraction, detergent, food science

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Authors: Tei Kim, Brooklynn McNeil, Kathryn Dunn, Douglas I. Walker

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To better characterize the relationship between complex chemical exposures and disease, our laboratory uses an approach that combines low-cost, polydimethylsiloxane (silicone) wristband samplers that absorb many of the chemicals we are exposed to with untargeted high-resolution mass spectrometry (HRMS) to characterize 1000’s of chemicals at a time. In studies with human populations, these wristbands can provide an important measure of our environment: however, there is a need to use this approach in large cohorts to study exposures associated with the disease. To facilitate the use of silicone samplers in large scale population studies, the goal of this research project was to establish automated sample preparation methods that improve throughput, robustness, and scalability of analytical methods for silicone wristbands. Using the Opentron OT2 automated liquid platform, which provides a low-cost and opensource framework for automated pipetting, we created two separate workflows that translate the manual wristband preparation method to a fully automated protocol that requires minor intervention by the operator. These protocols include a sequence generation step, which defines the location of all plates and labware according to user-specified settings, and a transfer protocol that includes all necessary instrument parameters and instructions for automated solvent extraction of wristband samplers. These protocols were written in Python and uploaded to GitHub for use by others in the research community. Results from this project show it is possible to establish automated and open source methods for the preparation of silicone wristband samplers to support profiling of many environmental exposures. Ongoing studies include deployment in longitudinal cohort studies to investigate the relationship between personal chemical exposure and disease.

Keywords: bioinformatics, automation, opentrons, research

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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Authors: Yassine Jamoussi, Ameni Youssfi, Henda Ben Ghezala

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With the growing interest in social networking, the interaction of social actors evolved to a source of knowledge in which it becomes possible to perform context aware-reasoning. The information extraction from social networking especially Twitter and Facebook is one of the problems in this area. To extract text from social networking, we need several lexical features and large scale word clustering. We attempt to expand existing tokenizer and to develop our own tagger in order to support the incorrect words currently in existence in Facebook and Twitter. Our goal in this work is to benefit from the lexical features developed for Twitter and online conversational text in previous works, and to develop an extraction model for constructing a huge knowledge based on actions

Keywords: social networking, information extraction, part-of-speech tagging, natural language processing

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Authors: Teerapon Pirom, Ura Pancharoen

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Amoxicillin is an antibiotic which is widely used to treat various infections in both human beings and animals. However, when amoxicillin is released into the environment, it is a major problem. Amoxicillin causes bacterial resistance to these drugs and failure of treatment with antibiotics. Liquid membrane is of great interest as a promising method for the separation and recovery of the target ions from aqueous solutions due to the use of carriers for the transport mechanism, resulting in highly selectivity and rapid transportation of the desired metal ions. The simultaneous processes of extraction and stripping in a single unit operation of liquid membrane system are very interesting. Therefore, it is practical to apply liquid membrane, particularly the HFSLM for industrial applications as HFSLM is proved to be a separation process with lower capital and operating costs, low energy and extractant with long life time, high selectivity and high fluxes compared with solid membranes. It is a simple design amenable to scaling up for industrial applications. The extraction and recovery for (Amoxicillin) through the hollow fiber supported liquid membrane (HFSLM) using aliquat336 as a carrier were explored with the experimental data. The important variables affecting on transport of amoxicillin viz. extractant concentration and operating time were investigated. The highest AMOX- extraction percentages of 85.35 and Amoxicillin stripping of 80.04 were achieved with the best condition at 6 mmol/L [aliquat336] and operating time 100 min. The extraction reaction order (n) and the extraction reaction rate constant (kf) were found to be 1.00 and 0.0344 min-1, respectively.

Keywords: aliquat336, amoxicillin, HFSLM, kinetic

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Authors: Ram Prasad Baral

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A large number of herb materials contain Essential Oils with extensive bioactivities. Acknowledging the importance of plants and its medicinal value, extraction of Essential Oil had been done using Steam Distillation method. In this project, Steam Distillation was used to extract oil from different plant materials like Chamomilla recutita (L.) Rauschert, Artemisia Vulgaris L, Rhododendron anthopogon D. Don, Cymbopogon nardus L, Andropogon nardus, Cinnamomum tamala, Juniperus spp, Cymbopohonflexuosus flexuous, Mantha Arvensia, Nardostachys Jatamansi, Wintergreen Essential Oil, and Valeriana Officinalis. Research has confirmed centuries of practical use of essential oils, and we now know that the 'fragrant pharmacy' contains compounds with an extremely broad range of biochemical effects. Essential oils are so termed as they are believed to represent the very essence of odor and flavor. The recovery of Essential Oil from the raw botanical starting material is very important since the quality of the oil is greatly influenced during this step. There is a variety of methods for obtaining volatile oils from plants. Steam distillation method was found to be one of the promising techniques for the extraction of essential oil from plants as reputable distiller will preserve the original qualities of the plant. The distillation was conducted in Clevenger apparatus in which boiling, condensing, and decantation was done. Analysis of essential oil was done using Gas Chromatography-Mass Spectrometer apparatus, which gives evaluates essential oil qualitatively and quantitatively. The volume of essential oil obtained was changing with respect to temperature and time of heating.

Keywords: Chamomilla recutita (L.) Rauschert, Artemisia Vulgaris L, Rhododendron anthopogon D. Don, Cymbopogon nardus L, Andropogon nardus, Cinnamomum tamala, Juniperus spp, Cymbopohonflexuosus flexuous, Mantha

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Authors: Omid Tavakol, Mahnaz Gholami

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Introduction : In this oral presentation the main goal is discussing immediate loading in dental implants , from treatment planning and surgical guide designing to delivery , follow up and occlusal consideration . Methods and materials : first of all systematic reviews about immediate loading will be considered . besides , a comparison will be made between immediate loading and conventional loading in terms of success rate and complications . After that different methods , prosthetic options and materials best used in immediate loading will be explained. Particularly multi unit abutments and their mechanism of function will be explained .Digital impressions and designing the temporaries is the next topic we are to explicate .Next issue is the differences between single unit , multiple unit and full arch implantation in immediate loading .Following we are going to describe methods for tissue engineering and papilla formation after extraction . Last slides are about a full mouth rehabilitation via immediate loading technique from surgical designing to follow up .At the end we would talk about potential complications , how to prevent from occurrence and what to do if we face up with .

Keywords: guided surgery, digital implantology, immediate loading, digital dentistry

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Authors: Marcela De Oliveira, Marina P. Da Silva, Fernando C. G. Da Rocha, Jorge M. Santos, Jaime S. Cardoso, Paulo N. Lisboa-Filho

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Multiple Sclerosis (MS) is an immune-mediated disease of the central nervous system characterized by neurodegeneration, inflammation, demyelination, and axonal loss. Magnetic resonance imaging (MRI), due to the richness in the information details provided, is the gold standard exam for diagnosis and follow-up of neurodegenerative diseases, such as MS. Brain atrophy, the gradual loss of brain volume, is quite extensive in multiple sclerosis, nearly 0.5-1.35% per year, far off the limits of normal aging. Thus, the brain volume quantification becomes an essential task for future analysis of the occurrence atrophy. The analysis of MRI has become a tedious and complex task for clinicians, who have to manually extract important information. This manual analysis is prone to errors and is time consuming due to various intra- and inter-operator variability. Nowadays, computerized methods for MRI segmentation have been extensively used to assist doctors in quantitative analyzes for disease diagnosis and monitoring. Thus, the purpose of this work was to evaluate the brain volume in MRI of MS patients. We used MRI scans with 30 slices of the five patients diagnosed with multiple sclerosis according to the McDonald criteria. The computational methods for the analysis of images were carried out in two steps: segmentation of the brain and brain volume quantification. The first image processing step was to perform brain extraction by skull stripping from the original image. In the skull stripper for MRI images of the brain, the algorithm registers a grayscale atlas image to the grayscale patient image. The associated brain mask is propagated using the registration transformation. Then this mask is eroded and used for a refined brain extraction based on level-sets (edge of the brain-skull border with dedicated expansion, curvature, and advection terms). In the second step, the brain volume quantification was performed by counting the voxels belonging to the segmentation mask and converted in cc. We observed an average brain volume of 1469.5 cc. We concluded that the automatic method applied in this work can be used for the brain extraction process and brain volume quantification in MRI. The development and use of computer programs can contribute to assist health professionals in the diagnosis and monitoring of patients with neurodegenerative diseases. In future works, we expect to implement more automated methods for the assessment of cerebral atrophy and brain lesions quantification, including machine-learning approaches. Acknowledgements: This work was supported by a grant from Brazilian agency Fundação de Amparo à Pesquisa do Estado de São Paulo (number 2019/16362-5).

Keywords: brain volume, magnetic resonance imaging, multiple sclerosis, skull stripper

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Authors: S. G. Vasantharaju, Viswanath Guptha, Raghavendra Shetty

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Introduction: Aminophylline is a methylxanthine derivative belonging to the class bronchodilator. From the literature survey, reported methods reveals the solid phase extraction and liquid liquid extraction which is highly variable, time consuming, costly and laborious analysis. Present work aims to develop a simple, highly sensitive, precise and accurate high-performance liquid chromatography method for the quantification of Aminophylline in rat plasma samples which can be utilized for preclinical studies. Method: Reverse Phase high-performance liquid chromatography method. Results: Selectivity: Aminophylline and the internal standard were well separated from the co-eluted components and there was no interference from the endogenous material at the retention time of analyte and the internal standard. The LLOQ measurable with acceptable accuracy and precision for the analyte was 0.5 µg/mL. Linearity: The developed and validated method is linear over the range of 0.5-40.0 µg/mL. The coefficient of determination was found to be greater than 0.9967, indicating the linearity of this method. Accuracy and precision: The accuracy and precision values for intra and inter day studies at low, medium and high quality control samples concentrations of aminophylline in the plasma were within the acceptable limits Extraction recovery: The method produced consistent extraction recovery at all 3 QC levels. The mean extraction recovery of aminophylline was 93.57 ± 1.28% while that of internal standard was 90.70 ± 1.30%. Stability: The results show that aminophylline is stable in rat plasma under the studied stability conditions and that it is also stable for about 30 days when stored at -80˚C. Pharmacokinetic studies: The method was successfully applied to the quantitative estimation of aminophylline rat plasma following its oral administration to rats. Discussion: Preclinical studies require a rapid and sensitive method for estimating the drug concentration in the rat plasma. The method described in our article includes a simple protein precipitation extraction technique with ultraviolet detection for quantification. The present method is simple and robust for fast high-throughput sample analysis with less analysis cost for analyzing aminophylline in biological samples. In this proposed method, no interfering peaks were observed at the elution times of aminophylline and the internal standard. The method also had sufficient selectivity, specificity, precision and accuracy over the concentration range of 0.5 - 40.0 µg/mL. An isocratic separation technique was used underlining the simplicity of the presented method.

Keywords: Aminophyllin, preclinical pharmacokinetics, rat plasma, RPHPLC

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: Arash Rafiei, Carroll Moore

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Leaching process as the first stage of hydrometallurgy is a multidisciplinary system including material properties, chemistry, reactor design, mechanics and fluid dynamics. Therefore, doing leaching system optimization by pure scientific methods need lots of times and expenses. In this work, a mixture of two titanium ores and one titanium slag are used for extracting titanium for leaching stage of TiO2 pigment production procedure. Optimum titanium extraction can be obtained from following strategies: i) Maximizing titanium extraction without selective digestion; and ii) Optimizing selective titanium extraction by balancing between maximum titanium extraction and minimum impurity digestion. The main difference between two strategies is due to process optimization framework. For the first strategy, the most important stage of production process is concerned as the main stage and rest of stages would be adopted with respect to the main stage. The second strategy optimizes performance of more than one stage at once. The second strategy has more technical complexity compared to the first one but it brings more economical and technical advantages for the leaching system. Obviously, each strategy has its own optimum operational zone that is not as same as the other one and the best operational zone is chosen due to complexity, economical and practical aspects of the leaching system. Experimental design has been carried out by using Taguchi method. The most important advantages of this methodology are involving different technical aspects of leaching process; minimizing the number of needed experiments as well as time and expense; and concerning the role of parameter interactions due to principles of multifactor-at-time optimization. Leaching tests have been done at batch scale on lab with appropriate control on temperature. The leaching tank geometry has been concerned as an important factor to provide comparable agitation conditions. Data analysis has been done by using reactor design and mass balancing principles. Finally, optimum zone for operational parameters are determined for each leaching strategy and discussed due to their economical and practical aspects.

Keywords: titanium leaching, optimization, experimental design, performance analysis

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Authors: Chahrazed Zouaoui

Abstract:

In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Nidal F. Shilbayeh, Remah W. Al-Khatib, Sameer A. Nooh

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Arabic offline handwriting recognition systems are considered as one of the most challenging topics. Arabic Handwritten Numeral Strings are used to automate systems that deal with numbers such as postal code, banking account numbers and numbers on car plates. Segmentation of connected numerals is the main bottleneck in the handwritten numeral recognition system.  This is in turn can increase the speed and efficiency of the recognition system. In this paper, we proposed algorithms for automatic segmentation and feature extraction of Arabic handwritten numeral strings based on Watershed approach. The algorithms have been designed and implemented to achieve the main goal of segmenting and extracting the string of numeral digits written by hand especially in a courtesy amount of bank checks. The segmentation algorithm partitions the string into multiple regions that can be associated with the properties of one or more criteria. The numeral extraction algorithm extracts the numeral string digits into separated individual digit. Both algorithms for segmentation and feature extraction have been tested successfully and efficiently for all types of numerals.

Keywords: handwritten numerals, segmentation, courtesy amount, feature extraction, numeral recognition

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Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

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This paper presents a comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in the speaker-dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signals to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients give best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose, the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfies the real-time requirements and is suitable for applications in embedded systems.

Keywords: isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW

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Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Pratima Kumari, Sukha Ranjan Samadder

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This research aims to contribute to the sustainable production of graphene materials by exploring the extraction of graphite from spent primary and secondary batteries. The increasing demand for graphene materials, a versatile and high-performance material, necessitates environmentally friendly methods for its synthesis. The process involves a well-planned methodology, beginning with the gathering and categorization of batteries, followed by the disassembly and careful removal of graphite from anode structures. The use of environmentally friendly solvents and mechanical techniques ensures an efficient and eco-friendly extraction of graphite. Advanced approaches such as the modified Hummers' method and chemical reduction process are utilized for the synthesis of graphene materials, with a focus on optimizing parameters. Various analytical techniques such as Fourier-transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy, thermogravimetric analysis, and Raman spectroscopy were employed to validate the quality and structure of the produced graphene materials. The major findings of this study reveal the successful implementation of the methodology, leading to the production of high-quality graphene materials suitable for advanced material applications. Thorough characterization using various advanced techniques validates the structural integrity and purity of the graphene. The economic viability of the process is demonstrated through a comprehensive economic analysis, highlighting the potential for large-scale production. This research contributes to the field of sustainable production of graphene materials by offering a systematic methodology that efficiently transforms spent batteries into valuable graphene resources. Furthermore, the findings not only showcase the potential for upcycling electronic waste but also address the pressing need for environmentally conscious processes in advanced material synthesis.

Keywords: spent primary batteries, spent secondary batteries, graphite extraction, advanced material synthesis, circular economy approach

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Authors: K. Benhabib, X. Pierens, V-D Nguyen, G. Mimanne

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The main hypothesis of the dynamics of solid phase microextraction (SPME) is that steady-state mass transfer is respected throughout the SPME extraction process. It considers steady-state diffusion is established in the two phases and fast exchange of the analyte at the solid phase film/water interface. An improved model is proposed in this paper to handle with the situation when the analyte (atrazine) is in contact with colloid suspensions (carboxylate latex in aqueous solution). A mathematical solution is obtained by substituting the diffusion coefficient by the mean of diffusion coefficient between analyte and carboxylate latex, and also thickness layer by the mean thickness in aqueous solution. This solution provides an equation relating the extracted amount of the analyte to the extraction a little more complicated than previous models. It also gives a better description of experimental observations. Moreover, the rate constant of analyte obtained is in satisfactory agreement with that obtained from the initial curve fitting.

Keywords: pesticide, solid-phase microextraction (SPME) methods, steady state, analytical model

Procedia PDF Downloads 459