Journal articles: 'Extraction de graphes'

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Ahmad, Jawad, Abdur Rehman, Hafiz Tayyab Rauf, Kashif Javed, Maram Abdullah Alkhayyal, and Abeer Ali Alnuaim. "Service Recommendations Using a Hybrid Approach in Knowledge Graph with Keyword Acceptance Criteria." Applied Sciences 12, no. 7 (March 31, 2022): 3544. http://dx.doi.org/10.3390/app12073544.

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Businesses are overgrowing worldwide; people struggle for their businesses and startups in almost every field of life, whether industrial or academic. The businesses or services have multiple income streams with which they generate revenue. Most companies use different marketing and advertisement strategies to engage their customers and spread their services worldwide. Service recommendation systems are gaining popularity to recommend the best services and products to customers. In recent years, the development of service-oriented computing has had a significant impact on the growth of businesses. Knowledge graphs are commonly used data structures to describe the relations among data entities in recommendation systems. Domain-oriented user and service interaction knowledge graph (DUSKG) is a framework for keyword extraction in recommendation systems. This paper proposes a novel method of chunking-based keyword extractions for hybrid recommendations to extract domain-specific keywords in DUSKG. We further show that the performance of the hybrid approach is better than other techniques. The proposed chunking method for keyword extraction outperforms the existing value feature entity extraction (VF2E) by extracting fewer keywords.

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Cramond, Fala, Alison O'Mara-Eves, Lee Doran-Constant, Andrew SC Rice, Malcolm Macleod, and James Thomas. "The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews." Wellcome Open Research 3 (March 7, 2019): 157. http://dx.doi.org/10.12688/wellcomeopenres.14738.3.

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Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we integrated and customised two existing JavaScript libraries to create a new web-based graphical data extraction tool to assist reviewers in extracting data from graphs. This tool aims to facilitate more accurate and timely data extraction through a user interface which can be used to extract data through mouse clicks. We carried out a non-inferiority evaluation to examine its performance in comparison with participants’ standard practice for extracting data from graphs in PDF documents. Results: We found that the customised graphical data extraction tool is not inferior to users’ (N=10) prior standard practice. Our study was not designed to show superiority, but suggests that, on average, participants saved around 6 minutes per graph using the new tool, accompanied by a substantial increase in accuracy. Conclusions: Our study suggests that the incorporation of this type of tool in online systematic review software would be beneficial in facilitating the production of accurate and timely evidence synthesis to improve decision-making.

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Hernández-García, Ángel, and Miguel Ángel Conde-González. "Bridging the Gap between LMS and Social Network Learning Analytics in Online Learning." Journal of Information Technology Research 9, no. 4 (October 2016): 1–15. http://dx.doi.org/10.4018/jitr.2016100101.

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Despite the great potential of social network analysis (SNA) methods and visualizations for learning analytics in computer-supported collaborative learning (CSCL), these approaches have not been fully explored due to two important barriers: the scarcity and limited functionality of built-in tools in Learning Management Systems (LMS), and the difficulty to import educational data from formal virtual learning environments into social network analysis programs. This study aims to cover that gap by introducing GraphFES, an application and web service for extraction of interaction data from Moodle message boards and generation of the corresponding social graphs for later analysis using Gephi, a general purpose SNA software. In addition, this paper briefly illustrates the potential of the combination of the three systems (Moodle, GraphFES and Gephi) for social learning analytics using real data from a computer-supported collaborative learning course with strong focus on teamwork and intensive use of forums.

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REBENCIUC, Ioana, and Ovidiu TIȚA. "Influence of Pectolytic Enzymes on the Quality of Wine Maceration." Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Animal Science and Biotechnologies 75, no. 1 (May 19, 2018): 53. http://dx.doi.org/10.15835/buasvmcn-asb:000417.

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Obtaining high-quality wines with a registered designation of origin means making the most of the specific features of the variety and those imprinted with technology and the place of harvesting. The aroma is due to the chemical compounds of terpenic nature that accumulate in the grapes (variety flavors) and the secondary aromas that are formed during the alcoholic fermentation and the aging period of the wines (Amrani, and Glories, 1995). The wine-making of the varieties is followed by the appreciation of the primary grapes. This is achieved by preferential maceration of the must by means of enzymes (Marin et al., 1998). The technology of aromatic wines has two fundamental objectives: extracting the primary aromas of grapes (terpenols) and favoring the formation of secondary fermentation aromas. In order to obtain aromatic wines with variety typology, the preferential stage is decisive. Pectolytic enzyme preparations are used in oenology to accelerate and complete the extraction and clarification processes of the must, extracting and stabilizing the color, highlighting the varietal aromatic potential of the varieties and improving the filterability and maturation of the wines.

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Cramond, Fala, Alison O'Mara-Eves, Lee Doran-Constant, Andrew SC Rice, Malcolm Macleod, and James Thomas. "The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews." Wellcome Open Research 3 (December 10, 2018): 157. http://dx.doi.org/10.12688/wellcomeopenres.14738.1.

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Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we developed a new web-based graphical data extraction tool to assist reviewers in extracting data from graphs. This tool aims to facilitate more accurate and timely data extraction through a user interface which can be used to extract data through mouse clicks. We carried out a non-inferiority evaluation to examine its performance in comparison to standard practice. Results: We found that our new graphical data extraction tool is not inferior to users’ prior preferred current approaches. Our study was not designed to show superiority, but suggests that there may be a saving in time of around 6 minutes per graph, accompanied by a substantial increase in accuracy. Conclusions: Our study suggests that the incorporation of this type of tool in online systematic review software would be beneficial in facilitating the production of accurate and timely evidence synthesis to improve decision-making.

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Cramond, Fala, Alison O'Mara-Eves, Lee Doran-Constant, Andrew SC Rice, Malcolm Macleod, and James Thomas. "The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews." Wellcome Open Research 3 (January 25, 2019): 157. http://dx.doi.org/10.12688/wellcomeopenres.14738.2.

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Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we integrated and customised two existing JavaScript libraries to create a new web-based graphical data extraction tool to assist reviewers in extracting data from graphs. This tool aims to facilitate more accurate and timely data extraction through a user interface which can be used to extract data through mouse clicks. We carried out a non-inferiority evaluation to examine its performance in comparison to standard practice. Results: We found that the customised graphical data extraction tool is not inferior to users’ prior preferred current approaches. Our study was not designed to show superiority, but suggests that there may be a saving in time of around 6 minutes per graph, accompanied by a substantial increase in accuracy. Conclusions: Our study suggests that the incorporation of this type of tool in online systematic review software would be beneficial in facilitating the production of accurate and timely evidence synthesis to improve decision-making.

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Taran, Nicolae, Boris Morari, and Olga Soldatenco. "INFLUENCE OF DIFFERENT TECHNOLOGICAL PROCESSES ON THE CONTENT OF BIOLOGICALLY ACTIVE SUBSTANCES AT THE PRODUCTION OF DRY RED WINE FROM THE CABERNET SAUVIGNON VARIETY." Akademos 60, no. 1 (June 2021): 63–67. http://dx.doi.org/10.52673/18570461.21.1-60.08.

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This research was focused on the influence of different fermentation-maceration processes for the optimization of the extraction of anthocyanins, tannins and biologically active substances from grapes of the Cabernet Sauvignon variety and their impact on the quality during dry red wine production. It was determined that increasing the duration of the fermentation-maceration process and extracting 20 % of the juice from the must allow the production of dry red wines with high proanthocyanidin content.

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Czyrski, Andrzej, and Hubert Jarzębski. "Response Surface Methodology as a Useful Tool for Evaluation of the Recovery of the Fluoroquinolones from Plasma—The Study on Applicability of Box-Behnken Design, Central Composite Design and Doehlert Design." Processes 8, no. 4 (April 17, 2020): 473. http://dx.doi.org/10.3390/pr8040473.

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The aim of this study was to find the best design that is suitable for optimizing the recovery of the representatives of the 2nd, 3rd and 4th generation of fluoroquinolones. The following designs were applied: Central Composite Design, Box–Behnken Design and Doehlert Design. The recovery, which was a dependent variable, was estimated for liquid–liquid extraction. The time of shaking, pH, and the volume of the extracting agent (dichloromethane) were the independent variables. All results underwent the statistical analysis (ANOVA), which indicated Central Composite Design as the best model for evaluation of the recovery. For each analyte, an equation was generated that enabled to estimate the theoretical value for the applied conditions. The graphs for these equations were provided by the Response Surface Methodology. The statistical analysis also estimated the most significant factors that have an impact on the liquid–liquid extraction, which occurred to be pH for ciprofloxacin and moxifloxacin and the volume of an extracting solvent for levofloxacin.

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Iglesias-Carres, Lisard, Anna Mas-Capdevila, Lucía Sancho-Pardo, Francisca Isabel Bravo, Miquel Mulero, Begoña Muguerza, and Anna Arola-Arnal. "Optimized Extraction by Response Surface Methodology Used for the Characterization and Quantification of Phenolic Compounds in Whole Red Grapes (Vitis vinifera)." Nutrients 10, no. 12 (December 5, 2018): 1931. http://dx.doi.org/10.3390/nu10121931.

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Scientific research has focused on the characterization of bioactive polyphenols from grape seeds and skins, and the pulp has often been overlooked. However, since the beneficial properties of grapes are associated with the consumption of whole fruit, a full extraction and posterior characterization of the phenolic compounds in whole grapes is required to identify the involved bioactive compounds. Such methodologies are not currently available for the whole edible parts of red grapes. This study aimed to determine the best polyphenol extraction conditions of whole red grapes, and apply the method to characterize and quantify the polyphenol composition of three different grapes. The optimized conditions were 80 mL/g, 65% methanol (1% formic acid), 72 °C, and 100 minutes under agitation of 500 rpm. Also, methanol and ethanol were compared as extraction solvents, and methanol achieved statistically higher extraction rates for anthocyanins. The results of this work suggest a higher quantification of phenolic compounds when red grapes are analyzed whole, including the seeds, pulp, and skin.

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Zohdi, Zeynab, Mahdi Hashemi, Abdusalam Uheida, Mohammad Moein, and Mohamed Abdel-Rehim. "Graphene Oxide Tablets for Sample Preparation of Drugs in Biological Fluids: Determination of Omeprazole in Human Saliva for Liquid Chromatography Tandem Mass Spectrometry." Molecules 24, no. 7 (March 27, 2019): 1191. http://dx.doi.org/10.3390/molecules24071191.

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In this study, a novel sort of sample preparation sorbent was developed, by preparing thin layer graphene oxide tablets (GO-Tabs) utilizing a mixture of graphene oxide and polyethylene glycol on a polyethylene substrate. The GO-Tabs were used for extraction and concentration of omeprazole (OME) in human saliva samples. The determination of OME was carried out using liquid chromatography-tandem mass spectrometry (LC–MS/MS) under gradient LC conditions and in the positive ion mode (ESI+) with mass transitions of m/z 346.3→198.0 for OME and m/z 369.98→252.0 for the internal standard. Standard calibration for the saliva samples was in the range of 2.0–2000 nmol L−1. Limits of detection and quantification were 0.05 and 2.0 nmol L−1, respectively. Method validation showed good method accuracy and precision; the inter-day precision values ranged from 5.7 to 8.3 (%RSD), and the accuracy of determinations varied from −11.8% to 13.3% (% deviation from nominal values). The extraction recovery was 60%, and GO-Tabs could be re-used for more than ten extractions without deterioration in recovery. In this study, the determination of OME in real human saliva samples using GO-Tab extraction was validated.

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Tsiropoulos, Nicholas G., Konstantinos Liapis, Dimitrios T. Likas, and George E. Miliadis. "Determination of Spiroxamine Residues in Grapes, Must, and Wine by Gas Chromatography/Ion Trap-Mass Spectrometry." Journal of AOAC INTERNATIONAL 88, no. 6 (September 1, 2005): 1834–39. http://dx.doi.org/10.1093/jaoac/88.6.1834.

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Abstract Analytical methodology was developed and validated for the determination of spiroxamine residues in grapes, must, and wine by gas chromatography/ion trap-mass spectrometry (GC/IT-MS). Two extraction procedures were used: the first involved grapes, must, and wine extraction with alkaline cyclohexane–dichloromethane (9 + 1, v/v) solution, and the second grape extraction with acetone, dichloromethane, and petroleum ether. In both procedures, the extract was centrifuged, evaporated to dryness, and reconstituted in cyclohexane or 2,2,4-trimethylpentane–toluene (9 + 1, v/v), respectively. Spiroxamine diastereomers A and B were determined by GC/IT-MS, and a matrix effect was observed in the case of grapes but not in must and wine. Recovery of spiroxamine from fortified samples at 0.02 to 5.0 mg/kg ranged from 78–102% for grapes and must, with relative standard deviation (RSD) <13%; for red and white wines, recoveries ranged from 90 to 101% with RSD <9%. The limit of quantification was 0.02 mg/kg for grapes, must, and wine or 0.10 mg/kg for grapes, depending on the extraction procedure used.

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GLAVAŠ, GORAN, and JAN ŠNAJDER. "Construction and evaluation of event graphs." Natural Language Engineering 21, no. 4 (May 1, 2014): 607–52. http://dx.doi.org/10.1017/s1351324914000060.

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AbstractEvents play an important role in natural language processing and information retrieval due to numerous event-oriented texts and information needs. Many natural language processing and information retrieval applications could benefit from a structured event-oriented document representation. In this paper, we proposeevent graphsas a novel way of structuring event-based information from text. Nodes in event graphs represent the individual mentions of events, whereas edges represent the temporal and coreference relations between mentions. Contrary to previous natural language processing research, which has mainly focused on individual event extraction tasks, we describe a complete end-to-end system for event graph extraction from text. Our system is a three-stage pipeline that performs anchor extraction, argument extraction, and relation extraction (temporal relation extraction and event coreference resolution), each at a performance level comparable with the state of the art. We presentEvExtra, a large newspaper corpus annotated with event mentions and event graphs, on which we train and evaluate our models. To measure the overall quality of the constructed event graphs, we propose two metrics based on the tensor product between automatically and manually constructed graphs. Finally, we evaluate the overall quality of event graphs with the proposed evaluation metrics and perform a headroom analysis of the system.

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Bahtaji, Michael Allan A. "Improving students graphing skills and conceptual understanding using explicit Graphical Physics Instructions." Cypriot Journal of Educational Sciences 15, no. 4 (August 31, 2020): 843–53. http://dx.doi.org/10.18844/cjes.v15i4.5063.

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The study presented investigates the effects of supportive graphical interventions on the graphing skills and conceptual understanding of students in physics. In this study, the first group of participants was presented with ready-made graphs during the instruction, the second group was instructed on the proper construction and extraction of graphs, while the third group was instructed to construct graphs independently. The groups were compared with respect to their scores in the graphing skills and achievement tests before and after the instructions. The group that received supportive intervention in construction and extraction of graphs attained the highest number of high-level graphs constructed and obtained the highest increase in the achievement test scores after the instruction. The results revealed that the use of the supportive graphical intervention in the construction and extraction of graphs improved the graphing skills and conceptual understanding of students, especially for those who experienced difficulties in dealing graphs. Keywords: Graphical interventions, construction of graph, interpretation of graph, graphing skills, conceptual understanding;

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Yusuf, Muhammad, Sri Indriati, Muhammad Irsal, Mahyati Latief, Nuraeni Umar, and Nur Fitriani Usdyana Attahmid. "Extraction Optimization of Pigeon Pea Seed Protein and Yield Using Response Surface Methodology." INTEK: Jurnal Penelitian 9, no. 1 (April 1, 2022): 66. http://dx.doi.org/10.31963/intek.v9i1.3530.

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Pigeon Pea (Casanus Cajan L.) is one of the local foods in South Sulawesi. Pigeon pea seeds contain protein that the body can absorb. This study aims to determine the optimum operating conditions for extracting pigeon pea on protein and yield using Ultrasonic-Assisted Extraction (UAE). Response Surface Methodology (RSM) with Box-Behnken Design (BBD) was used by considering three variables, time (30, 40, and 50 min), temperature (40, 50, and 60oC), and methanol concentration (50, 70, and 90%). The experiment results show that yield ranges from 8.85663% to 31.4766% and 46.1538 mg/l to 15584.6 mg/l. Response variables were computed and used to create the contour plot graphs. The optimum operating conditions for sonication extraction were a time of 44.760 minutes, a temperature of 60oC, and a 90% methanol concentration.

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Morris, J. R., W. A. Sistrunk, J. Junek, and C. A. Sims. "Effects of Fruit Maturity, Juice Storage, and Juice Extraction Temperature on Quality of ‘Concord’ Grape Juice." Journal of the American Society for Horticultural Science 111, no. 5 (September 1986): 742–46. http://dx.doi.org/10.21273/jashs.111.5.742.

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Abstract A factorial study was designed to examine the effects of fruit maturities, juice extraction temperatures, storage time, and storage temperature on the quality of ‘Concord’ grape (Vitis labrusca L.) juice. Mature grapes produced juice with superior sensory quality and better objective color initially than less-mature grapes, but juice from grapes at both maturities had similar sensory quality after 18 months. The high extraction temperature (99°C) resulted in juice with better color initially than extraction at 60°, but juice extracted at 85° or 99° resulted in greater browning and loss of total anthocyanins during storage than extraction at 60°. High storage temperature (35°) greatly accelerated quality loss. Sensory color ratings correlated better with a ratio of absorbances at 520/430 nm (r = 0.95) and a/b (r = 0.92) than other objective color measurements.

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Boné, João, Mariana Dias, João C. Ferreira, and Ricardo Ribeiro. "DisKnow: A Social-Driven Disaster Support Knowledge Extraction System." Applied Sciences 10, no. 17 (September 2, 2020): 6083. http://dx.doi.org/10.3390/app10176083.

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This research is aimed at creating and presenting DisKnow, a data extraction system with the capability of filtering and abstracting tweets, to improve community resilience and decision-making in disaster scenarios. Nowadays most people act as human sensors, exposing detailed information regarding occurring disasters, in social media. Through a pipeline of natural language processing (NLP) tools for text processing, convolutional neural networks (CNNs) for classifying and extracting disasters, and knowledge graphs (KG) for presenting connected insights, it is possible to generate real-time visual information about such disasters and affected stakeholders, to better the crisis management process, by disseminating such information to both relevant authorities and population alike. DisKnow has proved to be on par with the state-of-the-art Disaster Extraction systems, and it contributes with a way to easily manage and present such happenings.

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Yoshikawa, Tomohiro, Yuki Uchida, Takeshi Furuhashi, Eiji Hirao, and Hiroto Iguchi. "Extraction of Evaluation Keywords for Analyzing Product Evaluation in User-Reviews Using Hierarchical Keyword Graph." Journal of Advanced Computational Intelligence and Intelligent Informatics 13, no. 4 (July 20, 2009): 457–62. http://dx.doi.org/10.20965/jaciii.2009.p0457.

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Recently, the number of sites on the Internet which give users the opportunity to write their ideas and opinions for the public to read have been increasing. In addition, the number of people who want to know the opinions of others about interesting products has also been increasing. However, it is very difficult for people to read complete reviews on the Internet. This study tries to develop a new system for the analysis of reviews, a system which shows evaluation information about products using graphs of evaluation keywords. This paper focuses on the extraction of evaluation keywords from reviews on the Internet. This paper proposes a method for extracting evaluation keywords and displays its results as graphs. It employs HK Graph (Hierarchical Keyword Graph), which can visualize the relationship among words in a hierarchical network structure based on the co-occurrence information for the keyword graph.

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Khan, Naeemullah, Mustafa Tuzen, and Tasneem Gul Kazi. "Simple and Rapid Dual-Dispersive Liquid–Liquid Microextraction as an Innovative Extraction Method for Uranium in Real Water Samples Prior to the Determination of Uranium by a Spectrophotometric Technique." Journal of AOAC INTERNATIONAL 100, no. 6 (November 1, 2017): 1848–53. http://dx.doi.org/10.5740/jaoacint.17-0054.

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Abstract An innovative, rapid, and simple dual-dispersive liquid–liquid microextraction (DDLL-ME) approach was used to extract uranium from real samples for the first time. The main objective of this study was to disperse extraction solvent by using an air-agitated syringe system to overcome matrix effects and avoid dispersion of hazardous dispersive organic solvents by using heat. The DDLL-ME method consisted of two dispersive liquid–liquid extraction steps with chloroform as the extracting solvent. Uranium formed complexes with 4-(2-thiazolylazo) resorcinol in the aqueous phase and was extracted in extracting solvent (chloroform) after the first dispersive liquid–liquid process. Uranium was then back-extracted in the acidic aqueous phase in a second dispersive liquid–liquid process. Finally, uranium was determined by a spectrophotometric detection technique. The variables that played a key role in the proposed method were studied and optimized. The LOD and sensitivity enhancement factor for uranium were found to be 0.60 µg/L and 45, respectively, under optimized conditions. Calibration graphs were found to be linear in the range of 5.0–600 µg/L. The RSD was 2.5%. Reliability of the proposed method was verified by analyzing certified reference material TM-28.3.

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Niu, L., and Y. Q. Song. "A FASTER R-CNN APPROACH FOR EXTRACTING INDOOR NAVIGATION GRAPH FROM BUILDING DESIGNS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 865–72. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-865-2019.

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Abstract. The indoor navigation graph is crucial for emergency evacuation and route guidance. However, most of existing solutions are limited to the tedious manual solutions and inefficient automatic solutions of the indoor building designs. In this paper, we strive to combine the cutting-edge faster R-CNN deep learning models with spatial connection rules to provide fine quality indoor navigation graphs. The extraction experiment result is convincing for general navigation purpose. But there exist several shortages for faster R-CNN models to overcome, such as optimizations of the complex object detections and ability of handling irregular shape regions for indoor navigation graph extractions.

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Shi, Wei, Weiguo Zheng, Jeffrey Xu Yu, Hong Cheng, and Lei Zou. "Keyphrase Extraction Using Knowledge Graphs." Data Science and Engineering 2, no. 4 (November 16, 2017): 275–88. http://dx.doi.org/10.1007/s41019-017-0055-z.

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Karimiyan, Hanieh, Mohammad Reza Hadjmohammadi, Karthik Laxman Kunjali, Mohammad Mahdi Moein, Joydeep Dutta, and Mohamed Abdel-Rehim. "Graphene Oxide/Polyethylene Glycol-Stick for Thin Film Microextraction of β-Blockers from Human Oral Fluid by Liquid Chromatography-Tandem Mass Spectrometry." Molecules 24, no. 20 (October 11, 2019): 3664. http://dx.doi.org/10.3390/molecules24203664.

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A wooden stick coated with a novel graphene-based nanocomposite (Graphene oxide/polyethylene glycol (GO/PEG)) is introduced and investigated for its efficacy in solid phase microextraction techniques. The GO/PEG-stick was prepared and subsequently applied for the extraction of β-blockers, acebutolol, and metoprolol in human oral fluid samples, which were subsequently detected by liquid chromatography tandem mass spectrometry (LC-MS/MS). Experimental parameters affecting the extraction protocol including sample pH, extraction time, desorption time, appropriate desorption solvent, and salt addition were optimized. Method validation for the detection from oral fluid samples was performed following FDA (Food and Drug Administration) guidelines on bioanalytical method validation. Calibration curves ranging from 5.0 to 2000 nmol L−1 for acebutolol and 25.0 to 2000 nmol L−1 for metoprolol were used. The values for the coefficient of determination (R2) were found to be 0.998 and 0.996 (n = 3) for acebutolol and metoprolol, respectively. The recovery of analytes during extraction was 80.0% for acebutolol and 62.0% for metoprolol, respectively. The limit of detections (LODs) were 1.25, 8.00 nmol L−1 for acebutolol and metoprolol and the lower limit of quantifications (LLOQ) were 5.00 nmol L−1 for acebutolol and 25.0 nmol L−1 for metoprolol. Validation experiments conducted with quality control (QC) samples demonstrated method accuracy between 80.0% to 97.0% for acebutolol and from 95.0% to 109.0% for metoprolol. The inter-day precision for QC samples ranged from 3.6% to 12.9% for acebutolol and 9.5% to 11.3% for metoprolol. Additionally, the GO/PEG-stick was demonstrated to be reusable, with the same stick observed to be viable for more than 10 extractions from oral fluid samples.

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Yuan, Changsen, Heyan Huang, and Chong Feng. "Multi-Graph Cooperative Learning Towards Distant Supervised Relation Extraction." ACM Transactions on Intelligent Systems and Technology 12, no. 5 (October 31, 2021): 1–21. http://dx.doi.org/10.1145/3466560.

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The Graph Convolutional Network (GCN) is a universal relation extraction method that can predict relations of entity pairs by capturing sentences’ syntactic features. However, existing GCN methods often use dependency parsing to generate graph matrices and learn syntactic features. The quality of the dependency parsing will directly affect the accuracy of the graph matrix and change the whole GCN’s performance. Because of the influence of noisy words and sentence length in the distant supervised dataset, using dependency parsing on sentences causes errors and leads to unreliable information. Therefore, it is difficult to obtain credible graph matrices and relational features for some special sentences. In this article, we present a Multi-Graph Cooperative Learning model (MGCL), which focuses on extracting the reliable syntactic features of relations by different graphs and harnessing them to improve the representations of sentences. We conduct experiments on a widely used real-world dataset, and the experimental results show that our model achieves the state-of-the-art performance of relation extraction.

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Hohnová, B., L. Šťavíková, and P. Karásek. "Determination of anthocyanins in red grape skin by pressurised fluid extraction and HPLC." Czech Journal of Food Sciences 26, Special Issue (February 10, 2009): S39—S42. http://dx.doi.org/10.17221/243/2008-cjfs.

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Grape anthocyanins not only play an important role in the colour quality of red wines but they also have many beneficial effects on human health, e.g., reduction of coronary heart disease incidence, or anticarcinogenic and antioxidant properties. Therefore, a rapid and efficient extraction technique prior to chromatographic analysis is of primary interest. Pressurised Fluid Extraction (PFE) presents a fast, effective, and environmentally friendly extraction method for the analysis of red grape pigments. In this study, PFE in static mode was utilised for the extraction of 3-monoglucoside anthocyanins from the grape skin of highly pigmented variety Alibernet. The effects of the type of the extraction solvent and the extraction temperature were studied. The identification of the above given compounds were performed by high-performance liquid chromatography with diode array detection (HPLC-DAD) based on Synergi C-12 column separation. The wavelength was set at 520 nm. All compounds were determined and identified during 50 minutes.

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VICAS, Simona Ioana, Livia BANDICI, Alin Cristian TEUSDEA, and Gheorghe Emil BANDICI. "Extraction of Bioactive Compounds from Two Grape Varieties Using Pulsed Electric Field." Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Food Science and Technology 73, no. 2 (November 28, 2016): 85. http://dx.doi.org/10.15835/buasvmcn-fst:12212.

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In this paper, our objective was to investigate extraction efficiency of polyphenols with antioxidant capacity from two varieties of grapes (white-Muscat Ottonel (MO) and red-Pinot Noir (PN)) using pulsed electric field (PEF). Grapes were harvested in the Crisana Santimreu vineyard in 2015. The grapes were declustered and crushed, and have been divided into three parts. A part was treated in PEF, the second one was homogenized, and then was treated in PEF and the last part remained untreated, representing the control samples. The bioactive compounds, like total polyphenol content and total flavonoid content, were determined by the spectrophotometric method. The antioxidant capacity of the samples was determined by three methods (DPPH, FRAPand TEAC). Our results show that the application of PEF to the crushed grapes increases the total polyphenol content 2.28 and 3.15 times and the total flavonoid content 7.17 and 5.29 times for MO and PN, respectively. Also, the antioxidant capacity was significantly increased when it was compared with the control sample. When the treatment in PEF was applied on homogenized grapes both bioactive compounds and antioxidant capacity were significantly increased compared to the samples treated in PEF for crushed grapes. In the present research work, we demonstrated that the application of PEF to two different grape varieties significantly increased the level of total polyphenols and flavonoids and also the antioxidant capacity. The application of PEF to homogenized grapes was more efficient.

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Fia, Giovanna, Ginevra Bucalossi, Claudio Gori, Francesca Borghini, and Bruno Zanoni. "Recovery of Bioactive Compounds from Unripe Red Grapes (cv. Sangiovese) through a Green Extraction." Foods 9, no. 5 (May 4, 2020): 566. http://dx.doi.org/10.3390/foods9050566.

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Unripe grapes are a potential source of bioactive compounds which can exert antioxidant and antimicrobial activity. However, very little information is available about the composition of unripe grapes extracts and their extraction techniques. This study aims to evaluate the recovery of bioactive compounds and the antioxidant activity of the extract from unripe Sangiovese grapes obtained at an industrial-scale and the composition of the extract during processing. The extraction yield was approximately 75%. During the extraction, the total phenol (TP), antioxidant activity (AA) total anthocyanin (TAnt), pantothenic acid and choline content significantly increased. High concentrations of TP (2522 mgCATeq/L), AA (8227 μmolTEAC/L) and total water-soluble vitamins (1397 μg/L) were reached at the end of process. The antioxidant activity of the extract was positively correlated with all the phenol compounds and the highest correlations were found with procyanidin B1 (r = 0.994; p-value < 0.004), procyanidin B2 (r = 0.989; p-value < 0.004), kaempferol 3-O-glucoside (r = 0.995; p-value < 0.004) and quercetin 3-O-hexoside (r = 0.995; p-value < 0.071). Our findings contribute to the knowledge of the bioactive composition of unripe grapes. An efficient industrial-scale “green” extraction method, ready to be transferred to the wine sector, was developed to obtain a safe extract with a high concentration of bioactive compounds.

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Muñoz García, Raquel, Rodrigo Oliver-Simancas, María Arévalo Villena, Leticia Martínez-Lapuente, Belén Ayestarán, Lourdes Marchante-Cuevas, María Consuelo Díaz-Maroto, and María Soledad Pérez-Coello. "Use of Microwave Maceration in Red Winemaking: Effect on Fermentation and Chemical Composition of Red Wines." Molecules 27, no. 9 (May 7, 2022): 3018. http://dx.doi.org/10.3390/molecules27093018.

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The objective of this study was to evaluate the effect of microwave treatment of crushed grapes on the yeast population of the must and on the development of alcoholic fermentation, as well as on the extraction of different compounds from the grapes such as polysaccharides and amino acids that can affect the organoleptic quality and stability of the wine. This study demonstrated for the first time the effect of the microwave treatment of grapes on native yeast species and their diversity, producing an increase in fermentation kinetics and a decrease in the lag phase. The microwave treatment produced a positive effect on the extraction of amino acids and polysaccharides from the grapes, resulting in significantly higher amounts of the main amino acids of the must and some major volatile compounds in the treated samples. The polysaccharides most affected by the microwave treatment were the PRAGs, the main polysaccharides liberated from grapes during the maceration.

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Manousi, Natalia, Erwin Rosenberg, Eleni A. Deliyanni, and George A. Zachariadis. "Sample Preparation Using Graphene-Oxide-Derived Nanomaterials for the Extraction of Metals." Molecules 25, no. 10 (May 21, 2020): 2411. http://dx.doi.org/10.3390/molecules25102411.

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Graphene oxide is a compound with a form similar to graphene, composed of carbon atoms in a sp2 single-atom layer of a hybrid connection. Due to its significant surface area and its good mechanical and thermal stability, graphene oxide has a plethora of applications in various scientific fields including heterogenous catalysis, gas storage, environmental remediation, etc. In analytical chemistry, graphene oxide has been successfully employed for the extraction and preconcentration of organic compounds, metal ions, and proteins. Since graphene oxide sheets are negatively charged in aqueous solutions, the material and its derivatives are ideal sorbents to bind with metal ions. To date, various graphene oxide nanocomposites have been successfully synthesized and evaluated for the extraction and preconcentration of metal ions from biological, environmental, agricultural, and food samples. In this review article, we aim to discuss the application of graphene oxide and functionalized graphene oxide nanocomposites for the extraction of metal ions prior to their determination via an instrumental analytical technique. Applications of ionic liquids and deep eutectic solvents for the modification of graphene oxide and its functionalized derivatives are also discussed.

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Wang, Erniu, Fan Wang, Zhihao Yang, Lei Wang, Yin Zhang, Hongfei Lin, and Jian Wang. "A Graph Convolutional Network–Based Method for Chemical-Protein Interaction Extraction: Algorithm Development." JMIR Medical Informatics 8, no. 5 (May 19, 2020): e17643. http://dx.doi.org/10.2196/17643.

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Background Extracting the interactions between chemicals and proteins from the biomedical literature is important for many biomedical tasks such as drug discovery, medicine precision, and knowledge graph construction. Several computational methods have been proposed for automatic chemical-protein interaction (CPI) extraction. However, the majority of these proposed models cannot effectively learn semantic and syntactic information from complex sentences in biomedical texts. Objective To relieve this problem, we propose a method to effectively encode syntactic information from long text for CPI extraction. Methods Since syntactic information can be captured from dependency graphs, graph convolutional networks (GCNs) have recently drawn increasing attention in natural language processing. To investigate the performance of a GCN on CPI extraction, this paper proposes a novel GCN-based model. The model can effectively capture sequential information and long-range syntactic relations between words by using the dependency structure of input sentences. Results We evaluated our model on the ChemProt corpus released by BioCreative VI; it achieved an F-score of 65.17%, which is 1.07% higher than that of the state-of-the-art system proposed by Peng et al. As indicated by the significance test (P<.001), the improvement is significant. It indicates that our model is effective in extracting CPIs. The GCN-based model can better capture the semantic and syntactic information of the sentence compared to other models, therefore alleviating the problems associated with the complexity of biomedical literature. Conclusions Our model can obtain more information from the dependency graph than previously proposed models. Experimental results suggest that it is competitive to state-of-the-art methods and significantly outperforms other methods on the ChemProt corpus, which is the benchmark data set for CPI extraction.

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Wahyuni, Sri, Ranti Selvina, Puspa Julistia Puspita, Haryo Tejo Prakoso, Priyono Priyono, and Siswanto Siswanto. "EXTRACTION, CHARACTERIZATION AND APPLICATION OF CHITOSAN DERIVED FROM MAGGOT (BLACK SOLDIER FLY) WASTE AS EDIBLE COATING FOR RED GRAPES (Vitis vinifera)." Jurnal Penelitian Pascapanen Pertanian 18, no. 1 (July 13, 2021): 45. http://dx.doi.org/10.21082/jpasca.v18n1.2021.45-56.

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Black Soldier Fly (BSF) farming showed an increasing trend in the past 5 years. The production process generates a leftover, that is the exuviae which are still untapped. BSF exuviae contain chitin and chitosan which can be utilized in various fields, one of which is fruit preservatives. Grapes (Vitis vinifera) is known to have many benefits and has a content of vitamins A, B, C, and E but it has a short shelf life. The purpose of this study was to characterize chitosan from BSF exuviae and choose the best edible coating method to be applied to grapes to prolong the grape’s storage time. Characterization includes physical condition, percent solubility, degree of deacetylation, and yield of the chitosan. Then, edible coating tests were carried out with 2% acetic acid solvent followed by two different methods, namely dyeing method with 5, 10 and, 15 minutes immersion time and spray method with a chitosan solution concentration of 0,5%, 1%, 1,5%, 2 %, and 2,5%. The results showed that chitosan extracted from BSF exuviae produced a physical appearance in the form of white brown powder with 55% solubility and a degree of deacetylation of 91,88%. The chitin yield is 16,2%, followed by the chitosan yield of 4,8%. The best edible coating method which can maintain the physical appearance of grapes and inhibiting fruit decayed was obtained by dipping method at a concentration of 2,5% for 10 minutes. Based on the overall observations, however, the results obtained from the dip and spray method were not significantly different.

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Liu, Kai, Fei Wang, Zhaoyun Ding, Sheng Liang, Zhengfei Yu, and Yun Zhou. "Recent Progress of Using Knowledge Graph for Cybersecurity." Electronics 11, no. 15 (July 22, 2022): 2287. http://dx.doi.org/10.3390/electronics11152287.

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In today’s dynamic complex cyber environments, Cyber Threat Intelligence (CTI) and the risk of cyberattacks are both increasing. This means that organizations need to have a strong understanding of both their internal CTI and their external CTI. The potential for cybersecurity knowledge graphs is evident in their ability to aggregate and represent knowledge about cyber threats, as well as their ability to manage and reason with that knowledge. While most existing research has focused on how to create a full knowledge graph, how to utilize the knowledge graph to tackle real-world industrial difficulties in cyberattack and defense situations is still unclear. In this article, we give a quick overview of the cybersecurity knowledge graph’s core concepts, schema, and building methodologies. We also give a relevant dataset review and open-source frameworks on the information extraction and knowledge creation job to aid future studies on cybersecurity knowledge graphs. We perform a comparative assessment of the many works that expound on the recent advances in the application scenarios of cybersecurity knowledge graph in the majority of this paper. In addition, a new comprehensive classification system is developed to define the linked works from 9 core categories and 18 subcategories. Finally, based on the analyses of existing research issues, we have a detailed overview of various possible research directions.

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Plaza, E. G., R. Jurado, J. A. Iniesta, and A. B. Bautista-Ortín. "High power ultrasounds: A powerful, non-thermal and green technique for improving the phenolic extraction from grapes to must during red wine vinification." BIO Web of Conferences 12 (2019): 02001. http://dx.doi.org/10.1051/bioconf/20191202001.

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Wine color is one of the main organoleptic characteristics influencing its quality. It is of especial interest in red vinifications due to the economic resources that wineries have to invest for the extraction of the phenolic compounds. To increase this extraction, some chemical (maceration enzymes) or physical technologies (thermovinification, criomaceration, flash-expansion) can be applied. In this work, the results of the application of high power ultrasounds to the crushed grapes to increase the extraction of phenolic compounds are presented. Crushed grapes (400 kg) from the 2017 harvest were treated with ultrasound, and three different lengths of skin maceration period (2, 3 or 7 days) and the results were compared with a control vinification, where grapes were not subjected to any treatment and were skin macerated during 7 days. The wine chromatic characteristics and the individual phenolic compounds were followed during all the maceration period, at the end of alcoholic fermentation and after bottle storage. The wines made with ultrasound treated grapes presented differences with control wine, especially as regard color and total phenol and tannin content, the wines with three days of maceration time presenting similar chromatic characteristics than control wines with 7 days of maceration time.

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Maisonnave, Mariano, Fernando Delbianco, Fernando Tohme, Evangelos Milios, and Ana G. Maguitman. "Causal graph extraction from news: a comparative study of time-series causality learning techniques." PeerJ Computer Science 8 (August 3, 2022): e1066. http://dx.doi.org/10.7717/peerj-cs.1066.

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Causal graph extraction from news has the potential to aid in the understanding of complex scenarios. In particular, it can help explain and predict events, as well as conjecture about possible cause-effect connections. However, limited work has addressed the problem of large-scale extraction of causal graphs from news articles. This article presents a novel framework for extracting causal graphs from digital text media. The framework relies on topic-relevant variables representing terms and ongoing events that are selected from a domain under analysis by applying specially developed information retrieval and natural language processing methods. Events are represented as event-phrase embeddings, which make it possible to group similar events into semantically cohesive clusters. A time series of the selected variables is given as input to a causal structure learning techniques to learn a causal graph associated with the topic that is being examined. The complete framework is applied to the New York Times dataset, which covers news for a period of 246 months (roughly 20 years), and is illustrated through a case study. An initial evaluation based on synthetic data is carried out to gain insight into the most effective time-series causality learning techniques. This evaluation comprises a systematic analysis of nine state-of-the-art causal structure learning techniques and two novel ensemble methods derived from the most effective techniques. Subsequently, the complete framework based on the most promising causal structure learning technique is evaluated with domain experts in a real-world scenario through the use of the presented case study. The proposed analysis offers valuable insights into the problems of identifying topic-relevant variables from large volumes of news and learning causal graphs from time series.

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Cooray, Thilini, and Ngai-Man Cheung. "Graph-Wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (June 28, 2022): 6420–28. http://dx.doi.org/10.1609/aaai.v36i6.20593.

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Unsupervised graph-level representation learning plays a crucial role in a variety of tasks such as molecular property prediction and community analysis, especially when data annotation is expensive. Currently, most of the best-performing graph embedding methods are based on Infomax principle. The performance of these methods highly depends on the selection of negative samples and hurt the performance, if the samples were not carefully selected. Inter-graph similarity-based methods also suffer if the selected set of graphs for similarity matching is low in quality. To address this, we focus only on utilizing the current input graph for embedding learning. We are motivated by an observation from real-world graph generation processes where the graphs are formed based on one or more global factors which are common to all elements of the graph (e.g., topic of a discussion thread, solubility level of a molecule). We hypothesize extracting these common factors could be highly beneficial. Hence, this work proposes a new principle for unsupervised graph representation learning: Graph-wise Common latent Factor EXtraction (GCFX). We further propose a deep model for GCFX, deepGCFX, based on the idea of reversing the above-mentioned graph generation process which could explicitly extract common latent factors from an input graph and achieve improved results on downstream tasks to the current state-of-the-art. Through extensive experiments and analysis, we demonstrate that, while extracting common latent factors is beneficial for graph-level tasks to alleviate distractions caused by local variations of individual nodes or local neighbourhoods, it also benefits node-level tasks by enabling long-range node dependencies, especially for disassortative graphs.

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Ouadid, Youssef, Abderrahmane Elbalaoui, Mehdi Boutaounte, Mohamed Fakir, and Brahim Minaoui. "Handwritten tifinagh character recognition using simple geometric shapes and graphs." Indonesian Journal of Electrical Engineering and Computer Science 13, no. 2 (February 1, 2019): 598. http://dx.doi.org/10.11591/ijeecs.v13.i2.pp598-605.

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In this paper, a graph based handwritten Tifinagh character recognition system is presented. In preprocessing Zhang Suen algorithm is enhanced. In features extraction, a novel key point extraction algorithm is presented. Images are then represented by adjacency matrices defining graphs where nodes represent feature points extracted by a novel algorithm. These graphs are classified using a graph matching method. Experimental results are obtained using two databases to test the effectiveness. The system shows good results in terms of recognition rate.

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ANGELINI, E., I. BAZZO, M. SAVINO, and M. BORGO. "Ochratoxin A: Comparison of Extraction Methods from Grapes and Quantitative Determination by Different Competitive Enzyme-Linked Immunosorbent Assay Kits." Journal of Food Protection 71, no. 12 (December 1, 2008): 2488–96. http://dx.doi.org/10.4315/0362-028x-71.12.2488.

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The European Community has recently established a maximum limit for ochratoxin A (OTA) concentration in grapevine products, but many practical difficulties remain concerning the establishment of optimum cost-effective methods of quantification. The performance of four extraction procedures and three commercial competitive enzyme-linked immunosorbent assays (cELISAs) for grapes were compared. Results differed for the extractions and the cELISA kits. The advantage of using immunoaffinity columns (IACs) in the extraction was the excellent detection limit, which was between 0.06 and 0.0075 ng ml−1 depending on the cELISA kit used. Despite lower sensitivity (between 1.2 and 0.15 ng ml−1 depending on the cELISA kit), an extraction method in liquid phase, which was simple and inexpensive, was confirmed as suitable for quantifying OTA at levels estimated to be dangerous for human health. Two of the three cELISA kits produced satisfactory results. When these two cELISAs were coupled with IAC extraction, the lower quantification limits were 0.010 and 0.0075 ng ml−1, respectively, and the dynamic ranges were 50 and 27, respectively. The most reliable procedures were then compared with the reference method, high-performance liquid chromatography plus fluorescent detection coupled with an IAC. The results were very similar, although the cELISAs generally provided slightly higher values than did the chromatography method. The IAC method coupled with the cELISA was four times more sensitive than was the IAC method coupled with the chromatography method. The cELISA detection techniques were excellent alternatives to the already established chromatographic protocols, especially for mass screening and for determining concentrations of OTA as low as 0.010 ng ml−1.

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Ha, Jaeho, Hye-Young Seo, You-Shin Shim, Hyun-Jin Nam, Homoon Seog, Masahito Ito, and Hiroaki Nakagawa. "Rapid Method for the Determination of Capsaicin and Dihydrocapsaicin in Gochujang Using Ultra-High-Performance Liquid Chromatography." Journal of AOAC INTERNATIONAL 93, no. 6 (November 1, 2010): 1905–11. http://dx.doi.org/10.1093/jaoac/93.6.1905.

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Abstract A sensitive and specific heating block method coupled with ultra-HPLC (u-HPLC) was developed for the analysis of capsaicin in Gochujang and validated by comparing with a conventional HPLC (AOAC Method 995.03). The method validation parameters yielded good results, including linearity, precision, accuracy, and recovery. The u-HPLC separation was performed on a reversed C18 column (50 2 mm id, particle size 2 m), followed by fluorescence detection (excitation 280 nm, emission 325 nm). Methanol was used as the extracting solvent, and the amount of sample taken was approximately 0.2 g; the optimum amount of extraction solvent and extraction time were 15 mL and 1 h, respectively. The recovery of capsaicin in Gochujang was more than 93, and the LOD and LOQ of the u-HPLC analysis were 0.05 and 0.16 g/g for capsaicin and 0.05 and 0.16 g/g for dihydrocapsaicin. The calibration graphs for capsaicin and dihydrocapsaicin were linear from 0.2 to 10.0 g/mL for u-HPLC. The interday and intraday precisions (RSD values) were <6.27.

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Ašperger, Danijela, Marija Gavranić, Barbara Prišlin, Nera Rendulić, Iva Šikuten, Zvjezdana Marković, Bruna Babić, et al. "Optimization of Microwave-Assisted Extraction and Matrix Solid-Phase Dispersion for the Extraction of Polyphenolic Compounds from Grape Skin." Separations 9, no. 9 (September 1, 2022): 235. http://dx.doi.org/10.3390/separations9090235.

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Polyphenols are organic compounds that can be found in food, especially in fruits, vegetables, and their products. It was shown that their presence significantly affects the properties of food products and that the consumption of food rich in phenolic compounds has a beneficial effect on human health. The subjects of this research were polyphenols: anthocyanins, flavonols, and flavan-3-ols in the skin of grapevine variety Regent. Polyphenols from grape skins were extracted via microwave-assisted extraction (MAE) and matrix solid-phase dispersion (MSPD) as unconventional and green techniques. Therefore, the main aim of this work was to optimize the conditions for the extraction of polyphenolic compounds from grape skin using MAE and MSPD. The extracts were analyzed using high-performance liquid chromatography with a diode array detector and fluorescence detector. Analyses showed that MAE was a very effective method for extracting polyphenolic compounds from grape skin with 10 mL of 60% ethanol for 5 min at 40 °C. The best results for the MSPD extraction of polyphenolic compounds from grape skin were obtained with phenyl as an MSPD sorbent with 10 mL of acetonitrile:water 50:50 v/v as an elution solvent. This scientific research can be used for the better use of grapes as a basis for obtaining flavonoids for commercial purposes.

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Du, Weiwei, and Kiichi Urahama. "Unsupervised and Semi-Supervised Graph-Spectral Algorithms for Robust Extraction of Arbitrarily Shaped Fuzzy Clusters." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 6 (July 20, 2007): 554–60. http://dx.doi.org/10.20965/jaciii.2007.p0554.

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We present unsupervised and semi-supervised algorithms for extracting fuzzy clusters in weighted undirected regular, undirected bipartite, and directed graphs. We derive the semi-supervised algorithms from the Lagrangian function in unsupervised methods for extracting dominant clusters in a graph. These algorithms are robust against noisy data and extract arbitrarily shaped clusters. We demonstrate applications for similarity searches of data such as image retrieval in face images represented by undirected graphs, quantized color images represented by undirected bipartite graphs, and Web page links represented by directed graphs.

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Grabowecky, Marcia, Stacey Parrott, Emmanuel Guzman-Martinez, Laura Ortega, and Satoru Suzuki. "Auditory–visual, positional, and semantic effects in visual extraction of slope." Seeing and Perceiving 25 (2012): 196. http://dx.doi.org/10.1163/187847612x648251.

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Extracting slopes from arrays of visual features is crucial for interpreting graphs. To understand broader influences on slope perception, we investigated the effects of concurrent sounds, of relative graph location, and of semantic priming on a visual search task in which observers searched for a graph with a positive or negative slope. Four bar graphs or scatter plots were simultaneously presented in separate quadrants of a visual display. Participants pressed a key as quickly as possible if one of the graphs displayed the target slope and otherwise refrained from response. A concurrently presented ascending pitch slowed responses to negative-slope targets, and concurrently presented descending pitch slowed responses to positive-slope targets, indicating crossmodal interference. This interference was eliminated when the sounds were presented 200 ms before the graphs, consistent with crossmodal interaction rather than response bias. Positive slopes were detected slowest in the upper-left quadrant whereas negative slopes were detected slowest in the upper-right quadrant, suggesting that slope detection is impeded when a graph is placed inconsistently with a mental number-line representation (negative values on the left and positive values on the right). Finally, positive slopes were detected faster when the search display was immediately preceded by a briefly flashed word ‘uphill’ compared to the word ‘downhill’ (and the converse for negative slopes), indicating a semantic priming effect, but this was observed only for scatter plots (the stimulus specificity precluding response bias). In summary, perception of visual slope is systematically influenced by auditory signals, by location of graphs, and by semantic priming.

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Hink, Jessica K., Michael S. Wogalter, and Jason K. Eustace. "Display of Quantitative Information: Are Grables better than Plain Graphs or Tables?" Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 23 (October 1996): 1155–59. http://dx.doi.org/10.1177/154193129604002302.

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Previous research is equivocal on the most efficient, effective methods for displaying quantitative information in tables and graphs. Guidelines suggest different display types are more appropriate for certain purposes but not others. However, there is little empirical evidence to support the recommendations. This study examines several methods of displaying quantitative information (e.g., line graphs, bar charts, tables) factorially crossed with different kinds of data extraction questions (i.e., inquiries about trends, comparisons, and exact numerical quantities). Results showed that tables, bar grables (combined bar graph and table) and line grables produced the most accurate responses, and line graphs and bar charts produced the fastest responses across question types. Results are discussed with respect to prior theoretical work and the potential benefits of hybrid forms of quantitative data displays for multiple kinds of data extraction inquiries.

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Sergazina, Meruyert, Lua Vazquez, Maria Llompart, and Thierry Dagnac. "Occurrence of Fungicides in Vineyard and the Surrounding Environment." Molecules 26, no. 20 (October 12, 2021): 6152. http://dx.doi.org/10.3390/molecules26206152.

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Seventeen fungicides were determined in different matrices from vineyard areas, including vine leaves, soils, grapes and water, using gas chromatography coupled to tandem mass spectrometry (GC-MS/MS). For leaf analysis, ultrasound-assisted extraction (UAE) was performed evaluating different solvents. UAE was compared with other extraction techniques such as vortex extraction (VE) and matrix solid-phase dispersion (MSPD). The performance of the UAE method was demonstrated on vine leaf samples and on other types of samples such as tea leaves, underlining its general suitability for leaf crops. As regards other matrices, soils were analyzed by UAE and microwave-assisted extraction (MAE), grapes by UAE and waters by SPE using cork as the sorbent. The proposed method was applied to 17 grape leaf samples in which 14 of the target fungicides were detected at concentrations up to 1000 μg g−1. Furthermore, the diffusion and transport of fungicides was demonstrated not only in crops but also in environmental matrices.

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Kulichová, Jana, Mantana Buaong, Josef Balík, Pavel Híc, Jan Tříska, and Naděžda Vrchotová. "Juices enriched with phenolic extracts from grapes." Czech Journal of Food Sciences 36, No. 3 (June 28, 2018): 261–67. http://dx.doi.org/10.17221/383/2017-cjfs.

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The paper describes the preparation and evaluation of phenolic extracts from waste materials – pomace (grape marc), seeds and press oil cake of the white grape variety Irsai Oliver (Vitis vinifera L.) and their addition to apple and grape juices to increase the nutritional properties. The waste samples were extracted using 50 or 80% ethanol (v/v). Some of the samples were extracted for 60 min at boiling temperature under reflux; the remainder were processed for 24 h on a shaker at room temperature. The highest antioxidant capacity (as measured using DPPH (758 ± 28 mM Trolox/kg of extracted matter)) and content of total polyphenols (74 ± 0.7 g gallic acid/kg of extracted matter) were found in the extract of the seeds obtained through extraction using 50% ethanol (v/v) at boiling temperature for 60 minutes. The press oil cake extract obtained by means of 80% ethanol (v/v) at boiling temperature for 60 min was evaluated as the best for enriching the sensory quality of apple and grape juices. The addition of 1 g of freeze-dried press oil cake extract to 1 l of juice increased the antioxidant capacity and total polyphenol content two-fold

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Dabetić, Nevena, Vanja Todorović, Manuela Panić, Ivana Radojčić Redovniković, and Sladjana Šobajić. "Impact of Deep Eutectic Solvents on Extraction of Polyphenols from Grape Seeds and Skin." Applied Sciences 10, no. 14 (July 14, 2020): 4830. http://dx.doi.org/10.3390/app10144830.

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In the past few years, research efforts have focused on plant exploitation for deriving some valuable compounds. Extraction has been usually performed using petrochemical and volatile organic solvents, but nowadays, increased recognition of environmental pollution has prompted the utilization of green solvents as alternatives. Therefore, the aim of the present study was to exploit deep eutectic solvents (DES) (choline chloride: citric acid and choline chloride: glucose) as solvents for extracting valuable phenolic antioxidants from grapes. Investigation was conducted on ten grape varieties, observing seeds and skin as different matrix. Total polyphenol content (TPC) was determined by Folin-Ciocalteu spectrophotometric microassay. Antioxidant activity was investigated using four different tests and results were combined in a unique Antioxidant Composite Index (ACI) to reveal comprehensive information about this biological activity. Polyphenol compounds were identified and quantified with the aim of HPLC-diode array detector (DAD). Overall results support that DES (particularly choline chloride: citric acid) were comparable to conventional solvent, and in most cases even outperformed acidified aqueous ethanol (concerning extraction efficiency and antioxidant activity). Regardless of varietal distinctions, grape seeds have higher antioxidant capacity compared to grape skin, and such findings are according to their phenol compound concentrations.

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Huang, Xiayuan, Xiangli Nie, and Hong Qiao. "PolSAR Image Feature Extraction via Co-Regularized Graph Embedding." Remote Sensing 12, no. 11 (May 28, 2020): 1738. http://dx.doi.org/10.3390/rs12111738.

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Dimensionality reduction (DR) methods based on graph embedding are widely used for feature extraction. For these methods, the weighted graph plays a vital role in the process of DR because it can characterize the data’s structure information. Moreover, the similarity measurement is a crucial factor for constructing a weighted graph. Wishart distance of covariance matrices and Euclidean distance of polarimetric features are two important similarity measurements for polarimetric synthetic aperture radar (PolSAR) image classification. For obtaining a satisfactory PolSAR image classification performance, a co-regularized graph embedding (CRGE) method by combing the two distances is proposed for PolSAR image feature extraction in this paper. Firstly, two weighted graphs are constructed based on the two distances to represent the data’s local structure information. Specifically, the neighbouring samples are sought in a local patch to decrease computation cost and use spatial information. Next the DR model is constructed based on the two weighted graphs and co-regularization. The co-regularization aims to minimize the dissimilarity of low-dimensional features corresponding to two weighted graphs. We employ two types of co-regularization and the corresponding algorithms are proposed. Ultimately, the obtained low-dimensional features are used for PolSAR image classification. Experiments are implemented on three PolSAR datasets and results show that the co-regularized graph embedding can enhance the performance of PolSAR image classification.

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Liu, Jia-Wei, Khaled Murtada, Nathaly Reyes-Garcés, and Janusz Pawliszyn. "Systematic Evaluation of Different Coating Chemistries Used in Thin-Film Microextraction." Molecules 25, no. 15 (July 29, 2020): 3448. http://dx.doi.org/10.3390/molecules25153448.

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A systematic evaluation of eight different coatings made of solid phase extraction (SPE) and carbon-based sorbents immobilized with polyacrylonitrile in the thin-film microextraction (TFME) format using LC-MS/MS was described. The investigated coatings included graphene, graphene oxide, multi-walled carbon nanotubes (MWCNTs), carboxylated MWCNTs, as carbon-based coatings, and polystyrene-divinylbenzene (PS-DVB), octadecyl-silica particles (C18), hydrophilic–hydrophobic balance particles (HLB) and phenyl-boronic acid modified particles (PBA), as SPE-based coatings. A total of 24 compounds of diverse moieties and of a wide range of polarities (log P from −2.99 to 6.98) were selected as probes. The investigated coatings were characterized based on their extraction performance toward the selected probes at different pH values and at optimized desorption conditions. In the case of SPE-based coatings, PS-DVB and HLB exhibited a balanced extraction for compounds within a wide range of polarities, and C18 showed superior extraction recoveries for non-polar analytes. Carbon-based coatings showed high affinity for non-polar compounds given that their main driving force for extraction is hydrophobic interactions. Interestingly, among the studied carbon-based coatings, graphene oxide showed the best extraction capabilities toward polar compounds owing to its oxygen-containing groups. Overall, this work provided important insights about the extraction mechanisms and properties of the investigated coatings, facilitating the coating selection when developing new TFME applications.

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Hotta, Seiji, Kohei Inoue, and Kiichi Urahama. "Extraction of fuzzy clusters from weighted graphs." Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 86, no. 1 (September 17, 2002): 80–88. http://dx.doi.org/10.1002/ecjc.1133.

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LOURENS, TINO, and ROLF P. WÜRTZ. "EXTRACTION AND MATCHING OF SYMBOLIC CONTOUR GRAPHS." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 07 (November 2003): 1279–302. http://dx.doi.org/10.1142/s0218001403002848.

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We describe an object recognition system based on symbolic contour graphs. The image to be analyzed is transformed into a graph with object corners as vertices and connecting contours as edges. Image corners are determined using a robust multiscale corner detector. Edges are constructed by line-following between corners based on evidence from the multiscale Gabor wavelet transform. Model matching is done by finding subgraph isomorphisms in the image graph. The complexity of the algorithm is reduced by labeling vertices and edges, whereby the choice of labels also makes the recognition system invariant under translation, rotation and scaling. We provide experimental evidence and theoretical arguments that the matching complexity is below O(#V3), and show that the system is competitive with other graph-based matching systems.

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Cho, Yong-Jin, Ji-Young Hong, Hyang Sook Chun, Sang Kook Lee, and Hye-Young Min. "Ultrasonication-assisted extraction of resveratrol from grapes." Journal of Food Engineering 77, no. 3 (December 2006): 725–30. http://dx.doi.org/10.1016/j.jfoodeng.2005.06.076.

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El Alami El Hassani, Safae, Anas Driouich, Hamid Mellouk, Bouchra Bejjany, Adil Dani, and Khalid Digua. "Extraction of phenolic from Moroccan grape pomace: Optimization of decoction extraction of phenolic compounds using response surface methodology." Mediterranean Journal of Chemistry 7, no. 6 (December 16, 2018): 423–32. http://dx.doi.org/10.13171/mjc76198121610hm.

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The present study focuses on the optimization of the parameters to extract phenolic products by decoction and the quantification of these compounds from grape pomace, using a central experimental design. The antioxidant activity of methanolic extracts from grape skin grown in Morocco was evaluated. The grapes variety is “Michael Paleiri”, it is a black variety with pips, and they are from the region of Benslimane. The total phenolic compounds contents were determined by the Folin-Ciocalteu method. The optimization suggested that extraction with methanol for 29 min, at 60°C were the best solutions for this combination of variables.The largest amount obtained was 1042.06 mg EGA/g DW. The antioxidant activity is carried out by the radical scavenging method 1,1-diphenyl-2-picryl hydrazyl (DPPH°) and the ferric iron reduction capacity (FRAP). The DDPH inhibition capacity reached 20.78%, compared with 15.22% of a BHT solution at 0.001 g/L. A significant relationship between antioxidant capacity and total phenolic content is evident (R2=0.994). These results demonstrate that methanol extracts from the waste from grapes grown in Morocco could be used as potential sources of natural extracts rich in phenolic compounds and endowed with significant antioxidant activity.

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Madej, Katarzyna, Katarzyna Janiga, and Wojciech Piekoszewski. "The Potential of Graphene as an Adsorbent for Five Pesticides from Different Classes in Rape Oil Samples Using Dispersive Solid-Phase Extraction." Journal of Analytical Methods in Chemistry 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/3587860.

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Isolation conditions for five pesticides (metazachlor, tebuconazole, λ-cyhalothrin, chlorpyrifos, and deltamethrin) from rape oil samples were examined using the dispersive solid-phase graphene extraction technique. To determine the optimal extraction conditions, a number of experimental factors (amount of graphene, amount of salt, type and volume of the desorbing solvent, desorption time with and without sonication energy, and temperature during desorption) were studied. The compounds of interest were separated and detected by an HPLC-UV employing a Kinetex XB-C18 column and a mobile phase consisting of acetonitrile and water flowing in a gradient mode. The optimized extraction conditions were: the amount of graphene 15 mg, desorbing solvent (acetonitrile) 5 mL, time desorption 10 min at 40°C, and amount of NaCl 1 g. The detection limit for metazachlor, tebuconazole, λ-cyhalothrin, and chlorpyrifos was 62.5 ng·g−1, and for deltamethrin, it was 500 ng·g−1. The obtained results lead to the conclusion that graphene may be successfully used for the isolation of the five pesticides from rape oil. However, their determination at low concentration levels, as they occur in real oil samples, requires the employment of appropriately highly sensitive analytical methods, as well as a more suitable graphene form (e.g., magnetically modified graphene).

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Journal articles on the topic 'Extraction de graphes'

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