The Experts below are selected from a list of 13305 Experts worldwide ranked by ideXlab platform
Yves Bertheau - One of the best experts on this subject based on the ideXlab platform.
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Minimum cost acceptance sampling plans for grain control, with application to GMO Detection
Chemometrics and Intelligent Laboratory Systems, 2005Co-Authors: André Kobilinsky, Yves BertheauAbstract:Quality control by attribute [A. Hald, Statistical Theory of Sampling Inspection by Attributes, Academic Press, New York, 1981; E.G. Schilling, Acceptance sampling in quality control. In: Statistics: Textbooks and Monographs, Vol. 42, Dekker, 1982; J.J. Daudin, C.S. Tapiero. Les outils et le contrôle de la qualité. Economica (1996).] may be used with grain lots to control their purity. But usually the control cannot be made on each grain separately. The presence of an impurity is rather assayed in groups of grains the size of which is an important parameter which can be used to find a cost optimal acceptance sampling plan among those which give acceptable consumer's and producer's risks. This group control has been studied for virus or Bacterium Detection in grains by the Elisa method [Y. Maury, C. Duby, J.M. Bossenec, G. Boudazin, Group analysis using ELISA: determination of the level of transmission of Soybean Mosaic Virus in soybean seed, Agronomie 5, 1985, 405–415; Y. Maury, C. Duby, R.K. Khetarpal, Seed certification for viruses. In: Plant Virus, Disease Control, A. Hadidi, R.K. Khetarpal, H. Koganezawa, eds., APS Press, Chap. 18, 1998, 237–248.] and is advocated by Remund et al. [K. Remund, D. Dixon, D. Wright, L. Holden, Statistical considerations in seed purity testing for transgenic traits, Seed Sci. Res. 11, 2001, 101–119.] for genetically modified organism (GMO) Detection. But no optimization method to select the cheapest acceptance single- or double-sampling plan has yet been described.Given a control cost function depending on the number of groups to analyse and on the total number of grains, we describe in this paper a practical way to get the least expensive acceptance sampling plan keeping both the consumer's and the producer's risks below a predetermined threshold. The method is more specially illustrated by examples in GMO Detection
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Minimum cost acceptance sampling plans for grain control, with application to GMO Detection
Chemometrics and Intelligent Laboratory Systems, 2005Co-Authors: André Kobilinsky, Yves BertheauAbstract:Quality control by attribute [A. Hald, Statistical Theory of Sampling Inspection by Attributes, Academic Press, New York, 1981; E.G. Schilling, Acceptance sampling in quality control. In: Statistics: Textbooks and Monographs, Vol. 42, Dekker, 1982; J.J. Daudin, C.S. Tapiero. Les outils et le contrôle de la qualité. Economica (1996).] may be used with grain lots to control their purity. But usually the control cannot be made on each grain separately. The presence of an impurity is rather assayed in groups of grains the size of which is an important parameter which can be used to find a cost optimal acceptance sampling plan among those which give acceptable consumer's and producer's risks. This group control has been studied for virus or Bacterium Detection in grains by the Elisa method [Y. Maury, C. Duby, J.M. Bossenec, G. Boudazin, Group analysis using ELISA: determination of the level of transmission of Soybean Mosaic Virus in soybean seed, Agronomie 5, 1985, 405–415; Y. Maury, C. Duby, R.K. Khetarpal, Seed certification for viruses. In: Plant Virus, Disease Control, A. Hadidi, R.K. Khetarpal, H. Koganezawa, eds., APS Press, Chap. 18, 1998, 237–248.] and is advocated by Remund et al. [K. Remund, D. Dixon, D. Wright, L. Holden, Statistical considerations in seed purity testing for transgenic traits, Seed Sci. Res. 11, 2001, 101–119.] for genetically modified organism (GMO) Detection. But no optimization method to select the cheapest acceptance single- or double-sampling plan has yet been described.Given a control cost function depending on the number of groups to analyse and on the total number of grains, we describe in this paper a practical way to get the least expensive acceptance sampling plan keeping both the consumer's and the producer's risks below a predetermined threshold. The method is more specially illustrated by examples in GMO Detection
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MINIMISATION OF THE COST OF GMO Detection IN KERNELS USING CONTROL BY ATTRIBUTES
2002Co-Authors: André Kobilinsky, Yves BertheauAbstract:Quality control by attribute (2], (7] may be used with grain lots in order to detect GMO. But usually the control cannot be made on each grain separately. The presence of GMO is rather tested in groups of grains the size of which is an important parameter which can be used to find a cost optimal testing scheme among those which give acceptable buyer and seller risks. This group control has been studied for virus or Bacterium Detection in grains by the Elisa method (4],[3Jand is advocated by (6] for GMO Detection. But no optimisation method to select the cheapest testing scheme has yet been described. Given a cost function depending on the number of groups to analyse and of the total number of grains, we describe in this paper a practical way to get the less expensive testing scheme keeping both the consumer and the producer risks below a predetermined threshold.
André Kobilinsky - One of the best experts on this subject based on the ideXlab platform.
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Minimum cost acceptance sampling plans for grain control, with application to GMO Detection
Chemometrics and Intelligent Laboratory Systems, 2005Co-Authors: André Kobilinsky, Yves BertheauAbstract:Quality control by attribute [A. Hald, Statistical Theory of Sampling Inspection by Attributes, Academic Press, New York, 1981; E.G. Schilling, Acceptance sampling in quality control. In: Statistics: Textbooks and Monographs, Vol. 42, Dekker, 1982; J.J. Daudin, C.S. Tapiero. Les outils et le contrôle de la qualité. Economica (1996).] may be used with grain lots to control their purity. But usually the control cannot be made on each grain separately. The presence of an impurity is rather assayed in groups of grains the size of which is an important parameter which can be used to find a cost optimal acceptance sampling plan among those which give acceptable consumer's and producer's risks. This group control has been studied for virus or Bacterium Detection in grains by the Elisa method [Y. Maury, C. Duby, J.M. Bossenec, G. Boudazin, Group analysis using ELISA: determination of the level of transmission of Soybean Mosaic Virus in soybean seed, Agronomie 5, 1985, 405–415; Y. Maury, C. Duby, R.K. Khetarpal, Seed certification for viruses. In: Plant Virus, Disease Control, A. Hadidi, R.K. Khetarpal, H. Koganezawa, eds., APS Press, Chap. 18, 1998, 237–248.] and is advocated by Remund et al. [K. Remund, D. Dixon, D. Wright, L. Holden, Statistical considerations in seed purity testing for transgenic traits, Seed Sci. Res. 11, 2001, 101–119.] for genetically modified organism (GMO) Detection. But no optimization method to select the cheapest acceptance single- or double-sampling plan has yet been described.Given a control cost function depending on the number of groups to analyse and on the total number of grains, we describe in this paper a practical way to get the least expensive acceptance sampling plan keeping both the consumer's and the producer's risks below a predetermined threshold. The method is more specially illustrated by examples in GMO Detection
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Minimum cost acceptance sampling plans for grain control, with application to GMO Detection
Chemometrics and Intelligent Laboratory Systems, 2005Co-Authors: André Kobilinsky, Yves BertheauAbstract:Quality control by attribute [A. Hald, Statistical Theory of Sampling Inspection by Attributes, Academic Press, New York, 1981; E.G. Schilling, Acceptance sampling in quality control. In: Statistics: Textbooks and Monographs, Vol. 42, Dekker, 1982; J.J. Daudin, C.S. Tapiero. Les outils et le contrôle de la qualité. Economica (1996).] may be used with grain lots to control their purity. But usually the control cannot be made on each grain separately. The presence of an impurity is rather assayed in groups of grains the size of which is an important parameter which can be used to find a cost optimal acceptance sampling plan among those which give acceptable consumer's and producer's risks. This group control has been studied for virus or Bacterium Detection in grains by the Elisa method [Y. Maury, C. Duby, J.M. Bossenec, G. Boudazin, Group analysis using ELISA: determination of the level of transmission of Soybean Mosaic Virus in soybean seed, Agronomie 5, 1985, 405–415; Y. Maury, C. Duby, R.K. Khetarpal, Seed certification for viruses. In: Plant Virus, Disease Control, A. Hadidi, R.K. Khetarpal, H. Koganezawa, eds., APS Press, Chap. 18, 1998, 237–248.] and is advocated by Remund et al. [K. Remund, D. Dixon, D. Wright, L. Holden, Statistical considerations in seed purity testing for transgenic traits, Seed Sci. Res. 11, 2001, 101–119.] for genetically modified organism (GMO) Detection. But no optimization method to select the cheapest acceptance single- or double-sampling plan has yet been described.Given a control cost function depending on the number of groups to analyse and on the total number of grains, we describe in this paper a practical way to get the least expensive acceptance sampling plan keeping both the consumer's and the producer's risks below a predetermined threshold. The method is more specially illustrated by examples in GMO Detection
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MINIMISATION OF THE COST OF GMO Detection IN KERNELS USING CONTROL BY ATTRIBUTES
2002Co-Authors: André Kobilinsky, Yves BertheauAbstract:Quality control by attribute (2], (7] may be used with grain lots in order to detect GMO. But usually the control cannot be made on each grain separately. The presence of GMO is rather tested in groups of grains the size of which is an important parameter which can be used to find a cost optimal testing scheme among those which give acceptable buyer and seller risks. This group control has been studied for virus or Bacterium Detection in grains by the Elisa method (4],[3Jand is advocated by (6] for GMO Detection. But no optimisation method to select the cheapest testing scheme has yet been described. Given a cost function depending on the number of groups to analyse and of the total number of grains, we describe in this paper a practical way to get the less expensive testing scheme keeping both the consumer and the producer risks below a predetermined threshold.
Takahiro Arakawa - One of the best experts on this subject based on the ideXlab platform.
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Cavitas Sensors: Contact Lens Type Sensors & Mouthguard Sensors
Electroanalysis, 2016Co-Authors: Kohji Mitsubayashi, Takahiro ArakawaAbstract:Cavitas sensors attached to body cavities such as the contact lens and\nmouthguard (no implantable, no wearable) are attracted attention as\nself-detachable devices for daily medicine. Many types of contact lens\n(CL) sensors using electrical and optical methods have been developed\nfor monitoring not only chemicals (glucose, lactate) and electrical\nconductivity in tear fluid, but also transcutaneous gases at eyelid\nmucosa. A CL intraocular pressure telemetric sensor has been also\ncommercialized and applied to patients for monitoring the intraocular\npressure. Some mouthguard sensors have been investigated for a real-time\nmeasurement of salivary chemicals. A graphene based sensor on tooth\nenamel was reported to be capable of salivary Bacterium Detection. Here\nwe review the challenges regarding the integration of biosensors into\nmonitoring for biological information of body cavities. The\nself-detachable cavitas sensors are expected to improve the quality of\nlife in the near future.
Kohji Mitsubayashi - One of the best experts on this subject based on the ideXlab platform.
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Cavitas Sensors: Contact Lens Type Sensors & Mouthguard Sensors
Electroanalysis, 2016Co-Authors: Kohji Mitsubayashi, Takahiro ArakawaAbstract:Cavitas sensors attached to body cavities such as the contact lens and\nmouthguard (no implantable, no wearable) are attracted attention as\nself-detachable devices for daily medicine. Many types of contact lens\n(CL) sensors using electrical and optical methods have been developed\nfor monitoring not only chemicals (glucose, lactate) and electrical\nconductivity in tear fluid, but also transcutaneous gases at eyelid\nmucosa. A CL intraocular pressure telemetric sensor has been also\ncommercialized and applied to patients for monitoring the intraocular\npressure. Some mouthguard sensors have been investigated for a real-time\nmeasurement of salivary chemicals. A graphene based sensor on tooth\nenamel was reported to be capable of salivary Bacterium Detection. Here\nwe review the challenges regarding the integration of biosensors into\nmonitoring for biological information of body cavities. The\nself-detachable cavitas sensors are expected to improve the quality of\nlife in the near future.
Kemin Wang - One of the best experts on this subject based on the ideXlab platform.
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bionanotechnology based on silica nanoparticles
Medicinal Research Reviews, 2004Co-Authors: Xiaoxiao He, Xiaojun Julia Zhao, Timothy J Drake, Kemin Wang, Rahul P BagweAbstract:We have developed uniform core/shell nanoparticles, consisting of a silica layer coating and pigments or magnetite core, using a water-in-oil microemulsion method. The nanoparticles are highly luminescent and photostable with the size ranging from 5 nm to 400 nm. Bioconjugation of these silica nanoparticles adds unique biofunctions with various molecules such as enzymes, antibodies, and DNA molecules. Significant advantages have been shown in using bioconjugated nanoparticles for biosensing and bioimaging, such as cell staining, DNA Detection and separation, rapid single Bacterium Detection, and biotechnological application in DNA protection. © 2004 Wiley Periodicals, Inc. Med Res Rev, 24, No. 5, 621–638, 2004
