1,649 research outputs found
Pellegrini (Anthony D.) (Ed.). — The Future of Play Theory. A Multidisciplinary Inquiry into the Contributions of Brian Sutton-Smith.
No full textBrougere Gilles. Pellegrini (Anthony D.) (Ed.). — The Future of Play Theory. A Multidisciplinary Inquiry into the Contributions of Brian Sutton-Smith.. In: Revue française de pédagogie, volume 119, 1997. L'éducation préscolaire. pp. 156-157
2015 heart rhythm society expert consensus statement on the diagnosis and treatment of postural tachycardia syndrome, inappropriate sinus tachycardia, and vasovagal syncope
No full textAbstract not availableRobert S. Sheldon, Blair P. Grubb II, Brian Olshansky, Win-Kuang Shen, Hugh Calkins, Michele Brignole, Satish R. Raj, Andrew D. Krahn, Carlos A. Morillo, Julian M. Stewart, Richard Sutton, Paola Sandroni, Karen J. Friday, Denise Tessariol Hachul, Mitchell I. Cohen, Dennis H. Lau, Kenneth A. Mayuga, Jeffrey P. Moak, Roopinder K. Sandhu, Khalil Kanjwa
Microbiology Topics. ABOUT THE AUTHOR Measurement of Microbial Cells by Optical Density
No full text"Microbiology Topics" discusses various topics in microbiology of practical use in validation and compliance. We intend this column to be a useful resource for daily work applications. Reader comments, questions, and suggestions are needed to help us fulfill our objective for this column. Please send your comments and suggestions to column coordinator Scott Sutton at scott. [email protected] or journal coordinating editor Susan Haigney at [email protected]. KEY POINTS The following key points are discussed: Quality control (QC) microbiology tests require controlled levels of inocula and require fresh preparations of cells for those inocula The concentration of cells in a suspension can be estimated by optical density, but this must be confirmed by plate count The optical density readings against cell mass are specific to the microorganism species The qualification of these readings must be confirmed after major maintenance to the bench top spectrophotometer (e.g., after replacement of the bulb). There are, of course, two problems with these instructions. The first is that the technician is instructed to use an inoculum of about 10 8 microorganisms per milliliter and then instructed to determine this by plate count. Colony forming units (CFU) and cells (micro-organisms and spores) are different measures. This will inevitably lead to difficulties as the unfortunate lab worker cannot guarantee the number of cells in the suspension, only the number of CFU found. However, we can accept the scientific inaccuracy, as the numbers will generally work out. The more serious problem is the instruction to use the plate count CFU for determination of the inoculum for the test, and that the suspension shall be used immediately. This quite frankly cannot be done. If you use the suspension immediately, the plate counts are unavailable; if you use the plate counts to set the inoculum, then the suspension is at least a day old. DETERMINATION OF INOCULUM FOR THE AET Contrast these instructions with those in the United States Pharmacopeia (USP) (2) for the same exercise: Scott Sutton are needed to help us fulfill our objective fo fo for this column. Please send your comments an an and d d su u ugg gg gges es etions to column coordinator Scott Su Su Sutt tt tton n n at sc sc scot ot ott. t. t. [email protected] or journal co co coor o o dina a nating e e editor Susan Haigney at shaigney@ y@ [email protected]. KEY POINTS suspending fluid … Add sufficient suspend fluid to reduce the microbial count to about micro-organisms per milliliter…Remove imm ately a suitable sample from each suspension d d de d termine the number of colony-forming u per milliliter in each suspension by plate coun membrane filtration (2.6.12). This value se KEY POINTS The following key points are discuss sed ed: Quality control (QC) microbiolog gy test sts s re equ quire controlled levels of inocula and nd r re equi ire f fresh sh preparations of cells for those inocula The co o onc ncen en ntr tr trat at atio io ion n n of cells in n a a su uspen nsi sion o can be es s sti i imated b b by y y op op opti ti tical dens nsity, y, b but ut this s mu must s be membrane filtration (2.6.12). This value se to determine the inoculum and the baselin use in the test. The suspensions shall be u immediately." There are, of course, two problems with these t t tion n ns. s. s. T T The he he f f fir ir irst st i is s s th th hat at t t th h he t t tec e echnicia an is is i ins nstr truc u te an an an ino no noculum of a a abo out 10 0 0 8 8 8 m m mic croorg gan nisms s pe per m c co conf f fir rmed by p p plate te te c c cou o o nt t Th h he op p ptical den n nsit t ty r re rea adin ings gs a agai inst st cel e l m mass a are r s s sp s ec ec ec e ifi i ic to th h h he e e e m m mi m croo o o org gan an anis is sm specie ie es Th Th Th he q qu l l alif if ifi i ication of the h h se readings mu t t st be confirmed e e e a a a after m m m maj j j jor o o mai ai aint t ten e e ance ce ce t t to o o the e e be b b nc c ch h h t t top sp sp sp spec ec e ect t tropho ho ho hoto to to tom m meter r (e (e (e.g g g., aft fter er er r repla ace ement nt nt of the bulb) a a and d d th th then n n i i instru u ucte e ed to o o d d deter erm mine e thi his s by by plat C C Colony f f fo o orm m ming un n nits ( ( (CF C CFU) U) a and nd ce ells s ( (mi mic cro-or an an and d d d sp p por r res es es es) ) ) ) are d d dif f ffer er er ere e en e t measu ur u es es es. T This w w wil ill l l in l l lead d d d t t t to o o di di di dif fficulties as t t the unfortun t t ate lab wo k k rke guar r r ran a a a tee th th th he e e e numb mb mb ber of f f f ce ce ce cell ll lls s in t t the he he s s sus u u pens ns nsi i i the e e nu nu nu numb m m m er o o of CFU U U foun n n nd d. d. d H H Ho ow o ev ver er r, , w w we can n n a a ac scientific inaccuracy as the numbers will genera of the bulb) ) ). DE DE DE DETE TE TE TERM RM RM RMIN IN IN INAT AT AT ATIO IO IO ION N N N OF OF OF OF I I INO NO NOCU CU CULU LU LUM M M FO FO FOR R R scientific inaccuracy, y as the numbers will g genera ou ou ou out. t t t Th Th Th The e e e mo mo mo more re re re s s ser er er erio io io ious us us us p p p pro r ro robl bl bl blem em em i i is s s th th the e e in in inst st stru ru ruct ct ctio o th th th the e e e pl pl pl plat at at a e e e e co co co coun un un unt t t t CF CF CF CFU U U U fo fo fo for r r r de de de dete te te t rm rm rmin in inat at atio io ion n n of of of t t the he he i i in
Computing the complete CS decomposition
No full textAn algorithm for computing the complete CS decomposition of a partitioned uni-tary matrix is developed. Although the existence of the CS decomposition (CSD) has been recognized since 1977, prior algorithms compute only a reduced version. This reduced version, which might be called a 2-by-1 CSD, is equivalent to two simultane-ous singular value decompositions. The algorithm presented in this article computes the complete 2-by-2 CSD, which requires the simultaneous diagonalization of all four blocks of a unitary matrix partitioned into a 2-by-2 block structure. The algorithm appears to be the only fully specified algorithm available. The computation occurs in two phases. In the first phase, the unitary matrix is reduced to bidiagonal block form, as described by Sutton and Edelman. In the second phase, the blocks are simultane-ously diagonalized using techniques from bidiagonal SVD algorithms of Golub, Kahan, Reinsch, and Demmel. The algorithm has a number of desirable numerical features.
Limiting Avoidable Microbiological Variability
No full text[ "Microbiology Topics" discusses various topics in microbiology of practical use in validation and compliance. We intend this column to be a useful resource for daily work applications. Reader comments, questions, and suggestions are needed to help us fulfill our objective for this column. Case studies from readers are most welcome. Please send your comments and suggestions to column coordinator Scott Sutton at scott.sutton@microbiol. org or journal coordinating editor Susan Haigney at [email protected]. KEY POINTS The following key points are discussed in this article: • Quality control (QC) microbiology test data are subject to significant variability, both avoidable and unavoidable • Good microbiological procedures, backed by sound microbiological practices, can serve to minimize avoidable variability • The lab's standard operating procedure (SOP) system is a powerful tool to describe and document compliance with good practice • The lab should determine critical areas of coverage for the SOP system to ensure a comprehensive program • The SOP for a lab test should describe critical parameters of the test and meet the criteria of regulatory requirements and guidance for that procedure. The documentation of compliance with these requirements is both a legitimate good manufacturing practice (GMP) audit concern and a useful source of information for investigations. • A sound SOP system can serve to minimize avoidable variability in the microbiology lab • SOPs may be categorized into testing methods, documentation and SOPs, environmental monitoring, and laboratory support activities • Training for the members of the lab should be tightly tied to the SOP system, and can support functional specialization of staff • SOPs for each functional area are described • The content of this discussion should serve to benchmark your system, guide regulatory compliance, and be a framework for training • Considering the SOP system from a functional perspective links job skills to SOPs and facilitates tracking of revisions • Controlling variability and avoidable error is critical to successful microbiology laboratory operation because microbiology is exquisitely sensitive to personnel performance and techniques. INTRODUCTION Microbiology in the QC laboratory is subject to variability in the test results, in the samples taken, in the manner in which they are taken (with severe limitations in sample size contributing to the problem), and Limiting Avoidable Microbiological Variability Scott Sutton ABOUT THE AUTHOR Scott Sutton, Ph.D., is owner and operator of The Microbiology Network (www.microbiol.org), which provides services to microbiology-related user's groups. Dr. Sutton can be reached at scott. [email protected]. g x p a n d j v t . c o
The stochastic operator approach to random matrix theory
No full textThesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2005.Includes bibliographical references (p. 147-150) and index.Classical random matrix models are formed from dense matrices with Gaussian entries. Their eigenvalues have features that have been observed in combinatorics, statistical mechanics, quantum mechanics, and even the zeros of the Riemann zeta function. However, their eigenvectors are Haar-distributed-completely random. Therefore, these classical random matrices are rarely considered as operators. The stochastic operator approach to random matrix theory, introduced here, shows that it is actually quite natural and quite useful to view random matrices as random operators. The first step is to perform a change of basis, replacing the traditional Gaussian random matrix models by carefully chosen distributions on structured, e.g., tridiagonal, matrices. These structured random matrix models were introduced by Dumitriu and Edelman, and of course have the same eigenvalue distributions as the classical models, since they are equivalent up to similarity transformation. This dissertation shows that these structured random matrix models, appropriately rescaled, are finite difference approximations to stochastic differential operators. Specifically, as the size of one of these matrices approaches infinity, it looks more and more like an operator constructed from either the Airy operator, ..., or one of the Bessel operators, ..., plus noise. One of the major advantages to the stochastic operator approach is a new method for working in "general [beta] " random matrix theory. In the stochastic operator approach, there is always a parameter [beta] which is inversely proportional to the variance of the noise.(cont.) In contrast, the traditional Gaussian random matrix models identify the parameter [beta] with the real dimension of the division algebra of elements, limiting much study to the cases [beta] = 1 (real entries), [beta] = 2 (complex entries), and [beta] = 4 (quaternion entries). An application to general [beta] random matrix theory is presented, specifically regarding the universal largest eigenvalue distributions. In the cases [beta] = 1, 2, 4, Tracy and Widom derived exact formulas for these distributions. However, little is known about the general [beta] case. In this dissertation, the stochastic operator approach is used to derive a new asymptotic expansion for the mean, valid near [beta] = [infinity]. The expression is built from the eigendecomposition of the Airy operator, suggesting the intrinsic role of differential operators. This dissertation also introduces a new matrix model for the Jacobi ensemble, solving a problem posed by Dumitriu and Edelman, and enabling the extension of the stochastic operator approach to the Jacobi case.by Brian D. Sutton.Ph.D
FIGURES 77–84 in New species and host plants of Anastrepha (Diptera: Tephritidae) primarily from Suriname and Pará, Brazil
No full textFIGURES 77–84. Eversible membranes, dorsal unless otherwise indicated: 77–78, A. crassaculeus (Colombia: Pamplonita, ICAMF00000437; Suriname: Brownsberg, USNMENT00875105); 79–80, A. curvivenis (Brazil: Rio Urucu, USN- MENT01526558; 80, lateral); 81, A. curvivenis (Peru: Tarapoto, USNMENT00744647); 82–83, A. fuscoalata (Suriname: Berg en Dal, USNMENT01526233; 83, dorsoapical); 84, A. gangadini (Suriname: Brownsberg, USNMENT00875038).Published as part of Norrbom, Allen L., Muller, Alies, Gangadin, Anielkoemar, Sutton, Bruce D., Rodriguez, Erick J., Savaris, Marcoandre, Lampert, Silvana, Rodriguez, Pedro A., Steck, Gary J., Moore, Matthew R., Nolazco, Norma, Troya, Henry, Keil, Clifford B., Padilla, Anabel, Wiegmann, Brian M., Cassel, Brian, Branham, Marc & Ruiz-Arce, Raul, 2021, New species and host plants of Anastrepha (Diptera: Tephritidae) primarily from Suriname and Pará, Brazil, pp. 1-74 in Zootaxa 5044 (1) on page 63, DOI: 10.11646/zootaxa.5044.1.1, http://zenodo.org/record/553202
Preemptive Search and R&D Clustering Revisited
No full textThe results obtained by Cardon and Sasaki (1998) on R&D clustering are derived under the specific assumption that firms only can own one patent. When multiple patents are allowed, R&D clustering will come about more frequently if search costs are substantial.R&D clustering; persistence of monopoly
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Dillon and Boxt, eds.: Archaeology of the Three Springs Valley, California: A Study in Functional Cultural History
No full textArchaeology of the Three Springs Valley, California: A Study in Functional Cultural History. Brian D. Dillon and Matthew A. Boxt, eds. Los Angeles: University of California Institute of Archaeology Monograph 30, 1989, 191 pp., 58 figs., 57 tables, $17.50 (paper)
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