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1

Gradient estimation via perturbation analysis. Kluwer Academic Publishers, 1991.

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2

Glasserman, Paul. Gradient estimation via perturbation analysis. Kluwer Academic, 1991.

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3

Fu, Michael. Conditional Monte Carlo: Gradient estimation and optimization applications. Kluwer Academic Publishers, 1997.

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4

Fu, Michael. Conditional Monte Carlo: Gradient Estimation and Optimization Applications. Springer US, 1997.

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5

Skifstad, Kurt D. High-speed range estimation based on intensity gradient analysis. Springer-Verlag, 1991.

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6

Skifstad, Kurt D. High-Speed Range Estimation Based on Intensity Gradient Analysis. Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-3112-7.

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7

Skifstad, Kurt D. High-speed range estimation based on intensity gradient analysis. Springer-Verlag, 1991.

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8

High-speed range estimation based on intensity gradient analysis. Springer-Verlag, 1991.

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9

An introduction to cut-off grade estimation. Society for Mining, Metallurgy, and Exploration, 2008.

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10

Atherton, Gary L. Grading and paving construction: A practical approach to management and estimating. Sandcastles, 1986.

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11

Stevens, James A. Managing the stands of the future based on the lessons of the past: Estimating western timber species product recovery by using historical data. U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2000.

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12

Conditional Monte Carlo: Gradient Estimation and Optimization Applications. Springer, 2011.

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13

Skifstad, Kurt D. High-Speed Range Estimation Based on Intensity Gradient Analysis. Springer, 2011.

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14

High-Speed Range Estimation Based on Intensity Gradient Analysis. Springer, 2012.

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15

Cuddapah, Prabhakara, and Goddard Space Flight Center, eds. Global warming estimation from microwave sounding unit. National Aeronautics and Space Administration, Goddard Space Flight Center, 1998.

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16

Rendu, Jean-Michel. An Introduction to Cut-Off Grade Estimation, Second Edition. Society for Mining, Metallurgy, and Exploration, 2014.

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17

A, Metz R., and Society of Mining Engineers of AIME. Meeting, eds. Problems of sampling and grade control. Society of Mining Engineers of the American Institute of Mining, Metallurgical, and Petroleum Engineers, 1985.

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18

Kallmeyer, Andrea, José Luis Zamorano, G. Locorotondo, Madalina Garbi, José Juan Gómez de Diego, and Miguel Ángel García Fernández. Non-invasive haemodynamic assessment. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780199599639.003.0005.

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The diagnostic power of two-dimensional (2D) echocardiography resides not only in its capability of providing anatomical information and of studying myocardial contractile function, but also in the possibility of performing a non-invasive haemodynamic assessment. Such non-invasive haemodynamic assessment is the subject of this chapter.2D echocardiography, colour flow imaging, and Doppler modality make this haemodynamic assessment possible, by studying the following parameters: ◆ Blood flow velocities. ◆ Transvalvular pressure gradients. ◆ Valvular areas. ◆ Stroke volume, regurgitant volume, an
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19

Joynt, Gavin M., and Gordon Y. S. Choi. Blood gas analysis in the critically ill. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0072.

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Arterial blood gases allow the assessment of patient oxygenation, ventilation, and acid-base status. Blood gas machines directly measure pH, and the partial pressures of carbon dioxide (PaCO2) and oxygen (PaO2) dissolved in arterial blood. Oxygenation is assessed by measuring PaO2 and arterial blood oxygen saturation (SaO2) in the context of the inspired oxygen and haemoglobin concentration, and the oxyhaemoglobin dissociation curve. Causes of arterial hypoxaemia may often be elucidated by determining the alveolar–arterial oxygen gradient. Ventilation is assessed by measuring the PaCO2 in the
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