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In previous sections, we have used the banded matrix iterative approach and the conjugate gradient approach for treating matrix equations. The method was also enhanced by using canonical grid together with FFT (BMIA/CAG). In this section, a different iterative approach known as method of ordered multiple interactions (MOMI) is discussed. The method was first proposed in connection with using the parabolic equation method for rough surface scattering [Spivak, 1990; Holliday et al. 1996]. and was later extended to treat higher order scattering in random rough surface [Kapp and Brown, 1996]. 4.1 Matrix Equations Based on MFIE for TE and TM Waves for

larly relevant. Taking this perspective, this chapter explores the outlook of biotech, from the Darwinian evolution of underlying science to the practical application of the technology in the modern knowledge-based economy.

The method used MFIE for both TE and TM waves for perfect electric conductor. As discussed in 4, using MFIE for TM waves has been standard treatment. For TE waves, usually, EFIE is utilized. In 4, Section 3.2, we also derived the MFIE for TE case. We use pulse basis

-1 -2

Private _settings As MyMySettings Private ReadOnly Property Settings() As _ SystemConfigurationApplicationSettingsBase Get If _settings Is Nothing Then _settings = New MyMySettings End If Return _settings End Get End Property

x 10.3

1-.1

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functions and point matching. (A) For TE case, the integral equation is given by Eq. (4.3.32) with 'ljJ representing the electric field. In matrix form,

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creates an instance of your custom setting It then returns the custom setting for use within the base form class See 5 for more information on Property statements The next step is to create a method in your base form class to apply the settings from your custom MySettings object This method is called when the form is loaded to apply the settings to your form, basically resetting the form size and location to the saved settings

L Z~mvn = b'm,

(5.4.1)

Scienti c advances in molecular biology, computing, and new materials most commonly take the form of basic research conducted in academic, government, and industrial laboratories. Furthermore, these advances de ne what can be expected on the biotech technology and economic hori zons for years and decades in the future. For example, a drug discovered in a shaman s backpack by a researcher in the Amazon rain forest might eventually result in a potent cure for cancer or other disease only after years or even decades of clinical trials. Although the development time line for new drugs is well known by the pharmaceutical industry and the investment community, the time line for the development of new classes of drugs and other new products in the biotech arena is less well under stood. Nevertheless, the maturation of biotech products advances from Inception to Completion, as described by the Continuum Model dis cussed in 3. Of particular relevance to developments in biotech are the rate and method by which products move from Inception the conceptual stage to a demonstrable technology. This depends on the relative maturity of the scienti c basis for the evolving technology. Scienti c maturity is in turn a function of the availability, cost, and maturity of enabling processes and technologies. The enabling technologies relevant to the technological goals in the primary and secondary biotech industries range from gene chips, nanotechnology, and biological databases to increasingly powerful com puter hardware and software (see Figure 8.1).

where (5.4.2) (5.4.3)

-# n)

(5.4.4a)

''' <summary> ''' Apply the settings for every form ''' </summary> ''' <remarks></remarks> Private Sub ApplySettings() SettingsSettingsKey = MeName Dim theSettings As MyMySettings theSettings = DirectCast(Settings, MyMySettings) If theSettingsFormSize <> DrawingSizeEmpty Then MeSize = theSettingsFormSize End If If theSettingsFormLocation <> DrawingPointEmpty Then MeLocation = theSettingsFormLocation End If End Sub

(5.4.4b)

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