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company called National Public Finance Guarantee Corporation or simply National, which caused the stock to pop 30 percent for a day before it continued its tumble. Figure 12.1 shows MBIA s new structure. MBIA Inc. is the public holding company, so when investors buy MBIA s stock, this is the entity they own a stake in. Its primary asset and source of revenues is MBIA Insurance Corporation (MBIA Corp.), its regulated insurance subsidiary. This is the entity that writes the insurance at least it used to when it had an AAA rating and then it upstreams (dividends) its pro ts to MBIA Inc. To capitalize National, MBIA Inc. took $2.1 billion in cash from MBIA Corp. and transferred it to the new entity. In addition, according to MBIA s Q4 2008 investor presentation, MBIA Corp. reinsured $554 billion net par of domestic public nance business to National and noted that $2.89 billion of net UPR [unearned premium reserves], less ceding commission, and loss reserves transferred to National. In other words, MBIA Inc. took $554 billion of par insured of MBIA Corp. s good business, plus $2.1 billion in cash plus another $2.89 billion in cash re ecting prepaid premiums by muni policyholders, leaving MBIA Corp. with virtually all of the riskiest assets, yet 41 percent fewer claims-paying resources ($8.8 billion vs. $15.0 billion), as shown in Table 12.1.

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Preformed niacin is found in red meat, liver, pulses, eggs, milk and wholegrain wheat our, and is.

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Communication in concurrent or networked programming is often many-to-few, especially in client/server programming. Servers might handle many clients. Each server might need to dynamically activate other servers, spawn new processes, manage pools of resources across multiple service handlers, and maintain integrity of critical sections of code. In addition to synchronized messaging, servers might need to synchronize access to local shared resources. A multithreaded daemon might need to maintain thread-specific storage. A daemon that maintains a process pool and spawns off server instances in response to client requests might need to protect shared memory used by all the process instances. Programmers use several synchronization mechanisms, all based on the paradigm of requesting a lock on a resource, waiting to acquire it, and then releasing the lock after using the resource. Examples of synchronization primitives include mutexes, condition variables, reader/writer locks, and semaphores. These mechanisms have an assumption of good behavior, namely that all processes or threads will use the synchronization mechanism to access a critical resource. Programming errors, complex invocation patterns, or process failure could cause locks to be acquired but not released or for processes to hang in deadlock each waiting on another to relinquish a captured resource.

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// Prevent the menu from covering the button. tpm.cbSize = sizeof (tpm); CopyRect (&tpm.rcExclude, &rect); hMenu = LoadMenu (hInst, TEXT( DROPMENU )); hMenu = GetSubMenu ( hMenu, 0); TrackPopupMenuEx (hMenu, TPM_LEFTALIGN | TPM_VERTICAL, rect.left, rect.bottom, hWnd, &tpm); }

Therefore, at least m + 1 pairs of sample data (xi,yi) must be available in order that all the unknown coef cients can be evaluated. If there are exactly m + 1 data pairs, the a s can be evaluated by substituting the m + 1 (xi,yi) values in turn into Equation 4.4 thereby yielding m + 1 equations with m + 1 unknowns, and thus the a coef cients can be evaluated by solving these equations simultaneously. Conventional methods for solving system of linear equations like the Gaussian elimination, Gauss Seidel method etc. can be used to evaluate the coef cients. A standard function (MINVERSE) is also available within Microsoft Excel that can be used to solve a system of linear equations. If more than m + 1 data pairs are available, the least square error method can be used to nd the unknown coef cients that best t the sample data. Aconvenient way to solve for the model coef cients is to regard the polynomial (with x being the independent variable) as a multiple linear equation with the unknown coef cients treated as the independent variables (while the x terms, including all its higher order terms, will be of known values and are the coef cients of the unknowns). Once again, the standard Microsoft Excel function LINEST can be used for this purpose. Many statistics programs, e.g. SPSS+, include speci c modules for multiple linear regression analysis, which may also be used.

Before concluding this chapter, the modelling methods adopted in an air-conditioning plant simulation program (Yik & Burnett 1998; Yik & Chan 1998) are brie y described to illustrate how component models can be integrated to model the performance of an air-conditioning system The mathematical expressions used in the program to model the performance of equipment like chillers, pumps, cooling towers, heat exchangers, air-handling units, etc are as summarised in Table 44 The program includes a library of models for typical air-conditioning equipment, which is basically a database of the model coef cients, but the user may modify the coef cients to more accurately represent the performance of particular equipment The built-in models were established by regression methods on the basis of manufacturers performance data.

Just like text, images can be aligned to the left, right, or center. In fact, images have much more flexibility than text in terms of alignment. In addition to the same horizontal alignment options, you can align your images vertically in nine different ways. You can even turn a picture into a floating image type, enabling text to wrap around it.

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