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NOTE: Roger Pickett, Vice President of the Express Financial Corp., a mortgage brokerage f irm in Boca Raton, Florida, notes that most lenders insist that if the down payment comes from a gift (say a parent gives his or her child a portion of the down payment), at least 5 percent of the down payment must come from the donee s (person who received the gift s) own funds. Lenders count as the buyer s own funds only amounts that were in the buyer s bank account for at least three months. The reason, according to Pickett, is We want the child to feel that he has an interest in the property, too.

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where Zp1 and ZX are de ned in the crossing section next. Equations (3.4.9) (3.4.14) can be solved to yield, for Vi s and Vr s , p p Vs s e ZY 1 ZTX Y=Z p p p p p Vr s 1 Rs Y=Z 1 ZTX Y=Z e 2 ZY 1 Rs Y=Z 1 ZTX Y=Z 3:4:17 Vi s 1 1 ZTX

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tional novelty and none dynamical recon guration ability because they simply imitate architectures of silicon computing devices Experimental prototypes of reaction diffusion processors exploit interaction of wave fronts in a geometrically constrained chemical medium; that is, the computation is based on a stationary architecture of medium s inhomogeneities Constrained by stationary wires and gates reaction diffusion chemical universal processors pose a little computational novelty and no dynamic recon guration ability because they simply imitate architectures of conventional silicon computing devices To appreciate in full massive parallelism of thin-layer chemical media and to free the chemical processors from limitations of xed computing architectures, we adopt an unconventional paradigm of architectureless, or collision-based, computing An architecture-based, or stationary, computation implies that a logical circuit is embedded into the system in such a manner that all elements of the circuit are represented by the system s stationary states The architecture is static.

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Improved Tracking and Control Capability Reduces Container Inventory by Half Situation: An industry-leading provider of specialty materials and services to the worldwide semiconductor industry ships its product to customers in expensive specialized materials canisters. We could not always identify the specific quantities and types of canisters our customers had at their locations, the logistics director said. Thus, we were always forced to hold excess canister inventory. After a search of potential solutions, we deployed the Gemini Series supply chain execution software (ClearOrbit, Austin, Texas; www.clearorbit.com) to manage the receiving, inventory, and shipping processes at our manufacturing and distribution facilities, he explained. With increased canister visibility and tracking abilities, the company estimates that it can reduce the additions to its canister inventory by 45% or more. We anticipate that ClearOrbit s software will reduce our annual capital equipment costs of new canisters by 25% at one manufacturing facility alone, he continues. At the company s ultra-pure packaging facility, the Gemini Series has

with minor crimes. The individual is being well taught to continue to be dangerous. Policies can be generated with the best of intentions but, nevertheless, they can make things worse, or at least more risky and dangerous, in their negative senses. A rich literature of studies on how laws can have anti-therapeutic effects has been generated by the Therapeutic Jurisprudence movement (see the chapter by Petrucci, Winick and Wexler, in this volume, and references therein). Action is needed at the system level if these are to be tackled.

class tarn coupon leg payoff: def call (self, t, controller): event = controller.get event() flow = event.flow() id = event.reset id() obs = flow.observables()[id] model = controller.get model() env = controller.get environment() adjuvant table = controller.get adjuvant table() # lookup floor , fixed rate , leverage , target , # redemption floor and redemption cap floor = adjuvant table("floor"+str(id), flow.pay date()) fixed rate = adjuvant table("fixed rate"+str(id), flow.pay date()) leverage = adjuvant table("leverage"+str(id), flow.pay date()) target = adjuvant table("target"+str(id), flow.pay date()) redemption floor = adjuvant table("redemption floor"+str(id), flow.pay date()) redemption cap = adjuvant table("redemption cap"+str(id), flow.pay date()) requestor = model.requestor() state = model.state().fill(t, requestor, env) cpn = flow.year fraction()*max (floor \ , fixed rate+leverage*controller.libor(t, state)) # retrieve symbol representing target indicator indicator = controller.retrieve symbol("target indicator") # retrieve symbol representing accrued coupon accrued cpn = controller.retrieve symbol("accrued coupon") accrued cpn += cpn # actual coupon assuming a redemption cap and a redemption floor # potentially different from the target actual cpn = model.state().create variable()

Table 10.2 Histology and cellular subtype of epithelial ovarian neoplasms7 Histologic/cellular type Serous/endosalpingeal Benign Borderline Malignant Mucinous/endocervical Benign Borderline Malignant Endometrioid/endometrial Benign Borderline Malignant Clear cell/Mullerian Benign Borderline Malignant Transitional cell/transitional Benign Borderline Malignant Example

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