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The risk for major depression and anxiety disorders is higher for migraineurs than for nonmigraineous controls 2 This in uence is bi-directional Migraine increases the risk of a subsequent episode of major depression (adjusted relative risk 48), and major depression increases the risk of subsequent migraine (adjusted relative risk 33) 3 Comorbid anxiety and depression lead to increases in disability and contribute to headaches becoming intractable 4 Psychological distress is greater in headaches that are more frequent and chronic 5 Depression is implicated in the transformation of episodic to chronic tension-type headache 6 Certain personality disorders reveal a higher incidence of headache than otherwise would be expected Further evidence for the importance of considering psychological factors is obtained from research that has attempted to identify variables associated with outcome.

For example, studies have consistently shown that patients displaying only minor elevations on a scale commonly used to assess depression (Beck Depression Inventory) have a diminished response to self-regulatory treatments (Blanchard et al, 1985; Jacob, Turner, Szekely, & Eidelman, 1983) and even abortive medication (Holroyd et al, 1988) Other variables (anxiety, scales 1, 2, and 3 of the MMPI) have been suggested as predictive of response to behavioral treatments as well (Blanchard et al, 1985; Werder, Sargent, & Coyne, 1981) Holroyd et al (1988) found that patients who were high in trait anger, and to a lesser extent, depressive symptoms, were less likely to respond to abortive pharmacological agents for migraine headache but these variables were uncorrelated.

This section aims at providing the reader with a summary of gures and tables. Care must be taken when looking at these gures: they are only summaries of whole systems that are quite complex. Please do not consider that de nitive conclusions can be drawn from these tables. Further analyses are required, depending on one s goals.

One direct measure of the depth of a fraud-screening service is the number of descriptors it can relate back to help you understand why it scored the way it did. These are codes that tell you more about why it scored the way it did (i.e., can t verify address, geolocation inconsistency with country, high velocity of use, currently on a negative list).

Food Inventory (Asset) Debit Credit Balance $ 8,000 4,200 $ 12,200 3,200 $ 8,000 12,200 -03,200

If any of these assertions for a given employee is violated, then the employee is not a valid employee. Semantic integrity rules must be de ned before they can be enforced. Enforcing these assertions is the responsibility of the semantic integrity control module of the local DBE (see 1). These topics are discussed here under the topic of semantic integrity control or simply integrity control. In addition to de nition and enforcement of semantic integrity rules, the access to the database must be controlled. Only authenticated users with the proper authorization can be allowed to access the contents of the database. A DBA creates a list of valid

This is thus the then-part (or consequent) of the jth fuzzy rule of the fuzzy model. The output of each neuron is fj w2j cj . Layer 5 is the output layer. Each neuron in this layer represents an output variable as the summation of incoming signals from layer 4. The output of a neuron in layer 5 is y x

.Add(Type:=msoControlPopup, Before:=HelpMenu.Index, _ temporary:=True) End If Add a caption for the menu NewMenu.Caption = &Budgeting FIRST MENU ITEM Set MenuItem = NewMenu.Controls.Add _ (Type:=msoControlButton) With MenuItem .Caption = &Data Entry... .FaceId = 162 .OnAction = Macro1 End With SECOND MENU ITEM Set MenuItem = NewMenu.Controls.Add _ (Type:=msoControlButton) With MenuItem .Caption = &Generate Reports... .FaceId = 590 .OnAction = Macro2 End With THIRD MENU ITEM Set MenuItem = NewMenu.Controls.Add _ (Type:=msoControlPopup) With MenuItem .Caption = View &Charts .BeginGroup = True End With FIRST SUBMENU ITEM Set SubMenuItem = MenuItem.Controls.Add _ (Type:=msoControlButton) With SubMenuItem .Caption = Monthly &Variance .FaceId = 420 .OnAction = Macro3 End With

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5 L Girod, V Bychkovskiy, J Elson, and D Estrin Locating tiny sensors in time and space: A case study In Proceedings of the International Conference on Computer Design (ICCD 2002), Freiburg, Germany, September 2002 6 D L Mills Internet time synchronization: The network time protocol IEEE Transactions on Communications, 39(10):1482 1493, October 1991 7 J Elson and K Romer Wireless sensor networks: A new regime for time synchronization In Proceedings of the 1st Workshop on Hot Topics in Networks (HotNets-I), Princeton, New Jersey, October 2002 8 P Juang, H Oki, Y Wang, M Martonosi, L S Peh, and D Rubenstein Energy-ef cient computing for wildlife tracking: Design tradeoffs and early experiences with ZebraNet In Proceedings of the 10th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-X), pages 96 107, San Jose, California, October 2002 9 J Elson, L Girod, and D Estrin.