Author: claimsbot

1. A container comprising:
a container body defining a first body end, a second body end, an internal surface and an external su face;
a removable tray within the container body;
a membrane enclosing the first body end and the removable tray; and
at least two fingers extending upwardly from a bottom portion of the removable tray and that do not extend beyond the membrane.
2. The container of claim 1, wherein the container further comprises an overcap that encloses the membrane.
3. The container of claim 1, wherein the container body first body end further comprises a first end lip that extends a portion of a perimeter of the first body end.
4. The container of claim 1, wherein the removable tray comprises the same shape as the container body.
5. The container of claim 1, wherein the removable tray is a different shape as the container body.
6. The container of claim 1, wherein the membrane further comprises a pull tab.
7. The container of claim 1, wherein the at least two upwardly extending fingers are of the same shape.
8. The container of claim 1, wherein the container further comprises a housing that is securely fit between the at least two upwardly extending finger.
9. A container comprising:
a container body defining a first body end, a second body end, an internal surface and an external surface;
a removable tray within the container body;
a membrane enclosing the first body end and the removable tray; and
a ridge located on at least a portion of an external surface of the removable tray that mates with corresponding structure of internal surface of the container and that is located below the membrane.
10. The container of claim 9, wherein the container further comprises an overcap that encloses the membrane.
11. The container of claim 9, wherein the container body first body end further comprises a first end lip that extends a portion of a perimeter of the first body end.
12. The container of claim 9, wherein the removable tray comprises the same shape as the container body.
13. The container of claim 9, wherein the removable tray is a different shape as the container body.
14. The container of claim 9, wherein the membrane further comprises a pull tab.
15. The container of claim 9, wherein the internal surface of the container body further comprises a mating groove that mates with the ridge of the removable tray.
16. The container of claim 9, wherein the ridge of the removable tray is shaped a half-circle.
17. A container comprising:
a container body defining a first body end, a second body end, an internal surface and an external surface;
a removable tray within the container body;
a membrane enclosing the first body end and the removable tray;
at least two fingers extending upwardly from a bottom portion of the removable tray and that do not extend beyond the membrane; and
a ridge located on at least a portion of an external surface of the removable tray that mates with corresponding structure of internal surface of the container and that is located below the membrane.
18. The container of claim 17, wherein the container further comprises an overcap that encloses the membrane.
19. The container of claim 17, wherein the container further comprises a second removable tray within the container body and positioned underneath the removable tray.
20. The container of claim 19, wherein the container further comprises a third removable tray within the container body and positioned underneath the second removable tray.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A method, in a data processing system, for performing a remote direct memory access operation, the method comprising:
storing a virtual address to physical address translation of a pinned memory buffer and an access protection key in a translation protection table in a network interface controller;
responsive to receiving in the network interface controller a hash value of data to be copied from a source address in a source node to a destination address in a destination node in the remote direct memory access operation, performing, by the network interface controller, a lookup operation in the translation protection table in the network interface controller to match the hash value to a hash value for data existing in memory of the destination node; and
responsive to the network interface controller finding a match in the translation protection table at the virtual address of the pinned memory buffer, completing the remote direct memory access operation without transferring the data between the source node and the destination node, updating, by the network interface controller, the translation protection table to write the access protection key, the hash value, and a validinvalid bit in association with the destination address.
2. (canceled)
3. The method of claim 1, further comprising:
responsive to the network interface controller finding a match at a given memory location that is different from the destination address, performing a local copy operation to copy the data from the given memory location to the destination memory locations.
4. The method of claim 1, wherein the remote direct memory access operation is a remote direct memory access write operation, the method further comprising:
responsive to the network interface controller finding a match in the translation protection table, sending, by the network interface controller, an acknowledgement message to the source node.
5. The method of claim 4, the method further comprising:
responsive to the network interface controller not finding a match, sending, by the network interface controller, a negative acknowledgement message.
6. The method of claim 5, wherein responsive to receiving the negative acknowledgement message, the source node performs a traditional remote direct memory access write operation.
7. The method of claim 4, wherein source node computes a hash value of data to be copied from the source address at the source node to the destination address at the destination node and wherein the source node sends the computed hash value to the network interface controller.
8. The method of claim 1, wherein the remote direct memory access operation is a remote direct memory access read operation, the method further comprising:
sending, by the network interface controller, the source address to the source node in association with the remote direct memory access read operation; and
receiving, by the network interface controller, the hash value from the source node, wherein source node computes a hash value of data to be copied from the source address at the source node to the destination address at the destination node and wherein the source node sends the computed hash value to the network interface controller in response to receiving the source address from the destination node.
9. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a network interface controller, causes the network interface controller to;
store a virtual address to physical address translation of a pinned memory buffer and an access protection key in a translation protection table in a network interface controller;
responsive to receiving in the network interface controller a hash value of data to be copied from a source address in a source node to a destination address in a destination node in the remote direct memory access operation, perform, a lookup operation in the translation protection table in the network interface controller to match the hash value to a hash value for data existing in memory of the destination node; and
responsive to the network interface controller finding a match in the translation protection table at the virtual address of the pinned memory buffer, complete the remote direct memory access operation without transferring the data between the source node and the destination node, updating by, the network interface controller, the translation protection table to write the access protection key, the hash value, and a validinvalid bit in association with the destination address.
10. (canceled)
11. The computer program product of claim 9, wherein the computer readable program further causes the network interface controller to:
responsive to the network interface controller finding a match at a given memory location that is different from the destination address, perform a local copy operation to copy the data from the given memory location to the destination memory location.
12. The computer program product of claim 9, wherein the remote direct memory access operation is a remote direct memory access write operation, wherein the computer readable program further causes the network interface controller to:
responsive to the network interface controller finding a match in the translation protection table, send an acknowledgement message to the source node.
13. The computer program product of claim 12, wherein the computer readable program further causes the network interface controller to:
responsive to the network interface controller not finding a match, send a negative acknowledgement message.
14. The computer program product of claim 9, wherein the remote direct memory access operation is a remote direct memory access read operation, wherein the computer readable program further causes the network interface controller to:
send, by the network interface controller, the source address to the source node in association with the remote direct memory access read operation; and
receive the hash value from the source node, wherein source node computes a hash value of data to be copied from the source address at the source node to the destination address at the destination node and wherein the source node sends the computed hash value to the network interface controller in response to receiving the source address from the destination node.
15. (canceled)
16. (canceled)
17. An apparatus, comprising:
a network interface controller comprising a translation protection table; and
a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed by the network interface controller, causes the network interface controller to:
store a virtual address to physical address translation of a pinned memory buffer and an access protection key in a translation protection table in a network interface controller;
responsive to receiving in the network interface controller a hash value of data to be copied from a source address in a source node to a destination address in a destination node in the remote direct memory access operation, perform a lookup operation in the translation protection table in the network interface controller to match the hash value to a hash value for data existing in memory of the destination node; and
responsive to the network interface controller finding a match in the translation protection table at the virtual address of the pinned memory buffer, complete the remote direct memory access operation without transferring the data between the source node and the destination node, updating, by the network interface controller, the translation protection table to write the access protection key, the hash value, and a validinvalid bit in association with the destination address.
18. (canceled)
19. The apparatus of claim 17, wherein the computer readable program further causes the network interface controller to:
responsive to the network interface controller finding a match at a given memory location that is different from the destination address, perform a local copy operation to copy the data from the given memory location to the destination memory location.
20. The apparatus of claim 17, wherein the remote direct memory access operation is a remote direct memory access write operation, wherein the computer readable program further causes the network interface controller to:
responsive to the network interface controller finding a match in the translation protection table, send an acknowledgement message to the source node.
21. The apparatus of claim 20, wherein the computer readable program further causes the network interface controller to:
responsive to the network interface controller not finding a match, send a negative acknowledgement message.
22. The apparatus of claim 17, wherein the remote direct memory access operation is a remote direct memory access read operation, wherein the computer readable program further causes the network interface controller to:
send, by the network interface controller, the source address to the source node in association with the remote direct memory access read operation; and
receive the hash value from the source node, wherein source node computes a hash value of data to be copied from the source address at the source node to the destination address at the destination node and wherein the source node sends the computed hash value to the network interface controller in response to receiving the source address from the destination node.
23. The computer program product of claim 13, wherein responsive to receiving the negative acknowledgement message, the source node performs a traditional remote direct memory access write operation.
24. The computer program product of claim 12, wherein source node computes a hash value of data to be copied from the source address at the source node to the destination address at the destination node and wherein the source node sends the computed hash value to the network interface controller.
25. The apparatus of claim 20, wherein source node computes a hash value of data to be copied from the source address at the source node to the destination address at the destination node and wherein the source node sends the computed hash value to the network interface controller.

1. A data processing system for valuing contributions by one or more tangible or intangible elements of value to a value of a business enterprise, comprising:
(a) processing means for processing data;
(b) storage means for storing data;
(c) first means for obtaining data related to the value of the business enterprise, the business enterprise having one or more tangible or intangible elements of value contributing to the value of the business enterprise, and the value of the business enterprise including a revenue component, an expense component and a capital component;
(d) second means for calculating, for each one of the tangible or intangible elements of value, a composite variable characterizing performance of the tangible or intangible element of value of the business enterprise, second means including means for combining transaction data, transaction ratios and transaction trends to calculate the composite variable;
(e) third means for calculating the revenue, expense and capital components of the value of the business enterprise;
(f) fourth means for determining, for each one of the tangible or intangible elements of value, a percentage of the revenue component contributed by the tangible or intangible element of value, a percentage of expense component contributed by the tangible or intangible element of value and a percentage of the capital component contributed by the tangible or intangible element of value;
(g) fifth means for calculating a value for each of the tangible or intangible elements of value of the business enterprise based on the revenue, expense and capital components of alue of the business enterprise and the percentages of the revenue, expense and capital contributed by the tangible or intangible elements of value; and
(h) sixth means for displaying the values.
2. A data processing system as claimed in claim 1, wherein said second means further comprises:
(a) means for calculating for a range of time including a specified valuation date for each one of the tangible or intangible elements of value, the revenue, expense and capital components of the value of the business enterprise and the percentages of the revenue, expense and capital components contributed by each one of the tangible or intangible elements of value;
3. A data processing system as claimed in claim 1, further comprising:
(h) optionally sub-dividing the revenue, expense and capital components of the value of the business enterprise into sub-components to yield a more detailed analysis.
4. A data processing system as claimed in claim 1, wherein said fourth means further comprises:
(a) means for using output from a predictive model to determine the percentage of the revenue component contributed by the tangible or intangible element of value, the percentage of the expense component contributed by the tangible or intangible element of value, and the percentage of the capital component contributed by the tangible or intangible element of value.
5. A data processing system as claimed in claim 1, wherein said fourth means further comprises:
(b) means for using output from a neural network to determine the percentage of the revenue component contributed by the tangible or intangible element of value, the percentage of the expense component contributed by the tangible or intangible element of value, and the percentage of the capital component contributed by the tangible or intangible element of value.
6. A data processing system as claimed in claim 1, wherein said fourth means further comprises:
(c) means for using output from a regression network to determine the percentage of the revenue component contributed by the tangible or intangible element of value, the percentage of the expense component contributed by the tangible or intangible element of value, and the percentage of the capital component contributed by the tangible or intangible element of value.
7. A data processing system as claimed in claim 1 further comprising:
(i) means for using the composite variables to evaluate the impact of the tangible or intangible elements of value on the value of the business enterprise.
8. A data processing system for evaluating changes in contribution by one or more tangible or intangible elements of value to a value of a business enterprise, comprising:
(a) processing means for processing data;
(b) storage means for storing data;
(c) first means for obtaining data related to the value of the business enterprise, the business enterprise having one or more tangible or intangible elements of value contributing to the value of the business enterprise,
(d) second means for calculating, for each one of the tangible or intangible elements of value, a composite variable characterizing performance of the tangible or intangible element of value of the business enterprise, second means including means for combining transaction data, transaction ratios and transaction trends to calculate the composite variable;
(e) third means for calculating the value of the enterprise;
(f) fourth means for determining, for each one of the tangible or intangible elements of value, a percentage of the value of the business enterprise contributed by the tangible or intangible element of value;
(h) fifth means for user modification of, for each one of the tangible and intangible elements of value, selected one or ones of the value drivers that drive the value of the business enterprise; and
(g) sixth means for calculating a value for each of the tangible or intangible elements of value of the business enterprise based on the value of the business enterprise and the percentage of the value contributed by the tangible or intangible elements of value after user modification.
(h) seventh means for displaying the new value.
9. A data processing system as claimed in claim 8 wherein said fifth means comprises:
(a) means for user modification of, for each one of the tangible or intangible elements of value, selected one or ones of the composite variable characterizing the performance of tangible or intangible element of value of the business enterprise.
10. A data processing system as claimed in claim 8 wherein said fifth means comprises:
(a) means for user modification of, the value of each one of the tangible or intangible elements of value of the business enterprise.
11. A data processing system as claimed in claim 8 where the value of the business enterprise includes a revenue component, an expense component, a capital component and a real option category of value.
12. The data processing system of claim 8 wherein said third means comprises:
(a) means for calculating the revenue, expense and capital components of the value and the real option category of the value of the business enterprise.
13. The data processing system of claim 8 wherin said fourth means comprises:
(a) means for determining, for each one of the tangible or intangible elements of value, a percentage of the revenue component contributed by the tangible or intangible element of value, a percentage of expense component contributed by the tangible or intangible element of value, a percentage of the capital component contributed by the tangible or intangible element of value and a percentage of the real option category of value contributed by the tangible or intangible element of value; and.
14. The data processing system of claim 8 wherein said sixth means comprises:
(a) means for calculating the value for each one of the tangible or intangible elements of value based on the revenue, expense and capital components of value of the business enterprise, the real option category of the business enterprise and the percentages of the real option category and the revenue, expense and capital components of value contributed by the tangible or intangible element of value
15. A data processing system as claimed in claim 11, further comprising:
(i) means for sub-dividing the revenue, expense and capital components of the value of the business enterprise into sub-components to yield a more detailed analysis.
16. A data processing system as claimed in claim 8, wherein said fourth means further comprises:
(a) means for using output from a predictive model to determine the percentage of the revenue component contributed by the tangible or intangible element of value, the percentage of the expense component contributed by the tangible or intangible element of value, and the percentage of the capital component contributed by the tangible or intangible element of value.
17. A data processing system as claimed in claim 8, wherein said fourth means further comprises:
(b) means for using output from a data envelopment analysis to determine the percentage of the percentage of the real option category of value contributed by the tangible or intangible element of value.
18. A data processing system as claimed in claim 8 further comprising:
(i) means for directly valuing at least one of the tangible or intangible elements of value of the business enterprise.
19. A data processing system for identifying changes to one or more business enterprises of a value chain, comprising:
(a) processing means for processing data;
(b) storage means for storing data;
(c) first means for obtaining data related to the value of the value chain, the value chain having one or more business enterprises contributing to the value of the value chain,
(d) second means for calculating, for each one of the business enterprises, a composite variable characterizing performance of the business enterprise of the value chain;
(e) third means for calculating the value of the value chain;
(f) fourth means for determining, for each one of the business enterprises, a percentage of the value of the value chain contributed by the business enterprise;
(g) fifth means for calculating a value for each of the business enterprises of the value chain based on the value of the value chain and the percentage of the value of the value chain contributed by the business enterprises; and
(h) sixth means for user entry of a goal value related to the value chain; and
(i) seventh means for identifying changes to each one of the business enterprises of the value chain that will contribute to meeting the goal; and
(j) eigth means for displaying the changes.
20. A data processing system as claimed in claim 19 where the value of the value chain includes a revenue component, an expense component and a capital component.
21. A data processing system as claimed in claim 1, wherein said second means further comprises
(a) means for combining transaction data, transaction ratios, transaction trends transaction averages, time lagged transaction ratios, time lagged transaction trends, time lagged transaction averages, time lagged transaction data, transaction patterns, geospatial measures, relative rankings, links, frequencies, time periods, average time periods, cumulative time periods, rolling average time period, cumulative total values, the period to period rate of change in value to calculate the composite variable;
22. The data processing system of claim 19 wherein said third means comprises:
(a) means for calculating the value of the revenue, expense and capital components of the value of the value chain.
23. The data processing system of claim 19 wherein said fourth means comprises:
(a) means for determining, for each one of the business enterprises, a percentage of the revenue component contributed by the business enterprise, a percentage of expense component contributed by the business enterprise and a percentage of the capital component contributed by the business enterprise; and.
24. The data processing system of claim 19 wherein said fifth means comprises:
(a) means for calculating the value for each one of the business enterprises based on the revenue, expense and capital components of value of the value chain and the percentages of the revenue, expense and capital component of value contributed by the business enterprise.
25. A data processing system as claimed in claim 20, further comprising:
(i) means for sub-dividing the revenue, expense and capital components of the value of the value chain into sub-components to yield a more detailed analysis.
26. A data processing system as claimed in claim 19, wherein said fourth means further comprises:
(a) means for using output from a predictive model to determine the percentage of the revenue component contributed by the business enterprise, the percentage of the expense component contributed by the business enterprise, and the percentage of the capital component contributed by the business enterprise.
27. A data processing system as claimed in claim 19, wherein said fourth means further comprises:
(b) means for using output from a multivariate adaptive regression spline to determine the percentage of the revenue component contributed by the business enterprise, the percentage of the expense component contributed by the business enterprise, and the percentage of the capital component contributed by the business enterprise.
28. A data processing system as claimed in claim 19 further comprising:
(i) means for directly valuing at least one of the business enterprises of the value chain.
29. A data processing system as claimed in claim 19 where the goal value is the optimal value for one or more aspects of financial performance.
30. A data processing system as claimed in claim 19, wherein said seventh means further comprises:
(a) means for goal seeking and optimization.
31. A data processing system as claimed in claim 19, wherein said seventh means further comprises:
(a) means for multi criteria goal seeking and optimization.
32. A data processing system for valuing contributions by one or more business enterprise to a value of a value chain, comprising:
(a) processing means for processing data;
(b) storage means for storing data;
(c) first means for obtaining data related to the value of the value chain, the value chain having one or more business enterprise contributing to the value of the value chain, and the value of the value chain including a revenue component, an expense component and a capital component;
(d) second means for calculating, for each one of the business enterprises, a composite variable characterizing performance of the business enterprise,
(e) third means for calculating the revenue, expense and capital components of the value of the value chain;
(f) fourth means for determining, for each one of the business enterprises, a percentage of the revenue component contributed by the business enterprise, a percentage of expense component contributed by the business enterprise and a percentage of the capital component contributed by the business enterprise; and
(g) fifth means for calculating a value for each of the business enterprises of the value chain based on the revenue, expense and capital components of value of the value chain and the percentages of the revenue, expense and capital contributed by the business enterprises, and
(h) sixth means for displaying the value contributions.
33. A data processing system as claimed in claim 32, wherein said second means further comprises
(a) means for calculating for a range of time including a specified valuation date for each one of the business enterprises, the revenue, expense and capital components of the value of the value chain and the percentages of the revenue, expense and capital components contributed by each one of the business enterprises;
34. A data processing system as claimed in claim 32, wherein said second means further comprises
(a) means for combining transaction data, transaction ratios, transaction trends transaction averages, time lagged transaction ratios, time lagged transaction trends, time lagged transaction averages, time lagged transaction data, transaction patterns, geospatial measures, relative rankings, links, frequencies, time periods, average time periods, cumulative time periods, rolling average time period, cumulative total values, the period to period rates of change in value to calculate the composite variable;
35. A data processing system as claimed in claim 32, further comprising:
(h) optionally sub-dividing the revenue, expense and capital components of the value. of the value chain into sub-components to yield a more detailed analysis.
36. A data processing system as claimed in claim 32, wherein said fourth means further comprises:
(a) means for using output from a predictive model to determine the percentage of the revenue component contributed by each business enterprise, the percentage of the expense component contributed by each business enterprise, and the percentage of the capital component contributed by each business enterprise.
37. A data processing system as claimed in claim 32, wherein said fourth means further comprises:
(b) means for using output from a neural network to determine the percentage of the revenue component contributed by each business enterprise, the percentage of the expense component contributed by each business enterprise, and the percentage of the capital component contributed by each business enterprise.
38. A data processing system as claimed in claim 32, wherein said fourth means further comprises:
(c) means for using output from a regression network to determine the percentage of the revenue component contributed by the business enterprise, the percentage of the expense component contributed by the business enterprise, and the percentage of the capital component contributed by the business enterprise.
39. A data processing system as claimed in claim 32 further comprising:
(i) means for using the composite variables to evaluate the impact of the business enterprises on the value of the value chain.
40. A data processing system for evaluating changes in contribution by one or more business enterprises to a value of a value chain, comprising:
(a) processing means for processing data;
(b) storage means for storing data;
(c) first means for obtaining data related to the value of the value chain, the value chain having one or more business enterprises contributing to the value of the value chain,
(d) second means for calculating, for each one of the business enterprises, a composite variable characterizing performance of the business enterprise of the value chain;
(e) third means for calculating the value of the enterprise;
(f) fourth means for determining, for each one of the business enterprises, a percentage of the value of the value chain contributed by the business enterprise;
(g) fifth means for user modification of, for each one of the business enterprises, selected one or ones of the value drivers that drive the value of the value chain;
(i) sixth means for calculating a value for each of the business enterprises of the value chain based on the value of the value chain and the percentage of the value contributed by the business enterprises after incorporating user modifications; and
(h) seventh means for displaying the new value.
41. A data processing system as claimed in claim 40 wherein said fifth means comprises:
(a) means for user modification of, for each one of the business enterprises, selected one or ones of the composite variable characterizing the performance of business enterprise of the value chain.
42. A data processing system as claimed in claim 40 wherein said fifth means comprises:
(a) means for user modification of, the value of each one of the business enterprises of the value chain.
43. A data processing system as claimed in claim 40 where the value of the value chain includes a revenue component, an expense component, a capital component and a real option category of value.
44. The data processing system of claim 40 wherein said third means comprises:
(a) means for calculating the revenue, expense and capital components of the value and the real option category of the value of the value chain.
45. The data processing system of claim 40 wherein said fourth means comprises:
(a) means for determining, for each one of the business enterprises, a percentage of the revenue component contributed by the business enterprise, a percentage of expense component contributed by the business enterprise, a percentage of the capital component contributed by the business enterprise and a percentage of the real option category of value contributed by the business enterprise; and.
46. The data processing system of claim 40 wherein said sixth means comprises:
(a) means for calculating the value for each one of the business enterprises based on the revenue, expense and capital components of value of the value chain, the real option category of the value chain and the percentages of the real option category and of the revenue, expense and capital components of value contributed by the business enterprise after user modification.
47. A data processing system as claimed in claim 43, further comprising:
(i) means for sub-dividing the revenue, expense and capital components of the value of the value chain into sub-components to yield a more detailed analysis.
48. A data processing system as claimed in claim 40, wherein said fourth means further comprises:
(a) means for using output from a predictive model to determine the percentage of the revenue component contributed by each business enterprise, the percentage of the expense component contributed by each business enterprise, and the percentage of the capital component contributed by each business enterprise.
49. A data processing system as claimed in claim 40, wherein said fourth means further comprises:
(b) means for using output from a data envelopment analysis to determine the percentage of the percentage of the real option category of value contributed by the business enterprise.
50. A data processing system as claimed in claim 40, wherein said second means further comprises
(a) means for combining transaction data, transaction ratios, transaction trends transaction averages, time lagged transaction ratios, time lagged transaction trends, time lagged transaction averages, time lagged transaction data, transaction patterns, geospatial measures, relative rankings, links, frequencies, time periods, average time periods, cumulative time periods, rolling average time period, cumulative total values, the period to period rate of change in value to calculate the composite variable;
51. A data processing system as claimed in claim 40 further comprising:
(i) means for directly valuing at least one of the business enterprises of the value chain.
52. A data processing system for identifying changes to one or more tangible or intangible elements of value of a value of a business enterprise, comprising:
(a) processing means for processing data;
(b) storage means for storing data;
(c) first means for obtaining data related to the value of the business enterprise, the business enterprise having one or more tangible or intangible elements of value contributing to the value of the business enterprise,
(d) second means for calculating, for each one of the tangible or intangible elements of value, a composite variable characterizing performance of the tangible or intangible element of value of the business enterprise, second means including means for combining transaction data, transaction ratios and transaction trends to calculate the composite variable;
(e) third means for calculating the value of the business enterprise;
(f) fourth means for determining, for each one of the tangible or intangible elements of value, a percentage of the value of the business enterprise contributed by the tangible or intangible element of value;
(g) fifth means for calculating a value for each of the tangible or intangible elements of value of the business enterprise based on the value of the business enterprise and the percentage of the value of the business enterprise contributed by the tangible or intangible elements of value; and
(h) sixth means for user entry of a goal value related to the business enterprise; and
(i) seventh means for identifying changes to each one of the tangible or intangible elements of value of the business enterprise that will contribute to meeting the goal; and
(j) eigth means for displaying the changes.
53. A data processing system as claimed in claim 52 where the value of the business enterprise includes a revenue component, an expense component and a capital component.
54. The data processing system of claim 52 wherein said third means comprises:
(a) means for calculating the value of the revenue, expense and capital components of the value of the business enterprise.
55. The data processing system of claim 52 wherein said fourth means comprises:
(a) means for determining, for each one of the tangible or intangible elements of value, a percentage of the revenue component contributed by the tangible or intangible element of value, a percentage of expense component contributed by the tangible or intangible element of value and a percentage of the capital component contributed by the tangible or intangible element of value; and.
56. The data processing system of claim 52 wherein said fifth means comprises:
(a) means for calculating the value for each one of the tangible or intangible elements of value based on the revenue, expense and capital components of value of the business enterprise and the percentages of the revenue, expense and capital component of value contributed by the tangible or intangible element of value.
57. A data processing system as claimed in claim 54, further comprising:
(i) means for sub-dividing the revenue, expense and capital components of the value of the business enterprise into sub-components to yield a more detailed analysis.
58. A data processing system as claimed in claim 52, wherein said fourth means further comprises:
(a) means for using output from a predictive model to determine the percentage of the revenue component contributed by the tangible or intangible element of value, the percentage of the expense component contributed by the tangible or intangible element of value, and the percentage of the capital component contributed by the tangible or intangible element of value.
59. A data processing system as claimed in claim 52, wherein said fourth means further comprises:
(b) means for using output from a multivariate adaptive regression spline to determine the percentage of the revenue component contributed by the tangible or intangible element of value, the percentage of the expense component contributed by the tangible or intangible element of value, and the percentage of the capital component contributed by the tangible or intangible element of value.
60. A data processing system as claimed in claim 52 further comprising:
(i) means for directly valuing at least one of the tangible or intangible elements of value of the business enterprise.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A method of making an emulsion or latex containing polymer particles with a diameter greater than 0.02 micron (micrometer) comprising (i) forming a microemulsion containing particles of oligomers with a diameter less than 0.02 micron (micrometer) by combining water, at least one surfactant, a hydride functional organosilicon oligomer or a mixture of such oligomers, and an alkenyl functional organosilicon oligomer or a mixture of such oligomers; (ii) adding a catalyst to the microemulsion; (iii) initiating polymerization of the oligomers; and (iv) continuing polymerization until an emulsion or latex is formed containing polymer particles with a diameter greater than 0.02 micron (micrometer); the oligomers each having a viscosity of 1-50 centistoke (mm2s), and at least one of the oligomers containing more than two reactive sites.
2. A method according to claim 1 in which the oligomers have a formula selected from the group consisting of
4
5
where R1 is an alkyl group containing 1-6 carbon atoms or an aryl group; R2 is hydrogen or an alkenyl group; a and b are each 0-10, c is 1-10, and provided the sum of b and c is 1-10; and d and e are each 0-10 provided the sum of d and e is 3-10.
3. An emulsion or latex prepared by the method according to claim 1.
4. A cured film prepared by removing water from the emulsion or latex of claim 3.
5. A method of making an emulsion or latex containing polymer particles with a diameter greater than 0.02 micron (micrometer) comprising (i) forming a first microemulsion containing particles of oligomers with a diameter less than 0.02 micron (micrometer) by combining water, at least one surfactant, and a hydride functional organosilicon oligomer or a mixture of such oligomers; (ii) forming a second microemulsion containing particles of oligomers with a diameter less than 0.02 micron (micrometer) by combining water, at least one surfactant, an alkenyl functional organosilicon oligomer or a mixture of such oligomers, and a catalyst; (iii) combining the first microemulsion and the second microemulsion to initiate polymerization of the oligomers; and (iv) continuing polymerization until an emulsion or latex is formed containing polymer particles with a diameter greater than 0.02 micron (micrometer); the oligomers each having a viscosity of 1-50 centistoke (mm2s), and at least one of the oligomers containing more than two reactive sites.
6. A method according to claim 5 in which the oligomers have a formula selected from the group consisting of
6
7
where R1 is an alkyl group containing 1-6 carbon atoms or an aryl group; R2 is hydrogen or an alkenyl group; a and b are each 0-10, C is 1-10, provided the sum of b and c is 1-10; and d and e are each 0-10 provided the sum of d and e is 3-10.
7. An emulsion or latex prepared by the method according to claim 5.
8. A cured film prepared by removing water from the emulsion or latex of claim 7.