1. A kit for creating a modified handgun from a first handgun having a first frame and a first slide and barrel assembly comprising a first slide and first barrel, a first recoil spring and a first recoil spring guide, and a second handgun having a second frame and a second slide and barrel assembly comprising a second slide and second barrel, a second recoil spring, and a second recoil spring guide, wherein said first slide and barrel assembly is modified and connected to said second frame in replacement of said second slide and barrel assembly, said kit comprising:
a dust cover insert connectable to said first slide;
a replacement recoil spring guide configured to be connected to said first slide in replacement of said first recoil spring guide; and
a replacement recoil spring configured to be mounted on said replacement recoil spring guide in replacement of said first recoil spring,
whereby said kit is configured to create a modified first slide and barrel assembly which is connectable to said second frame in replacement of said second slide and barrel assembly.
2. The kit in accordance with claim 1 wherein said first slide has mounting rails and said dust cover insert is generally \u201cU\u201d shaped and has first and second mounts which engage said mounting rails.
3. The kit in accordance with claim 1 wherein said replacement recoil spring is longer than said second recoil spring and shorter than said first recoil spring.
4. The kit in accordance with claim 1 wherein said replacement recoil spring guide is longer than said second recoil spring guide and shorter than said second recoil spring guide.
5. The kit in accordance with claim 4 wherein said replacement recoil spring guide comprises a rod having a head located at a first end and a second tapered end.
6. The kit in accordance with claim 1 wherein said first recoil spring has a first length and said second recoil spring has a second length different than said first length.
7. the kit in accordance with claim 1 wherein said first recoil spring guide has a first length and said second recoil spring guide has a second length different than said first length.
8. The kit in accordance with claim 1 wherein said first slide and barrel assembly has a first length and said second slide and barrel assembly has a second length.
9. The kit in accordance with claim 8 wherein said dust cover insert has a length equal to the difference between said first length and said second length.
10. The kit in accordance with claim 1 wherein said first handgun comprises a Smith & Wesson Military and Police model 9 mm standard and said second handgun comprises a Smith & Wesson Military and Police model 9 mm compact.
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 non-compartmental method of predicting a time-dependent response of a component of a system to an input into the system, the method comprising:
identifying the system, the component, the input, and the time-dependent response; wherein, the input includes a set of actual inputs and a test input, and the time-dependent response includes a set of time-dependent actual responses and a test response;
obtaining the set of time-dependent actual responses of the component to the set of actual inputs;
using the set of actual inputs and the set of time-dependent actual responses to provide a model for predicting the test response to the test input, the model comprising the formula
C
\u2061
(
t
)
=
M
0
0
+
M
0
1
\u2061
(
kernel
)
+
\u2003
M
1
0
+
M
1
1
\u2061
(
kernel
)
\u2062
{
1
–
\u2147
–
N
1
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
1
+
(
\u2147
K
–
2
)
\u2062
\u2147
–
N
1
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
}
+
\u2026
+
M
n
0
+
M
n
1
\u2061
(
kernel
)
\u2062
{
1
–
\u2147
–
N
n
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
1
+
(
\u2147
K
–
2
)
\u2062
\u2147
–
N
n
0
+
N
n
1
\u2061
(
kernel
)
\u2062
t
}
(
9
)
wherein,
M00, . . . , M0n and M10, . . . , M1n are overall scaling parameters;
N01, . . . , N0n and N11, . . . , N1n are exponential scaling parameters;
n ranges from 1 to 4;
K is an overall shifting parameter; and,
C(t) is the time-dependent response to the test input at time t;
and,
kernel
\u2261
1
–
\u2147
–
\u03b1
p
\u2062
C
0
1
+
(
\u2147
K
p
–
2
)
\u2062
\u2147
–
\u03b1
p
\u2062
C
0
;
wherein, C0 is the initial amount of the test input; Kp is a shifting parameter related to C0; and, \u03b1p is shifting and scaling parameter related to C0;
and,
using the model to obtain the time-dependent test response to the test input.
2. The method of claim 1, wherein the system is an environmental system and the component is selected from the group consisting of air, water, and soil.
3. The method of claim 1, wherein the system is a mammal, and the component is selected from the group consisting of a cell, a tissue, an organ, a DNA, a virus, a protein, an antibody, a bacteria.
4. The method of claim 1, wherein the system is a chemical system.
5. The method of claim 1, wherein the system is a mechanical system.
6. The method of claim 1, wherein the system is an electrical system.
7. A non-compartmental method of predicting a time-dependent response of a component of a mammalian system to an input into the system, the method comprising:
selecting a component of the system, the component selected from the group consisting of a cell, a tissue, an organ, a DNA, a virus, a protein, an antibody, a bacteria;
selecting a set of actual inputs, the set of actual inputs having an element selected from the group consisting of a DNA, a virus, a protein, an antibody, a bacteria, a chemical, a dietary supplement, a nutrient, and a drug;
obtaining a set of time-dependent actual responses of the component to the set of actual inputs;
using the set of actual inputs and the set of time-dependent actual responses to provide a model for predicting a test response to a test input, the model comprising the formula
C
\u2061
(
t
)
=
M
0
0
+
M
0
1
\u2061
(
kernel
)
+
\u2003
M
1
0
+
M
1
1
\u2061
(
kernel
)
\u2062
{
1
–
\u2147
–
N
1
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
1
+
(
\u2147
K
–
2
)
\u2062
\u2147
–
N
1
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
}
+
\u2026
+
M
n
0
+
M
n
1
\u2061
(
kernel
)
\u2062
{
1
–
\u2147
–
N
n
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
1
+
(
\u2147
K
–
2
)
\u2062
\u2147
–
N
n
0
+
N
n
1
\u2061
(
kernel
)
\u2062
t
}
(
9
)
wherein,
M00, . . . , M0n and M10, . . . , M1n are overall scaling parameters;
N01, . . . , N0n and N11, . . . , N1n are exponential scaling parameters;
n ranges from 1 to 4;
K is an overall shifting parameter; and,
C(t) is the time-dependent response to the test input at time t;
and,
kernel
\u2261
1
–
\u2147
–
\u03b1
p
\u2062
C
0
1
+
(
\u2147
K
p
–
2
)
\u2062
\u2147
–
\u03b1
p
\u2062
C
0
;
wherein, C0 is the initial amount of the test input; Kp is a shifting parameter related to C0; and, \u03b1p is shifting and scaling parameter related to C0;
and,
using the model to obtain the time-dependent test response to the test input.
8. The method of claim 7, wherein the component is blood.
9. The method of claim 7, wherein the component is a tumor cell.
10. The method of claim 7, wherein the component is a virus.
11. The method of claim 7, wherein the component is a bacteria.
12. The method of claim 7, wherein the test response is a bacterial load.
13. The method of claim 7, wherein the test response is a viral load.
14. The method of claim 7, wherein the test response is a tumor marker.
15. The method of claim 7, wherein the test response is a blood chemistry.
16. The method of claim 7, wherein the set of actual inputs includes a set of dosages of a drug.
17. The method of claim 7, wherein the set of actual inputs includes a set of drugs.
18. The method of claim 7, wherein the input is a diabetes drug, and the time-dependent response is glucose in the bloodstream.
19. A device for predicting a time-dependent response of a component of a physical system to an input into the system, the device comprising:
a processor;
a database for storing a set of actual input data, a set of time-dependent actual response data, test input data, and time-dependent test response data on a non-transitory computer readable medium;
an enumeration engine on a non-transitory computer readable medium to parameterize a non-compartmental model for predicting a test response to a test input, the non-compartmental model comprising the formula
C
\u2061
(
t
)
=
M
0
0
+
M
0
1
\u2061
(
kernel
)
+
\u2003
M
1
0
+
M
1
1
\u2061
(
kernel
)
\u2062
{
1
–
\u2147
–
N
1
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
1
+
(
\u2147
K
–
2
)
\u2062
\u2147
–
N
1
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
}
+
\u2026
+
M
n
0
+
M
n
1
\u2061
(
kernel
)
\u2062
{
1
–
\u2147
–
N
n
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
1
+
(
\u2147
K
–
2
)
\u2062
\u2147
–
N
n
0
+
N
n
1
\u2061
(
kernel
)
\u2062
t
}
(
9
)
wherein,
M00, . . . , M0n and M10, . . . , M1n are overall scaling parameters;
N01, . . . , N0n and N11, . . . , N1n are exponential scaling parameters;
n ranges from 1 to 4;
K is an overall shifting parameter; and,
C(t) is the time-dependent response to the test input at time t;
and,
kernel
\u2261
1
–
\u2147
–
\u03b1
p
\u2062
C
0
1
+
(
\u2147
K
p
–
2
)
\u2062
\u2147
–
\u03b1
p
\u2062
C
0
;
wherein, C0 is the initial amount of the test input; Kp is a shifting parameter related to C0; and, \u03b1p is shifting and scaling parameter related to C0;
and,
a transformation module on a non-transitory computer readable medium to transform the test data into the time-dependent response data using the non-compartmental model.
20. The device of claim 19, wherein the system is an environmental system and the component is selected from the group consisting of air, water, and soil.
21. A device for predicting a time-dependent response of a component of a mammalian system to an input into the system, the device comprising:
a processor;
a database for storing a set of actual input data, a set of time-dependent actual response data, test input data, and time-dependent test response data on a non-transitory computer readable medium;
an enumeration engine on a non-transitory computer readable medium to parameterize a non-compartmental model for predicting a test response to a test input, the non-compartmental model comprising the formula
C
\u2061
(
t
)
=
M
0
0
+
M
0
1
\u2061
(
kernel
)
+
\u2003
M
1
0
+
M
1
1
\u2061
(
kernel
)
\u2062
{
1
–
\u2147
–
N
1
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
1
+
(
\u2147
K
–
2
)
\u2062
\u2147
–
N
1
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
}
+
\u2026
+
M
n
0
+
M
n
1
\u2061
(
kernel
)
\u2062
{
1
–
\u2147
–
N
n
0
+
N
1
1
\u2061
(
kernel
)
\u2062
t
1
+
(
\u2147
K
–
2
)
\u2062
\u2147
–
N
n
0
+
N
n
1
\u2061
(
kernel
)
\u2062
t
}
(
9
)
wherein,
M00, . . . , M0n and M10, . . . , M1n are overall scaling parameters;
N01, . . . , N0n and N11, . . . , N1n are exponential scaling parameters;
n ranges from 1 to 4;
K is an overall shifting parameter; and,
C(t) is the time-dependent response to the test input at time t;
and,
kernel
\u2261
1
–
\u2147
–
\u03b1
p
\u2062
C
0
1
+
(
\u2147
K
p
–
2
)
\u2062
\u2147
–
\u03b1
p
\u2062
C
0
;
wherein, C0 is the initial amount of the test input; Kp is a shifting parameter related to C0; and, \u03b1p is shifting and scaling parameter related to C0;
and,
a transformation module on a non-transitory computer readable medium to transform the test data into the time-dependent response data using the non-compartmental model.
22. The device of claim 21, wherein the component is blood.
23. The device of claim 21, wherein the component is a tumor cell.
24. The device of claim 21, wherein the component is a virus.
25. The device of claim 21, wherein the component is a bacteria.
26. The device of claim 21, wherein the time-dependent response is a bacterial load.
27. The device of claim 21, wherein the time-dependent response is a viral load.
28. The device of claim 21, wherein the time-dependent response is a tumor marker.
29. The device of claim 21, wherein the time-dependent response is a blood chemistry.
30. The device of claim 21, wherein the device is a handheld device.