1. A vehicle comprising:
an internal combustion engine having a plurality of cylinders;
an exhaust gas purification catalyst which is arranged in an exhaust passage of the internal combustion engine and purifies exhaust gas;
a first air-fuel ratio detecting portion that is arranged upstream of the exhaust gas purification catalyst;
a second air-fuel ratio detecting portion that is arranged downstream of the exhaust gas purification catalyst; and
a control apparatus of the internal combustion engine,
wherein the control apparatus executes main feedback control that controls an air-fuel ratio of the internal combustion engine based on a detection value of the first air-fuel ratio detecting portion, and sub-feedback control that calculates a learning value for correcting the main feedback control based on a detection value of the second air-fuel ratio detecting portion; and
wherein the controlling apparatus includes a rotational variation calculating portion that calculates a rotational variation of an output shaft of the internal combustion engine based on combustion of each of the cylinders, a variation integrating portion that calculates a cumulative value of the rotational variation by adding the rotational variation calculated by the rotational variation calculating portion to the rotational variation integrated thus far, an integration counting portion that counts the number of times the rotational variation has been integrated by the variation integrating portion, a combustion state estimating portion that estimates a combustion state of the internal combustion engine according to the cumulative value of the rotational variation integrated by the variation integrating portion, on the condition that the number of integrations counted by the integration counting portion has reached a predetermined value; and a learning value correcting portion that corrects the learning value of the sub-feedback control according to the combustion state estimated by the combustion state estimating portion.
2. The vehicle according to claim 1,
wherein the control apparatus further includes a rotational position detecting portion that detects a rotational position of the output shaft of the internal combustion engine, and a required time calculating portion that calculates the required time that it takes for the output shaft to rotate a predetermined angle from the combustion stroke of the cylinders, based on the rotational position of the output shaft detected by the rotational position detecting portion, and
wherein the rotational variation calculating portion calculates the rotational variation of the output shaft based on a pre-obtained required time during a complete misfire, which is the time that it takes for the output shaft to rotate die predetermined angle when a complete misfire occurs in the cylinders during the combustion stroke, and a pre-obtained required time during complete combustion, which is the time that it takes for the output shaft to rotate the predetermined angle when complete combustion occurs in the cylinders during the combustion stroke, and the required time calculated by the required time calculating portion.
3. The vehicle according to claim 1, further comprising:
a combustion pressure detecting portion that detects a combustion pressure in the cylinders,
wherein the rotational variation calculating portion calculates the rotational variation of the output shaft by comparing the combustion pressure detected by the combustion pressure detecting portion with a pre-obtained combustion pressure during complete combustion.
4. The vehicle according to claim 1, further comprising:
an ion current detecting portion that detects ion current produced inside the cylinders during the combustion stroke,
wherein the rotational variation calculating portion calculates the rotational variation of the output shaft by comparing the ion current value detected by the ion current detecting portion with a pre-obtained ion current value during complete combustion.
5. The vehicle according to claim 1,
wherein the control apparatus further includes a disturbance detecting portion that detects a disturbance that contributes to variation in the combustion state of the internal combustion engine, and
wherein the variation integrating portion stops integrating the rotational variation when a disturbance that contributes to variation in the combustion state is detected by the disturbance detecting portion.
6. The vehicle according claim 5, wherein the disturbance detecting portion detects a load of the internal combustion engine being equal to or less than a predetermined value as a disturbance that contributes to variation in the combustion state.
7. The vehicle according to claim 5, wherein the disturbance detecting portion detects a coolant temperature of the internal combustion engine being equal to or less than a predetermined value as a disturbance that contributes to variation in the combustion state.
8. A control method of a vehicle that includes an internal combustion engine having a plurality of cylinders; an exhaust gas purification catalyst which is arranged in an exhaust passage of the internal combustion engine and purifies exhaust gas; a first air-fuel ratio detecting portion that is arranged upstream of the exhaust gas purification catalyst; a second air-fuel ratio detecting portion that is arranged downstream of the exhaust gas purification catalyst; and a control apparatus of the internal combustion engine, the control method comprising:
executing main feedback control that controls an air-fuel ratio of the internal combustion engine based on a detection value of the first air-fuel ratio detecting portion;
executing sub-feedback control that calculates a learning value for correcting the main feedback control based on a detection value of the second air-fuel ratio detecting portion;
calculating a rotational variation of an output shaft of the internal combustion engine based on combustion of each of the cylinders;
calculating a cumulative value of the rotational variation by adding the calculated rotational variation to the rotational variation integrated thus far;
counting the number of times the rotational variation has been integrated;
estimating a combustion state of the internal combustion engine according to the cumulative value of integrated rotational variation, on the condition that the number of counted integrations has reached a predetermined value; and
correcting the learning value of the sub-feedback control according to the estimated combustion state.
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 testing for one or more colorectal pathologies in a test subject, the method comprising:
(a) providing data representing a level of one or more products of each of at least two biomarkers in a sample isolated andor derived from said test subject, wherein said biomarkers are genes selected from the group consisting of BCNP1, CD163, CDA, MS4A1, BANK1, and MGC20553; and
(b) applying to said data a formula based on (i) a dataset representing levels of one or more products of each of said biomarkers in each subject of a reference population having said one or more pathologies, and (ii) a dataset representing levels of one or more products of each of said biomarkers in each subject of a reference population not having said one or more pathologies, thus providing an indication of a probability that said test subject has said one or more colorectal pathologies.
2. A computer-based method for testing for one or more colorectal pathologies in a test subject, the method comprising:
inputting, to a computer, data representing a level of products of each of at least two biomarkers in a sample isolated andor derived from a test subject, wherein said biomarkers are genes selected from the group consisting of BCNP1, CD163, CDA, MS4A1, BANK1 and MGC20553; and
causing said computer to apply to said data, a formula based on (i) a dataset representing levels of one or more products of each of said biomarkers in each subject of a reference population having said one or more pathologies, and (ii) a dataset representing levels of one or more products of each of said biomarkers in each subject of a reference population not having said one or more pathologies, thus providing an indication of a probability that said test subject has said one or more colorectal pathologies.
3. The method of claims 1 or 2, wherein said formula has a form:
V=C+\u03a3\u03b2iXi,
wherein V is a value indicating a probability that said test subject has said one or more colorectal pathologies, Xi is a level of products of an ith biomarker of said biomarkers, \u03b2i is a coefficient, and C is a constant.
4. The method of claims 1 or 2, wherein said formula has a form:
V=C+\u03a3\u03b2ij(XiXj),
wherein V is a value indicating a probability that said test subject has said one or more colorectal pathologies, Xi is a level of products of an ith biomarker of said biomarkers; Xj is a level of products of a jth biomarker of said biomarkers where the ith biomarker is not the jth biomarker, \u03b2ij is a coefficient and C is a constant.
5. The method of claims 1 or 2, wherein said formula is derived by logistic regression.
6. The method of claims 1 or 2, wherein said sample is selected from the group consisting of blood, lymph and lymphoid tissue.
7. The method of claims 1 or 2 wherein said products in said sample are RNA.
8. The method of claims 1 or 2, wherein said sample is selected from the group consisting of a sample of serum-reduced blood, a sample of erythrocyte-reduced blood, a sample of serum-reduced and erythrocyte-reduced blood, a sample of unfractionated cells of lysed blood, and a sample of fractionated blood.
9. The method of claims 1 or 2, wherein said products in said sample are RNA, and whereas said data represents a level of cDNA, EST andor PCR product derived from said RNA.
10. A kit comprising packaging and containing at least two primer sets, wherein each set of which is able to generate an amplification product by selective amplification of at least a portion of a polynucleotide complementary to one or more RNA products of a biomarker, wherein said biomarker is a gene selected from the group consisting of: BCNP1, CD163, CDA, MS4A1, BANK1, and MGC20553; and wherein each set of said primer sets is selective for a different biomarker of said group.
11. The kit of claim 10, wherein said polynucleotide is selected from the group consisting of total RNA, mRNA, DNA, cDNA and EST.
12. The kit of claim 10, further comprising two or more oligonucleotide probes, wherein each of said probes is capable of selectively hybridizing to either a sense or an antisense strand of said amplification product.
13. The kit of claims 10, 11 or 12, further comprising two or more components selected from the group consisting of: a thermostable polymerase, a reverse transcriptase, deoxynucleotide triphosphates, nucleotide triphosphates and enzyme buffer.
14. The kit of claims 10, 11, 12 or 13, further comprising a computer-readable medium encoded with instructions for applying a formula to data representing levels of said amplification product in a sample isolated andor derived from a test subject, wherein said formula is said based on (i) a dataset representing levels of one or more products of each of said biomarkers in each subject of a reference population having one or more colorectal pathologies, and (ii) a dataset representing levels of one or more products of each of said biomarkers in each subject of a reference population not having said one or more pathologies, thus providing an indication of a probability that said test subject has said one or more colorectal pathologies.
15. The kit of claim 14, wherein said formula has a form:
V=C+\u03a3\u03b2iXi,
wherein V is a value indicating a probability that said test subject has said one or more colorectal pathologies, Xi is a level of products of an ith biomarker of said biomarkers, \u03b2i is a coefficient, and C is a constant.
16. The kit of claim 14, wherein said formula has a form:
V=C+\u03a3\u03b2ij(XiXj),
wherein V is a value indicating a probability that said test subject has said one or more colorectal pathologies, Xi is a level of products of an ith biomarker of said biomarkers, Xj is a level of products of a jth biomarker of said biomarkers where the ith biomarker is not the jth biomarker, \u03b2ij is a coefficient, and C is a constant.
17. The kit of claims 14, 15 or 16, wherein said sample is selected from the group consisting of blood, lymph and lymphoid tissue.
18. The kit of claims 14, 15 or 16, wherein said sample is selected from the group consisting of a sample of serum-reduced blood, a sample of erythrocyte-reduced blood, a sample of serum-reduced and erythrocyte-reduced blood, a sample of unfractionated cells of lysed blood and a sample of fractionated blood.
19. A computer-readable medium having instructions stored thereon that are operable when executed by a computer to apply a formula to data representing a level of one or more products of each of at least two biomarkers in a sample isolated andor derived from a test subject, wherein said biomarkers are genes selected from the group consisting of BCNP1, CD163, CDA, MS4A1, BANK1, and MGC20553, wherein said formula is based on (i) a dataset representing levels of one or more products of each of said biomarkers in each subject of a reference population having one or more colorectal pathologies, and (ii) a dataset representing levels of one or more products of each of said biomarkers in each subject of a reference population not having said one or more pathologies, thus providing an indication of a probability that said test subject has said one or more colorectal pathologies.
20. The computer-readable medium of claim 19, wherein said formula has a form:
V=C+\u03a3\u03b2iXi,
wherein V is a value indicating a probability that said test subject has said one or more colorectal pathologies, Xi is a level of products of an ith biomarker of said biomarkers, \u03b2i is a coefficient, and C is a constant.
21. The computer-readable medium of claim 19, wherein said formula has a form:
V=C+\u03a3\u03b2ij(XiXj),
wherein V is a value indicating a probability that said test subject has said one or more colorectal pathologies, Xi is a level of products of an ith biomarker of said biomarkers, and Xj is a level of products of a jth biomarker of said biomarkers, where the ith biomarker is not the jth biomarker, \u03b2ij is a coefficient and C is a constant.
22. The computer-readable medium of claim 19 wherein said formula is derived by logistic regression.
23. The computer-readable medium of claim 19 wherein said sample is selected from the group consisting of blood, lymph and lymphoid tissue.
24. The computer-readable medium of claims 19 wherein said products in said sample are RNA.
25. The computer-readable medium of claim 19, wherein said sample is selected from the group consisting of a sample of serum-reduced blood, a sample of erythrocyte-reduced blood, a sample of serum-reduced and erythrocyte-reduced blood, a sample of unfractionated cells of lysed blood, and a sample of fractionated blood.
26. The computer-readable medium of claim 19 wherein said products in said sample are RNA, and whereas said data represents a level of cDNA, EST andor PCR product derived from said RNA.
27. A computer system for providing an indication of a probability that a test subject has one or more colorectal pathologies, the computer system comprising
a processor; and
a memory configured with instructions that, when executed, cause said processor to provide a user with said indication, wherein said instructions comprise applying a formula to data representing a level of one or more products of each of at least two biomarkers in a sample isolated andor derived from said test subject, wherein said biomarkers are genes selected from the group consisting of BCNP1, CD163, CDA, MS4A1, BANK1, and MGC20553; and wherein said formula is based on (i) a dataset representing levels of one or more products of each of said biomarkers in each subject of a reference population having said one or more pathologies, and (ii) a dataset representing levels of one or more products of each of said biomarkers in each subject of a reference population not having said one or more pathologies, thus providing said indication of said probability that said test subject has said one or more colorectal pathologies.
28. The system of claim 27, wherein said formula has a form:
V=C+\u03a3\u03b2iXi,
wherein V is a value indicating a probability that said test subject has said one or more colorectal pathologies, Xi is a level of products of an ith biomarker of said biomarkers, \u03b2i is a coefficient, and C is a constant.
29. The system of claim 27, wherein said formula has a form:
V=C+\u03a3\u03b2ij(XiXj),
wherein V is a value indicating a probability that said test subject has said one or more colorectal pathologies, Xi is a level of products of an ith biomarker of said biomarkers, and Xj is a level of products of a jth biomarker of said biomarkers, where the ith biomarker is not the jth biomarker, \u03b2ij is a coefficient, and C is a constant.
30. The system of claim 27, wherein said formula is derived by logistic regression.
31. The system of claim 27, wherein said sample is selected from the group consisting of blood, lymph and lymphoid tissue.
32. The system of claim 27, wherein said products in said sample are RNA.
33. The system of claim 27 wherein said sample is selected from the group consisting of a sample of serum-reduced blood, a sample of erythrocyte-reduced blood, a sample of serum-reduced and erythrocyte-reduced blood, a sample of unfractionated cells of lysed blood, and a sample of fractionated blood.
34. The system of claim 27 wherein said products in said sample are RNA, and whereas said data represents a level of cDNA, EST andor PCR product derived from said RNA.