Author: claimsbot

1. A method of treating diseases caused all or in part by a deficiency in \u03b1-L-iduronidase, the method comprising
administering a pharmaceutical composition comprising a human recombinant \u03b1-L-iduronidase of SEQ ID NO:2, or a biologically active fragment thereof which possesses the same or similar biological activity to SEQ ID NO:2, a pharmaceutically acceptable carrier, and a polysorbate, wherein said recombinant \u03b1-L-iduronidase of SEQ ID NO:2 or biologically active fragment thereof has a purity of greater than 99%, to a human subject in need thereof in an amount effective to alleviate symptoms of said deficiency, wherein said treatment reduces lysosomal storage of glycosaminoglycans (GAGs) in the tissue of said human subject caused all or in part by said deficiency.
2. The method of claim 1 wherein the disease is mucopolysaccharidosis.
3. The method of claim 1 wherein the disease is MPS I.
4. The method of claim 1 wherein the disease is selected from the group consisting of: Hurler’s disease, Scheie syndrome and Hurler-Scheic syndrome.
5. The method of claim 1 wherein said subject suffering from the disease demonstrates about less than 1% or less of a normal \u03b1-L-iduronidase activity.
6. The method of claim 1 wherein a dose of at least about 100 units per kilogram body weight of said human recombinant \u03b1-L-iduronidase or biologically active fragment thereof is administered weekly to a patient suffering from said deficiency.
7. The method of claim 6, wherein said dose is administered over a four-hour infusion.
8. The method of claim 1 wherein said administering is a slow infusion of at least 3000 unitskg of said \u03b1-L-iduronidase or biologically active fragment thereof for about an hour, followed by a rapid two-hour infusion of at least 122,000 unitskg of said \u03b1-L-iduronidase or biologically active fragment thereof to achieve a dose of at least 125,000 unitskg or 100 SIUkg or 0.5 mgkg.
9. The method of claim 8, wherein said infusion is used to minimize complement mediated clinical allergic reactions.
10. The method of claim 1, wherein said polysorbate is polysorbate 80 or polysorbate 20.
11. The method of claim 10, wherein the concentration of said polysorbate 80 in said pharmaceutical composition is 5 to 10 \u03bcM.

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 location model updating apparatus to update a location model based on data uploaded from a mobile terminal, comprising:
a storage unit; and
a processor configured to perform an updating process in two stages including a first stage and a second stage,
wherein the first stage includes
computing a certainty of data observed at a location having a location name designated by a user of the mobile terminal, based on a previous histogram stored in the storage unit, for each of most recent check-in data uploaded during a time from a previous histogram updating to a current histogram updating, and using the computed certainty as a number of votes to a histogram indicating a reception state of data from each base station at the location of the mobile terminal; and
generating a most recent histogram based on the number of votes to the histogram computed for each of the most recent check-in data, and

wherein the second stage includes
detecting the location using the previous histogram, based on a received signal strength included in each of the most recent check-in data, in order to judge whether the check-in data is correct, depending on whether a location name of the detected location matches the location name designated by the user and included in each of the most recent check-in data;
obtaining a ratio of correct check-in data within each of the most recent check-in data, to compute a weight of the most recent histogram and a weight of the previous histogram from a ratio of correct check-in data currently obtained and a ratio of correct check-in data previously obtained; and
updating the previous histogram based on the weight of the most recent histogram and the previous histogram, in order to update the location model by storing the previous histogram that is updated, as the current histogram, in the storage unit.
2. The location model updating apparatus as claimed in claim 1, wherein the histogram indicates a missing frequency of data from each base station being observed, an observing frequency of data from each base station being observed, and a received signal strength from each base station, at the location of the mobile terminal.
3. The location model updating apparatus as claimed in claim 1, wherein the generating the most recent histogram includes
judging whether an initial histogram is stored in the storage unit when a number of most recent check-in data greater than or equal to a predetermined value is uploaded, and
creating the initial histogram when no initial histogram is stored in the storage unit.
4. The location model updating apparatus as claimed in claim 1, wherein
the detecting detects the location by counting a number of correct check-in data when the location name of the detected location matches the location name designated by the user and included in each of the most recent check-in data,
the obtaining obtains the ratio of the correct check-in data by computing a weighted average of the most recent histogram and a weighted average of the previous histogram, based on the weights of the most recent histogram and the previous histogram, the number of correct check-in data obtained when updating the previous histogram, and the number of correct check-in data that is counted, and
the updating updates the previous histogram based on the weighted average of the most recent histogram and the weighted average of the previous histogram, in order to update the location model by storing the previous histogram that is updated, as the current histogram, in the storage unit.
5. A position estimating method to estimate a position of a mobile terminal that is communicable with a plurality of base stations, comprising:
estimating, in the mobile terminal, the position of the mobile terminal based on a location model stored within the mobile terminal;
updating, in the mobile terminal, the location model based on data downloaded from a server; and
performing a location model updating process in two stages including a first stage and a second stage, in the server, to update the location model stored in a storage unit of the server, based on data uploaded from the mobile terminal,
wherein the first stage includes
computing a certainty of data observed at a location having a location name designated by a user of the mobile terminal, based on a previous histogram stored in the storage unit, for each of most recent check-in data uploaded during a time from a previous histogram updating to a current histogram updating, and using the computed certainty as a number of votes to a histogram indicating a reception state of data from each of the plurality of base stations at the location of the mobile terminal; and
generating a most recent histogram based on the number of votes to the histogram computed for each of the most recent check-in data, and

wherein the second stage includes
detecting the location using the previous histogram, based on a received signal strength included in each of the most recent check-in data, in order to judge whether the check-in data is correct, depending on whether a location name of the detected location matches the location name designated by the user and included in each of the most recent check-in data;
obtaining a ratio of correct check-in data within each of the most recent check-in data, and compute a weight of the most recent histogram and a weight of the previous histogram from a ratio of correct check-in data currently obtained and a ratio of correct check-in data previously obtained; and
updating the previous histogram based on the weight of the most recent histogram and the weight of the previous histogram, in order to update the location model by storing the previous histogram that is updated, as the current histogram, in the storage unit.
6. The position estimating method as claimed in claim 5, wherein the histogram indicates a missing frequency of data from each of the plurality of base stations being observed, an observing frequency of data from each of the plurality of base stations being observed, and a received signal strength from each of the plurality of base stations, at the location of the mobile terminal.
7. The position estimating method as claimed in claim 5, wherein the generating includes
judging whether an initial histogram is stored in the storage unit when a number of most recent check-in data greater than or equal to a predetermined value is uploaded, and
creating the initial histogram when no initial histogram is stored in the storage unit.
8. The position estimating method as claimed in claim 5, wherein
the detecting includes counting a number of correct check-in data when the location name of the detected location matches the location name designated by the user and included in each of the most recent check-in data,
the obtaining includes computing a weighted average of the most recent histogram and a weighted average of the previous histogram, based on the weights of the most recent histogram and the previous histogram, the number of correct check-in data obtained when updating the previous histogram, and the number of correct check-in data that is counted, and
the updating includes updating the previous histogram based on the weighted average of the most recent histogram and the weighted average of the previous histogram, in order to update the location model by storing the previous histogram that is updated, as the current histogram, in the storage unit.
9. A non-transitory computer-readable storage medium having stored therein a program for causing a computer to execute a process in two stages to update a location model based on data uploaded from a mobile terminal, the two stages of the process comprising:
a first stage including
computing a certainty of data observed at a location having a location name designated by a user of the mobile terminal, based on a previous histogram stored in a storage unit, for each of most recent check-in data uploaded during a time from a previous histogram updating to a current histogram updating, and using the computed certainty as a number of votes to a histogram indicating a reception state of data from each base station at the location of the mobile terminal; and
generating a most recent histogram based on the number of votes to the histogram computed for each of the most recent check-in data, and

a second stage including
detecting the location using the previous histogram, based on a received signal strength included in each of the most recent check-in data, in order to judge whether the check-in data is correct, depending on whether a location name of the detected location matches the location name designated by the user and included in each of the most recent check-in data;
obtaining a ratio of correct check-in data within each of the most recent check-in data, and compute a weight of the most recent histogram and a weight of the previous histogram from a ratio of correct check-in data currently obtained and a ratio of correct check-in data previously obtained; and
updating the previous histogram based on the weight of the most recent histogram and the weight of the previous histogram, in order to update the location model by storing the previous histogram that is updated, as the current histogram, in the storage unit.
10. The non-transitory computer-readable storage medium as claimed in claim 9, wherein the histogram indicates a missing frequency of data from each base station being observed, an observing frequency of data from each base station being observed, and a received signal strength from each base station, at the location of the mobile terminal.
11. The non-transitory computer-readable storage medium as claimed in claim 9, wherein the generating includes
judging whether an initial histogram is stored in the storage unit when a number of most recent check-in data greater than or equal to a predetermined value is uploaded, and
creating the initial histogram when no initial histogram is stored in the storage unit.
12. The non-transitory computer-readable storage medium as claimed in claim 9, wherein
the detecting includes counting a number of correct check-in data when the location name of the detected location matches the location name designated by the user and included in each of the most recent check-in data,
the obtaining includes computing a weighted average of the most recent histogram and a weighted average of the previous histogram, based on the weights of the most recent histogram and the previous histogram, the number of correct check-in data obtained when updating the previous histogram, and the number of correct check-in data that is counted, and
the updating includes updating the previous histogram based on the weighted average of the most recent histogram and the weighted average of the previous histogram, in order to update the location model by storing the previous histogram that is updated, as the current histogram, in the storage unit.
13. The location model updating apparatus as claimed in claim 1, wherein the computing computes the certainty that an RSSI (Received Signal Strength Indicator) data included in the most recent check-in data is definitely the data uploaded at the location having the location name included in the most recent check-in data.
14. The position estimating method as claimed in claim 5, wherein the computing computes the certainty that an RSSI (Received Signal Strength Indicator) data included in the most recent check-in data is definitely the data uploaded at the location having the location name included in the most recent check-in data.
15. The non-transitory computer-readable storage medium as claimed in claim 9, wherein computing computes the certainty that an RSSI (Received Signal Strength Indicator) data included in the most recent check-in data is definitely the data uploaded at the location having the location name included in the most recent check-in data.

What is claimed is:

1. A detergent composition comprising a maltogenic alpha-amylase enzyme and a detergent ingredient selected from the group consisting of a nonionic surfactant, a protease, a bleaching agent and mixtures thereof.
2. A detergent composition according to claim 1 wherein said maltogenic alpha-amylase enzyme is present at a level of from about 0.0002% to about 10% pure enzyme by weight of the total detergent composition.
3. A detergent composition according to claim 2 wherein said maltogenic alpha-amylase enzyme is present at a level of from about 0.001% to about 2% pure enzyme by weight of the total detergent composition.
4. A detergent composition according to claim 2 wherein said maltogenic alpha-amylase enzyme is present at a level of from about 0.001% to about 1% pure enzyme by weight of the total detergent composition.
5. A detergent composition according to claim 1 further comprising a starch-binding domain.
6. A detergent composition according to claim 5 wherein said starch-binding domain is present in or is added to said maltogenic alpha-amylase enzyme.
7. A detergent composition according to claim 1 wherein said nonionic surfactant is selected from the group consisting of polyethylene oxide condensates of alkyl alcohols, amide oxides, polyethylene oxide condensates of alkyl acids and mixtures thereof.
8. A detergent composition according to claim 1 wherein said bleaching agent is selected from the group consisting of Mn (5,12-dimethyl-1,5,8,12-tetraaza-bicyclo 6.6.2hexadecane)Cl2; Mn (5,12-diethyl-1,5,8,12-tetraaza-bicyclo 6.6.2 hexadecane); the combination of percarbonate with a bleach activator selected from nonanoyloxybenzene-sulfonate, phenolsulfonate ester of N-nonanoyl-6-aminocaproic acid, tetraacetylethylenediamine and mixtures thereof.
9. A detergent composition according to claim 1 wherein the protease is selected from the protease Subtilisin 309 from Bacillius subtilis, the Protease B variant with the substitution Y217L described in EP 251 446, the protease D variant with the substitution set N76DS 103AV104I; the protease described in WO9920727, WO9920726 and WO9920723 with the amino acid substitution set 101G103A104I159D232V236H245R248D252K and mixtures thereof.
10. A detergent composition according to claim 1 further comprising an enzyme selected from the group consisting of a lipase, an alpha-amylase, a cyclomaltodextrin transferase, an amyloglucosidase and mixtures thereof
11. Use of a maltogenic alpha-amylase enzyme and a detergent ingredient selected from the group consisting of a nonionic surfactant, a protease, a bleaching agent and mixtures thereof, in a detergent composition for the hydrolysis of retrograded andor raw starch.
12. Use according to claim 11 for the removal of starch-containing stains and soils, and upon formulation into a laundry composition, for excellent whiteness maintenance and dingy cleaning.

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 for cooling a combustion gas charge for combustion in an engine comprising:
providing a refrigerant compressor, a condenser, and an expansion valve in fluid communication with an evaporator, said evaporator receiving said combustion gas charge, said combustion gas charge comprising exhaust gas and compressed air, said exhaust gas and compressed air received separately by the evaporator;
wherein aid exhaust gas and compressed air are mixed in the evaporator;

circulating a refrigerant through said evaporator, wherein said refrigerant enters said evaporator in at least liquid form and exits said evaporator in a vapor form; and
directing said combustion gas charge through said evaporator, wherein said combustion gas charge has a higher mean temperature upon entering said evaporator than upon exiting said evaporator.
2. The method of claim 1 wherein said refrigerant comprises water and separating water vapor from said refrigerant.
3. The method of claim 2 further comprising delivering said water vapor to an engine radiator.
4. The method of claim 1 further comprising cooling said exhaust gas prior to directing said exhaust to said evaporator.
5. The method of claim 1 wherein said refrigerant comprises water at a pressure less than 760 mm Hg.
6. The method of claim 1 wherein said evaporator has an internal surface area greater than or equal to about 50 ft2.
7. The method of claim 1 wherein said refrigerant comprises a fluorocarbon compound.
8. The method of claim 1 wherein said refrigerant comprises an aqueous solution having a colligative agent.
9. A system for cooling a combustion gas charge for combustion in an engine comprising:
a refrigerant compressor, a condenser, and an expansion valve in fluid communication with an evaporator;
said evaporator receiving said combustion gas charge having a mean temperature T1, said combustion gas charge comprising exhaust gas and compressed air, said exhaust gas and compressed air received separately by the evaporator, wherein aid exhaust gas and compressed air are mixed in the evaporator; and discharging said combustion gas charge from said evaporator having a mean temperature T1, wherein T1> T2; and
said evaporator receiving and discharging a refrigerant, wherein said refrigerant enters said evaporator in at least liquid form and exits said evaporator in a vapor form.
10. The cooling system of claim 9 wherein said evaporator has an internal surface area greater than or equal to about 50 ft2.
11. The cooling system of claim 9 wherein said refrigerant comprises a fluorocarbon compound.
12. The cooling system of claim 9 wherein said refrigerant comprises water at a pressure less than 760 mm Hg.
13. The cooling system of claim 9 wherein said refrigerant comprises an aqueous solution having a colligative agent.
14. The cooling system of claim 9 wherein said compressed air is sourced from a turbocharger.
15. An internal combustion engine comprising:
a source of exhaust gas and a source of compressed air;
a system for cooling a combustion gas charge comprising:
a refrigerant compressor, a condenser, and an expansion valve in fluid communication with an evaporator;
said evaporator receiving said combustion gas charge having a mean temperature T1, said combustion gas charge comprising said exhaust gas and said compressed air (emphasis added), said exhaust gas and compressed air received separately by the evaporator; wherein aid exhaust qas and compressed air are mixed in the evaporator; and discharging said combustion gas charge from said evaporator having a mean temperature T2, wherein T1> T2; and
said evaporator receiving and discharging a refrigerant, wherein said refrigerant enters said evaporator in at least liquid form and exits said evaporator in a vapor form.
16. The engine of claim 15 wherein said evaporator has an internal surface area greater than or equal to about 50 ft2.
17. The engine of claim 15 wherein said refrigerant comprises a fluorocarbon compound.
18. The engine of claim 15 wherein said refrigerant comprises an aqueous solution having a colligative agent.
19. The engine of claim 15 wherein said refrigerant comprises water at a pressure less than 760 mm Hg.
20. The engine of claim 15 wherein said compressed air is sourced from a turbocharger.