All The Claims

1. A vehicle cowl structure comprising:
a cowl main body section that extends along a vehicle width direction, that forms an S-shaped cross-section configured from an upper side curved portion curving so as to bulge out toward a vehicle front-rear direction front side and a lower side curved portion curving so as to bulge out toward a vehicle front-rear direction rear side, and in which an upper portion extending from the upper side curved portion toward the vehicle front-rear direction rear side is joined to a lower face of a lower end portion of a front windshield, and a lower portion is joined to a dash panel; and
a front side reinforcement member that curves to as to bulge out toward the vehicle front-rear direction front side, that is provided at the vehicle front-rear direction front side of the lower side curved portion of the cowl main body section, and in which an upper end portion is joined to a location between the upper side curved portion and the lower side curved portion, and a lower end portion is joined to a location between the lower side curved portion and the lower portion joined to the dash panel.
2. The vehicle cowl structure of claim 1, wherein:
sound absorbing material with thickness in the vehicle front-rear direction is provided at the vehicle front-rear direction rear side of the cowl main body section; and
an upper end portion of the sound absorbing material is disposed in contact with, or in close proximity to, the upper portion of the cowl main body section.
3. The vehicle cowl structure of claim 1, wherein
both vehicle width direction side end portions of the cowl main body section are joined to front pillars provided at vehicle width direction outside sections of the vehicle.
4. The vehicle cowl structure of claim 1, wherein:
a rear side reinforcement member that extends along the vehicle width direction and curves so as to bulge out toward the vehicle front-rear direction rear side is provided at the vehicle front-rear direction rear side of the lower side curved portion of the cowl main body section; and
the rear side reinforcement member is joined to the cowl main body section, and both vehicle width direction side end portions of the rear side reinforcement member are joined to the front pillars provided at both the vehicle width direction outside sections of the vehicle.

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. Multicrystalline melamine powder having the following properties:
specific surface area: 0.7-5 m2g
content of oxygen-containing components<0.7 wt. %
APHA colour less than 17
melam: higher than 1.5 wt. %
2. Multicrystalline melamine powder according to claim 1, characterised in that the specific surface area is between 0.9 and 3 m2g.
3. Multicrystalline melamine powder according to either one of claims 1-2, characterised in that the colour is lower than 15 APHA.
4. Multicrystalline melamine powder according to any one of claims 1-3, characterised in that the melam concentration is higher than 2.0 wt. %.
5. Multicrystalline melamine powder according to any one of claims 1-4, characterised in that the melam concentration is higher than 2.5 wt. %.
6. Multicrystalline melamine powder according to claim 5, characterised in that the content of oxygen-containing components is below 0.4 wt. %.
7. Multicrystalline melamine powder according to any one of claims 1-6, characterised in that the ARC content is less than 0.15 wt. %.
8. Amino-formaldehyde resin comprising multicrystalline melamine with a melam content higher than 1.5 wt. %.
9. Multicrystalline melamine powder and amino-formaldehyde resin as substantially described with reference to the description and the Examples.

1. A structure comprising: a nitridated material, wherein the nitridated material has the characteristic of capturing CO2, wherein the nitridated material has a surface selected from: a nitridated silica material, a nitridated metal oxide material surface, or a nitridated non-metal oxide material, wherein the nitridated material is formed through cyclic chlorination and ammoniation of a material to densify NH2 groups on the material surface, wherein cyclic chlorination and ammoniation includes dehydroxilation of the material followed by chlorination with thionyl chloride and ammonia adsorption and subjecting the ammoniated trichlorosilylated material to another exposure to trichlorosilylation ammoniation to form a surface having a network of surface \u2014Si(NH)2\u2014(NH)\u2014Si\u2014(HN2)2 or 3.
2. The structure of claim 1, wherein the nitridated silica material has a plurality of silicon-amine groups.
3. The structure of claim 1, wherein the nitridated metal oxide material has a plurality of metal oxide-amine groups.
4. The structure of claim 1, wherein the nitridated non-metal oxide material has a plurality of non-metal oxide-amine groups.
5. The structure of claim 1, wherein the nitridated material has a structure selected from: a porous structure, a non-porous structure, an amorphous structure, and a crystalline structure.

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 computer-implemented method of generating a natural language spoken dialog system, the method comprising:
at each turn in a dialog, nominating a set of allowed dialog actions and a set of contextual features;
selecting an optimal action from the set of nominated allowed dialog actions using a machine learning algorithm; and
generating a response based on the selected optimal action at each turn in the dialog.
2. The method of claim 1, wherein the machine learning algorithm uses reinforcement learning.
3. The method of claim 1, wherein the machine learning algorithm is partially observable Markov decision process (POMDP) based.
4. The method of claim 1, wherein the set of nominated allowed dialog actions incorporates a set of business rules.
5. The method of claim 4, wherein prompt wordings in the generated natural language spoken dialog system are tailored to a current context while following the set of business rules.
6. The method of claim 1, wherein a compression label represents at least one of the nominated allowed dialog actions.
7. A system for generating a natural language spoken dialog system, the system comprising:
a processor;
a module configured to control the processor to nominate allowed dialog actions and a set of contextual features at each turn of a dialog;
a module configured to control the processor to select an optimal action from the set of nominated allowed dialog actions at each dialog turn based on machine learning algorithm; and
a module configured to control the processor to generate a response based on the selected optimal action at each turn in the dialog.
8. The system of claim 7, wherein the system uses reinforcement learning.
9. The system of claim 7, wherein the system is partially observable Markov decision process (POMDP) based.
10. The system of claim 7, wherein the set of manually nominated allowed dialog actions incorporates a set of business rules.
11. The system of claim 10, wherein prompt wordings in the generated natural language spoken dialog system are tailored to a current context while following the set of business rules.
12. The system of claim 7, wherein a compression label represents at least one of the manually nominated allowed dialog actions.
13. A tangible computer-readable storage medium storing a computer program having instructions for controlling a processor to generate a natural language spoken dialog system, the instructions comprising:
nominating allowed dialog actions and a set of contextual features at each turn of a dialog;
selecting an optimal action from the set of manually nominated allowed dialog actions at each turn of a dialog based on machine learning algorithm; and
generating a spoken dialog system based on a process of selecting optimal actions at each dialog turn.
14. The tangible computer-readable storage medium of claim 13, wherein the machine learning algorithm uses reinforcement learning.
15. The tangible computer-readable storage medium of claim 13, wherein the machine learning algorithm is partially observable Markov decision process (POMDP) based.
16. The tangible computer-readable storage medium of claim 13, wherein the set of manually nominated allowed dialog actions incorporates a set of business rules.
17. The tangible computer-readable storage medium of claim 16, wherein prompt wordings in the generated natural language spoken dialog system are tailored to a current context while following the set of business rules.