All The Claims

1. A process for recovering volatile compounds from an aqueous tea extract comprising:
providing a distillation assembly that contains less than 5 volume percent of non-condensable gases prior to commencing the distillation operation; wherein the distillation assembly is substantially free of air or any other non-condensable gas before commencing the distillation operation;
distilling said extract at not less than 0.7 bar absolute pressure by fractional distillation comprising
condensing of vapours,
separating the oil phase condensate from the aqueous phase and
refluxing the substantially oil-free aqueous phase;

wherein said fractional distillation is at near total reflux conditions.
2. A process as claimed in claim 1 wherein the distillation assembly is filled with steam before commencing the distillation operation.
3. A process as claimed in claim 1 wherein the distillation assembly comprises a reboiler, a distillation column, a condenser and a liquid-liquid separator wherein the volume ratio of the total feed to the reboiler to the total condensate hold up in the condensor and liquid-liquid separator at the conclusion of the distillation operation, is more than 100.
4. A process as claimed in claim 3 wherein said volume ratio is in the range of 100 to 2000.
5. A process as claimed in claim 1 wherein said distillation column has packings which provide a low hold up in the range of 10 to 20%.
6. A process as claimed in claim 1 wherein the ratio of the diameter of the condensate receiver to the diameter of the pipeline downsteam of it is in the range of 2 to 20.
7. A process as claimed in claim 1 comprising a relatively short packed column of 3 to 5 equilibrium stages.
8. A process as claimed in claim 1 wherein said condenser is a vertically mounted shell and tube condenser.
9. A process as claimed in claim 1 comprising distilling at a low boil-up rate in the range of 30 to 40% of flooding.

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 for determining influential andor popular participants in an online game network using messages exchanged among a group of participants, the method comprising:
representing the group of participants and the messages exchanged among participants on a game network server as nodes and links, respectively;
analyzing the messages to produce message relevant data for each node;
propagating the message relevant data of said each node out to other nodes in the network to propagate influence factors, which are graphically represented as link strengths, among neighboring nodes; and
repeating said propagating the message relevant data a sufficient number of times to spread the influence factors among neighboring nodes to produce a corresponding influence value for said each node,
wherein said influence value indicates relative size and strength of social activity or connections of a participant corresponding to said each node, and is determined by a combination of outbound influence factors to the neighboring nodes and inbound influence factors from the neighboring nodes, and
wherein a most influential andor popular participant is identified by a highest influence value;
wherein said analyzing the messages to produce message relevant data includes
selecting a friendship factor, a link strength factor, a message weight factor, for said each node,
wherein a starting weight for each factor is chosen in proportion to other factors including a total number of messages and message paths for said each node;
wherein said propagating said message relevant data includes:
designating said each node as a current node; and
selecting a weight and a message value for said each current node, and a link strength value for each link originating from said each current node;
wherein said propagating the message relevant data further comprises:
first increasing the weight of destination nodes by the product of the weight of said each current node, the friendship factor, the link strength factor, and the link strength value, for all links originating from said each current node;
second increasing the message value of said each current node by the link strength value, and the weight of said each current node by a first value, for all links whose destination is said each current node.
2. The method of claim 1, further comprising
ordering the group of participants by a plurality of influence values produced for the group of participants.
3. The method of claim 1, wherein said analyzing the messages includes:
recording chat messages; and
parsing the recorded chat messages to find said nodes and links.
4. The method of claim 1, wherein said first value is selected as a product of the message value of said each current node, the friendship factor, the message weight factor, and a number of links factor.
5. The method of claim 4, wherein said number of links factor is proportional to a number of links whose destination is said each current node.
6. The method of claim 1, wherein said first increasing the weight includes scaling the weight to prevent overflow and underflow.
7. The method of claim 1, wherein said repeating said propagating the message relevant data comprises:
repeating said first increasing and said second increasing with newly-updated weight and message value for said each node.
8. The method of claim 7, wherein said repeating said first increasing and said second increasing includes
repeating for a number of iterations equal to the square root of the total number of nodes in the network.
9. The method of claim 1, wherein a number associated with each factor of the outbound influence factors and the inbound influence factors represents a number of messages sent between said each node and the neighboring nodes.
10. The method of claim 1, wherein a number associated with each factor of the outbound influence factors and the inbound influence factors represents a combination of strength, quantity, and quality of messages sent between said each node and the neighboring nodes.
11. A system for determining influential andor popular participants in an online game network using messages exchanged among a group of participants, the system comprising a processor configured to execute:
a representation module, the representation module configured to represent the group of participants and the messages exchanged among the group of participants as nodes and links, respectively, wherein the group of participants exchange messages via a user interface of a computer system over the network;
a message data analysis module, the message data analysis module configured to analyze the messages exchanged over the network to produce message relevant data for each node, wherein each node is associated with a computer system representing a participant of the group of participants; and
a propagation module, the propagation module configured to propagate the message relevant data of said each node out to other nodes in the network to propagate influence factors, which are graphically represented as link strengths, among neighboring nodes, and to repeat the propagation of the message relevant data a sufficient number of times to spread the influence factors among neighboring nodes to produce an influence value for said each node,
wherein said influence value indicates relative size and strength of social activity or connections of a participant corresponding to said each node, and is determined by a combination of outbound influence factors to the neighboring nodes and inbound influence factors from the neighboring nodes, and
wherein a most influential andor popular participant is identified by a highest influence value;
wherein said message data analysis module includes a first selector to select a friendship factor, a link strength factor, a message weight factor, for said each node;
wherein said propagation module includes: a designating module to designate said each node as a current node; and a second selector to select a weight and a message value for said each current node, and a link strength value for each link originating from said each current node;
wherein said propagation module further comprises:
a first adjustment module to increase the weight of destination nodes by the product of the weight of said each current node, the friendship factor, the link strength factor, and the link strength value, for all links originating from said each current node; and
a second adjustment module to increase the message value of said each current node by the link strength value, and the weight of said each current node by a first value, for all links whose destination is said each current node,
wherein said first and second adjustment modules further operate to repeat the adjustment processes with newly-updated weight and message value for said each node.
12. The system of claim 11, the processor further configured to execute a participant ordering module, the participant ordering module configured to order the group of participants by a plurality of influences values produced for the group of participants.
13. The system of claim 11, wherein said message data analysis module includes:
a message recorder to record chat messages; and
a parsing module to parse the recorded chat messages to find said nodes and links.
14. The system of claim 11, wherein the adjustment processes are repeated for a number of iterations equal to the square root of the total number of nodes in the network.
15. The system of claim 11, wherein said first value is selected as a product of the message value of said each current node, the friendship factor, the message weight factor, and a number of links factor.
16. The system of claim 15, wherein said number of links factor is proportional to a number of links whose destination is said each current node.
17. The system of claim 11, wherein said first adjustment module includes a scaling module to scale the weight to prevent overflow and underflow.
18. A computer program, stored in a non-transmission computer-readable storage medium, for determining influential andor popular participants in an online game network using messages exchanged among a group of participants, the program comprising executable instructions that cause a computer to:
represent the group of participants and the messages exchanged among the group of participants as nodes and links, respectively;
analyze the messages to produce message relevant data for each node;
propagate said message relevant data of said each node out to other nodes in the network to propagate influence factors, which are graphically represented as link strengths, among neighboring nodes; and
repeat said propagating the message relevant data a sufficient number of times to spread the influence factors among neighboring nodes to produce an influence value for said each node,
wherein said influence value indicates relative size and strength of social activity or connections of a participant corresponding to said each node, and is determined by a combination of outbound influence factors to the neighboring nodes and inbound influence factors from the neighboring nodes, and
wherein a most influential andor popular participant is identified by a highest influence value;
wherein said analyzing the messages to produce message relevant data includes
selecting a friendship factor, a link strength factor, a message weight factor, for said each node;
wherein a starting weight for each factor is chosen in proportion to other factors including a total number of messages and message paths for said each node;
wherein said propagating said message relevant data includes:
designating said each node as a current node; and
selecting a weight and a message value for said each current node, and a link strength value for each link originating from said each current node;
wherein said propagating the message relevant data further comprises:
first increasing the weight of destination nodes by the product of the weight of said each current node, the friendship factor, the link strength factor, and the link strength value, for all links originating from said each current node;
second increasing the message value of said each current node by the link strength value, and the weight of said each current node by a first value, for all links whose destination is said each current node.
19. An apparatus for determining influential andor popular participants in an online game network using messages exchanged among a group of participants, comprising:
a processor including
means for representing the group of participants and the messages exchanged among the group of participants as nodes and links, respectively;
means for analyzing the messages to produce message relevant data for each node; and
means for propagating the message relevant data of said each node out to other nodes in the network to propagate influence factors, which are graphically represented as link strengths, among neighboring nodes, and to repeat the propagation of the message relevant data a sufficient number of times to spread the influence factors among neighboring nodes to produce an influence value for said each node,
wherein said influence value indicates relative size and strength of social activity or connections of a participant corresponding to said each node, and is determined by a combination of outbound influence factors to the neighboring nodes and inbound influence factors from the neighboring nodes, and
wherein a most influential andor popular participant is identified by a highest influence value;
wherein said analyzing the messages to produce message relevant data includes
selecting a friendship factor, a link strength factor, a message weight factor, for said each node,
wherein a starting weight for each factor is chosen in proportion to other factors including a total number of messages and message paths for said each node;
wherein said propagating said message relevant data includes:
designating said each node as a current node; and
selecting a weight and a message value for said each current node, and a link strength value for each link originating from said each current node;
wherein said propagating the message relevant data further comprises:
first increasing the weight of destination nodes by the product of the weight of said each current node, the friendship factor, the link strength factor, and the link strength value, for all links originating from said each current node;
second increasing the message value of said each current node by the link strength value, and the weight of said each current node by a first value, for all links whose destination is said each current node.

1-49. (canceled)
50. A method for making a medical device comprising:
applying an undercoat polymer to a substrate surface to form a polymeric undercoat layer;
treating the polymeric undercoat layer to reflow the undercoat polymer;
applying a top coat polymer to the undercoat layer to form a polymeric top coat layer.
51. The method of claim 50 wherein treating the undercoat layer to reflow the undercoat polymer causes formation of a conformable interface between the undercoat layer and the substrate surface.
52. The method of claim 50 wherein treating the undercoat layer to reflow the undercoat polymer comprises using a technique selected from the group consisting of thermal treatment, infrared treatment, microwave treatment, RF treatment, mechanical treatment and solvent treatment.
53. The method of claim 50 wherein treating the undercoat layer to reflow the undercoat polymer comprises heating the undercoat layer to at least about the melt flow temperature of the undercoat polymer for a time sufficient to reflow the polymer.
54. The method of claim 50 wherein treating the undercoat layer to reflow the undercoat polymer comprises heating the undercoat layer to at least about 200\xb0 C. for a time period sufficient to reflow the undercoat polymer.
55. The method of claim 50 wherein the undercoat polymer comprises a polyurethane.
56. The method of claim 50 wherein the substrate surface comprises a material selected from the group consisting of ceramic, glass, metal and a polymer.
57. The method of claim 50 wherein the top coat layer comprises an active agent.
58. The method of claim 50 wherein the top coat layer comprises an elutable active agent that elutes from the device at a slower rate and for a longer duration than the active agent elutes from a comparable device without the polymeric undercoat layer.
59. The method of claim 50 wherein the device is a stent.
60-75. (canceled)
76. A method for making a medical device comprising:
applying an polymer to a substrate surface to form a polymeric layer; and
treating the polymeric layer to reflow the polymer.
77. The method of claim 76 wherein treating the polymeric layer to reflow the polymer causes formation of a conformable interface between the polymeric layer and the substrate surface.
78. The method of claim 76 wherein treating the polymeric layer to reflow the polymer comprises using a technique selected from the group consisting of thermal treatment, infrared treatment, microwave treatment, RF treatment, mechanical treatment and solvent treatment.
79. The method of claim 76 wherein treating the polymeric layer to reflow the polymer comprises heating the polymeric layer to at least about the melt flow temperature of the polymer for a time sufficient to reflow the polymer.
80. (canceled)

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 seed of soybean variety OW1113014, wherein a representative sample of seed of said soybean variety OW1113014 has been deposited under ATCC Accession Number PTA-120160.
2. A soybean plant, or a part thereof, a representative sample of seed of said soybean plant variety OW1113014 has been deposited under ATCC Accession Number PTA-120160.
3. A soybean plant, comprising all the physiological and morphological characteristics of the soybean plant OW1113014, of claim 2.
4. A plant part of claim 2, wherein said part is pollen, root, seed, seed coat, cell, leaf, stem, anther, or an ovule.
5. A soybean plant obtained by transforming the soybean variety of claim 2.
6. A seed of the soybean plant according to claim 5.
7. A method for producing a soybean seed comprising crossing soybean plants and harvesting the resultant soybean seed, wherein at least one soybean plant is the soybean plant of claim 2.
8. An F1 soybean seed produced by the method of claim 7.
9. An F1 soybean seed produced by the method of claim 7 wherein at least one of the soybean plants carries a heritable transgenic event.
10. An F1 soybean plant, or part thereof, produced by growing said seed of claim 9.
11. A method for developing a second soybean plant through plant breeding comprising applying plant breeding to said soybean plant, or parts thereof according to claim 8, wherein said plant breeding results in development of said second soybean plant.
12. A method of producing a soybean plant comprising a desired trait, the method comprising introducing at least one transgene or locus conferring the desired trait into a plant of soybean variety OW1113014 according to claim 2.
13. An insect, disease or herbicide resistant plant produced by the method of claim 12, wherein the plant comprises all of the physiological and morphological characteristics of soybean cultivar OW1113014.
14. The method of claim 12, wherein the desired trait is selected from the group consisting of male sterility, herbicide tolerance, insect or pest resistance, disease resistance, fungal resistance, modified fatty acid metabolism, modified carbohydrate metabolism, drought tolerance, stress tolerance, and modified nutrient deficiency tolerances.
15. The method of claim 12, wherein the desired trait is herbicide tolerance and the tolerance is conferred to an herbicide selected from the group consisting of glyphosate, sulfonylurea, imidazolinone, dicamba, glufosinate, phosphinothricin, phenoxypropionic acid, cyclohexanedione, triazine, benzonitrile and bromoxynil.
16. A plant produced by the method of claim 12, wherein the plant has the desired trait, and wherein the plant comprises all of the physiological and morphological characteristics of soybean cultivar OW1113014.
17. A method of introducing a desired trait into a soybean variety derived from OW1113014, wherein the method comprises: (a) crossing a OW1113014 plant of claim 2 with a plant of another soybean variety that comprises the desired trait to produce new progeny plants, wherein the desired trait is selected from the group consisting of male sterility, herbicide resistance, disease resistance, insect resistance, modified fatty acid metabolism, modified carbohydrate metabolism, resistance to bacterial disease, resistance to fungal disease, and resistance to viral disease; (b) selecting one or more new progeny plants that have the desired trait to produce selected progeny plants; (c) selfing selected progeny plants or crossing the selected progeny plants with the OW1113014 plants to produce late generation selected progeny plants; (d) crossing or further selecting for later generation selected progeny plants that have the desired trait and physiological and morphological characteristics of soybean variety OW1113014 to produce selected next later generation progeny plants; and optionally (e) repeating crossing or selection of later generation progeny plants to produce progeny plants that comprise the desired trait and all of the physiological and morphological characteristics of soybean variety OW1113014 when grown in the same location and in the same environment.
18. A plant produced by the method of claim 17, wherein the plant has the desired trait.
19. A commodity plant product produced by a method comprising the steps of obtaining the plant of claim 2 or a part thereof and producing said commodity plant product wherein said commodity product comprises protein concentrate, protein isolate, soybean hulls, meal, or flour.
20. A seed that produces the plant of claim 16.