CTNF 19/072,692 CTNF 85658 2454 Detailed Action Claims 1-20 are pending. Claims 1-20 are rejected. Double Patenting 08-33 AIA The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg , 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman , 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi , 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum , 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel , 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington , 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA/25, or PTO/AIA/26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp. 08-34 AIA Claim s 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim s 1-20 of US Patent No. 12,293,232 . Although the claims at issue are not identical, they are not patentably distinct from each other because the instant claims have a broader scope than corresponding to the patent system claims and it would have been obvious to one ordinary skill in the art before the effective filing date of the invention to omit the additional limitation in the patent claims to achieve the instant claimed limitation . Instant claims Patent claims 1. A system for tracking digital resources across multiple virtual reality computing environments, the system comprising: - a first computing platform including a first memory and one or more first computing processor devices in communication with the first memory, wherein the first memory stores a resource exchange event application executable by and configured to cause at least one of the one or more first computing processor devices to: - process resource exchange events, each resource exchange event conducted (i) by two or more users in a virtual reality computing environment that includes sub- environments, each of the sub-environments representing a corresponding entity , (ii) within one of the sub-environments, and (iii) between one of the users and the corresponding entity, wherein processing includes receiving digital resources from the user and tagging the digital resources with a tag that identifies at least a location of the resource exchange event; and - a second computing platform including a second memory and one or more second computing processor devices in communication with the second memory, wherein the second memory stores one or more machine-learning based algorithms executable by and configured to cause at least one of the one or more second computing devices to:- receive and analyze the tags to determine one or more resource exchange event movement patterns for digital resources. 1. A system for tracking digital resources across multiple virtual reality computing environments, the system comprising: - a first computing platform including a first memory and one or more first computing processor devices in communication with the first memory, wherein the first memory stores a virtual reality application executable by at least one of the one or more first computing processor devices and configured to: - present, to users, a virtual reality computing environment that includes sub- environments, each of the sub-environments representing a corresponding entity; a second computing platform including a second memory and one or more second computing processor devices in communication with the second memory, wherein the second memory stores a resource exchange event application executable by at least one of the one or more second computing processor devices and configured to: - process resource exchange events, each resource exchange event conducted (i) within one of the sub-environments, and (ii) between one of the users and the corresponding entity, wherein processing includes receiving digital resources from the user and tagging the digital resources with a tag that identifies at least a location of the resource exchange event; and - a third computing platform including a third memory and one or more third computing processor devices in communication with the third memory, wherein the third memory stores one or more machine-learning based algorithms executable by at least one of the one or more third computing devices and configured to:- receive and analyze the tags to determine one or more resource exchange event movement patterns for digital resources. 2. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to cause at least one of the one or more second computing processor devices to analyze the tags to determine the one or more resource exchange event movement patterns for the digital resources, wherein the one or more resource exchange event movement patterns include a resource exchange event movement pattern that provides for movement of digital resources across two or more virtual reality computing environments. 2. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to analyze the tags to determine the one or more resource exchange event movement patterns for the digital resources, wherein the one or more resource exchange event movement patterns include a resource exchange event movement pattern that provides for movement of digital resources across two or more virtual reality computing environments. 3. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to cause at least one of the one or more second computing processor devices to analyze the tags to determine the one or more resource exchange event movement patterns for the digital resources, wherein the one or more resource exchange event movement patterns include a resource exchange event movement pattern that provides for movement of digital resources into or out of a non-virtual computing environment. 3. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to analyze the tags to determine the one or more resource exchange event movement patterns for the digital resources, wherein the one or more resource exchange event movement patterns include a resource exchange event movement pattern that provides for movement of digital resources into or out of a non-virtual computing environment. 4. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to cause at least one of the one or more second computing processor devices to analyze the tags to determine the one or more resource exchange event movement patterns for the digital resources, wherein the one or more resource exchange event movement patterns include a resource exchange event movement pattern that provides for movement of the digital resources prior to the tagging of the digital resources. 4. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to analyze the tags to determine the one or more resource exchange event movement patterns for the digital resources, wherein the one or more resource exchange event movement patterns include a resource exchange event movement pattern that provides for movement of the digital resources prior to the tagging of the digital resources. 5. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to cause at least one of the one or more second computing processor devices to analyze the tags to determine the one or more resource exchange event movement patterns for the digital resources, wherein the one or more resource exchange movement patterns include resource exchange event movement patterns that are specific to at least one of (i) one of the users, (ii) a group of the users, and (iii) an entity represented by a sub-environment. 5. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to analyze the tags to determine the one or more resource exchange event movement patterns for the digital resources, wherein the one or more resource exchange movement patterns include resource exchange event movement patterns that are specific to at least one of (i) one of the users, (ii) a group of the users, and (iii) an entity represented by a sub-environment. 6. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to cause at least one of the one or more second computing processor devices to identify users or groups of users connected to the one or more resource exchange event movement patterns. 6. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to identify users or groups of users connected to the one or more resource exchange event movement patterns. 7. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to cause at least one of the one or more second computing processor devices to identify suspicious activity based on the one or more resource exchange event movement patterns and, in response to identifying suspicious activity, generate and communicate signals to the resource exchange event application that are configured to prevent at least one of (i) one of the users from conducting a subsequent resource exchange event, and (ii) specified digital resources being used to conduct a subsequent resource exchange event. 7. The system of Claim 1, wherein the one or more machine-learning based algorithms are further configured to identify suspicious activity based on the one or more resource exchange event movement patterns and, in response to identifying suspicious activity, generate and communicate signals to the resource exchange event application that are configured to prevent at least one of (i) one of the users from conducting a subsequent resource exchange event, and (ii) specified digital resources being used to conduct a subsequent resource exchange event. 8. The system of Claim 1, further comprising a plurality of distributed trust computing networks, each distributed trust computing network (i) associated with one or more of the entities represented by the sub-environments and (ii) comprising a plurality of decentralized nodes, each decentralized node having a third memory and one or more third computing processor devices in communication with the third memory, wherein the third memory of the decentralized nodes is configured to store at least one distributed ledger comprising a plurality of data blocks, wherein the plurality of data blocks store resource exchange event data including the tags. 8. The system of Claim 1, further comprising a plurality of distributed trust computing networks, each distributed trust computing network (i) associated with one or more of the entities represented by the sub-environments and (ii) comprising a plurality of decentralized nodes, each decentralized node having a fourth memory and one or more fourth computing processor devices in communication with the fourth memory, wherein the fourth memory of the decentralized nodes is configured to store at least one distributed ledger comprising a plurality of data blocks, wherein the plurality of data blocks store resource exchange event data including the tags. 9. The system of Claim 8, wherein a plurality of the entities represented by the sub- environments have access to the plurality distributed trust computing networks for purposes of accessing the tags and analyzing the tags with the one or more machine-learning based algorithms. 9. The system of Claim 8, wherein a plurality of the entities represented by the sub- environments have access to the plurality distributed trust computing networks for purposes of accessing the tags and analyzing the tags with the one or more machine-learning based algorithms. 10. The system of claim 1, wherein the first and the second computing platform are the same computing platform. See claim 1 Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAMZA N ALGIBHAH whose telephone number is (571)270-7212. The examiner can normally be reached on 7:30 am - 3:30 pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Umar Cheema can be reached on (571) 270-3037. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. 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If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /HAMZA N ALGIBHAH/Primary Examiner, Art Unit 2441 Application/Control Number: 19/072,692 Page 2 Art Unit: 2441 Application/Control Number: 19/072,692 Page 3 Art Unit: 2441 Application/Control Number: 19/072,692 Page 4 Art Unit: 2441 Application/Control Number: 19/072,692 Page 5 Art Unit: 2441 Application/Control Number: 19/072,692 Page 6 Art Unit: 2441 Application/Control Number: 19/072,692 Page 7 Art Unit: 2441 Application/Control Number: 19/072,692 Page 8 Art Unit: 2441 Application/Control Number: 19/072,692 Page 9 Art Unit: 2441 Application/Control Number: 19/072,692 Page 10 Art Unit: 2441 Application/Control Number: 19/072,692 Page 11 Art Unit: 2441 Application/Control Number: 19/072,692 Page 12 Art Unit: 2441 Application/Control Number: 19/072,692 Page 13 Art Unit: 2441 Application/Control Number: 19/072,692 Page 14 Art Unit: 2441 Application/Control Number: 19/072,692 Page 15 Art Unit: 2441 Application/Control Number: 19/072,692 Page 16 Art Unit: 2441 Application/Control Number: 19/072,692 Page 17 Art Unit: 2441 Application/Control Number: 19/072,692 Page 18 Art Unit: 2441 Application/Control Number: 19/072,692 Page 19 Art Unit: 2441 Application/Control Number: 19/072,692 Page 20 Art Unit: 2441
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