CTNF 18/779,998 CTNF 86601 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Response to continuation request The request for a continuation is acknowledged. For a continuation to be applied as per the MPEP, the application discloses and claims only subject matter disclosed in prior Applications, and names the inventor or at least one joint inventor named in the prior application. Accordingly, this application may constitute a continuation or divisional. Should applicant desire to claim the benefit of the filing date of the prior application, attention is directed to 35 U.S.C. 120, 37 CFR 1.78, and MPEP § 211 et seq. Filed IDS of 07/22/2024 has been entered and considered. Claims 1-20 are currently pending. Please refer to the action below. Examiner Notes The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. However, the claimed subject matter, not the specification, is the measure of the invention. The claimed computer readable media of claim 1 (“ Emphasis Added” as cited in the specification, page 2, [0043] “As defined herein, computer-readable media does not include transitory media, such as modulated data signals and carrier waves, and/or signals”) is read as a non-transitory medium. 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 §§ 706.02(l)(1) - 706.02(l)(3) 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. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp. Claims 1, 11, and 16 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1, 11, and 16 of US Patent 11687318. Instant Application 18779998 (“9998”) Allowed Patent US 11687318 (“7318”) 1. A system, comprising: a processor; a display screen operably connected to the processor; and a computer-readable media storing instructions which, when executed by processor, cause the processor to: display, via the display screen, a first portion of a user interface; receive, while the first portion is being displayed, information indicative of an audio input; determine, by providing, as an input, at least a portion of the audio input to a machine learning (ML) model, a confidence level associated with a label, the confidence level being indicative of a degree to which the label corresponds to the input; identify, based on the label, a second portion of the user interface; determine that the confidence level is higher than a threshold; and present, via the display screen and based on determining that the confidence level is higher than the threshold, the second portion of the user interface. 11. A method comprising: displaying, by a processor and via a display operably connected to the processor, a first portion of a user interface; receiving, by the processor and while the first portion is being displayed, information indicative of an audio input; determining, by the processor and based on inputting at least a portion of the audio input to a machine learning (ML) model, a confidence level associated with a label, the confidence level being indicative of a degree to which the label corresponds to the input; identifying, by the processor and based on the label, a second portion of the user interface; determining, by the processor, that the confidence level is higher than a threshold; and based on determining that the confidence level is higher than the threshold, presenting, by the processor and via the display, the second portion of the user interface. 16. A device, comprising: a processor; a display operably connected to the processor; a microphone operably connected to the processor; and a memory coupled to the processor, the memory storing instructions executable by the processor to perform operations comprising: displaying, via the display, a first portion of a user interface; receiving, while the first portion is being displayed, information indicative of an audio input; determining, based on inputting at least a portion of the audio input to a machine learning (ML) model, a confidence level associated with a label, the confidence level being indicative of a degree to which the label corresponds to the input; identifying, based on the label, a second portion of the user interface; determining that the confidence level is higher than a threshold; and based on determining that the confidence level is higher than the threshold, presenting, via the display, the second portion of the user interface. 1. A method of providing a user interface on a device, the user interface having at least a first display portion, a second display portion and a third display portion, the second display portion including a link to the third display portion that, when activated by a user, cause the device to present the third display portion of the user interface, the first display portion not including the link to the third display portion, the method comprising: causing the first display portion to be presented on a display of the device; receiving audible input while the first display portion is being displayed; determining one or more labels that match an utterance in the audible input; processing the one or more labels to determine a confidence level, the confidence level indicating a degree to which a label of the one or more labels corresponds to the utterance; and based at least in part on the confidence level, determining that the third display portion corresponds to the utterance in the audible input and causing the third display portion to be presented on the display. 11. One or more computer-readable media storing instructions that, when executed by one or more processors of a device, configure the device to provide a user interface on the device, the user interface having at least a first display portion, a second display portion and a third display portion, the second display portion including a link to the third display portion that, when activated by a user, cause the device to present the third display portion of the user interface, the first display portion not including the link to the third display portion, the instructions configuring the device to perform operations including: causing the first display portion to be presented on a display of the device; receiving audible input while the first display portion is being displayed; determining one or more labels that match an utterance in the audible input; processing the one or more labels to determine a confidence level, the confidence level indicating a degree to which a label of the one or more labels corresponds to the utterance; and based at least in part on the confidence level, determining that the third display portion corresponds to the utterance in the audible input and causing the third display portion to be presented on the display. 16. A device, comprising: one or more processors; and memory coupled to the one or more processors, the memory storing instructions executable by the one or more processors to perform operations to configure the device to provide a user interface on the device, the user interface having at least a first display portion, a second display portion and a third display portion, the second display portion including a link to the third display portion that, when activated by a user, cause the device to present the third display portion of the user interface, the first display portion not including the link to the third display portion, the operations comprising: causing the first display portion to be presented on a display of the device; receiving audible input while the first display portion is being displayed; determining one or more labels that match an utterance in the audible input; processing the one or more labels to determine a confidence level, the confidence level indicating a degree to which a label of the one or more labels corresponds to the utterance; and based at least in part on the confidence level, determining that the third display portion corresponds to the utterance in the audible input and causing the third display portion to be presented on the display. Regarding Instant independent claims 1, 11, and 16 corresponding respectively to at least claims 1, and 16 of the Co-Pending Application “7318”: Although the claims at issue are not identical, they are not patentably distinct from each other. As claim 16 of “7318” encompasses all the teachings of the instant claims 1 and 16, similarly to claim 1 of “7318” encompasses all the teachings of the instant claim 11, except for citing specifically “receiving, while the first portion is being displayed, information indicative of an audio input; determining, based on inputting at least a portion of the audio input to a machine learning (ML) model, a confidence level associated with a label, the confidence level being indicative of a degree to which the label corresponds to the input; identifying, based on the label, a second portion of the user interface; determining that the confidence level is higher than a threshold; and based on determining that the confidence level is higher than the threshold, presenting, via the display, the second portion of the user interface” Vs “ providing a user interface on a device, the user interface having at least a first display portion, a second display portion and a third display portion, the second display portion including a link to the third display portion that, when activated by a user, cause the device to present the third display portion of the user interface, the first display portion not including the link to the third display portion, the method comprising: causing the first display portion to be presented on a display of the device; receiving audible input while the first display portion is being displayed; determining one or more labels that match an utterance in the audible input; processing the one or more labels to determine a confidence level, the confidence level indicating a degree to which a label of the one or more labels corresponds to the utterance; and based at least in part on the confidence level, determining that the third display portion corresponds to the utterance in the audible input and causing the third display portion to be presented on the display”. Thus, the invention of claims 1, 11, and 16 of the reference Patent “7318” is in effect a “species” of the “generic” invention of the instant application claims 1. 11, and 16, respectively. It has been held that the generic invention is “anticipated” by the “species”. See In re Goodman, 29 USPQ2d 2010 (Fed. Cir. 1993). Since instant application claims 1, 11, and 16 are at least anticipated and obvious by either claims 1, 11, or 16 of the reference patent, respectively, they are not patentably distinct from claims 1, 11, and 16 of the reference patent. As one skill in the art would further appreciate that known learning or neural network methods/systems may be employed to cause the user interface, based on the received input user audible while the first display portion is being displayed, to provide a second or more display portion other than the first display portion according to determined one or more labels that match an utterance in the audible input as said one or more labels understoodly correspond to a confidence level indicating a degree to which a label of the one or more labels corresponds to the utterance to cause said user interface to display the requested display link presented on the display, according to known methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F). This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented. Dependent claims 2-10, 12-15, and 17-20 are also rejected as they failed to solve the above problem. Accordingly, the claimed subject matter of this application as currently claimed is unpatentable under the provisions of the nonstatutory obviousness-type double patenting rejection. Therefore, those claims are rejected as best understood by examiner as indicated in this office action above. Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 07-20-aia AIA The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 1, 11, and 16 is/are further rejected under 35 U.S.C. 103 as obvious over Isaacson et al. (US 20190306137, A1) in view of Abuelsaad et al. (US 11868678, A1). Regarding claim 1, Isaacson teaches a system (para. 0049-0057 teaches a system configured to present a user interface comprising at least a first display portion which the user interacts with, the system is further to cause the display device to present another display portion based on processed user request of further para. 0149-0152 received via the first display portion) comprising: a processor (para. 0015); a display screen operably connected to the processor (cited display user interface of further para. 0049-0057 further supported by 0149-0152 displaying at least an implied main menu first display portion); and a computer-readable media (para. 0015) storing instructions which, when executed by processor, cause the processor to: display, via the display screen, a first portion of a user interface (display first portion of at least Figs. 2-3); receive, while the first portion is being displayed, information indicative of an audio input (received user dialog further in para. 0033, 0149-0152 and 0182 while the first portion is being displayed, including query information indicative in a case of cited speech/voice input for linking to an offered service); determine, by providing, as an input, at least a portion of the audio input to a machine learning (ML) model, a confidence level associated with a label , the confidence level being indicative of a degree to which the label corresponds to the input (processing further in at least para. 0033, 0149-0152 voice user link request such as by providing, as an input, at least one of a portion or the entire portion of the audio input to a known natural language model such as obviously said learning (ML) model of at least para. 0694 to determine as illustrated further in at least para. 0182 a confidence level associated with known learned label or requested displayed options of Figs. 2-4, the confidence level being indicative of a degree to which the known learned label or learned requested displayed options corresponds to the input); identify, based on the label , a second portion of the user interface (the system may identify at least in para. 0033, 0182 and 0239-0240 and Figs. 2-3 a second linking portion of the user interface associated with known or implied learned label or requested displayed options of Figs. 2-4 and para. 0033 and 0182); determine that the confidence level is higher than a threshold (the system further in at least para. 0182 may determine that “….may have a confidence score of 95% that the user wants a silver iPhone 5S” which confidence value further indicative of said confidence level is higher than a threshold); and present, via the display screen and based on determining that the confidence level is higher than the threshold, the second portion of the user interface (and to cause presenting as indicated further in at least para. 0182 and Figs. 3-4, via the display screen and based on determining that the confidence level is 95 % higher than the threshold, a second display portion of the user interface). Isaacson is silent regarding the above lined-out except for said determine, by providing, as an input, at least a portion of the audio input to a machine learning (ML) model, said confidence level associated with a label, said confidence level being indicative of a degree to which the label corresponds to the input and identify, based on the label, said second portion of the user interface. Abuelsaad teaches at least in Figs. 3-4 and Col. 12, lines 15-67 further supported by Col. 5-6 and example 5 of Cols. 15-16 methods and systems for, mapping received audio input via a presented user interface screen corresponding to specific selected and displayed browsing domain portion of the user interface, using a machine learning model, and adapted to identifying based on a confidence threshold score whether a requested browsing domain portion of the user interface corresponds to the received audio input, said confidence level being further indicative of a degree to which a signature label corresponds to the input and capable of presenting, via the display presentation screen and based on determining that the confidence level is higher than the threshold, corresponding second browsing portion according to the received audio input. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Isaacson in view of Abuelsaad to include wherein determine, by providing, as an input, at least a portion of the audio input to a machine learning (ML) model, said confidence level associated with a label, said confidence level being indicative of a degree to which the label corresponds to the input and identify, based on the label, said second portion of the user interface, as discussed above, as Isaacson in view of Abuelsaad are in the same of endeavor employing methods and systems for presenting a requested second display portion via the display screen while a first portion is being displayed, according to received user audio input instruction, Abuelsaad’s combination of using a machine learning system to map received user audio inputs instruction to specific display link/browsing portion further complements the methods and systems of Isaacson for presenting a requested second display portion via the display screen while a first portion is being displayed, according to received user audio input instruction, in a sense that when combined with the machine learning system of Abuelsaad enables the methods and systems of Isaacson for accurately mapping user input audio data to specific display links of a user interface, the mapping further advantageously allow accurately learned audio input labels associated with specific display links further allowing the system to properly detect and identify one or more targeted second display link portion while a first portion is being displayed, according to further known methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F). Regarding claim 11, Isaacson teaches a method of at least para. 0049-0057 and 0154 comprising: displaying, by a processor and via a display operably connected to the processor, a first portion of a user interface (para. 0015 teaches at least a processor configured to display of at least Figs. 2-3 via a display operably connected to the processor of device 106, a first portion of a user interface); receiving, by the processor and while the first portion is being displayed, information indicative of an audio input (received user dialog further in para. 0033, 0149-0152 and 0182 while the first portion is being displayed, including query information indicative in a case of cited speech/voice input for linking to an offered service); determining, by the processor and based on inputting at least a portion of the audio input to a machine learning (ML) model, a confidence level associated with a label , the confidence level being indicative of a degree to which the label corresponds to the input (processing further in at least para. 0033, 0149-0152 voice user link request such as by providing, as an input, at least one of a portion or the entire portion of the audio input to a known natural language model such as obviously said learning (ML) model of at least para. 0694 to determine as illustrated further in at least para. 0182 a confidence level associated with known learned label or requested displayed options of Figs. 2-4, the confidence level being indicative of a degree to which the known learned label or learned requested displayed options corresponds to the input); identifying, by the processor and based on the label , a second portion of the user interface (the system may identify at least in para. 0033, 0182 and 0239-0240 and Figs. 2-3 a second linking portion of the user interface associated with known or implied learned label or requested displayed options of Figs. 2-4 and para. 0033 and 0182); determining, by the processor, that the confidence level is higher than a threshold (the system further in at least para. 0182 may determine that “….may have a confidence score of 95% that the user wants a silver iPhone 5S” which confidence value further indicative of said confidence level is higher than a threshold); and based on determining that the confidence level is higher than the threshold, presenting, by the processor and via the display, the second portion of the user interface (and to cause presenting as indicated further in at least para. 0182 and Figs. 3-4, via the display screen and based on determining that the confidence level is 95 % higher than the threshold, a second display portion of the user interface). Isaacson is silent regarding the above lined-out except for said determining, by providing, as an input, at least a portion of the audio input to a machine learning (ML) model, said confidence level associated with a label, said confidence level being indicative of a degree to which the label corresponds to the input and identify, based on the label, said second portion of the user interface. Abuelsaad teaches at least in Figs. 3-4 and Col. 12, lines 15-67 further supported by Col. 5-6 and example 5 of Cols. 15-16 methods and systems for, mapping received audio input via a presented user interface screen corresponding to specific selected and displayed browsing domain portion of the user interface, using a machine learning model, and adapted to identifying based on a confidence threshold score whether a requested browsing domain portion of the user interface corresponds to the received audio input, said confidence level being further indicative of a degree to which a signature label corresponds to the input and capable of presenting, via the display presentation screen and based on determining that the confidence level is higher than the threshold, corresponding second browsing portion according to the received audio input. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Isaacson in view of Abuelsaad to include wherein determine, by providing, as an input, at least a portion of the audio input to a machine learning (ML) model, said confidence level associated with a label, said confidence level being indicative of a degree to which the label corresponds to the input and identify, based on the label, said second portion of the user interface, as discussed above, as Isaacson in view of Abuelsaad are in the same of endeavor employing methods and systems for presenting a requested second display portion via the display screen while a first portion is being displayed, according to received user audio input instruction, Abuelsaad’s combination of using a machine learning system to map received user audio inputs instruction to specific display link/browsing portion further complements the methods and systems of Isaacson for presenting a requested second display portion via the display screen while a first portion is being displayed, according to received user audio input instruction, in a sense that when combined with the machine learning system of Abuelsaad enables the methods and systems of Isaacson for accurately mapping user input audio data to specific display links of a user interface, the mapping further advantageously allow accurately learned audio input labels associated with specific display links further allowing the system to properly detect and identify one or more targeted second display link portion while a first portion is being displayed, according to further known methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F). Regarding claim 16, Isaacson teaches in at least Figs. 1-3 and para. 0154 a device 106, comprising: a processor (para. 0015); a display operably connected to the processor (the display of at least Figs. 2-4); and a microphone operably connected to the processor (a microphone of at least para. 0222); and a memory coupled to the processor (para. 0015) the memory storing instructions executable by the processor to perform operations comprising: displaying, via the display, a first portion of a user interface (displaying further in at least Figs. 2-4 via the display, a first portion of a user interface in a case before receiving a user audio input); receiving, while the first portion is being displayed, information indicative of an audio input (received user dialog further in para. 0033, 0149-0152 and 0182 while the first portion is being displayed, including query information indicative in a case of cited speech/voice input for linking to an offered service); determining, based on inputting at least a portion of the audio input to a machine learning (ML) model, a confidence level associated with a label , the confidence level being indicative of a degree to which the label corresponds to the input (processing further in at least para. 0033, 0149-0152 voice user link request such as by providing, as an input, at least one of a portion or the entire portion of the audio input to a known natural language model such as obviously said learning (ML) model of at least para. 0694 to determine as illustrated further in at least para. 0182 a confidence level associated with known learned label or requested displayed options of Figs. 2-4, the confidence level being indicative of a degree to which the known learned label or learned requested displayed options corresponds to the input); identifying, based on the label , a second portion of the user interface (the system may identify at least in para. 0033, 0182 and 0239-0240 and Figs. 2-3 a second linking portion of the user interface associated with known or implied learned label or requested displayed options of Figs. 2-4 and para. 0033 and 0182); determining that the confidence level is higher than a threshold (the system further in at least para. 0182 may determine that “….may have a confidence score of 95% that the user wants a silver iPhone 5S” which confidence value further indicative of said confidence level is higher than a threshold); and based on determining that the confidence level is higher than the threshold, presenting, via the display, the second portion of the user interface (and to cause presenting as indicated further in at least para. 0182 and Figs. 3-4, via the display screen and based on determining that the confidence level is 95 % higher than the threshold, a second display portion of the user interface). Isaacson is silent regarding the above lined-out except for said determining, by providing, as an input, at least a portion of the audio input to a machine learning (ML) model, said confidence level associated with a label, said confidence level being indicative of a degree to which the label corresponds to the input and identify, based on the label, said second portion of the user interface. Abuelsaad teaches at least in Figs. 3-4 and Col. 12, lines 15-67 further supported by Col. 5-6 and example 5 of Cols. 15-16 methods and systems for, mapping received audio input via a presented user interface screen corresponding to specific selected and displayed browsing domain portion of the user interface, using a machine learning model, and adapted to identifying based on a confidence threshold score whether a requested browsing domain portion of the user interface corresponds to the received audio input, said confidence level being further indicative of a degree to which a signature label corresponds to the input and capable of presenting, via the display presentation screen and based on determining that the confidence level is higher than the threshold, corresponding second browsing portion according to the received audio input. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Isaacson in view of Abuelsaad to include wherein determine, by providing, as an input, at least a portion of the audio input to a machine learning (ML) model, said confidence level associated with a label, said confidence level being indicative of a degree to which the label corresponds to the input and identify, based on the label, said second portion of the user interface, as discussed above, as Isaacson in view of Abuelsaad are in the same of endeavor employing methods and systems for presenting a requested second display portion via the display screen while a first portion is being displayed, according to received user audio input instruction, Abuelsaad’s combination of using a machine learning system to map received user audio inputs instruction to specific display link/browsing portion further complements the methods and systems of Isaacson for presenting a requested second display portion via the display screen while a first portion is being displayed, according to received user audio input instruction, in a sense that when combined with the machine learning system of Abuelsaad enables the methods and systems of Isaacson for accurately mapping user input audio data to specific display links of a user interface, the mapping further advantageously allow accurately learned audio input labels associated with specific display links further allowing the system to properly detect and identify one or more targeted second display link portion while a first portion is being displayed, according to further known methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARCELLUS AUGUSTIN whose telephone number is (571)270-3384. The examiner can normally be reached 9 AM- 5 PM. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, BENNY TIEU can be reached at 571-272-7490. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /MARCELLUS J AUGUSTIN/Primary Examiner, Art Unit 2682 04/27/2026 Application/Control Number: 18/779,998 Page 2 Art Unit: 2682 Application/Control Number: 18/779,998 Page 3 Art Unit: 2682 Application/Control Number: 18/779,998 Page 4 Art Unit: 2682 Application/Control Number: 18/779,998 Page 6 Art Unit: 2682 Application/Control Number: 18/779,998 Page 7 Art Unit: 2682 Application/Control Number: 18/779,998 Page 8 Art Unit: 2682 Application/Control Number: 18/779,998 Page 9 Art Unit: 2682 Application/Control Number: 18/779,998 Page 10 Art Unit: 2682 Application/Control Number: 18/779,998 Page 11 Art Unit: 2682 Application/Control Number: 18/779,998 Page 12 Art Unit: 2682 Application/Control Number: 18/779,998 Page 13 Art Unit: 2682 Application/Control Number: 18/779,998 Page 14 Art Unit: 2682 Application/Control Number: 18/779,998 Page 15 Art Unit: 2682 Application/Control Number: 18/779,998 Page 16 Art Unit: 2682 Application/Control Number: 18/779,998 Page 17 Art Unit: 2682 Application/Control Number: 18/779,998 Page 18 Art Unit: 2682 Application/Control Number: 18/779,998 Page 19 Art Unit: 2682 Application/Control Number: 18/779,998 Page 20 Art Unit: 2682 Application/Control Number: 18/779,998 Page 21 Art Unit: 2682 Application/Control Number: 18/779,998 Page 22 Art Unit: 2682 Application/Control Number: 18/779,998 Page 23 Art Unit: 2682 Application/Control Number: 18/779,998 Page 24 Art Unit: 2682 Application/Control Number: 18/779,998 Page 25 Art Unit: 2682 Application/Control Number: 18/779,998 Page 26 Art Unit: 2682 Application/Control Number: 18/779,998 Page 27 Art Unit: 2682 Application/Control Number: 18/779,998 Page 28 Art Unit: 2682 Application/Control Number: 18/779,998 Page 29 Art Unit: 2682 Application/Control Number: 18/779,998 Page 30 Art Unit: 2682 Application/Control Number: 18/779,998 Page 31 Art Unit: 2682 Application/Control Number: 18/779,998 Page 32 Art Unit: 2682
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