CTFR 19/012,648 CTFR 93093 DETAILED ACTION 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. Applicant(s) Response to Official Action The response filed on 04/27/2026 has been entered and made of record. Response to Arguments/Amendments Presented arguments have been fully considered, but are rendered moot in view of the new ground(s) of rejection necessitated by amendment(s) initiated by the applicant(s). Claim Rejections - 35 USC § 112 07-30-02 AIA The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. 07-34-01 AIA Claim 9 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention. Claim 9 recites the limitation: "… modified by another generative AI process … modified by the other generative AI process." (emphasis added to accentuate insufficient antecedent basis). The phrasing of “the other” generative AI process lacks clarity, since only one instance of the “generative AI process” was mentioned previously. For the purposes of examination, the limitation is interpreted as the following: “… modified by another generative AI process … modified by the other the generative AI process.” Claim Rejections - 35 USC § 103 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. 07-21-aia AIA Claim s 1-2 , 4-7 , 9-13 , 21-24 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al., hereinafter referred to as Wang (US 2018/0278964 A1) in view of Hannuksela et al., hereinafter referred to as Hannuksela (WO 2024/134557 A1) in further view of Chen et al., hereinafter referred to as Chen (WO 2024/020603 A2) . As per claim 1 , Wang discloses a method of processing a video bitstream (Wang: Abstract) , the method comprising: receiving the video bitstream comprising (i) one of a picture and a video and (ii) a neural- network supplemental enhancement information (SEI) message including instructions for a generative artificial intelligence (Al) process, the generative AI process including a neural-network post-filtering process, the neural-network SEI message being associated with the one of the picture and the video (Wang: Paras. [0019], [0081], [0091] disclose receiving an encoded video bitstream comprising VCL NAL units (picture/video) and SEI NAL units (supplemental enhancement information messages) associated with the video data; Wang: Para. [0093] & Table 1 disclose a “post_filter_hint [claimed post-filtering process]”.) , the neural-network SEI message including text data purposed for use with the generative AI process (Wang: Paras. [0054], [0093], [0159] disclose that SEI messages can carry text data such as subtitling, captioning, or user data unregistered for private use.) ; and extracting the text data from the neural-network SEI message (Wang: Para. [0247] discloses decoder can parse essential information carrying SEI messages.) , wherein the text data includes a text string prompt that is input to the neural-network post-filtering process . However, Wang does not explicitly disclose “… a neural-network supplemental enhancement information (SEI) message […] for a generative artificial intelligence (Al) process […] the generative AI process including a neural-network post-filtering process, the neural-network SEI message being associated […] the neural-network SEI message […] purposed for use with the generative AI process; and […] data from the neural-network SEI message […] the text data includes a text string prompt that is input to the neural-network post-filtering process.”. Further, Hannuksela is in the same field of endeavor and teaches a neural-network supplemental enhancement information (SEI) message for a generative artificial intelligence (Al) process (Hannuksela: Para. [00161] discloses “The neural-network post-filter characteristics (NNPFC) SEI message and the neural-network post-filter activation (NNPFA) SEI message [claimed neural-network supplemental enhancement information (SEI) message]” and Hannuksela: Para. [00231] discloses “SEI message … uses a generative neural network [claimed for a generative artificial intelligence (Al) process]”..) ; the generative AI process including a neural-network post-filtering process (Hannuksela: Para. [00165] discloses “specifies the neural-network post-processing filter [claimed neural-network post-filtering process]”.) , the neural-network SEI message being associated with the one of the picture and the video (Hannuksela: Para. [00231] discloses “SEI message may comprise, but may not be limited to, one or more of the following: An indication … be present in the video [associated with the one of the picture and the video]”.) , the neural-network SEI message purposed for use with the generative AI process (Hannuksela: Para. [00231] discloses “SEI message may comprise, but may not be limited to, one or more of the following: An indication … be present in the video … An indication that the video … uses a generative neural network [claimed purposed for use with the generative AI process]”.) ; data from the neural-network SEI message that is input to the neural-network post-filtering process (Hannuksela: Para. [00243] discloses “The SEI message payload of one or more NNPFC SEI messages may be included in a machine consumption indication SEI message and define the post-filter”.) . Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, and having the teachings of Wang and Hannuksela before him or her, to modify the video coding system of Wang to include the neural-network SEI message and neural-network post-processing filter feature as described in Hannuksela. The motivation for doing so would have been to improve machine analysis precision in video coding systems by providing a standardized bitstream signaling mechanism to identify advanced neural-network post-processing pipeline operations. However, Wang-Hannuksela do not explicitly disclose “… the text data includes a text string prompt that is input to the neural-network post-filtering process.” Furthermore, Chen is in the same field of endeavor and teaches the text data includes a text string prompt that is input to the neural-network post-filtering process (Chen: Paras. [0005], [0075], [0086] disclose using commentaries [text] as an information source for a system that automatically converts the text into embedded visualizations using NLP and computer vision models (a generative AI process). For example, Chen: Para. [0096] discloses “Suppose the input text is “Nole crosscourt with a sharp angle. He is brilliant!” [claimed wherein the text data includes a text string prompt]” and Chen: Para. [0106] discloses taking “a piece of text, a video clip, and sports data extracted from the video clip as the input [claimed that is input to the neural-network post-filtering process]”).) . Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, and having the teachings of Wang-Hannuksela and Chen before him or her, to modify the SEI messaging neural-network post-filtering process of Wang-Hannuksela to include the text string prompts feature as described in Chen. The motivation for doing so would have been to improve user viewing experience by providing a configuration that enables generative content to be transmitted alongside video content in a standardized bitstream format, ensuring the receiving device has the necessary data to perform the augmentation/visualization. As per claim 2 , Wang-Hannuksela-Chen disclose the method of claim 1, wherein after the one of the picture and the video is decoded, the decoded one of the picture and the video is modified with the generative AI process based on the text string prompt when the generative AI process is to be applied to the one of the picture and the video data (Wang: Para. [0093] discloses post-decoding operations and Chen: Paras. [0005], [0009], [0086] disclose a frame buffer for storing video stream comprising a temporal sequence of video frames, embedding the visualizations in the frames of the video stream and augmenting sports video clips based on a text by automatically converting the text into embedded visualizations and generating the visual content based on text descriptions using natural language processing (NLP) models (e.g., large language models.).) . As per claim 4 , Wang-Hannuksela-Chen disclose the method of claim 1, wherein the text string prompt includes the instructions for the generative AI process to modify the one of the picture and the video (Chen: Fig. 1 & Para. [0076] disclose obtaining raw video footage 102 and commentary text 106 of racket-based sports as input 104, and outputs an augmented video 134 [generative AI process to modify the one of the picture and the video].) . As per claim 5 , Wang-Hannuksela-Chen disclose the method of claim 1, wherein the neural-network post-filtering process includes one or more neural networks (Chen: Para. [0077] discloses the system 108 may include a video processor 116 for pre-processing and/or postprocessing the input video, which may include computer vision techniques based on deep learning, object detection, object tracking, pose estimation, and/or segmentation and Chen: Para. [0083] discloses utilizing a ViT-Adapter [a neural network] trained on COCO 164K to perform tasks.) . As per claim 6 , Wang-Hannuksela-Chen disclose the method of claim 1, wherein the neural-network SEI message indicates neural-network post-filter information of the neural-network post-filtering process (Chen: Para. [0077] discloses the system 108 may include a video processor 116 for pre-processing and/or postprocessing the input video, which may include computer vision techniques based on deep learning, object detection, object tracking, pose estimation, and/or segmentation and Chen: Para. [0083] discloses utilizing a ViT-Adapter [a neural network] trained on COCO 164K to perform tasks. Further, Hannuksela: Para. [00243] discloses “The SEI message payload of one or more NNPFC SEI messages may be included in a machine consumption indication SEI message and define the post-filter”.) . As per claim 7 , Wang-Hannuksela-Chen disclose the method of claim 1, wherein the text string prompt is carried in a payload of the neural-network SEI message (Wang: Paras. [0053], [0093], [0159] disclose a payload of the SEI message carrying essential information, such as subtitling, captioning [text data] and Chen: Paras. [0005], [0075], [0086] disclose using commentaries [text string prompt] as an information source for a system that automatically converts the text into embedded visualizations using NLP and computer vision models (a generative AI process).) . As per claim 9 , Wang-Hannuksela-Chen disclose the method of claim 1, wherein the neural-network SEI message does not indicate that the one of the picture and the video has been modified by another generative AI process and the neural-network SEI message does not indicate that the one of the picture and the video has not been modified by the other generative AI process (Wang: Paras. [0054], [0093], [0159] do not disclose the SEI message indicating that the one of the picture and the video has been or has not been modified by any generative AI process and therefore, does not indicate that the one of the picture and the video has not been or has been modified by the other generative AI process.) . As per claim 10 , Wang discloses a method for generating a neural-network supplemental enhancement information (SEI) message (Wang: Abstract) , the method comprising: obtaining text data purposed for use with a generative artificial intelligence (AI) process including a neural-network post-filtering process (Wang: Paras. [0054], [0093], [0159] disclose obtaining SEI messages carrying text data such as subtitling, captioning, or user data unregistered for private use.) ; and encoding a video bitstream comprising (i) one of a picture and a video and (ii) the neural- network SEI message including instructions for the generative AI process that includes the neural-network post-filtering process, the neural-network SEI message being associated with the one of the picture and the video (Wang: [0065] discloses “the encoding device 104 encodes the video data to generate an encoded video bitstream”; Wang: Paras. [0019], [0081], [0091] disclose the encoded video bitstream comprising VCL NAL units (picture/video) and SEI NAL units (supplemental enhancement information messages) associated with the video data and Wang: Para. [0093] & Table 1 disclose a “post_filter_hint [claimed post-filtering process]”.) , the neural-network SEI message including the text data (Wang: Paras. [0054], [0093], [0159] disclose that SEI messages can carry text data such as subtitling, captioning, or user data unregistered for private use.) , wherein the text data includes a text string prompt that is input to the neural-network post-filtering process . However, Wang does not explicitly disclose “… a generative artificial intelligence (Al) process including a neural-network post-filtering process […] the neural-network SEI message […] for the generative AI process that includes the neural-network post-filtering process, the neural-network SEI message being associated […] wherein the text data includes a text string prompt that is input to the neural-network post-filtering process.”. Further, Hannuksela is in the same field of endeavor and teaches a generative artificial intelligence (AI) process including a neural-network post-filtering process (Hannuksela: Para. [00165] discloses “specifies the neural-network post-processing filter [claimed neural-network post-filtering process]” and Hannuksela: Para. [00231] discloses “SEI message … uses a generative neural network [claimed generative artificial intelligence (AI) process]”.)) , the neural-network SEI message for the generative AI process that includes the neural-network post-filtering process (Hannuksela: Para. [00161] discloses “The neural-network post-filter characteristics (NNPFC) SEI message and the neural-network post-filter activation (NNPFA) SEI message [claimed neural-network supplemental enhancement information (SEI) message]” and Hannuksela: Para. [00231] discloses “SEI message … uses a generative neural network [claimed for a generative artificial intelligence (Al) process]”.) ; the neural-network SEI message being associated with the one of the picture and the video (Hannuksela: Para. [00231] discloses “SEI message may comprise, but may not be limited to, one or more of the following: An indication … be present in the video [associated with the one of the picture and the video]”.) , data that is input to the neural-network post-filtering process (Hannuksela: Para. [00243] discloses “The SEI message payload of one or more NNPFC SEI messages may be included in a machine consumption indication SEI message and define the post-filter”.) . Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, and having the teachings of Wang and Hannuksela before him or her, to modify the video coding system of Wang to include the neural-network SEI message and neural-network post-processing filter feature as described in Hannuksela. The motivation for doing so would have been to improve machine analysis precision in video coding systems by providing a standardized bitstream signaling mechanism to identify advanced neural-network post-processing pipeline operations. However, Wang-Hannuksela do not explicitly disclose “… wherein the text data includes a text string prompt that is input to the neural-network post-filtering process.” Furthermore, Chen is in the same field of endeavor and teaches wherein the text data includes a text string prompt that is input to the neural-network post-filtering process (Chen: Paras. [0005], [0075], [0086] disclose using commentaries [text] as an information source for a system that automatically converts the text into embedded visualizations using NLP and computer vision models (a generative AI process). For example, Chen: Para. [0096] discloses “Suppose the input text is “Nole crosscourt with a sharp angle. He is brilliant!” [claimed wherein the text data includes a text string prompt]” and Chen: Para. [0106] discloses taking “a piece of text, a video clip, and sports data extracted from the video clip as the input [claimed that is input to the neural-network post-filtering process]”).) . Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, and having the teachings of Wang-Hannuksela and Chen before him or her, to modify the SEI messaging neural-network post-filtering process of Wang-Hannuksela to include the text string prompts feature as described in Chen. The motivation for doing so would have been to improve user viewing experience by providing a configuration that enables generative content to be transmitted alongside video content in a standardized bitstream format, ensuring the receiving device has the necessary data to perform the augmentation/visualization. As per claim 11 , Wang-Hannuksela-Chen disclose the method of claim 10, wherein the neural-network post-filtering process includes one or more neural networks (Chen: Para. [0077] discloses the system 108 may include a video processor 116 for pre-processing and/or postprocessing the input video, which may include computer vision techniques based on deep learning, object detection, object tracking, pose estimation, and/or segmentation and Chen: Para. [0083] utilizing a ViT-Adapter [a neural network] trained on COCO 164K to perform tasks.) . As per claim 12 , the claim(s) recites analogous limitations to claim(s) 6 above, and is/are therefore rejected on the same premise. As per claim 13 , Wang-Hannuksela-Chen disclose the method of claim 10, wherein the text string prompt is carried in a payload of the neural-network SEI message (Wang: Paras. [0053], [0093], [0159] disclose a payload of the SEI message carrying essential information, such as subtitling, captioning [text data].) . As per claim 21 , Wang discloses non-transitory computer-readable storage medium storing instructions which when executed by a processor cause the processor to perform a method of encoding a video bitstream (Wang: Abstract) , the method comprising : obtaining text data purposed for use with a generative artificial intelligence (AI) process including a neural-network post-filtering process (Wang: Paras. [0054], [0093], [0159] disclose obtaining SEI messages carrying text data such as subtitling, captioning, or user data unregistered for private use; Wang: Para. [0093] & Table 1 disclose a “post_filter_hint [claimed post-filtering process]”.) ; encoding the video bitstream comprising (i) one of a picture and a video and (ii) a neural- network supplemental enhancement information (SEI) message including instructions for the generative AI process that includes the neural-network post-filtering process, the neural-network SEI message being associated with the one of the picture and the video (Wang: [0065] discloses “the encoding device 104 encodes the video data to generate an encoded video bitstream”; Wang: Paras. [0019], [0081], [0091] disclose the encoded video bitstream comprising VCL NAL units (picture/video) and SEI NAL units (supplemental enhancement information messages) associated with the video data and Wang: Para. [0093] & Table 1 disclose a “post_filter_hint [claimed post-filtering process]”.) , the neural-network SEI message including the text data (Wang: Paras. [0054], [0093], [0159] disclose that SEI messages can carry text data such as subtitling, captioning, or user data unregistered for private use.) ; and transmitting the video bitstream, wherein the text data includes a text string prompt that is input to the neural-network post-filtering process (Wang: Para. [0244] discloses the “encoded bitstream can be transmitted over a network”.) . However, Wang does not explicitly disclose “… a generative artificial intelligence (Al) process […] including a neural-network post-filtering process […] a neural-network supplemental enhancement information (SEI) message […] for the generative AI process that includes the neural-network post-filtering process, the neural-network SEI message being associated […] wherein the text data includes a text string prompt that is input to the neural-network post-filtering process.”. Further, Hannuksela is in the same field of endeavor and teaches a generative artificial intelligence (Al) process including a neural-network post-filtering process (Hannuksela: Para. [00165] discloses “specifies the neural-network post-processing filter [claimed neural-network post-filtering process]” and Hannuksela: Para. [00231] discloses “SEI message … uses a generative neural network [claimed generative artificial intelligence (AI) process]”.)) , a neural-network supplemental enhancement information (SEI) message for the generative AI process that includes the neural-network post-filtering process (Hannuksela: Para. [00161] discloses “The neural-network post-filter characteristics (NNPFC) SEI message and the neural-network post-filter activation (NNPFA) SEI message [claimed neural-network supplemental enhancement information (SEI) message]” and Hannuksela: Para. [00231] discloses “SEI message … uses a generative neural network [claimed for a generative artificial intelligence (AI) process]”.) ; the neural-network SEI message being associated with the one of the picture and the video (Hannuksela: Para. [00231] discloses “SEI message may comprise, but may not be limited to, one or more of the following: An indication … be present in the video [associated with the one of the picture and the video]”.) , data that is input to the neural-network post-filtering process (Hannuksela: Para. [00243] discloses “The SEI message payload of one or more NNPFC SEI messages may be included in a machine consumption indication SEI message and define the post-filter”.) . Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, and having the teachings of Wang and Hannuksela before him or her, to modify the video coding system of Wang to include the neural-network SEI message and neural-network post-processing filter feature as described in Hannuksela. The motivation for doing so would have been to improve machine analysis precision in video coding systems by providing a standardized bitstream signaling mechanism to identify advanced neural-network post-processing pipeline operations. However, Wang-Hannuksela do not explicitly disclose “… wherein the text data includes a text string prompt that is input to the neural-network post-filtering process.” Furthermore, Chen is in the same field of endeavor and teaches wherein the text data includes a text string prompt that is input to the neural-network post-filtering process (Chen: Paras. [0005], [0075], [0086] disclose using commentaries [text] as an information source for a system that automatically converts the text into embedded visualizations using NLP and computer vision models (a generative AI process). For example, Chen: Para. [0096] discloses “Suppose the input text is “Nole crosscourt with a sharp angle. He is brilliant!” [claimed wherein the text data includes a text string prompt]” and Chen: Para. [0106] discloses taking “a piece of text, a video clip, and sports data extracted from the video clip as the input [claimed that is input to the neural-network post-filtering process]”).) . Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, and having the teachings of Wang-Hannuksela and Chen before him or her, to modify the SEI messaging neural-network post-filtering process of Wang-Hannuksela to include the text string prompts feature as described in Chen. The motivation for doing so would have been to improve user viewing experience by providing a configuration that enables generative content to be transmitted alongside video content in a standardized bitstream format, ensuring the receiving device has the necessary data to perform the augmentation/visualization. As per claim 22 , the claim(s) recites analogous limitations to claim(s) 11 above, and is/are therefore rejected on the same premise. As per claim 23 , the claim(s) recites analogous limitations to claim(s) 6 above, and is/are therefore rejected on the same premise. As per claim 24 , the claim(s) recites analogous limitations to claim(s) 7 above, and is/are therefore rejected on the same premise . 07-21-aia AIA Claim s 8 , 14 , 25 are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Hannuksela in view of Chen in further view of Pettersson et al., hereinafter referred to as Pettersson (WO 2022/220724 A1) . As per claim 8 , Wang-Hannuksela-Chen disclose the method of claim 7, wherein the payload of the neural-network SEI message comprises a flag indicating that a remainder of the payload of the neural-network SEI message is to be processed (Wang: Paras. [0053], [0093], [0157], [0159], [0163] disclose a payload of the SEI message carrying essential information, such as subtitling, captioning [text data] described in SEI prefix indication. For example, prefix_sei_payload_type indicates the payloadType value of the SEI messages for which one or more SEI prefix indications are provided in the SEI prefix indication SEI message.) . However, Wang-Hannuksela-Chen do not explicitly disclose “… a flag indicating that a remainder of the payload of the neural-network SEI message is to be processed.”. Furthermore, Pettersson is in the same field of endeavor and teaches a flag indicating that a remainder of the payload of the neural-network SEI message is to be processed (Pettersson: Paras. [0055], [0072]-[0073] disclose a film_grain_characteristics_cancel_flag found within the film grain characteristics SEI message syntax, determines if the subsequent parameters in the payload should be processed. For example, if the flag is set to a first value (e.g., 0), the remaining parameters (syntax elements) in the payload follow and are processed to enable the film grain process.) . Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, and having the teachings of Wang-Hannuksela-Chen and Pettersson before him or her, to modify the video encoding decoding system of Wang-Hannuksela-Chen to include the flag indicating remainder feature as described in Pettersson. The motivation for doing so would have been to improve video coding efficiency by providing a configuration that reduces the overall bit cost of the video stream when functionalities are used arbitrarily or intermittently. As per claim 14 , the claim(s) recites analogous limitations to claim(s) 8 above, and is/are therefore rejected on the same premise. As per claim 25 , the claim(s) recites analogous limitations to claim(s) 8 above, and is/are therefore rejected on the same premise . Allowable Subject Matter Claim 3 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim provided that the rejection pertinent to 35 U.S.C. 112(b) is overcome. Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and can be viewed in the list of references . Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL . See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to PEET DHILLON whose telephone number is (571)270-5647. The examiner can normally be reached M-F: 5am-1:30pm. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /PEET DHILLON/Primary Examiner Art Unit: 2488 Date: 06-11-2026 Application/Control Number: 19/012,648 Page 2 Art Unit: 2488 Application/Control Number: 19/012,648 Page 3 Art Unit: 2488 Application/Control Number: 19/012,648 Page 4 Art Unit: 2488 Application/Control Number: 19/012,648 Page 5 Art Unit: 2488 Application/Control Number: 19/012,648 Page 6 Art Unit: 2488 Application/Control Number: 19/012,648 Page 7 Art Unit: 2488 Application/Control Number: 19/012,648 Page 8 Art Unit: 2488 Application/Control Number: 19/012,648 Page 9 Art Unit: 2488 Application/Control Number: 19/012,648 Page 10 Art Unit: 2488 Application/Control Number: 19/012,648 Page 11 Art Unit: 2488 Application/Control Number: 19/012,648 Page 12 Art Unit: 2488 Application/Control Number: 19/012,648 Page 13 Art Unit: 2488 Application/Control Number: 19/012,648 Page 14 Art Unit: 2488 Application/Control Number: 19/012,648 Page 15 Art Unit: 2488 Application/Control Number: 19/012,648 Page 16 Art Unit: 2488
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