CTNF 18/531,508 CTNF 86559 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. Claims 1-20 are pending for examination. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. Step 2A Prong 1: Claims 1, 9 and 17 , the claim(s) recite(s) the limitation of “determining a predicted mode of the workload of the virtual system based on the access data; determining an upgrade preference for the virtual system based on at least one of the access data and user settings of the virtual system”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “determining” in the context of this claim encompasses simple determination that may be performed within the mind such as making observations, evaluations, judgements and opinion regarding the access data and user setting, and what a predicted mode of the workload would be based on those received data. Similarly, the limitation of “selecting a cloud service usable to upgrade the virtual system from the group of candidate cloud services based on the predicted mode and the upgrade preference, the selecting resulting in a selected cloud service”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “selecting” in the context of this claim encompasses making observations, evaluations, judgements and opinion regarding the criteria/evaluation corresponding to candidate cloud services, as thought of mentally above, to evaluate which cloud service should be selected. Similarly, the limitation of “generating a recommendation report indicating the selected cloud service” as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind and/or with the aid of pen and paper. For example, “generating” in the context of this claim encompasses a person thinking about the selected cloud service, and write a recommendation report regarding the selected cloud service, perhaps using pen and paper. Additional elements are evaluated below. Claims 2, 10, 18 , similarly, the limitation of “the upgrade preference indicates one or more performance metrics of the virtual system, and wherein selecting the cloud service usable to upgrade the virtual system comprises: for a candidate cloud service in the group of candidate cloud services, determining a first expected value of the one or more performance metrics when the candidate cloud service is used for the virtual system based on the predicted mode and the attribute set; determining, based on the predicted mode, a current expected value of the one or more performance metrics without upgrading”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “determining” in the context of this claim encompasses simple determinations that may be performed within the mind such as making observations, evaluations, judgements and opinion regarding an expected value of the performance metrics when candidate cloud service are used, as thought of mentally above, to evaluate which candidate cloud service’s expected value is better than the current expected value. Similarly, the limitations of “selecting the candidate cloud service in response to determining that the expected value is better than the current expected value according to a defined performance criterion.”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “selecting” in the context of this claim encompasses making observations, evaluations, judgements and opinion regarding the criteria/evaluation of the expected value of the performance metrics, as thought of mentally above, to evaluate which candidate cloud service should be selected, and make a judgement of the cloud service accordingly. Claims 3, 11, 19 : similarly, the limitation of “wherein selecting the candidate cloud service comprises: determining a second expected value of the one or more performance metrics when a combination of multiple candidate cloud services of different types is used for the virtual system”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “determining” in the context of this claim encompasses simple determinations that may be performed within the mind such as making observations, evaluations, judgements and opinion regarding an expected value of the performance metrics when candidate cloud service are used, as thought of mentally above, to evaluate which candidate cloud service’s expected value is better than the current expected value. Similarly, the limitations of “selecting the combination in response to the second expected value of the combination being better than the current expected value according to the defined performance criterion”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “selecting” in the context of this claim encompasses making observations, evaluations, judgements and opinion regarding the criteria/evaluation of the expected value of the performance metrics, as thought of mentally above, to evaluate which candidate cloud service should be selected, and make a judgement of the cloud service accordingly. Claims 4, 12, 20 : Similarly, the limitations of “wherein the upgrade preference further comprises one or more weights of the one or more performance metrics, and wherein the determining that the expected value is better than the current expected value comprises: determining that the expected value is better than the current expected value based on the one or more weights”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “determine” in the context of this claim encompasses making observations, evaluations, judgements and opinion regarding the criteria/evaluation of the expected values based on the weights of the performance metrics, as thought of mentally above, to evaluate which candidate cloud service should be selected. Additional elements are evaluated below. Claims 5, 13 : similarly, the limitation of “scheduling the upgrade of the virtual system based on the predicted mode”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “scheduling” in the context of this claim encompasses making observations, evaluations, judgements and opinion regarding the criteria/evaluation of the expected values based on the weights of the performance metrics, as thought of mentally above, to evaluate which candidate cloud service should be selected to be upgraded, and determine when the upgrade is to be performed, which results in scheduling the upgrade. Claims 6, 14 : similarly, the limitation of “determining the predicted mode comprises identifying an expected distribution of geographical locations associated with traffic of the virtual system, and selecting the cloud service usable to upgrade the virtual system comprises: for a candidate cloud service in the group of candidate cloud services, determining a first expected service latency of the virtual system when the candidate cloud service is used for the virtual system based on the expected distribution and the attribute set” as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “determining” in the context of this claim encompasses simple determinations that may be performed within the mind such as making observations, evaluations, judgements and opinion regarding an expected value of the latency when candidate cloud service are used, as thought of mentally above, to evaluate which candidate cloud service’s expected value is better than the current expected value. Similarly, the limitation of “in response to determining that the first expected service latency is less than a second expected service latency of the virtual system without upgrading, selecting the candidate cloud service” as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “selecting” in the context of this claim encompasses making observations, evaluations, judgements and opinion regarding the criteria/evaluation of the expected value of the latency, as thought of mentally above, to evaluate which candidate cloud service should be selected, and make a judgement of the cloud service accordingly. Claims 7, 15 : similarly, the limitation of “determining the predicted mode comprises identifying an expected read/write mode corresponding to a user of the virtual system, and selecting the cloud service usable to upgrade the virtual system comprises: for a candidate cloud service in the group of candidate cloud services, determining a first expected unit charge of the virtual system when the candidate cloud service is used for the virtual system based on the expected read/write mode and the attribute set” as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “determining” in the context of this claim encompasses simple determinations that may be performed within the mind such as making observations, evaluations, judgements and opinion regarding an expected unit charge when candidate cloud service are used, as thought of mentally above, to evaluate which candidate cloud service’s expected value is better than the current expected value. Similarly, the limitation of “ in response to determining that the first expected unit charge is lower than a second expected unit charge of the virtual system without upgrading, selecting the candidate cloud service” as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “selecting” in the context of this claim encompasses making observations, evaluations, judgements and opinion regarding the criteria/evaluation of the expected unit of charge, as thought of mentally above, to evaluate which candidate cloud service should be selected, and make a judgement of the cloud service accordingly. Claims 8, 16 : similarly, the limitation of “the upgrade preference comprises geographical location restrictions, and selecting the cloud service usable to upgrade the virtual system from the group of candidate cloud services comprises: determining whether a deployment location of the cloud service satisfies the geographical location restrictions” as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “determining” in the context of this claim encompasses simple determinations that may be performed within the mind such as making observations, evaluations, judgements and opinion regarding geographical location restrictions and a deployment location of the cloud service, as thought of mentally above, to evaluate which candidate cloud service satisfies the geographical location restrictions. Step 2A Prong 2: Claims 1, 9 and 17 : This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements –“recording, access data of a virtual system that is to be upgraded and that uses a cloud service”, “in response to receiving an attribute set of a group of candidate cloud services,” which are merely insignificant pre and post solution data gathering activity which does not meaningfully limit the judicial exception, see MPEP § 2106.05(g). In addition, the claim recites additional elements – “a system comprising at least one processor”, “virtual system”, “cloud service” in claim 1, “a device comprising a processor, memory coupled with the processor”, “virtual system”, “cloud service” in claim 9, and “a computer program product stored on a non-transitory computer readable medium and comprising machine executable instruction”, “virtual system”, “cloud service” in claim 16, which are merely recitations of generic computing components and functions (see MPEP § 2106.05(b)) which does not integrate a judicial exception into practical application. Claims 4, 12 and 20: This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements, “in response to receiving an instruction to upgrade the virtual system based on the recommendation report” which are merely insignificant pre and post solution data gathering activity which does not meaningfully limit the judicial exception, see MPEP § 2106.05(g). Claims 2-3, 5-8, 10-11, 13-16, 18-19 : they do not recite any additional elements. Therefore, , “Do the claims recite additional elements that integrate the judicial exception into a practical application? No, these additional elements do not integrate the abstract idea into a practical application and they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. After having evaluating the inquires set forth in Steps 2A Prong 1 and 2, it has been concluded that the claims 1, 9 and 17 not only recite a judicial exception but that the claims are directed to the judicial exception as the judicial exception has not been integrated into practical application. Step 2B: Claims 1, 9 and 17 , the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, additional elements -“ recording, access data of a virtual system that is to be upgraded and that uses a cloud service”, “in response to receiving an attribute set of a group of candidate cloud services” which are merely insignificant pre and post solution data gathering activity which does not meaningfully limit the judicial exception, see MPEP § 2106.05(g). This pre-solution data gathering do not impose meaning limits on practicing the abstract idea and thus cannot provide an inventive concept. Also the additional elements of “a system comprising at least one processor”, “virtual system”, “cloud service” in claim 1, “a device comprising a processor, memory coupled with the processor”, “virtual system”, “cloud service” in claim 9, and “a computer program product stored on a non-transitory computer readable medium and comprising machine executable instruction”, “virtual system”, “cloud service” in claim 16, amount to no more than generic computing components which do not amount to significantly more than the abstract idea. Therefore, “Do the claims recite additional elements that amount to significantly more than the judicial exception? No, these additional elements, alone or in combination, do not amount to significantly more than the judicial exception. Having concluded analysis within the provided framework, Claims 1, 9 and 17 do not recite patent eligible subject matter under 35 U.S.C. § 101. Claim 4, 12 and 20 : the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, additional elements - “in response to receiving an instruction to upgrade the virtual system based on the recommendation report” which are merely insignificant pre-solution data gathering activity, see MPEP § 2106.05(g). This pre-solution data gathering does not impose meaning limits on practicing the abstract idea and thus cannot provide an inventive concept. Claims 2-3, 5-8, 10-11, 13-16, 18-19 they do not recite any additional elements. Therefore, “Do the claims recite additional elements that amount to significantly more than the judicial exception? No, these additional elements do not amount to significantly more than the judicial exception. Having concluded analysis within the provided framework, Claims 1-20 are not eligible subject matter under 35 U.S.C. § 101. 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 (i.e., changing from AIA to pre-AIA) 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. 07-21-aia AIA Claim (s) 1-3, 5, 7, 9-11, 13, 15, 17-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hari US Pub 2020/0089515 (hereafter Hari) in view of Toal et al. US Pub 2022/0350664 (hereafter Toal) . As per claim 1, Hari teaches the invention substantially as claimed including a method, comprising: recording, by a system comprising at least one processor, access data of a virtual system that is to be upgraded and that uses a cloud service (para[0023, 0027-0029, 0034-0036, 0061, 0092], monitors and records the performance of an application container (virtual instance), hosted by a cloud provider service, including processor, memory and storage usage, and identifies application container should be updated); in response to receiving an attribute set of a group of candidate cloud services, determining a predicted mode of the workload of the virtual system based on the access data (para[0022, 0050, 0061], receive pricing information from available cloud services, and generate predictions (output vectors for the application container) that are used to generate migration instruction for migrating the application to a updated cloud provider service); determining an upgrade preference for the virtual system based on at least one of the access data and user settings of the virtual system (para[0053, 0057, 0059-0060], determine budget information (cost limits, cost reduction threshold to upgrade) from the user setting inputs for the application containers); selecting a cloud service usable to upgrade the virtual system from the group of candidate cloud services based on the predicted mode and the upgrade preference, the selecting resulting in a selected cloud service (para[0059-0069], FIG. 3, using the historical performance information, budge information and pricing information, generate output vector and determined updated application configuration, and generate migration instructions by comparing cloud service costs and budget goals to migrate containerized application from current cloud provider service to selected cloud provider services). Hari does not explicitly teach generating a recommendation report indicating the selected cloud service. However, Toal teach generating a recommendation report indicating the selected cloud service (para[0020, 0055-0056, 0065, 0074-0075], the recommender recommends an instance type replacement for the current instance, where each container is mapped to an instance type that provides a cloud computing service, if the instance type can provide a more optimal level of performance and cost than the current instance). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Toal’s teaching to Hari’s invention in order to provide a method to automatically identifying and right sizing container instances by collecting data related to the current state and desired state for the recommender that provides recommended instance type to replace the current one which improves both performance and cost (para[0073]). As per claim 2, Hari and Toal teach the method according to claim 1, Toal teaches wherein the upgrade preference indicates one or more performance metrics of the virtual system, and wherein selecting the cloud service usable to upgrade the virtual system comprises: for a candidate cloud service in the group of candidate cloud services, determining a first expected value of the one or more performance metrics when the candidate cloud service is used for the virtual system based on the predicted mode and the attribute set (para[0060, 0068-0070], FIG. 3A, determine whether there is an instance type (service) with a resource profile that provides a more optimal level of performance, indicated that the expected value of the performance metric); determining, based on the predicted mode, a current expected value of the one or more performance metrics without upgrading; and selecting the candidate cloud service in response to determining that the expected value is better than the current expected value according to a defined performance criterion (para[0060, 0068-0070], if the instance type with a more optimal level of performance is not the current instance type, indicating that the expected value is better than the current expected value, then selected instance type is recommended). As per claim 3, Toal teaches wherein selecting the candidate cloud service comprises: determining a second expected value of the one or more performance metrics when a combination of multiple candidate cloud services of different types is used for the virtual system; and selecting the combination in response to the second expected value of the combination being better than the current expected value according to the defined performance criterion (para[0054-0056, 0068], one or more instance types are used for the current service, and examine the performance and cost of the proposed instance types, and identify instance types that are more optimal than the current types, thus the different types are examined and recommended if their expected performance metrics is more optimal). As per claim 5, Hari teaches further comprising: in response to receiving an instruction to upgrade the virtual system based on the recommendation report, scheduling the upgrade of the virtual system based on the predicted mode (para[0066-0069], migrate (upgrade) containerized application from current cloud provider service to selected cloud provider service based on output vector by executing the migration instruction, thus scheduling the migration (upgrade of the cloud service) according to the migration instruction). As per claim 7, Hari teaches wherein determining the predicted mode comprises identifying an expected read/write mode corresponding to a user of the virtual system (para[0043, 0059-0060], memory and storage (performance) usages are measured and inputted into the model to predict and generate output which determines updated application configuration); and selecting the cloud service usable to upgrade the virtual system comprises: for a candidate cloud service in the group of candidate cloud services, determining a first expected unit charge of the virtual system when the candidate cloud service is used for the virtual system based on the expected read/write mode and the attribute set; and in response to determining that the first expected unit charge is lower than a second expected unit charge of the virtual system without upgrading, selecting the candidate cloud service (para[0061-0062, 0065-066], the machine instance type needs to be updated, and migration service identifies the cloud service by selecting the instance type that meets the minimum hardware specifications for the application with the lowest cost). As per claim 9, it is a device claim of claim 1 above, thus it is rejected for the same rationale. As per claim 10, it is a device claim of claim 2 above, thus it is rejected for the same rationale. As per claim 11, it is a device claim of claim 3 above, thus it is rejected for the same rationale. As per claim 13, it is a device claim of claim 5 above, thus it is rejected for the same rationale. As per claim 15, it is a device claim of claim 7 above, thus it is rejected for the same rationale. As per claim 17, it is a computer program product claim of claim 1 above, thus it is rejected for the same rationale. As per claim 18, it is a computer program product claim of claim 2 above, thus it is rejected for the same rationale. As per claim 19, it is a computer program product claim of claim 3 above, thus it is rejected for the same rationale . 07-22-aia AIA Claim (s) 4, 6, 8, 12, 14, 16, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hari in view of Toal as applied to claim 2 above, and further in view of Shah et al. US Pub 2024/0118911 (hereafter Shah) . As per claim 4, Hari and Toal teach the method according to claim 2, and Toal teaches wherein the determining that the expected value is better than the current expected value comprises: determining that the expected value is better than the current expected value (para[0054-0056, 0068], one or more instance types are used for the current service, and examine the performance and cost of the proposed instance types, and identify instance types that are more optimal than the current types, thus the different types are examined and recommended if their expected performance metrics is more optimal). Hari and Toal do not explicitly teach wherein the upgrade preference further comprises one or more weights of the one or more performance metrics, and determining that the expected value is better based on the one or more weights. However, Shah teaches wherein the upgrade preference further comprises one or more weights of the one or more performance metrics, and determining that the expected value is better based on the one or more weights (para[0043, 0046], assigning a weight to the desired latency metric and cost metric, and a public cloud is selected based on both parameters and their assigned weight values). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Shah’s teaching to Hari and Toal’s invention in order to provide a multicloud scalable middlebox service solution to deploy cluster of service machines to a primary cloud to supplement a primary cluster of service machines according to the user defined criteria and metrics of the candidate clouds, which is cost and latency aware, and minimizes either or both (para[0003]). As per claim 6, Hari and Toal teach The method according to claim 1, and Toal teaches determining that the first expected service latency is less than a second expected service latency of the virtual system without upgrading (para[0035, 0041, 0054-0056, 0068], one or more instance types are used for the current service, and examine the performance (including latency) and cost of the proposed instance types, and identify instance types that are more optimal than the current types, thus the different types are examined and recommended if their expected performance metrics is more optimal). Hari and Toal do not teach determining the predicted mode comprises identifying an expected distribution of geographical locations associated with traffic of the virtual system, and selecting the cloud service usable to upgrade the virtual system comprises: for a candidate cloud service in the group of candidate cloud services, determining a first expected service latency of the virtual system when the candidate cloud service is used for the virtual system based on the expected distribution and the attribute set; and in response to determining that the first expected service latency is less, selecting the candidate cloud service. However, Shah teaches wherein determining the predicted mode comprises identifying an expected distribution of geographical locations associated with traffic of the virtual system, and selecting the cloud service usable to upgrade the virtual system comprises: for a candidate cloud service in the group of candidate cloud services, determining a first expected service latency of the virtual system when the candidate cloud service is used for the virtual system based on the expected distribution and the attribute set; and in response to determining that the first expected service latency is less, selecting the candidate cloud service (para[0043, 0048-0049, 0053, 0058-0060], metrics specifying the region for a public cloud and latency metrics are used to select the public cloud to deploy the service machines). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Shah’s teaching to Hari and Toal’s invention in order to provide a multi-cloud scalable middlebox service solution to deploy cluster of service machines to a primary cloud to supplement a primary cluster of service machines according to the user defined criteria and metrics of the candidate clouds, which is cost and latency aware, and minimizes either or both (para[0003]). As per claim 8, Hari and Toal teach The method according to claim 1, but they do not explicitly teach the upgrade preference comprises geographical location restrictions, and selecting the cloud service usable to upgrade the virtual system from the group of candidate cloud services comprises: determining whether a deployment location of the cloud service satisfies the geographical location restrictions. However, Shah teaches wherein the upgrade preference comprises geographical location restrictions, and selecting the cloud service usable to upgrade the virtual system from the group of candidate cloud services comprises: determining whether a deployment location of the cloud service satisfies the geographical location restrictions (para[0053, 0061], a list of clouds with different regions are compared with the regions the user desires to deploy the service machine cluster and select one of these public cloud providers). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Shah’s teaching to Hari and Toal’s invention in order to provide a multi-cloud scalable middlebox service solution to deploy cluster of service machines to a primary cloud to supplement a primary cluster of service machines according to the user defined criteria and metrics of the candidate clouds, which is cost and latency aware, and minimizes either or both (para[0003]). As per claim 12, it is a device claim of claim 4 above, thus it is rejected for the same rationale. As per claim 14, it is a device claim of claim 6 above, thus it is rejected for the same rationale. As per claim 16, it is a device claim of claim 8 above, thus it is rejected for the same rationale. As per claim 20, it is a computer program product claim of claim 4 above, thus it is rejected for the same rationale . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Balakrishnan et al. US Pub 2023/0280982 teaches real-time resource deployment and integration can include determining one or more performance priorities for a user computer system based on a plurality of system-generated processing metrics. Based on the one or more performance priorities, a candidate cloud-based service can be determined among one or more previously unanalyzed cloud-based services identified by an automated watcher configured to search a plurality of communication network sites. The current performance of the user computer system can be compared to a potential performance of the user computer system were the candidate cloud-based service deployed. Gelle et al. US Pub 2023/0214901 teaches a method determining, based on historical time series data for the one or more services provided by at least one cloud service provider, a predicted trend of future values for the set of usage-related parameters for the one or more cloud services for the at least one cloud service provider; evaluating the predicted trend of future values for the set of usage-related parameters for the one or more cloud services for each of the at least one cloud service providers to generate a recommendation that best corresponds, at least within a specified threshold, to the values for the set of usage-related parameters received from the user. Any inquiry concerning this communication or earlier communications from the examiner should be directed to TAMMY EUNHYE LEE whose telephone number is (571)270-7773. The examiner can normally be reached Mon, Tues, Thur 9PM-4PM. 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, Meng-Ai An can be reached at (571)272-3756. 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. /TAMMY E LEE/Primary Examiner, Art Unit 2195 Application/Control Number: 18/531,508 Page 2 Art Unit: 2195 Application/Control Number: 18/531,508 Page 3 Art Unit: 2195 Application/Control Number: 18/531,508 Page 4 Art Unit: 2195 Application/Control Number: 18/531,508 Page 5 Art Unit: 2195 Application/Control Number: 18/531,508 Page 6 Art Unit: 2195 Application/Control Number: 18/531,508 Page 7 Art Unit: 2195 Application/Control Number: 18/531,508 Page 8 Art Unit: 2195 Application/Control Number: 18/531,508 Page 9 Art Unit: 2195 Application/Control Number: 18/531,508 Page 10 Art Unit: 2195 Application/Control Number: 18/531,508 Page 11 Art Unit: 2195 Application/Control Number: 18/531,508 Page 12 Art Unit: 2195 Application/Control Number: 18/531,508 Page 13 Art Unit: 2195 Application/Control Number: 18/531,508 Page 14 Art Unit: 2195 Application/Control Number: 18/531,508 Page 16 Art Unit: 2195 Application/Control Number: 18/531,508 Page 17 Art Unit: 2195 Application/Control Number: 18/531,508 Page 18 Art Unit: 2195 Application/Control Number: 18/531,508 Page 20 Art Unit: 2195 Application/Control Number: 18/531,508 Page 21 Art Unit: 2195
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