CTNF 18/258,364 CTNF 92146 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. Notice to Applicant This Non-Final Office Action is the second Non-Final Office Action in response to Applicants Arguments submitted on March 13, 2026 for Application Serial Number: 18/258,364, filed on June 20, 2023. Claims 1, 2 and 4-12 are pending in this application and have been rejected below. Response to Amendment Applicant's amendments are acknowledged. Regarding the 35 U.S.C. 101 rejection, Applicants arguments and amendments have been considered but are insufficient to overcome the rejection. The 35 U.S.C. § 103 rejections are hereby amended pursuant to Applicants Remarks regarding claim 1. Updated 35 U.S.C. § 103 rejections have been applied to amended claims 1, 2 and 4-12. Response to Arguments Applicant's Arguments/Remarks filed March 13, 2026 ( hereinafter Applicant Remarks ) have been fully considered but are not persuasive. Applicant’s Remarks will be addressed herein below in the order in which they appear in the response filed March 13, 2026. Regarding the 35 U.S.C. 101 rejection, Applicant states the Office Action, it is alleged that the claim limitations amount to operations that are based on observations, evaluations, judgements, and/or opinions that can be performed through human effort or activity (i.e., human mind, pen, and paper). Applicant disagrees with this assessment because the claimed embodiment is rooted in computer technology as a computing device can receive information from one or more units in a plant in near real-time. In addition, the processor can receive and/or access information related to operators assigned to service and/or repair plant units. The processor can use this information to dynamically adjust the assignment/reassignment of operators to various areas of the plant when problems arise within the plant by evaluating the detailed situation of the plant or each operator, or an impact on the entire plant (hereinafter referred to as a plant integrated unit), such as risk, a handling time, and costs under simultaneous operation of a plurality of units. Current computing solutions allows for the tracking of current operator work assignments and roles within a plant environment. The claimed embodiment improves upon the current technology, by providing time critical operation and near real-time processing that reduces risk, improves work efficiency, and reduce costs by setting details of parameters (risk, handling time, etc.) that affect the entire plant at the time of an event on the basis of the detailed situation for each plant and for each operator, presenting a schedule for each operator in accordance with the details of the parameters, and identifying and supplementing the most suitable operator when there is a shortage of operators. In response Examiner respectfully disagrees. Examiner notes in Finjan , the court identified that the claims were an improvement in computer functionality, reciting specific steps in sufficient detail of a behavior-based approach to virus scanning which is an improvement over traditional code-matching virus scanning that enabled a computer security system to do things it could not do before with a new kind of file. DDR Holdings is an example of a case that presents an invention that is rooted in computer technology. Specifically, the court found when a third party's advertisement hyperlink was selected by a user on a host's web page, the system would automatically identify the host web page, retrieve corresponding "look and feel" information from storage for the host page and generate a hybrid web page including the merchant information from the third-party web page with the "look and feel" elements of the host's website. This is different from conventional Internet hyperlink operations which would redirect a user to the third-party page away from the host's web page when the hyperlink is activated and therefore added a specific limitation other than what is well-understood, routine and conventional in the field. Examiner finds there is not similar improvement here. In contrast, the present claims are directed to the data analysis of evaluating risk or work procedure impact and determining the necessity of additional operators. Examiner finds even in a computer environment, these limitations are still considered abstract by reciting limitations that mimic human thought processes of observation, evaluations, judgement and opinion, that can feasibly be performed with pen and paper, where the data interpretation is perceptible in the human mind. Claims can recite a mental process even if they are claimed as being performed on a computer; see MPEP 2106.04(a)(2)(III)(C). Examiner finds Applicant’s arguments are directed to improvements to an existing business process (e.g. schedule management). Applicant has not identified any limitations in the claimed invention that shows or submits that the technology used is being improved or there was a problem in the technology that the claimed invention solves. Regarding the 35 U.S.C. 101 rejection, Applicant states independent claim 1 does not recite any of the judicial exceptions enumerated in the 2019 PEG including reliance on human activity or effort. Rather, under its broadest reasonable interpretation, claim 1 does not cover performance in the mind but requires action by a processor that cannot be practically applied in the mind such that time critical problems within a plant can be resolved, mitigated, and/or addressed with the allocation/reallocation of operators as needed. In particular, the system is configured to (Applicant cites limitations of claim 1, see p. 8-9, Applicant Remarks), which in total involves operations that cannot be practically performed in the human mind or through pen and paper because the combined features require the dynamic assessment of the plant relative to an event, the dynamic assessment of operators equipped to address the event, and the calculation of the impact on operation of the plant based on the assessments. The speed and accuracy of a processor configured as recited in the claims increases response when an unexpected combination of events occurs, which may lead to a severe accident. In response, Examiner respectfully disagrees. As states above, even in a computer environment, managing plant operation scheduling based on the criteria of Applicants abovementioned remarks is still considered abstract by reciting limitations that mimic human thought processes of observation, evaluations, judgement and opinion, that can feasibly be performed with pen and paper, where the data interpretation is perceptible in the human mind, as well as, methods based on business relations. Examiner notes claims can recite a mental process even if they are claimed as being performed on a computer; see MPEP 2106.04(a)(2)(III)(C). Examiner maintains the pending claims recite similar limitations to claims the courts have indicated may not be sufficient in showing an improvement in computer-functionality, such as accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016); Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017), A commonplace business method being applied on a general purpose computer, Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1976; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48; see MPEP 2106.05(a)(I) and MPEP 2106.05(a)(II). Examiner maintains Applicants arguments improves an existing business process (e.g. schedule management) and not a technology, technological field or computer related technology. The claims recite a judicial exception. Regarding the 35 U.S.C. 101 rejection, Applicant states the Office Action further asserts that it finds Applicant's arguments regarding the 101 rejections are directed to improvement to an existing business process (e.g. schedule management). See Office Action at Pages 5-6. Applicant respectfully disagrees and submits that, as described throughout the Subject Application, the features of independent claim 1 are directed to the operation of a plant, which is clearly a technology or technological field/process, and that the features of independent claim 1 are directed to improvements in the technological field/process of plant operation (see p. 10-11, Applicant Remarks). In response, Examiner respectfully disagrees. Examiner finds the pending claims merely limits to use of schedule management (e.g. operator and work schedules) to a particular technological environment (e.g. plant) without the claim citing any improvement to a technology, a technological field or computer related technology. Examiner maintains Applicant has not identified any limitations in the claimed invention that shows or submits that the technology used is being improved or there was a problem in the technology that the claimed invention solves. For example, reducing risk, improving work efficiency, and reducing costs, for example, by setting details of parameters that affect the entire plant at the time of an even on the basis of the detailed situation for each plant and for each operator, and by presenting a schedule for each operator in accordance with the details of the parameters, and identifying and supplementing the most suitable operator when there is a shortage of operators, are arguments directed to the business operations in a plant environment. Examiner finds the claims are directed towards managing plant operation scheduling of work procedures and operators without meaningful limitations that are indicative of integrating the abstract idea into a practical application. Furthermore, Examiner finds physically contacting a necessary operator is both a mental process and certain methods of organizing human activity (i.e., business relations) that can be performed human to human without the use of a computer environment. Examiner maintains the additional elements recited in the pending claim are generic computer components used as tools to apply the instructions of the abstract idea. Applicant has not made any persuasive argument that would alter this analysis. For at least these reasons the claims remain rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter. Regarding the 35 U.S.C. 103 rejection, Applicant traverses this rejection because the cited art fails to disclose or suggest at least "acquire plant information associated with a plurality of plants, the plant information including an impact degree of an event, an event probability, a handling time for the event, and varying information including an operation history of the plant," as recited in independent claim 1 (see p. 11-14, Applicant Remarks). In response, Examiner acknowledges Applicants remarks. However, Examiner finds Lepine sufficiently discloses the event probability limitations. Examiner notes, Applicants Specification disclose event probability at a high level of generality (see par. 0009, 0019, 0027; Fig. 4). Thus, Examiner finds the a prediction for a future performance of equipment in Lepine teaches the event probability limitation of the pending claim. For instance, Lepine teaches, in at least par. 0088-0089 of Lepine, the performance model compares the performance information, maintenance information, and operational state information for the steam turbine to a performance rule for the steam turbine. The performance model then outputs a result that indicates that the steam turbine is not performing as expected, and predicts that the performance of the steam turbine in the future ( within one month ) will not be as expected. The performance model then schedules a maintenance task for the steam turbine to be performed immediately. Given the broadest reasonable interpretation, Examiner interprets the steam turbine not performing as expected to be the event and the predicted future timeframe (i.e., within one month) to be the probability. For at least these reasons the claims remain rejected under 35 U.S.C. § 103 as being unpatentable over the prior art of record. 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. Step 1: The claimed subject matter falls within the four statutory categories of patentable subject matter. Claims 1, 2 and 4-12 are directed towards a system, which is among the statutory categories of invention. Step 2A – Prong One: The claims recite an abstract idea. Claims 1, 2 and 4-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite managing plant operation scheduling. Claim 1 recites limitations directed to an abstract idea based on mental processes and certain methods of organizing human activity. Specifically, process the plant information and identify one or more events occurring at the plant based on static event information and dynamic event information included in the plant information; determine, for the plurality of plants, a priority for handling each identified event by calculating at least a risk of impact on the plant for each event and determining an operation procedure for each plant when the one or more events occur; schedule a work procedure for each plant on a basis of the determined handling priority for the plurality of plants and to output a plurality of work procedure schedules; determine an operator state by analyzing a work status and dynamic physical qualities of each plant operator including at least a workload and fatigue level based on the acquired operator information and the acquired work information; set, for the plurality of plants, a plurality of parameters affecting operation of the plurality of plants during the one or more events, on a basis of the operator state and the handling priority determined for the plurality of plants; calculate an impact on the operation of the plant integrated circuitry using the set plurality of parameters, evaluate the work procedure schedules output based on calculated risk of impact on each plant; and determine necessity of operator addition based on the evaluation result according to the addition necessity determination rule constitutes methods based on observations, evaluations, judgements and/or opinion that can be performed by a combination of the human mind and a human using pen and paper, as well as, methods based on business relations. The recitation of a system comprising a plurality of storage units and the determination circuitry does not take the claim out of the mental processes and certain methods of organizing human activity groupings. Thus the claim recites an abstract idea. Step 2A – Prong Two: The judicial exception is not integrated into a practical application. The judicial exception is not integrated into a practical application. In particular, claim 1 recites access a first storage unit over a system bus and acquire plant information associated with a plurality of plants, the plant information including an impact degree of an event, an event probability, a handling time for the event, and varying information including an operation history of the plant; access a second storage unit over the system but and acquire operator information for plural plant operators including information on an owned qualification, a proficiency level, and a work status for operators of the plant; access a third storage unit over the system bus and acquire work information of the plant including work contents, a work procedure, and a work difficulty level; access a fourth storage unit configured to store an additional necessity determination rule of an operator of the plants; access the plant information stored in the plant information storage unit includes dynamic information such as plant parameters or an operation history; access the operator information stored in the operator information storage unit includes dynamic information such as the operator state or biometric information of an operator; send an evaluation result of the work procedure schedules to an output device for presentation to a user, the evaluation result including an operational response to the one or more identified events; and contact a necessary operator according to the necessity determination circuitry, which are limitations considered to be an insignificant extra-solution activity of collecting and delivering data; see MPEP 2106.05(g). Additionally, claim 1 recites system comprising a plurality of storage units, an output device and determination circuitry at a high-level of generality such that they amounts to no more than generic computer components used as tools to apply the instructions of the abstract idea; see MPEP 2106.05(f). Thus, the additional element do not integrate the abstract idea into practical application because it does not impose any meaningful limitations on practicing the abstract idea. Claim 1 is directed to an abstract idea Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements in the claims other than the abstract idea per se, including system comprising a plurality of storage units, output device and determination circuitry amount to no more than a recitation of generic computer elements utilized to perform generic computer functions, such as receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec , 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); buySAFE, Inc. v. Google, Inc. , 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); electronic recordkeeping, Ultramercial , 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log) and storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs. , 788 F.3d at 1363, 115 USPQ2d at 1092-93; see MPEP 2106.05(d)(II). Viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Therefore, since there are no limitations in the claim that transform the abstract idea into a patent eligible application such that the claim amounts to significantly more than the abstract idea itself, the claims are rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter. § 101 Analysis of the dependent claims. Regarding the dependent claims, dependent claim 2 recites limitations that are not technological in nature and merely limits the abstract idea to a particular environment. Claims 4 and 7 recites an a storage units configured to store an evaluation determination rule for a schedule of the work procedure for each plant; and claims 5 and 8-12 recites one or more processors configured to receive the schedules selected by the user, which are limitations considered to be insignificant extra-solution activities of collecting and delivering data; see MPEP 2106.05(g) and does not integrate the abstract idea into practical application. Claims 4-12 recites a plurality of storage units and memory devices, which amount to no more than generic computer components used as tools to apply the instructions of the abstract idea; MPEP 2106.05(f). Additionally, claims 2 and 4-12 recite steps that further narrow the abstract idea. Therefore claims 2 and 4-12 do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. 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, 4, 5, 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Lepine et al., U.S. Publication No. 2017/0117064 [hereinafter Lepine] , in view of Schuck et al., U.S. Publication No. 2023/0067083 [hereinafter Schuck] , and further in view of Day et al., U.S. Publication No. 2021/0193302 [hereinafter Day] . Referring to Claim 1, Lepine teaches: A plant operation assistance system comprising: memory that stores programming code for the plant operation assistance system; one or more processors configured to execute the programming code stored in memory, which causes the one or more processors to be further configured to (Lepine, [0045]; [0050]) : access a first storage unit over a system bus and acquire plant information, the plant information including an impact degree of an event, an event probability, a handling time for the event, and varying information including an operation history of the plant (Lepine, [0022]), “the analysis result of the equipment performance analytics may include a performance metric that indicates a present level of performance of equipment, a prediction for a future performance of equipment, information that identifies a set of X tasks (e.g., preventative maintenance tasks, repair tasks, tasks associated with observing ongoing performance of equipment, etc.) that may need to be performed on one or more items of equipment (e.g., in order to maintain or improve performance of the equipment)”, Examiner interprets a prediction for a future performance of equipment, information that identifies a set of X tasks to be event probability ; (Lepine, [0088]-[0089]), “The performance model compares the performance information, maintenance information, and operational state information for the steam turbine to a performance rule for the steam turbine… The performance model then outputs a result that indicates that the steam turbine is not performing as expected, and predicts that the performance of the steam turbine in the future (within one month) will not be as expected. The performance model then schedules a maintenance task for the steam turbine to be performed immediately. The immediate maintenance task is to remove the steam turbine blades to check for cracks and to repair the blades as appropriate”; (Lepine, [0078]); (Lepine, [0016]), “the analytics platform receives nuclear plant information from various sources in the nuclear plant… the nuclear plant information may include… operational information…”; (Lepine, [0056]), “the operational information may include maintenance information that describes a maintenance task (e.g., being performed, to be performed, previously performed) on equipment 215 in the nuclear plant, such as information that identifies the task, information that indicates progress of the task, information that identifies a date that the task was completed, or the like. As another example, the operational information may include information that identifies an operational state of equipment 215 (e.g., operational, not operational, damaged, offline, in repair, operating at peak performance, operating at Z % of peak performance, or the like)”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0055]; [0057]; [0082]-[0083]; [0092];[0111]); access a second storage unit over the system but and acquire operator information for plural plant operators including information on an owned qualification, a proficiency level, and a work status for operators of the plant (Lepine, [0078]); (Lepine, [0016]), “the analytics platform receives nuclear plant information from various sources in the nuclear plant… the nuclear plant information may include… worker information…”; (Lepine, [0098]), “worker information (e.g., in order to determine capability and/or availability of workers to perform the task)”; (Lepine, [0018]), “worker information may include information associated with a worker in the nuclear plant, such as dosimetry information related to a radiation dosage experienced by a worker, assigned task information that relates to a task to which a worker is assigned, training information that identifies a level of training of a worker, qualification information that identifies a level of qualification of a worker, or the like”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0060]-[0062]); access a third storage unit over the system bus and acquire work information of the plant including work contents, a work procedure, and a work difficulty level (Lepine, [0078]); (Lepine, [0016]), “the analytics platform receives nuclear plant information from various sources in the nuclear plant… the nuclear plant information may include… operational information… environmental information, inventory information, security information, or the like”; (Lepine, [0061]), “task information may include timing information (e.g., a time the worker started or is to start the task, a time that the worker completed or is to complete the task), a date associated with the task, information that identifies the task and/or the associated equipment 215, information that identifies a tool and/or a part needed for the task, progress information associated with a task being performed”; (Lepine, [0097]), “the maintenance value model may be designed to receive, as input, information associated with a set of tasks, such as a task name, an amount of time to complete the task, a level of training or qualification needed to perform the task, a tool needed for the task, a part needed for the task, information that identifies equipment 215 associated with the task, or the like.”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0025]; [0082]; [0101]; [0103]; [0125]); access the plant information stored in the plant information storage unit includes dynamic information such as plant parameters or an operation history (Lepine, [0078]), “since the nuclear plant information may be stored by analytics platform 220 within cloud computing environment 225 (e.g., rather than each worker device 210 and each item of equipment 215), memory resources and/or processing resources may be conserved on worker device 210 and/or equipment 215. Moreover, collection of the nuclear plant information from the many different sources (e.g., in real-time or near real-time) facilitates analysis of the nuclear plant information that may yield improved operation, performance, and/or maintenance, associated with the nuclear plant, as described below (e.g., as compared to a nuclear plant that operates in a traditional manner, without analytics platform 220). Furthermore, collection of the nuclear plant information from the many different sources (e.g., in real-time or near real-time) facilitates analysis of the nuclear plant information quickly and more efficiently”; (Lepine, [0111]), “plant-wide operation and/or maintenance may be achieved in real-time or near real-time. In some implementations, the analysis result may be updated (e.g., automatically) when analytics platform 220 receives additional nuclear plant information. For example, an analysis result of performing equipment performance analytics may be updated as analytics platform 220 receives additional operational information.); (Lepine, [0126]); process the plant information and identify one or more events occurring at the plant based on static event information and dynamic event information included in the plant information (Lepine, [0022]), “the analytics platform may perform an analysis of the nuclear plant information… the analysis result of the equipment performance analytics may include a performance metric that indicates a present level of performance of equipment, a prediction for a future performance of equipment, information that identifies a set of X tasks (e.g., preventative maintenance tasks, repair tasks, tasks associated with observing ongoing performance of equipment, etc.) that may need to be performed on one or more items of equipment (e.g., in order to maintain or improve performance of the equipment)”; (Lepine, [0083]); determine, for the plurality of plants, a priority for handling each identified event (Lepine, [0023]), “task valuation analytics may include an analysis associated with prioritizing, valuing, organizing, and/or scheduling a task associated with equipment in the nuclear plant”; (Lepine, [0024]), “an analysis result of the task valuation analysis may include a priority for the set of X tasks (e.g., a priority corresponding to each task), a schedule for performing the X tasks (e.g., including a date and/or time that each task is to be performed)”; (Lepine, [0072]), “the nuclear plant information may include information from multiple nuclear plants. This allows analytics platform 220 to operate based on nuclear plant information from multiple nuclear plants (e.g., such that analytics platform 220 may generate an analysis result for a first nuclear plant based on nuclear plant information from a second nuclear plant)”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0095]-[0096]; [0099]); schedule a work procedure for each plant on a basis of the determined handling priority for the plurality of plants and to output a plurality of work procedure schedules (Lepine, [0072]; [0074]); (Lepine, [0112]; [0115]), “a work package”; (Lepine, [0099]), “an analysis result of performing task valuation analytics may include information that identifies a priority, an order, or the like, for the set of tasks. In this way, tasks may be automatically prioritized such that tasks of higher value are performed first, which may lead to improved operational efficiency of equipment 215, reduced down time (e.g., since urgent tasks may be performed first), or the like. For example, the analysis result may include a set of scores, corresponding to each task, where each score represents a value (e.g., low, medium, high; a value from 1 to 10) for each task based on which a nuclear plant operator may schedule the set of tasks. As another example, the analysis result may include a prioritized list of the set of tasks (e.g., indicating an order in which the tasks should be performed)”; (Lepine, [0024]), “an analysis result of the task valuation analysis may include a priority for the set of X tasks (e.g., a priority corresponding to each task), a schedule for performing the X tasks (e.g., including a date and/or time that each task is to be performed)”; (Lepine, [0096]), “a maintenance value model designed to prioritize, schedule, and/or organize tasks”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0095]; [0104]; [0110]); set, for the plurality of plants, a plurality of parameters affecting operation of the plurality of plants during the one or more events, on a basis of the operator state and the handling priority determined for the plurality of plants (Lepine, [0023]), “analyzing the nuclear plant information, the analytics platform may perform task valuation analytics based on the nuclear plant. In some implementations, task valuation analytics may include an analysis associated with prioritizing, valuing, organizing, and/or scheduling a task associated with equipment in the nuclear plant”; (Lepine, [0027]), “the analytics platform may collect and analyze nuclear plant information, associated with the nuclear plant, and provide analysis results that support improved operation of the nuclear plant (e.g., by automatically determining performance results, identifying tasks to be performed, scheduling tasks and assigning workers, adjusting equipment parameters or settings without human intervention, or the like)”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0016]), “nuclear plant information”; (Lepine, [0095]), “Task valuation analytics may include an analysis associated with prioritizing, valuing, organizing, and/or scheduling a task”; (Lepine, [0072]; [0085]-[0086]), and calculate an impact on the operation of the plant integrated circuitry using the set plurality of parameters, and evaluate the work procedure schedules output based on calculated risk of impact on each plant (Lepine, [0083]), “analytics platform 220 may provide, as input to the performance model, one or more items of nuclear plant information and may receive, as an output, an analysis result associated with a performance of equipment 215. In some implementations, the analysis result of performing equipment performance analytics may include information that describes the performance of equipment 215, such as a current level of performance (e.g., relative to one or more other items of equipment 215, a performance metric, or the like), an indication whether the current performance is satisfactory (e.g., pass or fail), a performance score for the current performance (e.g., a value between 1 and 100, a grade from A to F, or the like), a metric associated with a change in performance (e.g., a percentage in degradation of performance over a period of time, such as a day, a week, a year, or the like), a prediction for a future level of performance, or the like. Additionally, or alternatively, the analysis result may include information that describes a task (e.g., a preventative maintenance task, a repair task, a task associated with observing ongoing performance of equipment 215, or the like), that may need to be performed for equipment 215. In other words, the analysis result may include information that describes a task associated with improving performance of equipment 215 or preventing degraded performance of equipment 215”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0094]-[0096]; [0099]; [0080]; [0106]); and send an evaluation result of the work procedure schedules to an output device for presentation to a user, the evaluation result including an operational response to the one or more identified events (Lepine, [0110]), “analytics platform 220 may provide information associated with the analysis result for display via worker device 210. For example, analytics platform 220 may provide information associated with an analysis result of performing equipment performance analytics in order to allow a worker and/or a nuclear plant operator to view information that describes the performance of an item of equipment 215. As another example, analytics platform 220 may provide information associated with an analysis result of performing task valuation analytics in order to allow a worker and/or a nuclear plant operator to view information that describes a priority of a set of tasks to be performed and/or a schedule generated for performing the set of tasks”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0056]), “the operational information may include maintenance information that describes a maintenance task (e.g., being performed, to be performed, previously performed) on equipment 215 in the nuclear plant, such as information that identifies the task, information that indicates progress of the task, information that identifies a date that the task was completed, or the like”; (Lepine, [0026]; [0033]; Fig. 4, [0109]; [0114]). Lepine teaches an analytics platform that may aggregate nuclear plant information from many different sources (see par. 0078, 0011) and task valuation analytics associated with prioritizing, valuing, organizing, and/or scheduling a task and determining a priority, an order, a schedule, and/or a value associated with a task (see par. 0095), but Lepine does not explicitly teach: acquire plant information associated with a plurality of plants; access a fourth storage unit configured to store an additional necessity determination rule of an operator of the plants; access the operator information stored in the operator information storage unit includes dynamic information such as the operator state or biometric information of an operator; determine an operator state by analyzing a work status and dynamic physical qualities of each operator including at least a workload and fatigue level based on the acquired operator information and the acquired work information; and calculating at least a risk of impact on the plant for each event and determining an operation procedure for each plant when the one or more events occur; determine necessity of operator addition based on the evaluation result according to the addition necessity determination rule; and contact a necessary operator according to the necessity determination circuitry. However Schuck teaches: acquire plant information associated with a plurality of plants (Schuck, [0029]), “The network 150 connects the plant management system 110, one or more operator devices 130, and one or more manufacturing plants 140. Although the below description describes a single manufacturing plant 140 being controlled/monitored by the plant management system 110, in some implementations, multiple manufacturing plants 140 may be controlled/monitored by the plant management system 110” ; and calculating at least a risk of impact on the plant for each event and determining an operation procedure for each plant when the one or more events occur (Schuck, [0054]), “Work order parameters 216 specify the impact of outstanding work order(s) on the operation of a particular plant device… the individual risk value for a work order can be computed by (1) assigning a weight to each work order risk factor with a corresponding value for that factor and (2) generating an aggregated weighted risk using the risk factor weights and their corresponding values”; (Schuck, [0060]) . At the time the invention was filed, it would have been obvious to a person of ordinary skill in the art to have modified the plant information for different sources and task valuation analytics in Lepine to include the plant and calculated risk limitations as taught by Schuck. The motivation for doing this would have been to improve the method of providing information associated with an analysis result of performing task valuation analytics in Lepine (see par. 0110) to efficiently include the results of adjusting operations based on an overall risk (see Schuck par. 0003). Lepine teaches task valuation analytics associated with prioritizing, valuing, organizing, and/or scheduling a task and determining a priority, an order, a schedule, and/or a value associated with a task (see par. 0095), determine capability and/or availability of workers to perform the task (see par. 0098) and an analytics platform that may identify a worker to which the work package is to be made available (see par. 0115), but Lepine does not explicitly teach: access a fourth storage unit configured to store an additional necessity determination rule of an operator of the plants; access the operator information stored in the operator information storage unit includes dynamic information such as the operator state or biometric information of an operator; determine an operator state by analyzing a work status and dynamic physical qualities of each operator including at least a workload and fatigue level based on the acquired operator information and the acquired work information; and determine necessity of operator addition based on the evaluation result according to the addition necessity determination rule; and contact a necessary operator according to the necessity determination circuitry. However Day teaches: access a fourth storage unit configured to store an additional necessity determination rule of an operator of the plants (Day, [0060]), “The system policy data 132d can also include resource information regarding restrictions or requirements of resources distribution and utilization… the system policy data 132d can also define provide rules or regulations regarding qualifications of workers for performing certain tasks (e.g., required skill set)”; (Day, [0057]), “The defined workflows can include information regarding the specific workflow events to be performed as well as rules regarding when, where, how and by whom the respective workflow events are to be performed…”; (Day, [0041]; [0077]) access the operator information stored in the operator information storage unit includes dynamic information such as the operator state or biometric information of an operator (Day, [0051]), “The operating conditions data 102b can also include information regarding staff, including the identities of staff currently working and/or available… The current staff information can also identify tasks and/or activities currently being performed by and/or assigned for performance by specific staff members. In this regard, the activity information can identify or indicate whether a staff member is available, busy, with a patient, when they will be available to perform another task and the like… the operating conditions data 102b can also include information regarding the current staff fatigue level, stress level and the like (e.g., captured via one or more medical monitoring/biofeedback devices)”; determine an operator state by analyzing a work status and dynamic physical qualities of each operator including at least a workload and fatigue level based on the acquired operator information and the acquired work information (Day, [0094]), “the resource allocation optimizer can further determine how to assign staff …while balancing staff workload (e.g., toward on equal distribution of the workload amongst the available staff) in view of staff availability, qualifications, and patient needs. The resource allocation optimizer can also apply constraints regarding assignment restrictions, shift constraints (e.g., timing of shifts, maximum and minimum job allocation per staff member per shift, etc.) and capacity constraints (e.g., regarding system capacity) in association with task assignment rules (e.g., fair distribution of task rules, policy, zone rules….”; (Day, [0052]), “the optimization component 118, in some implementations, staff scheduling, and assignments can be changed and updated in real-time to facilitate optimizing operations at the medical facility system based on a current and/or forecasted state of the medical facility system. Such changes in staff scheduling and assignments can also be reflected in the current operating conditions data 102b”; (Day, [0114]; [0116]); and determine necessity of operator addition based on the evaluation result according to the addition necessity determination rule (Day, [0086]), determine optimal reactive solutions regarding patient sequencing, patient placement and/or resource allocation that achieves and/or balances (e.g., in accordance with defined weights) the one or more optimization objectives (e.g., as provided by the optimization criteria data 132e) based on relevant parameters included in the current state data 102, the future state information (e.g., including the timeline forecasts 136 and/or the resource demand forecasts 138), and defined system constraints (e.g., system architecture constraints, defined workflow constraints, defined staffing constraints, and defined system rule/policy based constraints, as respectively provided by the medical facility system data 132) that control or influence patient sequencing and timing, placement and/or resource allocation…”; (Day, [0111]; [0034]; [0087]; [0094]; [0096]); and contact a necessary operator according to the necessity determination circuitry (Day, [0096]), “the output data 134 can be provided to relevant entities or users (e.g., staff at the medical facility) in real-time via a graphical user interface (GUI) tile at one or more devices associated with the relevant entities or users. The output data 134 can be reported using various suitable data structures (e.g., as machine readable text, as human readable text, as a graphical visualization, etc.) and/or electronic rendering applications”; (Day, [0112]), “The dashboard 800 can present a variety of relevant information regarding the timeline forecasts 136, the resource demand forecasts 138… the resource allocation solutions 144 and/or the alerts 606”; (Day, [0094]; [0052]; [0111]). At the time the invention was filed, it would have been obvious to a person of ordinary skill in the art to have modified the plant information, task valuation analytics and identified workers in Lepine to include the necessity determination rule and operator limitations as taught by Day. The motivation for doing this would have been to improve the method of providing information associated with an analysis result of performing task valuation analytics in Lepine (see par. 0110) to efficiently include the results of resource allocation that achieves and/or balances based on relevant parameters included in the current state data and defined system constraints (e.g., system architecture constraints, defined workflow constraints, defined staffing constraints, and defined system rule/policy based constraints) (see Day par. 0086). Referring to Claim 4, Lepine in view of Schuck in view of Day teaches the plant operation assistance system according to claim 1. Lepine further teaches: further comprising: a fifth storage unit configured to store an evaluation determination rule for a schedule of the work procedure for each plant (Lepine, [0078]); (Lepine, [0096]), “analytics platform 220 may analyze the nuclear plant information and/or information associated with a task (e.g., a task identified by an equipment performance analysis result, a task created by a worker and/or operator of the nuclear plant) using a maintenance value model designed to prioritize, schedule, and/or organize tasks”; (Lepine, [0077]), “analytics platform 220 may receive the nuclear plant information from another device, such as a user device via which a user inputs information for storage”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0097]; [0099]); wherein the one or more processors in further configured to: receive a schedule selection from a user (Lepine, [0099]), “the analysis result may include a set of scores, corresponding to each task, where each score represents a value (e.g., low, medium, high; a value from 1 to 10) for each task based on which a nuclear plant operator may schedule the set of tasks”; (Lepine, [0102]), “maintenance value model then analyzes this information and defines an order in which the tasks should be performed, along with a value of each task”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0104]); update the evaluation determination rule according to the received schedule (Lepine, [0096]), “generate the maintenance value model based on… an outcome associated with the task (e.g., a subsequent impact on performance)”; (Lepine, [0099]), “the analysis result may include information associated with a cost or a risk of not performing a task or delaying performance of the task. As such, risk assessment may be at least partially automated (e.g., by a plant operator), which may lead to more accurate risk assessment (e.g., as compared to risk assessment based on human intuition)”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0085]-[0086]; [0097]; [0107]; [0126]). Referring to Claim 5, Lepine in view of Schuck in view of Day teaches the plant operation assistance system of any one of claims 4. Lepine further teaches: wherein the one or more processor is further configured to: the schedules selected by the user; and notify each operator of the result of the schedule according to the received schedules (Lepine, [0024]), “the analytics platform may perform task valuation analytics for tasks identified based on user input to the analytics platform. As shown, an analysis result of the task valuation analysis may include a priority for the set of X tasks (e.g., a priority corresponding to each task), a schedule for performing the X tasks (e.g., including a date and/or time that each task is to be performed), information that identifies workers to be assigned to each of the set of X tasks, information that identifies a tool and/or a part that has been reserved and/or ordered in association with performing the task, or the like”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0077]). Referring to Claim 9, Lepine in view of Schuck in view of Day teaches the plant operation assistance system according to claim 3. Lepine further teaches: wherein the one or more processors is further configured to: receive the schedules selected by the user; and notify each operator of the result of the schedule according to the received schedules (Lepine, [0024]), “the analytics platform may perform task valuation analytics for tasks identified based on user input to the analytics platform. As shown, an analysis result of the task valuation analysis may include a priority for the set of X tasks (e.g., a priority corresponding to each task), a schedule for performing the X tasks (e.g., including a date and/or time that each task is to be performed), information that identifies workers to be assigned to each of the set of X tasks, information that identifies a tool and/or a part that has been reserved and/or ordered in association with performing the task, or the like”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0077]). Referring to Claim 10, the combination of Lepine in view of Schuck in view of Day teaches the plant operation assistance system according to claim 4. Lepine further teaches: wherein the one or more processors is further configured to: receive input the schedules selected by the user; and notify each operator of the result of the schedule according to the received schedules (Lepine, [0024]), “the analytics platform may perform task valuation analytics for tasks identified based on user input to the analytics platform. As shown, an analysis result of the task valuation analysis may include a priority for the set of X tasks (e.g., a priority corresponding to each task), a schedule for performing the X tasks (e.g., including a date and/or time that each task is to be performed), information that identifies workers to be assigned to each of the set of X tasks, information that identifies a tool and/or a part that has been reserved and/or ordered in association with performing the task, or the like”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0077]) . 07-21-aia AIA Claim s 2, 6-8, 11 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Lepine et al., U.S. Publication No. 2017/0117064 [hereinafter Lepine] , in view of Schuck et al., U.S. Publication No. 2023/0067083 [hereinafter Schuck] , in view of Day et al., U.S. Publication No. 2021/0193302 [hereinafter Day] , and further in view of Wolfe, U.S. Publication No. 2013/0073611 [hereinafter Wolfe] . Referring to Claim 2, Lepine in view of Schuck in view of Day teaches the plant operation assistance system according to claim 1. Lepine teaches providing information associated with the analysis result for display via worker device (see par. 0110), but Lepine does not explicitly teach: wherein the evaluation result of the schedules is presented by sectioning a display position in accordance with variables and values of the parameters when an event occurs. However Wolfe teaches: wherein the evaluation result of the schedules is presented by sectioning a display position in accordance with variables and values of the parameters when an event occurs (Wolfe, [0025]), “data is also manipulated by the data computer 20 with ftp uploads wherein operating parameters are displayed graphically in a tabular format which are color coded to provide an indication of normal operation, warning status or alarm conditions. The information from the sensors are used for determining critical information for the proper evaluation of reverse osmosis membrane performance per (salt rejection, permeate flow; feed/brine average rejection and simple rejection) which is normalized in accordance with AST Standards and graphically displayed for performance evaluation, preventative maintenance, scheduling, or for trouble shooting”; (Wolfe, [0026]). At the time the invention was filed, it would have been obvious to a person of ordinary skill in the art to have modified the displayed analysis result in Lepine to include the display limitations as taught by Wolfe. The motivation for doing this would have been to improve the method of providing information associated with an analysis result of performing task valuation analytics in Lepine (see par. 0110) to efficiently include the results of monitoring, maintaining supervising and trouble shooting process plant system performance (see Wolfe par. 0028). Referring to Claim 6, the combination of Lepine in view of Schuck in view of Day in view of Wolfe teaches the plant operation assistance system according to claim 2. Lepine further teaches: further comprising: a sixth memory device configure to store an addition necessity determination rule of an operator of the plants (Lepine [0078]); (Lepine, [0107]), “analyzing the nuclear plant information may include another type of analytics, such as worker analytics that facilitates assessment of workers and/or contractors (e.g., temporary employees). Here, analytics platform 220 may analyze historical information associated with a worker (e.g., a task name, a task type, a task start time, a task completion time, or the like) in order to improve assessment of productivity of the worker, training planning for the worker, planning and/or estimation of a future need for additional workers, or the like”; (Lepine, [0050]), “hardware circuitry and software”; determine necessity of operator addition according to the addition necessity determination rule (Lepine, [0113]), “the work package may include information for supporting performance of the task, such as… an interface that supports audio and/or video communication with a remote worker (e.g., such that the worker may communicate with the remote worker for assistance with performing the task), or the like”; (Lepine, [0126]), “provisioning of the analysis result may allow for improved (e.g., real-time or near real-time) plant-wide performance monitoring and reduced equipment 215 down time (e.g., due to efficient and organized task scheduling), while efficiently utilizing nuclear plant resources (e.g., parts, tools, workers)”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0014]; [0025]); and contact a necessary operator according-to an output of the operator addition necessity determination (Lepine, [0025]), “the analytics platform may provide the work packages to worker devices corresponding to workers that have been assigned to perform the respective tasks. For example, as shown, the analytics platform may provide a task 1 work package to worker device 3 that is carried by a worker assigned to perform task 1, and may provide a task X work package to worker device 5 that is carried by a worker assigned to perform task X”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0113]; [0122]). Referring to Claim 7, the combination of Lepine in view of Schuck in view of Day in view of Wolfe teaches the plant operation assistance system according to claim 2. Lepine further teaches: further comprising: a seventh memory device configure to store an evaluation determination rule for a schedule of the work procedure for each plant (Lepine, [0078]); (Lepine, [0096]), “analytics platform 220 may analyze the nuclear plant information and/or information associated with a task (e.g., a task identified by an equipment performance analysis result, a task created by a worker and/or operator of the nuclear plant) using a maintenance value model designed to prioritize, schedule, and/or organize tasks”; (Lepine, [0077]), “analytics platform 220 may receive the nuclear plant information from another device, such as a user device via which a user inputs information for storage”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0097]; [0099]); wherein the one or more processors is further configured to: receive a schedule selection from a user (Lepine, [0099]), “the analysis result may include a set of scores, corresponding to each task, where each score represents a value (e.g., low, medium, high; a value from 1 to 10) for each task based on which a nuclear plant operator may schedule the set of tasks”; (Lepine, [0102]), “maintenance value model then analyzes this information and defines an order in which the tasks should be performed, along with a value of each task”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0104]); update the evaluation determination rule according to the received schedule (Lepine, [0096]), “generate the maintenance value model based on… an outcome associated with the task (e.g., a subsequent impact on performance)”; (Lepine, [0099]), “the analysis result may include information associated with a cost or a risk of not performing a task or delaying performance of the task. As such, risk assessment may be at least partially automated (e.g., by a plant operator), which may lead to more accurate risk assessment (e.g., as compared to risk assessment based on human intuition)”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0107]). Referring to Claim 8, the combination of Lepine in view of Schuck in view of Day in view of Wolfe teaches the plant operation assistance system according to claim 2. Lepine further teaches: wherein the one or more processors is further configure to: receive the schedules selected by the user; and notify each operator of the result of the schedule according to the received schedule (Lepine, [0024]), “the analytics platform may perform task valuation analytics for tasks identified based on user input to the analytics platform. As shown, an analysis result of the task valuation analysis may include a priority for the set of X tasks (e.g., a priority corresponding to each task), a schedule for performing the X tasks (e.g., including a date and/or time that each task is to be performed), information that identifies workers to be assigned to each of the set of X tasks, information that identifies a tool and/or a part that has been reserved and/or ordered in association with performing the task, or the like”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0077]). Referring to Claim 11, the combination of Lepine in view of Schuck in view of Day in view of Wolfe teaches the plant operation assistance system according to claim 6. Lepine further teaches: wherein the one or more processors is further configured to: receive the schedules selected by the user; and notify each operator of the result of the schedule according to the received schedules (Lepine, [0024]), “the analytics platform may perform task valuation analytics for tasks identified based on user input to the analytics platform. As shown, an analysis result of the task valuation analysis may include a priority for the set of X tasks (e.g., a priority corresponding to each task), a schedule for performing the X tasks (e.g., including a date and/or time that each task is to be performed), information that identifies workers to be assigned to each of the set of X tasks, information that identifies a tool and/or a part that has been reserved and/or ordered in association with performing the task, or the like”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0077]). Referring to Claim 12, the combination of Lepine in view of Schuck in view of Day in view of Wolfe teaches the plant operation assistance system according to claim 7. Lepine further teaches: wherein the one or more processors is further configured to: receive the schedules selected by the user; and notify each operator of the result of the schedule according to the received schedule (Lepine, [0024]), “the analytics platform may perform task valuation analytics for tasks identified based on user input to the analytics platform. As shown, an analysis result of the task valuation analysis may include a priority for the set of X tasks (e.g., a priority corresponding to each task), a schedule for performing the X tasks (e.g., including a date and/or time that each task is to be performed), information that identifies workers to be assigned to each of the set of X tasks, information that identifies a tool and/or a part that has been reserved and/or ordered in association with performing the task, or the like”; (Lepine, [0050]), “hardware circuitry and software”; (Lepine, [0077]) . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Tamma et al. (US 20180247276 A1) – Variety of approaches to provide a workflow management with location, temporal, and biometric information are described. A scheduling service initiates operations to provide the workflow management upon receiving a start task signal from a client device of an employee at a start time-period associated with a task. The start task signal includes a biometric identifier associated with the employee, a location of the client device, and a task identifier of the task. The task is identified within a schedule using the task identifier. The schedule is composed by a manager of the employee. The biometric identifier is verified as matching the employee. The location of the client device is confirmed as within a geo-fenced area designated to the task. A status of the task is recorded as started within the schedule. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Crystol Stewart whose telephone number is (571)272-1691. The examiner can normally be reached 9:00am-5:00pm. 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, Patty Munson can be reached on (571)270-5396. 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. /CRYSTOL STEWART/Primary Examiner, Art Unit 3624 Application/Control Number: 18/258,364 Page 2 Art Unit: 3624 Application/Control Number: 18/258,364 Page 3 Art Unit: 3624 Application/Control Number: 18/258,364 Page 4 Art Unit: 3624 Application/Control Number: 18/258,364 Page 6 Art Unit: 3624 Application/Control Number: 18/258,364 Page 7 Art Unit: 3624 Application/Control Number: 18/258,364 Page 8 Art Unit: 3624 Application/Control Number: 18/258,364 Page 9 Art Unit: 3624 Application/Control Number: 18/258,364 Page 10 Art Unit: 3624 Application/Control Number: 18/258,364 Page 11 Art Unit: 3624 Application/Control Number: 18/258,364 Page 12 Art Unit: 3624 Application/Control Number: 18/258,364 Page 13 Art Unit: 3624 Application/Control Number: 18/258,364 Page 14 Art Unit: 3624 Application/Control Number: 18/258,364 Page 15 Art Unit: 3624 Application/Control Number: 18/258,364 Page 16 Art Unit: 3624 Application/Control Number: 18/258,364 Page 17 Art Unit: 3624 Application/Control Number: 18/258,364 Page 18 Art Unit: 3624 Application/Control Number: 18/258,364 Page 19 Art Unit: 3624 Application/Control Number: 18/258,364 Page 20 Art Unit: 3624 Application/Control Number: 18/258,364 Page 21 Art Unit: 3624 Application/Control Number: 18/258,364 Page 22 Art Unit: 3624 Application/Control Number: 18/258,364 Page 23 Art Unit: 3624 Application/Control Number: 18/258,364 Page 24 Art Unit: 3624 Application/Control Number: 18/258,364 Page 25 Art Unit: 3624 Application/Control Number: 18/258,364 Page 26 Art Unit: 3624 Application/Control Number: 18/258,364 Page 27 Art Unit: 3624 Application/Control Number: 18/258,364 Page 28 Art Unit: 3624 Application/Control Number: 18/258,364 Page 29 Art Unit: 3624 Application/Control Number: 18/258,364 Page 30 Art Unit: 3624 Application/Control Number: 18/258,364 Page 31 Art Unit: 3624
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