DETAILED CORRESPONDENCE
This Office action is in response to the application filed on 12/02/2024, with claims 1-12 pending.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 12/02/2024 and 12/01/2025 complies with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
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.
Regarding Claims 1-4 and 8-12
Claims 1-4 and 8-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 recites:
one or more processors; and
a storage medium configured to store road information and an algorithm configured to be run by the one or more processors, and storing computer-readable instructions that, when executed by the one or more processors, enable the one or more processors to:
perform control to receive driving guidance information and location information of an electric vehicle, and
output a guidance screen corresponding to the driving guidance information, wherein the driving guidance information includes charging guidance information intended to prevent a battery charge level of the electric vehicle from being lower than a target remaining battery charge level generated based on internal and external state information of the electric vehicle and current-driver information related to a current driver.
Step 1: Statutory category- Yes
The claim recites an apparatus. The claim falls within one of the four statutory categories. See MPEP 2106.03
Step 2A Prong one evaluation: Judicial Exception - Yes – Mathematical Concept.
In Step 2A, Prong one of the 2019 Patent Eligibility Guidance (PEG), a claim is to be analyzed to determine whether it recites subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) mental processes, and/ or c) certain methods of organizing human activity.
The Office submits that the foregoing bolded limitation(s) constitutes judicial exceptions in terms of “mathematical concept” because under its broadest reasonable interpretation, the limitations are a “relationship between variables or number”. See MPEP 2106.04(a)(2)(I).
The claim recites:
perform control to receive driving guidance information and location information of an electric vehicle
The “perform control” limitation, as drafted, under their broadest reasonable interpretation, is part of a mathematical process. The mere recitation of perform does not take this claim limitation out of the mathematical concept grouping because the claim language does not positively recite controlling the electrical vehicle.
Thus, claim 1 recites a mathematical process.
Step 2A Prong two evaluation: Practical Application – No
In Step 2A, Prong two of the 2019 PEG, a claim is to be evaluated whether, as a whole, it integrates the recited judicial exception into a practical application. As noted in MPEP 2106.04( d), it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception. The courts have indicated that additional elements such as: merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
The Office submits that the foregoing underlined limitation(s) recite additional elements that do not integrate the recited judicial exception into a practical application.
The claim recites the additional elements of:
a storage medium configured to store road information and an algorithm configured to be run by the one or more processors, and storing computer-readable instructions that, when executed by the one or more processors, enable the one or more processors to [data gathering—a pre-solution activity]:
output a guidance screen corresponding to the driving guidance information, wherein the driving guidance information includes charging guidance information intended to prevent a battery charge level of the electric vehicle from being lower than a target remaining battery charge level generated based on internal and external state information of the electric vehicle and current-driver information related to a current driver [data gathering—a post-solution activity].
These additional elements are merely insignificant extra solution activities. These claims does not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. These additional limitations are no more than mere data gathering.
Accordingly, even in combination, this additional elements does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Respectively, dependent claims 2-4 and 9-11, as a whole, do not integrate the recited judicial exception into a practical application.
Regarding claim 8 and 12. Claims 8 and 12 similar to claim 1; therefore, claims 8 and 12 are rejected under the same rationale of claim 1.
Step 2B evaluation: Inventive Concept: - No
In Step 2B of the 2019 PEG, the claim(s) is to be evaluated as to whether the claim, as a whole, amounts to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
As discussed with respect to Step 2A Prong Two, the additional elements in claims 2-4, 6, 7, and 9-11 amount to no more than mere data gathering step, data manipulation, insignificant extra solution activity and/or data output. The same analysis applies here in 2B, i.e., data manipulation and/or data output to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B, MPEP 2106.0S(f).
Thus, these claims are ineligible.
Regarding Claims 5-7
Claims 5-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 5 recites:
a driving information management server comprising:
one or more processors; and
a storage medium configured to store computer-readable instructions that, when executed by the one or more processors, enable the one or more processors to:
set up connections to exchange information with driving information display apparatuses of a plurality of electric vehicles;
receive internal and external state information and current-driver information of each of the plurality of electric vehicles; and
obtain a target remaining battery charge level for a given electric vehicle of the plurality of electric vehicles, based on the internal and external state information and the current-driver information of the plurality of electric vehicles, and transmit charging guidance information, generated using the target remaining battery charge level, to the given electric vehicle.
Step 1: Statutory category- Yes
The claim recites an apparatus. The claim falls within one of the four statutory categories. See MPEP 2106.03
Step 2A Prong one evaluation: Judicial Exception - Yes – Mathematical Concept.
In Step 2A, Prong one of the 2019 Patent Eligibility Guidance (PEG), a claim is to be analyzed to determine whether it recites subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) mental processes, and/ or c) certain methods of organizing human activity.
The Office submits that the foregoing bolded limitation(s) constitutes judicial exceptions in terms of “mathematical concept” because under its broadest reasonable interpretation, the limitations are a “relationship between variables or number”. See MPEP 2106.04(a)(2)(I).
The claim recites:
obtain a target remaining battery charge level for a given electric vehicle of the plurality of electric vehicles
The “obtain” limitation, as drafted, under their broadest reasonable interpretation, is part of a mathematical process. The mere recitation of obtain does not take this claim limitation out of the mathematical concept grouping because the claim language does not positively recite controlling the electrical vehicle.
Thus, claim 5 recites a mathematical process.
Step 2A Prong two evaluation: Practical Application – No
In Step 2A, Prong two of the 2019 PEG, a claim is to be evaluated whether, as a whole, it integrates the recited judicial exception into a practical application. As noted in MPEP 2106.04( d), it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception. The courts have indicated that additional elements such as: merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
The Office submits that the foregoing underlined limitation(s) recite additional elements that do not integrate the recited judicial exception into a practical application.
The claim recites the additional elements of:
a storage medium configured to store computer-readable instructions that, when executed by the one or more processors, enable the one or more processors to [data gathering—a pre-solution activity]:
set up connections to exchange information with driving information display apparatuses of a plurality of electric vehicles [data gathering—a pre-solution activity];
receive internal and external state information and current-driver information of each of the plurality of electric vehicles[data gathering—a post-solution activity];
These additional elements are merely insignificant extra solution activities. These claims does not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. These additional limitations are no more than mere data gathering.
Accordingly, even in combination, this additional elements does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Respectively, dependent claims 6 and 7 as a whole, do not integrate the recited judicial exception into a practical application.
Claim Rejections - 35 USC § 102
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.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-3, 5-10 and 12 are rejected under 35 U.S.C. 102(a)(1) as being anticipate by Girard et al., US 2023/0304813 hereinafter, “Girard”.
Claims 1, 8 and 12. Girard teaches a driving information display apparatus comprising:
one or more processors ([0050]—“a plurality of processors 114”); and
a storage medium configured to store road information and an algorithm configured to be run by the one or more processors, and storing computer-readable instructions that, when executed by the one or more processors ([0090]-[0093] reads on these elements as such—“The at least one processor can receive or retrieve pertinent data, such as from a non-transitory processor-readable storage medium at the vehicle (e.g. any of non-transitory processor-readable storage mediums 126), or from a remote device such as a server (e.g. management device 110 or device 130).”), enable the one or more processors to:
perform control to receive driving guidance information and location information of an electric vehicle (At 402, an indication of at least one trip to be performed by a vehicle is received. In a first example, an operator of a vehicle can input a desired destination or route into a route planning system.), and
output a guidance screen corresponding to the driving guidance information, wherein the driving guidance information includes charging guidance information intended to prevent a battery charge level of the electric vehicle from being lower than a target remaining battery charge level generated based on internal and external state information of the electric vehicle and current-driver information related to a current driver ([0128]-[0134] reads on this element as such—“FIG. 8 is a schematic diagram which illustrates an exemplary display 800. Display 800 presents a graphical user interface displayed to a user, which shows a map area 810 and energy information area…This estimated energy consumption is presented to the user via display 800 in Energy information area 820 (11 kWh, in the illustrated example). Display 800 also shows an amount of energy available in the vehicle battery in Energy information area 820 (20 kWh in the illustrated example). Amount of energy available could be identified based on a state of charge indication from the vehicle (e.g. received over port 702), or by determining battery level based on a measured voltage of the battery, as non-limiting examples….However, a safety threshold could also be considered, where the available energy should exceed the estimated energy consumption by a certain amount in order for the trip to definitively be indicated as possible, in the event that the estimated energy consumption is below an actual energy consumption for the trip.”).
Claims 2 and 9. Girard teaches the apparatus of claim 1, wherein the target remaining battery charge level is generated based on per-driver-artificial-intelligence-model information obtained by entering the internal and external state information into a per-driver artificial intelligence model that is generated by training on a driver charging information database that records the internal and external state information and an amount of electricity charged whenever the current driver previously charged the electric vehicle in a first past period of time ([0060] and [0093] reads on this element as such—“In an exemplary use case, device 130 may generate range metrics, models, or profiles as discussed in detail later for at least one plurality of vehicles, based on a large amount of vehicle data available to device 130….energy consumption by the vehicle to an amount of energy available to the vehicle (e.g. charge level or energy capacity of the vehicle battery). Based on the comparison, the at least one processor can determine whether completion of the trip is possible or not. Alternatively, the at least one processor can return a confidence score which indicates how likely it is the vehicle will be able to complete the trip. The at least one processor can also estimate expected energy remaining for the vehicle after the trip ( e.g. charge level of the battery after the trip), to provide an operator with the ability to assess travel options after arriving at the destination….”).
Claim 3 and 10. Girard teaches the apparatus of claim 2 and further teaches, wherein, in response to that the per-driver artificial intelligence model has not been generated for the current driver, the target remaining battery charge level is generated based on general-artificial-intelligence-model information obtained by entering the internal and external state information into a general artificial intelligence model that is generated by training on a general charging information database that records the internal and external state information and the amount of electricity charged whenever each of a large set of drivers previously charged their electric vehicles in a second past period of time ([0095]-[0096] reads on this element as such—“This could be performed manually by the operator, or could be automated. In some cases, trip data for previous routes may be accessible. For example, the operator's present vehicle can be equipped with telematics capabilities (e.g. a telematics monitoring device), which can collect trip data regarding where the vehicle has been driven to and from, speeds of travel, temperature data, braking events, or any other appropriate information. As another example, a navigation system of the operator's present vehicle may have travel history stored, which shows where the vehicle has been driven to. In either case, data which is not available can be determined or retrieved by at least one processor. For example, if speed data is not available, vehicle speed can be determined based on geographic position data and timestamps as discussed above. As another example, if temperature data is not available from the trip data, historical temperature data could be retrieved from a temperature data
provider. Based on data for the desired or historical routes and trips, the at least one processor can evaluate Formula (1) to estimate energy consumption for any pertinent number of trips, in accordance with act 404, for at least one candidate battery-powered vehicle under consideration. In accordance with act 406, the at least one processor can compare the estimated energy consumption to an amount of energy available to the vehicle. The compared energy consumption
can be for any number of trips sequentially (i.e., any number of trips on a single battery charge) as appropriate for a given application. If the operator is satisfied with the capabilities of a particular candidate vehicle for their needs, they can proceed to acquire said vehicle.”).
Claim 5. Girard teaches a driving information management server comprising:
one or more processors ([0050]—“a plurality of processors 114”); and
a storage medium configured to store computer-readable instructions that, when executed by the one or more processors, enable the one or more processors to:
set up connections to exchange information with driving information display apparatuses of a plurality of electric vehicles (fig. 1 along with fig. 2 best illustrates this element. [0051] teaches “example, management device 110 is shown as communicating with vehicle devices in four vehicles 120a, 120b, 120c, and 120d ( collectively referred to as vehicles 120). However, management device 110 could communicate with vehicle devices in any appropriate number of vehicles, such as one vehicle, dozens of vehicles, hundreds of vehicles, thousands of vehicles, or even more vehicles. In some exemplary implementations, management device 110 is a telematics server, which collects and stores telematics data for a fleet of vehicles”. [0139] teaches “In an illustrative example (applicable in the two preceding implementations), a fleet of vehicles operates during the day, and returns to a depot at night for charging. Energy consumption for each vehicle for the next day (i.e. energy consumption for at least one trip expected to be performed by the vehicle the next day) is estimated in accordance with method 200 (either by vehicles devices 122 or by management device 110).” Figure 8 illustrates the display. Thus, when taken together the cited section reads on this element);
receive internal and external state information and current-driver information of each of the plurality of electric vehicles (In other exemplary implementations, management device 110 is a location specific device, which manages vehicles for a particular location (or vehicles for a plurality of locations). In any of these examples, management device 110 can be used to monitor state of charge of batteries for vehicles, and thus can be used to prioritize charging of certain vehicles that need it most (e.g. because charge level is low, and/or is insufficient for an upcoming trip). In some implementations such prioritization of charging is performed on a per-location basis, to assist drivers and/or jockeys to couple vehicles to charge stations as appropriate to optimize charging of the fleet,); and
obtain a target remaining battery charge level for a given electric vehicle of the plurality of electric vehicles, based on the internal and external state information and the current-driver information of the plurality of electric vehicles, and transmit charging guidance information, generated using the target remaining battery charge level, to the given electric vehicle (Take together the cited sections describes this element as such—[0099] teaches –“Trips may be grouped on a per-vehicle basis, in order to determine whether at least one trip corresponding to each vehicle can be performed on a single charge of a battery of a candidate vehicle. That is, for each existing vehicle in the fleet, expected trips to be performed between opportunities to charge are identified or input. This could comprise each trip a vehicle is expected to perform in a day, where the vehicle will be charged overnight. Such identification of trips could be based on the actual trips each individual existing vehicle performs, in order to identify individually whether it would be feasible to replace each individual existing vehicle with a candidate battery-power vehicle.” While [0093] teaches –“estimated energy consumption by the vehicle to an amount of energy available to the vehicle ( e.g. charge level or energy capacity of the vehicle battery). Based on the comparison, the at least one processor can determine whether completion of the trip is possible or not. Alternatively, the at least one processor can return a confidence score which indicates how likely it is the vehicle will be able to complete the trip. The at least one processor can also estimate expected energy remaining for the vehicle after the trip ( e.g. charge level of the battery after the trip), to provide an operator with the estimated energy consumption by the vehicle to an amount of energy available to the vehicle ( e.g. charge level or energy capacity of the vehicle battery). Based on the comparison, the at least one processor can determine whether completion of the trip is possible or not. Alternatively, the at least one processor can return a confidence score which indicates how likely it is the vehicle will be able to complete the trip. The at least one processor can also estimate expected energy remaining for the vehicle after the trip ( e.g. charge level of the battery after the trip), to provide an operator with the”).
Claim 6. Girard teaches the server of claim 5 and further teaches, wherein the instructions further enable the one or more processors to:
in response to the given electric vehicle being charged, receive and store the internal and external state information and the current-driver information of the given electric vehicle in a driver charging information database for each given driver (example, management device 110 is shown as communicating with vehicle devices in four vehicles 120a, 120b, 120c, and 120d ( collectively referred to as vehicles 120). However, management device 110 could communicate with vehicle devices in any appropriate number of vehicles, such as one vehicle, dozens of vehicles, hundreds of vehicles, thousands of vehicles, or even more vehicles. In some exemplary implementations, management device 110 is a telematics server, which collects and stores telematics data for a fleet of vehicles); and
obtain the target remaining battery charge level based on per-driver-artificial-intelligence-model information obtained by entering the internal and external state information into a per-driver artificial intelligence model that is generated by training on the current-driver information of the driver charging information database corresponding to a current driver ([0060] reads on this element as such—“In an exemplary use case, device 130 may generate range metrics, models, or profiles as discussed in detail later for at least one plurality of vehicles, based on a large amount of vehicle data available to device 130 communicates such metrics, models, or profiles to management device 110, which management device 110 then uses to perform analysis, assessment, or prediction for similar vehicles in a fleet managed by management device 110 (e.g. vehicles 120). In this way, management device 110 can assess models for vehicles based on a large amount of statistical data that management device 110 itself does not have access to.”)
Claim 7. Girard teaches the server of claim 6 and further teaches, wherein the instructions further enable the one or more processors to:
store the internal and external state information and the current-driver information in a general charging information database that stores the internal and external state information and the current-driver information of a large set of drivers in an integrated manner (For example, weight coefficients α1, α2 , α3 , and a 4 can be retrieved from a database of information for the specific vehicle being operated (for example stored on at least one non-transitory processor readable storage medium 126 of a vehicle 120; or stored on at least one non-transitory processor-readable storage medium 116 or 136 remote from the vehicle). Further, the at least one processor can determine expected distance of the trip based on the route. Further, the at least one processor can determine expected duration of the trip, and expected speed profile during the trip, based on the determined distance and based on speed limits and/or typical travel speeds along roadways in the route (e.g. from a database which stores roadway information, for example stored on at least one non-transitory processor-readable storage medium 126 of a vehicle 120;); and
in response to that the per-driver artificial intelligence model has not been generated for the current driver, obtain the target remaining battery charge level based on general-artificial-intelligence-model information obtained by entering the internal and external state information of the current driver into a general artificial intelligence model that is generated by training on the general charging information database ([0062] teaches a scenario that reads on this element as such—“As another example, for an expected trip (i.e. a trip which has not yet occurred), expected data for the trip can be modeled. Such modeled data could include, as non-limiting examples: a plurality of expected geographic positions of the vehicle during the trip; a plurality of expected timestamps (e.g. a timestamp associated with each geographic position of the vehicle, or expected timestamps at the beginning or end of the trip); temperature data representing expected temperature of an environment of the vehicle; expected speed or velocity data of the vehicle; or any other appropriate data.”).
Claim Rejections - 35 USC § 103
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.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 4 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Girard in view of Conway, US 2011/0288765.
Claims 4 and 11. Girard teaches the apparatus of claim 1 and further teaches the concept of a charging station (see [0135], [0137]) along with weather information (see at least [0068], [0131] and fig. 2). However, Girard is silent on the term preferred. Yet, Conway teaches wherein the internal and external state information includes one of or any combination of:
a normalized value of a number of charging stations within a predetermined distance from a destination;
current-driver-fatigue information related to a fatigue level of the current driver generated based on an image from an internal camera of the electric vehicle;
preferred-charging-station information related to a preferred charging station generated based on brand information of a set of previously-used charging stations previously used by the current driver of the electric vehicle (Conway: [0012] reads on this element as such in some instances a driver may prefer to shop at preferred brand of charging station (e.g., ABC Electric Company vs. XYZ Electric Company), or may prefer to shop at the least expensive station);
incident-facilities information related to incident facilities of a given charging station generated based on whether the incident facilities of the given charging station were previously used by the current driver of the electric vehicle.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Conway with the invention Girard because such combination would provide refueling driving plan (Conway, [0001] and [0003]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANA D THOMAS whose telephone number is (571)272-8549. The examiner can normally be reached Monday - Friday 8 - 5.
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, Ramya Burgess can be reached at 571-272-6011. 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.
/A.D.T/ /RUSSELL FREJD/Examiner, Art Unit 3661 Primary Examiner, Art Unit 3661
Prosecution Insights