DETAILED ACTION
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 .
Response to Amendment
Examiner acknowledges receipt of Applicant’s amendments and arguments filed 05/13/2026. The arguments set forth are addressed herein below.
Applicant’s amendments necessitated the new ground of rejection set forth herein; therefore, this action is made Final.
Previous specification objection is withdrawn.
Previous rejections under 35 USC 112(b) and 35 USC 112 sixth paragraph are withdrawn.
Claims 1-11 are now pending.
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.
Claims 1 to 11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claimed invention is directed to non-statutory subject matter because the claim(s) as a whole, considering all claim elements both individually and in combination, is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The examiner follows the two step-analysis, as described in MPEP 2106 (available at https://www.uspto.gov/web/offices/pac/mpep/s2106.html). The following diagram is an overview of the steps involved.
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Step 1 of the two step-analysis considers whether the claims fall into one of the four statutory categories of invention such as a process, machine, manufacture, or composition of matter. The instant invention claims an information processing device, and an information processing method. As such, the claimed invention falls into the broad statutory categories of invention. However, claims that fall within one of the four statutory categories may nevertheless be ineligible if they encompass laws of nature, physical phenomena, or abstract ideas.
Step 2A has been further divided into two prongs as shown in the following diagram.
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Under prong 1 of step 2A, the examiner considers whether the claim recites an abstract idea, law of nature or natural phenomenon. The term “abstract idea” is not interpreted as a layperson might. Instead, the term “abstract idea” is interpreted as described in legal opinions by courts.
According to MPEP 2106.04(a):
the Office has set forth an approach to identifying abstract ideas that distills the relevant case law into enumerated groupings of abstract ideas. The enumerated groupings are firmly rooted in Supreme Court precedent as well as Federal Circuit decisions interpreting that precedent, as is explained in MPEP § 2106.04(a)(2). This approach represents a shift from the former case-comparison approach that required examiners to rely on individual judicial cases when determining whether a claim recites an abstract idea. By grouping the abstract ideas, the examiners’ focus has been shifted from relying on individual cases to generally applying the wide body of case law spanning all technologies and claim types.
The enumerated groupings of abstract ideas are defined as:
1) Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations (see MPEP § 2106.04(a)(2), subsection I);
2) Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) (see MPEP § 2106.04(a)(2), subsection II); and
3) Mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (see MPEP § 2106.04(a)(2), subsection III).
Here, representative claim 1 recites the following (with emphasis)(and similarly recited Claims 10 and 11): “Claim 1, and similarly recited Claims 10 and 11, (Currently Amended) An information processing device, comprising:
at least one processor configured to:
learn, through machine learning, first user on an application of a plurality of applications
perform, based on a result of the machine learning, an operation assistance process that assists a first [[an]] input by the first user on the application, wherein
in the operation assistance process, the at least one processor is further configured to:
determine, based on the result of the machine learning, whether to substitute the first input of the first user with a second input different from the first input and
provide, based on the determination, one of the first input of the first user or the second input to the application for execution
The underlined portions of representative claim 1 generally encompass the abstract idea, with substantially similar features in claims 10 and 11. The abstract idea may be viewed, for example, as:
use of machine learning in a given environment (e.g., for learning an action of a user) as discussed in Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205 (Fed. Cir. 2025); and/or
mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (see MPEP § 2106.04(a)(2), subsection III).
Like the claims in Recentive, the instant claims merely recite the use of generic machine learning applied to a given data environment. The Recentive court determined that claimed methods are not rendered patent eligible by the fact that using existing machine learning technology they perform a task previously undertaken by humans with greater speed and efficiency than could previously be achieved. The courts have consistently held, in the context of computer-assisted methods, that such claims are not made patent eligible under § 101 simply because they speed up human activity. The claims generally encompass the steps of learning, identifying, calculating, and assisting, which are steps that can be done in the human mind. The dependent claims further define the abstract idea by identifying correlations between user operations and outcomes; calculating or specifying input values based on learned correlations; and assisting, replacing, or coaching user input). These dependent claims include limitations that either further define the abstract idea (and thus don’t make the abstract idea any less abstract) or amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they’re merely incidental or token additions to the claims that do not alter or affect how the process steps are performed. Accordingly, each of Claims 1 to 11 recites an abstract idea.
Step 2A, Prong 2
Under prong 2 of step 2A, the examiner considers whether the additional elements in the claims integrate the abstract idea into a practical application. According to 2019 PEG, a consideration indicative of integration into a practical application includes improvements to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)) or adding a specific limitation other than what is well-understood, routine, conventional activity, or adding unconventional steps that confine the claim to a particular application (a non-conventional and non-generic arrangement of various computer components for filtering Internet content, as discussed in BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1350-51, 119 USPQ2d 1236, 1243 (Fed. Cir. 2016) (MPEP § 2106.05(d)). Conversely, considerations not indicative of integration include adding words “apply it” (or equivalent) with the judicial exception or mere instructions to implement the abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. (MPEP 2106.05(f)); adding insignificant extra-solution activity (MPEP 2106.05(g)), or generally linking the use of the abstract idea to a particular technological environment or field of use (MPEP 2106.05(h)).
Here, the abstract idea is not integrated into a practical application. Claims 1, 11, and 12 further recite at least one processor, an information processing device, generic machine learning, and/or a network, yet these are recited so generically (no details whatsoever are provided other than in name only) that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014).
The learning, performing, determining, and providing steps in the claims are deemed to be data gathering and data presentation for the use of the judicial exception and similarly are recited at a high level of generality. Thus, these limitations are a form of insignificant extra-solution activity (See MPEP 2106.05(g), See also selecting a particular source and type of data to be manipulated where “Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)).
Even when the limitations are viewed in combination, the additional elements in this claim do no more than automate the organizing activities needed to be performed, using the one of more computer components as tools. While this type of automation is an improvement in a general sense as opposed to performance manually, there is no change to the computers and other technology that are recited in the claim as automating the abstract ideas, and thus this claim cannot improve computer functionality or other technology. See, e.g., Trading Technologies Int’l v. IBG, Inc., 921 F.3d 1084, 1093 (Fed. Cir. 2019) (using a computer to provide a trader with more information to facilitate market trades improved the business process of market trading, but not the computer) and the cases discussed in MPEP 2106.05(a)(I), particularly FairWarning IP, LLC v. Latric Sys., 839 F.3d 1089, 1095 (Fed. Cir. 2016) (accelerating a process of analyzing audit log data is not an improvement when the increased speed comes solely from the capabilities of a general-purpose computer) and Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055 (Fed. Cir. 2017) (using a generic computer to automate a process of applying to finance a purchase is not an improvement to the computer’s functionality).
Furthermore, the additional elements do not serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Accordingly, Claims 1, 10, and 11 as a whole does not integrate the recited judicial exception into a practical application and these claims are directed to the judicial exception. Thus, Claims 1-11 lack the eligibility requirements of Step 2 Prong II.
STEP 2B
Finally, under step 2B, the examiner evaluates whether the additional elements:
add a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
The present claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements recite a learning unit and an assistance unit. These additional elements are generically claimed computer components which enable a game to be conducted by performing the basic functions of: (i) receiving, processing, and storing data, (ii) automating mental tasks and (iii) receiving or transmitting data over a network, e.g., using the Internet to gather data. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application.
Additionally, a claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. While the specification discusses the use of machine learning, it does not provide any indication that the machine learning themselves are improved in any way. In light of the court decision in Recentive, this is not sufficient to save a claim from abstraction. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
Furthermore, taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements in independent Claims 1, 10, and 11 (and their dependent Claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment. That is, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity. When viewed as a combination, these above-identified additional elements simply instruct the practitioner to conduct a game with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. The above-identified additional elements, when viewed as whole, 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.
For at least the above reasons, the apparatuses of Claims 1 to 11 are directed to applying an abstract idea (e.g., mental process) on a general purpose computer without (i) improving the performance of the computer itself (as in McRO, Bascom and Enfish), or (ii) providing a technical solution to a problem in a technical field (as in DDR). In other words, none of Claims 1 to 11 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Therefore, the claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. See Alice Corporation Pty. Ltd. v. CLS Bank International, et al., 573 U.S. 208 (2014).
AIA Notice
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Rejections - 35 USC § 103
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 of this title, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 1-2, 4, and 9 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by U.S Patent 11,724,186 B2 to Musbah et al.
Regarding Claim 1, and similarly recited Claims 10 and 11, (Currently Amended) Musbah discloses an information processing device, comprising:
at least one processor (fig. 6, Col. 16:30-65) configured to:
learn, through machine learning, first user on an application of a plurality of applications
perform, based on a result of the machine learning, an operation assistance process that assists a first [[an]] input by the first user on the application (fig. 4, Col. 7:13-20 discloses user interaction model 408 can use the actual user inputs and/or application outputs 410 to generate automated user inputs 412; see also Col. 7:26-33, Col. 9:52-56), wherein
in the operation assistance process, the at least one processor is further configured to:
determine, based on the result of the machine learning (see Claims 13-15, Col 12:10-18 discloses a predictive model can learn when to substitute predicted user input for actual user input, e.g., using additional features describing network conditions (e.g., latency, bandwidth, packet drops, etc.). Likewise, a predictive model can learn to combine predicted user input with actual user input to reduce the impact of disruptions on a user … Col. 12:23-32 discloses one or more triggering criteria can be used to determine whether the input adjudicator 416 selects the actual user inputs 406 or the automated user inputs 412), whether to substitute the first input of the first user with a second input different from the first input (figs. 3A-3E, illustrates an actual directional input 312 and a distinct automated directional input 314 and an actual trigger input 322 and a distinct automated trigger input 324, Col. 5:60 – Col. 6:6, 30-48 discloses in FIG. 3D, the automated directional input 314 is used instead of the stale most recently-received user input, and the automated directional input sharply turns the car to the left while the automated trigger input 324 reduces the throttle to slow the car 302. Thus, because the car is controlled by the automated user inputs during the disruption, the car continues down the road 304 without drifting off of the road) (the second input is thus different from and substituted for the first), and
provide, based on the determination, one of the first input of the first user or the second input to the application for execution
Regarding Claim 2, (Currently Amended) Musbah discloses the information processing device according to claim 1, wherein the application is a game application, and
the at least one processor is further configured to:
learn a the action of the first user performed before [[an]]the first input with respect to the first input in the game application and a result of the first input[[,]] (Col. 8:26-36 discloses prediction model 500 maintains time aligned windows of user input and application output - For instance, the following example assumes a one second time window. The preprocessing can include performing time alignment of the actual user input to corresponding frames of video and/or audio data; Col. 9:40-52 discloses The recurrent neural network 512 can also maintain internal recurrent state that can be used to represent previous output of the recurrent network, and this internal recurrent state can include information that is not present in the current input/output windows)(This is learning the correlation between actions performed before an input and the result of that output); and
based on [[uses ]]a learning result of the correlation, assist the first input by the first user so that a result of the first input by the first user becomes successful (Col. 8:26-36 discloses prediction model 500 maintains time aligned windows of user input and application output - For instance, the following example assumes a one second time window. The preprocessing can include performing time alignment of the actual user input to corresponding frames of video and/or audio data; Col. 9:40-52 discloses The recurrent neural network 512 can also maintain internal recurrent state that can be used to represent previous output of the recurrent network, and this internal recurrent state can include information that is not present in the current input/output windows)(This is learning the correlation between actions performed before an input and the result of that output).
Regarding Claim 4, (Currently Amended) Musbah discloses the information processing device according to claim 3, wherein the at least one processor is further configured to temporarily invalidate first input by the first user and replace first input by the first user with the second input
Regarding Claim 9, (Currently Amended) Musbah discloses the information processing device according to claim 2, wherein
the at least one processor is further configured to notify a second first user is assisted by the operation assistance process and the second user is different from the first user (fig. 6, Col. 15:50-65).
Claims 3, 5-7 are rejected under 35 U.S.C. 103 as being unpatentable over U.S Patent 11,724,186 B2 to Musbah et al. in view of U.S. Patent 10,576,380 B1 to Beltran et al. .
Regarding Claim 3, (Currently Amended) Musbah discloses the information processing device according to claim 2, but does not explicitly disclose wherein the at least one processor is further configured to:
calculate, for each pattern of the action performed before the first input, a of the second input that causes irst input to be successful , wherein the value of the second input is calculated based on the learning result of the correlation[[,]];
detect a pattern of the action performed before the first input by the first user; and based on the detection of [[a ]]the pattern of the action performed first input by the first user specify the value of the second input that corresponds to the detected pattern
In a related invention, Beltran discloses wherein the at least one processor is further configured to:
calculate, for each pattern of the action performed before the first input, a of the second input that causes irst input to be successful , wherein the value of the second input is calculated based on the learning result of the correlation[[,]] (Col. 22:12-30 discloses trained AI model 160 links learned paths and learned patterns to a given set of inputs relating to game paly of a scenario; Col. 26:15-19 discloses the input control sequence parser 147a of the analyzer 140 is configured to determine the sequence of controller inputs used by the player to control the game play);
detect a pattern of the action performed before the first input by the first user; and based on the detection of [[a ]]the pattern of the action performed first input by the first user specify the value of the second input that corresponds to the detected pattern
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Musbah’s user tuned input with Beltran’s trained game AI as Beltran expressly contemplates AI model taking over game play on the player’s behalf via task auto-play engine 145b (Col. 27:52-58). Each performs its established function and the combination yields no more than predictable results.
Regarding Claim 5, (Currently Amended) Musbah in view of Beltran discloses the information processing device according to claim 2, wherein the at least one processor is further configured to perform process that provides of performing coaching to the first user regarding [[on ]]the first input by the first user (Col. 34:61 – Col. 35:30).
Regarding Claim 6, (Currently Amended) Musbah in view of Beltran discloses the information processing device according to claim 5, wherein the at least one processor is further configured to perform executes the operation assistance process to provide the in first user (Col. 27:33-40, Col. 26:10-14).
Regarding Claim 7. (Currently Amended) Musbah discloses the information processing device according to claim 5, wherein the at least one processor is further configured to:
detect a pattern of the action performed before the first input by the first user (Col. 18:48-55, Col. 27:15-20); and
perform based on the detection of [[a ]]the pattern of the action performed before the first input process to provide, in real time, detected pattern of the operation action performed before the first input .
Allowable Subject Matter
Claim 8 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Response to Arguments/Remarks
Applicant’s arguments filed 05/13/2026 have been fully considered.
Regarding the rejection of the claims under 35 USC 102(a)(2) over Beltran, Applicant’s arguments at pages 14-17 are persuasive as to the “determine whether to substitute” and “provide one of the first input or second input” limitations only. Thus, this anticipation rejection is hereby withdrawn.
Regarding the rejection of the claims under 35 U.S.C. 101, Applicant’s arguments at pages 10-14 have been fully considered but are not persuasive. Under Step 2A, Prong 2, Applicant argues that the claims are not “merely an instruction to apply machine learning” it is a specific technical pipeline in which machine learning output is integrated into every step of an input processing mechanism that produces execution-level result. Here the claims, however, recite machine learning only functionally: “learn, through machine learning, an action of a first user on an application.” There is no model architecture, training procedure, or data structure claimed. This is similar to Recentive Analytics, Inc. v. Fox Corp, 134 F.4th 1205 (Fed. Cir. 2025), which held ineligible claims that do no more than apply established machine-learning methods to a new data environment and which rejected the argument that training a model on domain-specific supplies a technological improvement.
Regarding the analogies to Enfish and McRO, Enfish claimed a specific self-referential data structure that improved database operation itself. McRO recited specific rules that produced the automated result. The present claims recite no data structure and no rules – only that a model determines an outcome. A claim reciting a desired result without reciting how it is achieved does not integrate the exception into a practical application. Two-Way Media Ltd. v. Comcast Cable Commc’ns, LLC, 874 F.3d 1329, 1337 (Fed. Cir. 2017).
The improvement cited from specification paragraphs [0033]-[0034] – improving “convenience” in gameplay by the user regardless of the game application – is an improvement to the user’s experience, not to the computer or any technology. Trading Techs. Int’l, Inc. v. IBG LLC, 921 F.3d 1084, 1090 (Fed. Cir. 2019).
Under Step 2B, Applicant is correct that eligibility must consider the element as an ordered combination, and that BASCOM can supply an inventive concept from a non-conventional arrangement. BASCOM, however, turned on the placement of a known filtering tool at a particular network location, combined with individually customizable filtering – an arrangement of components producing a benefit that neither location could achieve alone.
The ordered combination Applicant identifies here – lean from user actions, then determine whether to substitute, then provide one input or the other – is the recited abstract idea presented in sequence. Beyond “at least one processor” and “an application” no components are arranged in an ordered combination.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHAUNA-KAY HALL whose telephone number is (571)270-1419. The examiner can normally be reached M-F 9:00AM-5:00PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Xuan Thai can be reached at (571) 272-7147. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/S.N.H/Examiner, Art Unit 3715
/XUAN M THAI/Supervisory Patent Examiner, Art Unit 3715
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