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 .
Claim Status
Claims 1-16 are pending and examined.
Information Disclosure Statement
The information disclosure statements (IDS) received on 12/26/2024 and 8/26/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Specification
The disclosure is objected to because of the following informalities:
The specification is replete with grammatical and syntax errors which make the content therein difficult to understand. Examples include:
Pg. 1, Lns. 14-15 of the instant Specification recites, “Business environment has encountered a drastic transformation in this decade due to stiff global competition”, which should read, “Business environments have encountered a drastic transformation in this decade due to stiff global competition” to be grammatically correct.
Pg. 1, Lns. 23-24 of the instant Specification recites, “In search of innovative ways to generate more profit, chemical reactor attracts the focus of plant managers and researchers”. It is unclear what this sentence intends to convey.
Pg. 2 Ln. 3 of the instant Specification recites, “Data is considered as new oil in current time”. However, it is unclear what this expression means.
Pg. 2 Lns. 29-31 of the instant Specification recites, “To tackle the above challenges US 9,892,238 B2 found a technique to detecting abnormal events in an ethylene oxide reaction process using multivariate statistical techniques and artificial neural network”, which should read, “To tackle the above challenges US 9,892,238 B2 found a technique to detect abnormal events in an ethylene oxide reaction process using multivariate statistical techniques and artificial neural network” to be grammatically correct.
Numerous other grammatical and syntax errors are found throughout the Specification, and must be corrected.
Appropriate correction is required.
Claim Objections
Claims 1, 7 and 10 are objected to because of the following informalities:
Regarding claim 1, Lns. 6-8 recite, “comparing the future value to a predefined reference and based on a result of said comparison; and generating the signal for adjusting the parameter”. However, this limitation is grammatically incorrect, as it does not link the step of generating the signal to the comparison, which is Applicant’s intent, as evidenced by Pg. 3 Lns. 17-23 of the instant Specification. The Examiner suggests amending the above limitation to recite, “comparing the future value to a predefined reference and based on a result of said comparison, generating the signal for adjusting the parameter”.
Regarding claim 7, 2nd to Last Ln. and Last Ln. each recite, “CO2”, which is a typo of “CO2”.
Further regarding claim 7, Last Ln. recites, “carbonate flow, density, temperature”. However, an “and/or” should precede “temperature” to be grammatically correct, as this is the last item in a list.
Regarding claim 10, the step “Analyzing (700) the second process data…” does not end in a comma, which is grammatically incorrect. A comma should be placed after “the second future value” to be grammatically correct.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 3-4, 7, and 10-16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
A broad range or limitation together with a narrow range or limitation that falls within the broad range or limitation (in the same claim) may be considered indefinite if the resulting claim does not clearly set forth the metes and bounds of the patent protection desired. See MPEP § 2173.05(c). In the present instance, claim 3 recites the broad recitation “a second…model”…, and the claim also recites “in particular a first principle-based kinetic, model…”, which is the narrower statement of the range/limitation. The claim(s) are considered indefinite because there is a question or doubt as to whether the feature introduced by such narrower language is (a) merely exemplary of the remainder of the claim, and therefore not required, or (b) a required feature of the claims.
Claim 4 is rejected at least for depending on claim 3, a rejected claim.
Claim 7 is similarly rejected for reciting, “internal reactor data, in particular – an age of a catalyst…and/or external reactor data, in particular – EO stripper bottom temperature and pressure…Cycle water system data, in particular water flow and temperature…CO2 removal system data, in particular carbonate flow, density, temperature”.
Claim 11 is similarly rejected for reciting, “Saturated hydrocarbon inlet concentration, in particular ethane inlet concentration…CO2 inlet concentration and/or the oxygen inlet concentration, in particular both the CO2 and oxygen inlet concentrations…”.
Claims 12-16 are rejected at least for depending on a rejected claim.
Regarding claim 10, 5th to Last Ln. -4th to Last Ln. recite, “a second predefined reference”. It is unclear if this second predefined reference is the same as or different from the second predefined reference previously recited in claim 10. For purposes of compact prosecution, the above limitation has been examined as, “the second predefined reference”.
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 1-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The subject matter eligibility test for the claims is shown below:
Step 1: Claim 1 is directed toward a method, which is a statutory category.
Step 2A, Prong One: Identify the law of nature/natural phenomenon/abstract idea.
Claim 1 recites predicting a future value for a parameter based on process data and comparing the future value to a predefined reference. The acts of predicting a future value for a parameter based on process data and comparing the future value to a predefined reference are a determination/evaluation-type mental process that can be practically performed in the human mind, particularly as the steps are performed at a high level of generality, and do not recite a specialized computer for performing the mental processes. Evaluation/determination-type mental processes are abstract ideas.
Step 2A, Prong Two: Has the abstract idea been integrated into a particular practical application?
No. After the prediction and comparison steps are made, the claim additionally recites generating a signal for adjusting the parameter based on a result of the comparison. However, this additional element amounts to no more than a recitation of the words “apply it” (or an equivalent). See MPEP 2106.05(f). The claim further recites measuring and/or acquiring process data of the process for ethylene oxide production. However, this is mere data-gathering that is necessary in order to perform the remainder of the claimed method steps, and is therefore insignificant extra-solution activity. See MPEP 2106.05(g).
Step 2B: Does the claim recite any elements which are significantly more than the abstract idea?
As previously stated in Step 2A Prong Two, Claim 1 additionally recites measuring and/or acquiring process data of the process for ethylene oxide production, and based on the comparison between the predicted future value and a predefined reference, generating the signal for adjusting the parameter. The step of measuring and/or acquiring process data is mere data-gathering that is necessary in order to perform the remainder of the claimed method steps, and is therefore insignificant extra-solution activity, and the step of generating the signal for adjusting the parameter is no more than a recitation of the words “apply it” (or an equivalent). See MPEP 2106.05(f) and MPEP 2106.05(g). Claim 1 recites the additional element of a process for ethylene oxide production. However, this limitation amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use. See MPEP 2106.05(h). Further, a process for ethylene oxide production is well-understood, routine, and conventional activity that is previously known to the industry. See MPEP 2106.05(d).
Further, with regards to the generically recited process for ethylene oxide production, the following prior art is relied upon to show that the above element is well-understood, routine, and conventional:
Wells et al. (US Pub. No. 2024/0150307; hereinafter Wells; already of record on the IDS received 8/26/2025) teaches a process for ethylene oxide production ([0034]).
Lee et al. (US Pub. No. 2024/0279193; hereinafter Lee) teaches a process for ethylene oxide production ([0001]).
Claim 2 recites the specifics of how the future value is predicted, by applying a genetic programming model and/or a kinetic based detail phenomenological model. A model is just an algorithm or a series of mental steps that are performed by a computer. A claim that requires a computer may still recite a mental process, particularly as the recitation “a genetic programming model and/or a kinetic based detail phenomenological model” is recited at a high level of generality, and amounts to a generic computer, where the computer is used as a tool to perform the concept of predicting the future value, i.e. the mental process-type abstract idea.
Claims 3 and 4, similarly to claim 2, recite different models used to predict the future value, and are similarly rejected under 35 U.S.C. 101.
Claim 5 recites that the process is performed in an ethylene oxide reactor, and the signal represents an adjustment of a process parameter formed in the reactor. These limitations do no more than associate the mental process-type judicial exception with the technological field of ethylene oxide production. Further, the recited step of the signal representing an adjustment of a process parameter amounts merely to the words “apply it”.
Claims 6-7 contain further details of how the process data is retrieved and what the process data comprises, and merely further describes the data-gathering, which is insignificant extra-solution activity.
Claim 8 recites training a genetic programming by using sensor data. A model is just an algorithm or a series of mental steps that are performed by a computer. A claim that requires a computer may still recite a mental process, particularly as the recitation “a genetic programming” is recited at a high level of generality, and amounts to a generic computer. Further, the genetic programming that is trained does not tie into the remainder of the method, and therefore does not amount to a particular practical application of the judicial exception, or significantly more than the judicial exception.
Claim 9 further describes the judicial exception of predicting a future value for the parameter, and that is predicted based on partial correlation co-efficient methodology and/or a combination of artificial neural network and genetic programming. A model is just an algorithm or a series of mental steps that are performed by a computer. A claim that requires a computer may still recite a mental process, particularly as the recitation “partial correlation co-efficient methodology and/or a combination of artificial neural network and genetic programming” is recited at a high level of generality, and amounts to a generic computer, where the computer is used as a tool to perform the concept of predicting the future value, i.e. the mental process-type abstract idea.
Claim 10 further recites measuring and/or acquiring second process data, which is mere data-gathering, and is insignificant extra-solution activity. Claim 10 additionally recites predicting a second future value for the parameter based on the second process data, analyzing the second process data with respect to the second future value, and comparing a result of the analysis to a second predefined reference. Similarly to the analysis of claim 1, this is a determination/evaluation-type mental process that can be practically performed in the human mind, particularly as the steps are performed at a high level of generality, and do not recite a specialized computer for performing the mental processes. Finally, claim 10 additionally recites that, based on the comparison, the signal for adjusting the parameter is amended, and/or a model used for modelling the ethylene oxide production process is invalidated. The step of amending a signal for adjusting the parameter amounts to no more than a recitation of the words “apply it”, while the step of invalidating a model based on the comparison is also a determination/evaluation-type mental process that can be practically performed in the human mind.
Claims 11-16 further define what the process data comprises, and merely further describe the data-gathering, which is insignificant extra-solution activity.
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 1-3 and 5-12 are rejected under 35 U.S.C. 103 as being unpatentable over Lahiri et al., “Model of Commercial Ethylene Oxide Reactor: A Hybrid Approach by Artificial Neural Network & Differential Evolution”, 2010, International Journal of Chemical Reactor Engineering, Vol. 8, Pgs. 1-28 (hereinafter Lahiri; already of record on the IDS received 12/26/2024) in view of Salhov et al. (US Pub. No. 2022/0299952; hereinafter Salhov).
Regarding claim 1, Lahiri discloses a method of modelling a process for ethylene oxide production (see Pgs. 4-6 at 1. Introduction, Pgs. 12-13 at 3. Differential Evolution (DE) at a glance, and Pgs. 15-22 at 5. Case study: Study of industrial ethylene oxide reactor) comprising the steps:
measuring and/or acquiring process data of the process for ethylene oxide production (Pg. 19 2nd to Last Para.).
predicting a future value for the parameter based on the process data (Pg. 20 Last Para., see Pg. 21 at Table 2).
Lahiri fails to explicitly disclose:
that the method is of generating a signal for adjusting a parameter of the process for ethylene oxide production; and that the method comprises:
comparing the future value to a predefined reference and based on a result of said comparison, generating the signal for adjusting the parameter.
Salhov is in the analogous field of systems and methods for optimally controlling a plant (Salhov [0002]). Salhov teaches a method of generating a signal for adjusting a parameter of a process for chemical production (Salhov; [0121]-[0122], [0180]-[0181]), where the method comprises comparing the future value to a predefined reference and based on a result of the comparison, generating a signal for adjusting the parameter (Salhov; [0121]-[0122], [0180]-[0181]). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to modify the method of Lahiri with the teachings of Salhov so that the method is of generating a signal for adjusting a parameter of a process for ethylene oxide production, the method comprising comparing the future value to a predefined reference and based on a result of said comparison, generating the signal for adjusting the parameter, as Salhov teaches that comparing predicted values of controlled variables to a target or setpoint, and iteratively adjusting the values of manipulated values to minimize the difference between the predicted values to the target or setpoint will optimize the chemical process (Salhov; [0121]-[0122], [0180]-[0181]).
Regarding claim 2, modified Lahiri discloses the method of claim 1. Modified Lahiri further discloses that the prediction of the future value is performed by applying the acquired process data to a genetic programming model and/or a kinetic based detail phenomenological model (Lahiri; Pg. 13 at 1st Para., Pg. 19 at 2nd to Last Para., the algorithm uses a combination of an artificial neural network and differential evolution).
Regarding claim 3, modified Lahiri discloses the method of claim 1. Modified Lahiri further discloses that the prediction of the future value is performed by applying the acquired process data to a combination of a genetic programming model and a second, in particular a first principle-based kinetic, model of the process (Lahiri; Pg. 13 at 1st Para., Pg. 19 at 2nd to Last Para., the algorithm uses a combination of an artificial neural network and differential evolution).
Regarding claim 5, modified Lahiri discloses the method according to claim 1. Modified Lahiri further discloses that the process is performed in an ethylene oxide reactor and the signal is representing an adjustment of a parameter of the process performed in said reactor (see Claim 1 above at Lahiri teaching an ethylene oxide reactor in Pgs. 4-6 at 1. Introduction, Pgs. 12-13 at 3. Differential Evolution (DE) at a glance, and Pgs. 15-22 at 5. Case study: Study of industrial ethylene oxide reactor, and Salhov teaching a signal represent an adjustment of a process parameter in [0121]-[0122], [0180]-[0181]).
Regarding claim 6, modified Lahiri discloses the method according to claim 1. Modified Lahiri further discloses that the process data are current data acquired by means of a sensor or wherein the process data are retrieved from a data storage device (Lahiri; Pg. 19 at 2nd to Last to Last Paras., see also Pg. 21 at Table 2. This process data is intrinsically retrieved from a data storage device).
Regarding claim 7, modified Lahiri discloses the method according to claim 1. Modified Lahiri further discloses that the acquired process data comprise: internal reactor data, in particular - an age of a catalyst, and/or - a selectivity of a catalyst and/or - a temperature and/or - a pressure and/or - inlet moisture and/or - inlet ethylene oxide concentration or amount - an ethane concentration and/or external reactor data, in particular - EO stripper bottom temperature and pressure and/or - Cycle water system data, in particular cycle water flow and temperature, and/or - CO2 regenerator bottom temperature and/or - CO2 removal system data, in particular carbonate flow, density, temperature (see Lahiri Pg. 21 at Table 2).
Regarding claim 8, modified Lahiri discloses the method according to claim 1. Modified Lahiri further discloses training a genetic programming by using sensor data of the process for ethylene production (Lahiri; Pg. 19 at 2nd to Last to Last Paras., the algorithm uses a combination of an artificial neural network and differential evolution, see also Pg. 21 at Table 2).
Regarding claim 9, modified Lahiri discloses the method according to claim 1. Modified Lahiri further discloses that the step of predicting a future value for the parameter based on the process data comprises using - partial correlation co-efficient methodology and/or - a combination of artificial neural network and genetic programming on the acquired process data (Lahiri; Pg. 19 at 2nd to Last to Last Paras., the algorithm uses a combination of an artificial neural network and differential evolution, see also Pg. 21 at Table 2).
Regarding claim 10, modified Lahiri discloses the method according to claim 1.
Modified Lahiri fails to explicitly disclose the steps of
Measuring (500) and/or acquiring second process data of the process for ethylene oxide production,
Predicting (600) a second future value for the parameter based on the second process data,
Analyzing (700) the second process data with respect to the second future value,
Comparing (800) a result of said analysis to a second predefined reference and based on a result of said comparison of said analysis to a second predefined reference
Amending (900) the signal for adjusting the parameter and/or
Invalidating (1000) a model used for modelling the process for ethylene oxide parameter.
Salhov further teaches a measuring/acquiring step of second process data, predicting a second future value, analyzing the second process data with respect to the second future value, comparing the analysis result to a second predefined reference and based on a result of said comparison amending the signal for adjusting the parameter (Salhov; [0121]-[0122], [0180]-[0181], the process of optimizing the value of the MV’s based on the error between the predicted value of the CV’s and target or setpoint values is iterative, i.e. the steps will be repeated multiple times). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to modify the method of modified Lahiri with the further teachings of Salhov to comprise the steps of measuring (500) and/or acquiring second process data of the process for ethylene oxide production, predicting (600) a second future value for the parameter based on the second process data, analyzing (700) the second process data with respect to the second future value, comparing (800) a result of said analysis to a second predefined reference and based on a result of said comparison of said analysis to a second predefined reference, amending (900) the signal for adjusting the parameter and/or invalidating (1000) a model used for modelling the process for ethylene oxide parameter, in order to iteratively adjust the values of manipulated values to minimize the difference between the predicted values to the target or setpoint, thereby optimizing the chemical process (Salhov; [0121]-[0122], [0180]-[0181]).
Regarding claim 11, modified Lahiri discloses the method according to claim 1, wherein the process data comprise or consist of at least one of:
a) Total inlet chloride moderator concentration
b) Saturated hydrocarbon inlet concentration, in particular ethane inlet concentration
c) CO2 inlet concentration and/or the oxygen inlet concentration, in particular both the CO2 and oxygen inlet concentrations
d) Moisture (H2O) inlet concentration
e) Work Rate
f) C2H4 (ethylene) inlet concentration and/or ethylene oxide inlet concentration (see Lahiri Pg. 21 at Table 2, which lists ethane inlet concentration, carbon dioxide concentration, and inlet concentration as input variables for the ANN).
Regarding claim 12, modified Lahiri discloses the method according to claim 11, wherein the process data are a combination of one or more of input variables a) to f) (see Lahiri Pg. 21 at Table 2, which lists ethane inlet concentration, carbon dioxide concentration, and inlet concentration as input variables for the ANN).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Lahiri in view of Salhov as applied to claims 1-3 and 5-12 above, and further in view of Wells.
Regarding claim 4, modified Lahiri discloses the method according to claim 3. Modified Lahiri further discloses that a prediction error of the model is minimized by an artificial intelligence-based data driven model (Lahiri Pg. 25 at 1st Para.).
Modified Lahiri fails to explicitly disclose that the model is a first principle-based kinetic model.
Wells is in the analogous field of ethylene oxide production (Wells [0034]). Wells teaches a first principle-based kinetic model (Wells [0140]). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to modify the method of modified Lahiri with the teachings of Wells so that the model is a first principle-based kinetic model, as Wells teaches that a kinetic model can be used to model the performance of an ethylene oxide production system (Wells [0140]), and would benefit from the error minimizing taught by Lahiri.
Claims 13-16 are rejected under 35 U.S.C. 103 as being unpatentable over Lahiri in view of Salhov as applied to claims 1-3 and 5-12 above, and further in view of Lee.
Regarding claim 13, modified Lahiri discloses the method according to claim 11.
Modified Lahiri fails to explicitly disclose that the process data are a combination of a) and b).
Lee is in the analogous field of ethylene oxide production (Lee [0001]). Lee teaches inlet chloride moderator concentration (Lee [0010]), ethane inlet concentration (Lee [0064]), carbon dioxide and oxygen inlet concentrations (Lee; [0073], [0075]), moisture inlet concentration (Lee [0075]), work rate (Lee [0130]), and ethylene inlet concentration (Lee [0074]) as variables for optimizing ethylene oxide production. It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to modify the method of modified Lahiri with the teachings of Lee so that the process data are a combination of a) to f), which thereby includes a) and b), as these variables can be used to optimize ethylene oxide production (Lee; [0010], [0065], [0073]-[0075], [0130]).
Regarding claim 14, modified Lahiri discloses the method according to claim 11.
Modified Lahiri fails to explicitly disclose that the process data are a combination of a) to c).
Lee teaches inlet chloride moderator concentration (Lee [0010]), ethane inlet concentration (Lee [0064]), carbon dioxide and oxygen inlet concentrations (Lee; [0073], [0075]), moisture inlet concentration (Lee [0075]), work rate (Lee [0130]), and ethylene inlet concentration (Lee [0074]) as variables for optimizing ethylene oxide production. It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to modify the method of modified Lahiri with the teachings of Lee so that the process data are a combination of a) to f), which thereby includes a) to c), as these variables can be used to optimize ethylene oxide production (Lee; [0010], [0065], [0073]-[0075], [0130]).
Regarding claim 15, modified Lahiri discloses the method according to claim 11.
Modified Lahiri fails to explicitly disclose that the process data are a combination of a) to d).
Lee teaches inlet chloride moderator concentration (Lee [0010]), ethane inlet concentration (Lee [0064]), carbon dioxide and oxygen inlet concentrations (Lee; [0073], [0075]), moisture inlet concentration (Lee [0075]), work rate (Lee [0130]), and ethylene inlet concentration (Lee [0074]) as variables for optimizing ethylene oxide production. It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to modify the method of modified Lahiri with the teachings of Lee so that the process data are a combination of a) to f), which thereby includes a) to d), as these variables can be used to optimize ethylene oxide production (Lee; [0010], [0065], [0073]-[0075], [0130]).
Regarding claim 16, modified Lahiri discloses the method according to claim 11.
Modified Lahiri fails to explicitly disclose that the process data are a combination of a) to e).
Lee teaches inlet chloride moderator concentration (Lee [0010]), ethane inlet concentration (Lee [0064]), carbon dioxide and oxygen inlet concentrations (Lee; [0073], [0075]), moisture inlet concentration (Lee [0075]), work rate (Lee [0130]), and ethylene inlet concentration (Lee [0074]) as variables for optimizing ethylene oxide production. It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to modify the method of modified Lahiri with the teachings of Lee so that the process data are a combination of a) to f), which thereby includes a) to e), as these variables can be used to optimize ethylene oxide production (Lee; [0010], [0065], [0073]-[0075], [0130]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to John McGuirk whose telephone number is (571)272-1949. The examiner can normally be reached M-F 8am-530pm.
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/JOHN MCGUIRK/Primary Examiner, Art Unit 1798
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