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. Information Disclosure Statement The information disclosure statement s (IDS) were submitted on 02/05/2024 and 03/14/2024 . The submission s are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement s are being considered by the examiner. Claim Status Claim(s) 1 , 3-8, 13, 18, 19 are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Yu (US 20190110776 A1) . Claim (s) 2, 9-10, 12, 23-24 are rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Crawford (US 20220270762 A1) . Claim (s) 11 is rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Crawford (US 20220270762 A1) and in further view of Isgum (US 20210334963 A1) . Claim (s) 15 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Isgum (US 20210334963 A1) . Claim (s) 20 is rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Schlager (US 6024705 A) Claim (s) 22 is rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Isgum (US 20210334963 A1) and in further view of Haase (US 20200390345 A1) . Claim (s) 14 is rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Janssen (Janssen, J. P., Koning, G., de Koning, P. J. H., Tuinenburg, J. C., & Reiber, J. H. C. (2002). A novel approach for the detection of pathlines in X-Ray angiograms: the wavefront propagation algorithm. The International Journal of Cardiovascular Imaging , 18 (5), 317–324. https://doi.org/10.1023/A:1016004005730) . Claim (s) 16-17 is rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of So ( US 20230346330 A1 ) . 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. (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claim(s) 1 , 3-8, 13, 18, 19 are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Yu (US 20190110776 A1) . Regarding claim 1, Yu discloses A computer-implemented method for characterizing a property of microvascular tissue ( ¶26 “ calculation of … index of microcirculation resistance based on the high precision registration model. ” ) that is supplied with blood via a coronary artery under investigation, the method comprising : ( ¶26 “ calculation of coronary blood flow” ) i) obtaining an x-ray angiographic image sequence of the coronary artery under investigation ( ¶26 “ comprises acquisition of coronary angiography of coronary vessels, ” ) acquired while contrast agent flows into and through the coronary artery under investigation; ( ¶27 “ Coronary angiography uses X-ray to generate projections of human body along a certain direction by injecting contrast through vessels, ” ) ii) using the angiographic image sequence of i) to determine a volumetric flow rate for flow through the coronary artery under investigation; and ( ¶35 “ compute coronary blood flow using equation (1): ” ) iii) determining an index that represents a property of the microvascular tissue that is supplied with blood via the coronary artery under investigation based on the volumetric flow rate of ii). ( ¶ 40 “ the said index of microcirculation resistance is determined ” ) Regarding claim 3 , Yu discloses wherein the volumetric flow rate is based on flow velocity of a contrast bolus front within the angiographic image sequence of i) and cross-sectional area of the coronary artery ( ¶39 “ As illustrated in FIG. 2, the lumen volume between L.sub.p and L.sub.d and the pressure drop calculation method require intravascular imaging to accurately determine vessel area at each cross-section. ” ) under investigation at multiple positions along the coronary artery under investigation within the angiographic image sequence of i). ( ¶13 “ and measure the transit time of the contrast traveling through the vessel segment, and compute the lumen volume of the vessel segment in the high precision registration model, and calculate blood flow based on equation (1) ” ) Regarding claim 4 , Yu discloses wherein the volumetric flow rate is based on propagation time of a contrast bolus front within the angiographic image sequence of i) and a vessel volume for the coronary artery of interest. ( ¶13 “ and measure the transit time of the contrast traveling through the vessel segment, and compute the lumen volume of the vessel segment in the high precision registration model, and calculate blood flow based on equation (1) : ” ) Regarding claim 5 , Yu discloses wherein the vessel volume is determined from a 3D reconstruction of the coronary artery of interest. ( ¶36 “ The lumen volume between L.sub.p and L.sub.d can be determined based on the three dimensional models of the vessel ” ¶39 “ determine the lumen borders of the vessel in each frame, based on which reconstruction of the blood vessel model can be conducted, ” Yu discloses Fig. 2 displ a ys a 3 D reconstruction of the vessel ) Regarding claim 6 , Yu discloses wherein the vessel volume is based on determining one or more diameters of the coronary artery of interest along the of the coronary artery of interest. ( ¶ 37 “ In particular, the precision of vessel diameter d is of paramount importance. ” ) Regarding claim 7 , Yu discloses wherein the flow velocity of the contrast bolus front is determined from distance that the contrast bolus front travels in the angiographic image sequence of i) as a function of time. ( ¶13 “ and measure the transit time of the contrast traveling through the vessel segment, and compute the lumen volume of the vessel segment in the high precision registration model, and calculate blood flow based on equation (1) : ” ) Regarding claim 8 , Yu discloses wherein the flow velocity of the contrast bolus front is determined from image analysis of the angiographic image sequence of i), wherein the image analysis determines a proximal position for the coronary artery of interest, ( ¶ 15 “ The method to measure the contrast transit time ΔT inside the vessel segment is to inject contrast at the proximal end of the vessel, ” ) a proximal position for the coronary artery of interest, a vessel path extending along the coronary vessel of interest between the proximal position to the distal position, and propagation of the contrast bolus front along the vessel path. ( ¶ 15 “ Then the contrast transit time is obtained as ΔT=T.sub.d−T.sub.p, where T.sub.p is the contrast arriving time at the proximal end of the vessel segment, and T.sub.d is the contrast arriving time at the distal end of the vessel segment. ” ) Regarding claim 13 , Yu discloses wherein the proximal position is determined from detection of position of a guiding catheter used for injection of the contrast agent into the coronary vessel of interest. ( ¶15 “ The method to measure the contrast transit time ΔT inside the vessel segment is to inject contrast at the proximal end of the vessel, ” ) Regarding claim 18 , Yu discloses wherein the index comprises quantitative data that represents amount of dysfunction or resistance in the microvascular tissue that is supplied with blood via the coronary artery under investigation. ( ¶26 “ a method to compute coronary indexes based on a high precision model … calculation of … index of microcirculation resistance ” ) Regarding claim 19 , Yu discloses wherein determining a pressure drop associated with the coronary artery under investigation; ( ¶36 “ The coronary blood flow Q determined from equation (1) can be used in subsequent calculations of pressure drop and FFR. ” ) wherein the index of iii) is determined from the volumetric flow rate of ii) and the pressure drop ¶36 “ The coronary blood flow Q determined from equation (1) can be used in subsequent calculations of pressure drop and FFR. ” Blood flow Q refers to volumetric flow rate as disclosed in ¶13 “ measure the transit time of the contrast traveling through the vessel segment, and compute the lumen volume of the vessel segment in the high precision registration model, and calculate blood flow based on equation (1) : ” ) 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. Claim (s) 2, 9-10, 12 , 23-24 are rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Crawford (US 20220270762 A1) . Regarding claim 2 , Yu discloses the claimed invention except for wherein the operations of i) to iii) are performed automatically by a processor without human input. In related art, Crawford discloses the operations of i) to iii) are performed automatically by a processor without human input. ( Crawford: ¶ 23 “ a non-transitory computer-readable memory medium having instructions stored thereon is provided, that when loaded by at least one processor cause the at least one processor to : receive medical images of a patient and metadata associated with the medical images indicative of a selected pathology … generate physiological information associated with the selected pathology for the 3D surface mesh model based on the extracted information. ” ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate a processor to automatically perform the function of the invention disclosed by Crawford into the method of microvascular coronary flow characteristic determination disclosed by Yu to automate the process of capturing images of coronary arteries and performing analysis to extract information from the captured images . Regarding claim 9 , Yu discloses the claimed invention except for wherein at least one of the proximal position and the distal position is determined using artificial intelligence and/or deep learning techniques. In related art, Crawford discloses at least one of the proximal position and the distal position is determined using artificial intelligence and/or deep learning techniques. ( Crawford: ¶80 “ For example, the start and end points may be determined via a machine learning algorithm that explores the anatomical knowledge dataset to derive the start and end points of the isolated anatomical feature ” ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate the start point or end point being determined by a machine learning algorithm disclosed by Crawford into the method of microvascular coronary flow characteristic determination disclosed by Yu to determine the start and end of the coronary artery being examined . Regarding claim 10 , Yu , as modified by Crawford, disclose the claimed invention except for wherein the artificial intelligence and/or deep learning techniques ( Crawford: ¶7 “ a neural network or machine learning algorithm is trained to identify the anatomical features within a set of medical images ” ) employ dichotomous image segmentation. ( Crawford: ¶11 “ the classified patient specific anatomical features generated using the segmentation algorithm described above are delineated into binary labels, e.g., bone/not bone, vessel/not vessel, organ/not organ, etc. ” ) I t would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate binary segmentation disclosed by Crawford into the method of microvascular coronary flow characteristic determination disclosed by Yu to define one class containing the anatomical feature of interest and another class not containing the anatomical feature of interest. Regarding claim 12, Yu, as modified by Crawford disclose wherein the artificial intelligence and/or deep learning techniques employ ( Crawford: ¶7 “ a neural network or machine learning algorithm is trained to identify the anatomical features within a set of medical images ” ) a vesselness filter applied to multiple image frames of the angiographic image sequence of i). ( Crawford: ¶72 “ Anatomical feature identification module 116 may then use an anatomical feature identification algorithm to explore the anatomical knowledge dataset to identify the patient specific anatomical features within the medical images … existing knowledge may include known information regarding various anatomic features such as …blood vessel” ) I t would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate the a machine learning algorithm for vessel detection and analysis disclosed by Crawford into the method of microvascular coronary flow characteristic determination disclosed by Yu to determine characteristics about vessels of interest such as start points and end points . Regarding claim 23 , Yu discloses the claimed invention except for wherein A non-transitory computer readable medium, having stored thereon, instructions, which when executed by a computing device, cause the computing device to perform the method according claim 1. In related art, Crawford discloses A non-transitory computer readable medium, having stored thereon, instructions, which when executed by a computing device, cause the computing device to perform the method according claim 1. ( Crawford: ¶23 “ a non-transitory computer-readable memory medium having instructions stored thereon is provided, that when loaded by at least one processor cause the at least one processor to : receive medical images of a patient and metadata associated with the medical images indicative of a selected pathology … generate physiological information associated with the selected pathology for the 3D surface mesh model based on the extracted information. ” ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate a non-transitory computer readable medium containing executable instructions disclosed by Crawford into the method of microvascular coronary flow characteristic determination disclosed by Yu to store the process of capturing images of coronary arteries and performing analysis to extract information from the captured images . Regarding claim 24 , Yu discloses wherein characterize a property of microvascular tissue that is supplied with blood via a coronary artery under investigation. ( Yu: ¶10 “ propose a more precise method to computationally … index of microcirculation resistance. ” ) Yu fails to specifically disclose An apparatus for acquiring an image data set of a patient, the apparatus comprising a data processing module configured to perform the method according to claim 1 to In related art, Crawford discloses An apparatus for acquiring an image data set of a patient, the apparatus comprising a data processing module configured to perform the method according to claim 1 to ( Crawford: ¶23 “ a non-transitory computer-readable memory medium having instructions stored thereon is provided, that when loaded by at least one processor cause the at least one processor to : receive medical images of a patient and metadata associated with the medical images indicative of a selected pathology … generate physiological information associated with the selected pathology for the 3D surface mesh model based on the extracted information. ” ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate a processor to automatically perform the function of the invention disclosed by Crawford into the method of microvascular coronary flow characteristic determination disclosed by Yu to automate the process of capturing images of coronary arteries and performing analysis to extract information from the captured images . Claim (s) 11 is rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Crawford (US 20220270762 A1) and in further view of Isgum (US 20210334963 A1) . Regarding claim 11, Yu , as modified by Crawford, disclose the artificial intelligence and/or deep learning techniques ( Crawford: ¶7 “ a neural network or machine learning algorithm is trained to identify the anatomical features within a set of medical images ” ) and time between image frames. ( Yu: ¶15 “ The method to measure the contrast transit time ΔT inside the vessel segment is to inject contrast at the proximal end of the vessel, and record the time of the first frame of the coronary angiography T.sub.1, the time of the second frame T.sub.2, and so forth ” ) Yu, as modified by Crawford fails to specifically disclose employ additional information selected from the groups consisting of vessel type, rotation and angulation used in image acquisition, ECG information, heart dominance information, In related art, Isgum discloses employ additional information selected from the groups consisting of vessel type, ( Isgum: ¶25 “ At least one aim of CCTA is to identify cardiac and coronary artery anatomy ” ) rotation and angulation used in image acquisition, ( Isgum: ¶79 “ The gantry provides for rotating the X-ray source and detector at a continuous speed during the scan around the patient who is supported on a table between the X-ray source and detector. ” ) ECG information, ( Isgum: ¶128 “ When an Electro Cardio Gram (ECG) is available from the patient, its characteristics can be used as additional information. ” ) heart dominance information, ( Isgum: ¶132 “ Other features that can be used are … coronary tree dominance ” ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate the use of vessel type information, rotation during image acquisition, ECG information, and coronary tree dominance information disclosed by Isgum into the method of microvascular coronary flow characteristic determination and machine learning techniques disclosed by Yu, as modified by Crawford to analyze features of coronary arteries . Claim (s) 15 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Isgum (US 20210334963 A1) . Regarding claim 15, Yu discloses the claimed invention except for wherein the microvascular tissue is part of the myocardium. In related art, Isgum discloses the microvascular tissue is part of the myocardium. ( Isgum: ¶1 4 “ The status of myocardial microvasculature indicates if a certain portion of the heart can be regarded to be healthy ” ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate analyzing the microvascular tissue of the myocardium disclosed by Isgum into the method of microvascular coronary flow characteristic determination and disclosed by Yu to analyze the microvascular tissue of the heart . Regarding claim 21, Yu discloses the claimed invention except for wherein the index comprises quantitative data that represents the ratio of flow through the coronary artery under investigation at rest relative to flow through the coronary artery under investigation in the hyperemic state. In related art Isgum discloses the index comprises quantitative data that represents the ratio of flow through the coronary artery under investigation at rest relative to flow through the coronary artery under investigation in the hyperemic state. ( Isgum: ¶139 “ the reference value (603) can be the measured coronary flow reserve ” ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate calculating the coronary flow reserve (CFR) disclosed by Isgum into the method of microvascular coronary flow characteristic determination disclosed by Yu to use CFR as an index assessing coronary artery function . Claim (s) 20 is rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Schlager (US 6024705 A) Regarding claim 20 Yu discloses the claimed invention except for wherein the index of iii) is normalized based on at least one parameter selected from the group consisting of cardiac mass, coronary volume, coronary artery cross-sectional area, patient weight, height, body surface area (BSA) or body mass index (BMI), heart dominance, or combinations thereof. In related art, Schlager discloses the index of iii) is normalized based on at least one parameter selected from the group consisting of cardiac mass, coronary volume, coronary artery cross-sectional area, patient weight, height, body surface area (BSA) or body mass index (BMI), heart dominance, or combinations thereof. ( Schlager: Col 7 lines 35-38 “ Height and weight of the patient are also required to calculate an estimate of body surface area which is used in determining certain cardiac indexes which normalize cardiac output based on body surface area. ” ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate utilizing body surface area to normalize cardiac indexes disclosed by Schlager into the method of microvascular coronary flow characteristic determination disclosed by Yu to process data such that it is easier to do extract and compare information from various sources . Claim (s) 22 is rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Isgum (US 20210334963 A1) and in further view of Haase (US 20200390345 A1) . Regarding claim 22, Yu, as modified by Isgum, disclose the claimed invention except for wherein using the at least one angiographic image of i) to determine a first volumetric flow rate for flow through the coronary artery under investigation with the patient in a rest state; using the at least one angiographic image of i) to determine a second volumetric flow rate for flow through the coronary artery under investigation with the patient in an active/hyperemic state; and determining the index from the first and second volumetric flow rates. In related art Haase discloses using the at least one angiographic image of i) to determine a first volumetric flow rate for flow through the coronary artery under investigation with the patient in a rest state; ( Haase: ¶25 “ A flow ratio like the Coronary Flow Reserve (CFR), which corresponds to the ratio of the volumetric flow rate under hyperemic (Q.sub.H) and resting (Q.sub.R) conditions may thus be derived ” ) using the at least one angiographic image of i) to determine a second volumetric flow rate for flow through the coronary artery under investigation with the patient in an active/hyperemic state; and ( Haase: ¶25 “ A flow ratio like the Coronary Flow Reserve (CFR), which corresponds to the ratio of the volumetric flow rate under hyperemic (Q.sub.H) and resting (Q.sub.R) conditions may thus be derived ” ) determining the index from the first and second volumetric flow rates. ( Haase: ¶25 “ A flow ratio like the Coronary Flow Reserve (CFR), which corresponds to the ratio of the volumetric flow rate under hyperemic (Q.sub.H) and resting (Q.sub.R) conditions may thus be derived ” ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate calculating coronary flow reserve (CFR) by calculating volumetric flow rate at rest and during hyperemia disclosed by Haase into the method of microvascular coronary flow characteristic determination disclosed by Yu, as modified by Isgum to use coronary flow reserve as an index representing coronary artery function . Claim (s) 14 is rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of Janssen (Janssen, J. P., Koning, G., de Koning, P. J. H., Tuinenburg, J. C., & Reiber, J. H. C. (2002). A novel approach for the detection of pathlines in X-Ray angiograms: the wavefront propagation algorithm. The International Journal of Cardiovascular Imaging , 18 (5), 317–324. https://doi.org/10.1023/A:1016004005730) . Regarding claim 14 , Yu discloses the claimed invention except for wherein the vessel path is determined using a wave propagation algorithm between the proximal position and distal position. In related art, Janssen discloses the vessel path is determined using a wave propagation algorithm between the proximal position and distal position. ( Janssen: Page 319-320 “ To achieve this, one proximal point and two distal points are needed … we can use solely one single wave and let it propagate ” Janssen discloses utilizing a wave propagation algorithm between the proximal and distal position ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate the wave propagation algorithm disclosed by Janssen into the method of microvascular coronary flow characteristic determination disclosed by Yu to determine the pathline between a proximal end and distal end within an artery . Claim (s) 16 -17 is rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20190110776 A1) in view of So ( US 20230346330 A1 ) . Regarding claim 16, Yu discloses the claimed invention except for wherein the volumetric flow rate of ii) is characteristic of volumetric flow rate for part of a cardiac cycle. In related art, So discloses the volumetric flow rate of ( So: ¶71 “ As the volumetric flow rate describes the volume of blood passes through per unit time ” ) ii) is characteristic of volumetric flow rate for part of a cardiac cycle. ( So: ¶26 “ FIG. 9B shows image acquisition covering a full cardiac cycle ” ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate volumetric flow rate as a characteristic of the cardiac cycle disclosed by So into the method of microvascular coronary flow characteristic determination disclosed by Yu to observe blood flow characteristics across a cardiac cycle . Regarding claim 17, Yu discloses the claimed invention except for wherein the volumetric flow rate of ii) is characteristic of average flow velocity and average volumetric flow rate over a cardiac cycle. In related art, So discloses the volumetric flow rate of ii) is characteristic of average flow velocity and average volumetric flow rate ( So: ¶71 “ As the volumetric flow rate describes the volume of blood passes through per unit time ” The volume of blood passing per unit of time discloses flow velocity and flow rate ) over a cardiac cycle. ( So: ¶26 “ FIG. 9B shows image acquisition covering a full cardiac cycle ” ) Therefore, it would have been obvious to for one of ordinary skill in the art before the effective filing date to incorporate volumetric flow rate as a characteristic of the cardiac cycle disclosed by So into the method of microvascular coronary flow characteristic determination disclosed by Yu to observe blood flow characteristics across a cardiac cycle . Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure : Edic (US 20170325770 A1) discloses a non-invasive methodology for estimation of coronary flow and/or fractional flow reserve. In certain implementations, various approaches for personalizing blood flow models of the coronary vasculature are described. The described personalization approaches involve patient-specific measurements and do not assume or rely on the resting coronary flow being proportional to myocardial mass. Consequently, there are fewer limitations in using these approaches to obtain coronary flow and/or fractional flow reserve estimates non-invasively. So (US 20210228171 A1) discloses a computer implemented method for dynamic angiographic imaging including: obtaining image data comprising a plurality of corresponding images capturing at least a portion of both an increase phase and a decline phase of a contrast agent in a blood vessel of interest; generating at least one time-enhancement curve of the contrast agent based on the image data; determining a blood flow characteristic in the blood vessel of interest based on the time-enhancement curve. Systems for implementing the method and computer readable media incorporating the method are also described. Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT MICHAEL KIM MAIDEN whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (703)756-1264 . The examiner can normally be reached FILLIN "Work Schedule?" \* MERGEFORMAT Monday - Friday 7:30 am - 5:00 pm . 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, FILLIN "SPE Name?" \* MERGEFORMAT Stephen Koziol can be reached at FILLIN "SPE Phone?" \* MERGEFORMAT 4089187630 . 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. /MICHAEL KIM MAIDEN/ Examiner, Art Unit 2665 /BOBBAK SAFAIPOUR/ Primary Examiner, Art Unit 2665