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 .
Status of claims: claims 1-20 are examined below.
Election/Restrictions
Upon further review the Restriction, dated 8/7/2025, has been withdrawn. Claims 1-20 are examined below.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 7/17/2023 was filed and considered. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claim 16 recites the limitation "…trained according to claims 6-12" in claim 16. There is insufficient antecedent basis for this limitation in the claim and the metes and bounds are unclear. Claim 16 is dependent on claim 13 that is dependent on claim 10, which is dependent on independent claim 8. Dependent claims 6, 7 and 9 are dependent on independent claim 1, which stand alone from independent claim 8. The metes and bounds of the claim is unclear. Examiner is unsure how claim 16 cross over different independent claims for training. Please amend with clarification on the proper dependency of the claims and what it is trained on.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claim 1 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 34 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 34 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 1.
Claim 2 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 44 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 44 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 2.
Claim 3 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 19 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 19 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 3.
Claim 4 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 2 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 2 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 4.
Claim 5 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 3 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 3 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 5.
Claim 6 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 22 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 22 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 6.
Claim 7 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 5 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 5 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 7.
Claim 8 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 22 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 22 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 8.
Claim 9 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 43 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 43 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 9.
Claim 10 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 22 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 22 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 10.
Claim 11 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 44 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 44 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 11.
Claim 12 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 19 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 19 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 12.
Claim 13 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 20 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 20 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 13.
Claim 14 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 12 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 12 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 14.
Claim 15 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 22 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 22 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 15.
Claim 16 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 22 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 22 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 16.
Claim 17 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 24 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 24 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 17.
Claim 18 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 22 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 22 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 18.
Claim 19 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 43 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 43 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 19.
Claim 20 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 22 of U.S. Patent No. 11,593,590. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 22 of U.S. Patent No. 11,593,590 anticipate the instant claims as presented claim 20.
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, 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.
Claims 1-2, 4 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Cheverton (US 2007/0116350) in view of GALLAGHER-GRUBER et al (US 2021/090238).
Claim 1:
Cheverton (US 2007/0116350) teaches the following subject matter:
A system for an image-based assay, comprising:
a sample holder comprising two plates that each has a sample contact area and sandwich a sample into a layer of a thickness of 200 um or less, wherein the sample contact area contact a sample contains or is suspected containing an analyte, wherein the sample contact area of one or both of the plates comprising a plurality of monitoring markers (figure 1 and 0021 teaches glass plate 24 and display film 4, sample holder that sandwich the analyte, with alignment guides 26 (plurality of monitor markers), where one ordinary in the art know the range of thickness of a model sandwich between sample holder and film is between 1-300 um);
an imager that takes one or more images of the sample contact area (figure 1 and 0022 teaches a low resolution scanning camera 12 and a high resolution camera 14 respectively that are used to capture images of the display film 4 or the mold and transmit these images to a control system 16, further 0022-0024);
and monitoring markers imaged using a low-quality imaging system and one or more images of the same sample and the same monitoring markers imaged using high-quality imaging system (paragraph 0022-0024 teaches automated detection system using an algorithm for series of process action to identify and filter number of defects alongside detecting fiducial marks (monitoring markers));
wherein a low quality imaging system comprise more imperfection than a high quality imaging system (0022-0024 detail low resolution images with defects where algorithm for series of process action to identify and filter number of defects as detail in 0024).
Cheverton teaches all the subject matter above, but not the following:
a first machine learning computer-readable storage medium that stores a machine learning model that was trained using one or more images of a sample
GALLAGHER-GRUBER et al (US 2021/090238) teaches the following subject matter:
a first machine learning computer-readable storage medium that stores a machine learning model that was trained using one or more images of a sample (paragraph 0119 teaches imaging for samples between slides, where 0171 detail quality assessment of the sample image with high and low region of interest that machine learning classifier are trained).
Cheverton and GALLAGHER-GRUBER et al are both in the field of image analysis especially imaging samples of interest between slides/plate/films for analysis such that the combine outcome is predictable.
Therefore it would have been obvious to one having ordinary skill before the effective filing date to modify Cheverton by GALLAGHER-GRUBER et al using machine learning trained using region of interest (ROI) extracted to identify regions of interest which match known respirable (eg asbestos) fibre images as disclosed by GALLAGHER-GRUBER et al in paragraph 0171.
Claim 2:
GALLAGHER-GRUBER et al further teaches:
The system of claim 1 further comprising a second machine learning model that corrects an imperfection in the one or more images using the monitoring marks (0029 teaches one or more machine learning, a second machine learning, for filtering such as background, diffusion pixel blob, where 0155 detail further filter for dirt (imperfection) for feature or edge).
Claim 3:
Cheverton further teaches:
The system of claim 1 further comprising a second imager (figure 1 and 0022 teaches camera 12 and 14 (second imager)).
Claim 4:
Cheverton further teaches:
The system of claim 1, further comprising:
a second sample holder that a second sample forming a thin layer on an imaging area of, wherein the second sample holder is a marked sample holder that comprising one or more monitoring marks on the imaging area of the second sample holder identical to the one or more monitoring marks on the first sample holder (figure 1 part 4 and 2);
imaging, using a low-quality imaging system, a second of the samples on the imaging area of the third sample holder (paragraph 0022 teaches low resolution camera 12 of sample on figure 1);
correcting, using the monitoring marks, an imperfection in the third image, generating a corrected third image (above teaches markers; paragraph 0010-0011 teaches correct of defect, filtering defect and stored to memory device (third image)); and
analyzing the transformed corrected third image using the machine learning model trained in claim 1 and generating an assay result (0045 teaches where corrective action are employed and used for classification purposes (machine learning)).
Claim 7:
Cheverton further teaches:
The system of any one of claims 1 and 2, wherein the first sample and the second sample are the same sample, and the first sample holder and the second sample holder are the same (figure 1 and 0021-0023 teaches sample holder 4 and 2 as one).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Cheverton (US 2007/0116350) in view of GALLAGHER-GRUBER et al (US 2021/090238) as applied to claim 1 above, and further in view of JACKSON et al (US 2022/0026699).
Claim 5:
Cheverton and GALLAGHER-GRUBER et al teaches all the subject matter above, but not the following:
The system of any one of claims 1, wherein the machine learning model comprises a cycle generative adversarial network (CycleGAN).
JACKSON et al teaches the following subject matter: The system of any one of claims 1-3, wherein the machine learning model comprises a cycle generative adversarial network (CycleGAN) (012 teaches using cycleGAN on images from camera imaging the XY plane, where 0058 detail the XY plane with sample plates capture with optics).
Cheverton and GALLAGHER-GRUBER et al and JACKSON et al are all in the field of image analysis of images of samples with optics such that the combine outcome is predictable.
Therefore it would have been obvious to one having ordinary skill before the effective filing date to modify Cheverton and GALLAGHER-GRUBER et al by JACKSON et al where the use of cycleGAN is the advantage of the cycle consistency approach is that it does not require perfect registration between the Z-sweeps and in-focus projection images. Imperfect registration may for instance occur when there is slight movement in X-Y plane when the camera as disclosed by JACKSON et al in 0012.
Claims 8-9 are rejected under 35 U.S.C. 103 as being unpatentable over Cheverton (US 2007/0116350) in view of Liu et al (US 2017/0357911).
Claim 8:
Cheverton (US 2007/0116350) teaches the following subject matter:
A method to train a machine learning model for image-based assays, the method comprising:
receiving a first image, captured by a first optical sensor, of a sample holder containing a sample, wherein the sample holder is fabricated with a standard of patterned structural elements at predetermined positions (figure 1 cameras 12 and 14 with sample holder 2 and 4 and paragraph 0021-0024 with mold that are cylindrical or flat with alignment guides 26 (predetermined positions));
identifying a first region in the first image based on locations of one or more structural elements of the patterned structural elements in the first image (0021-0024 teaches mold that are cylindrical or flat with alignment guides 26);
determining a spatial transform associated with the first region based on a mapping between the locations of the one or more structural elements in the first image and predetermined positions of one or more structural elements in the sample holder (0021-0024 teaches mold that are cylindrical or flat with alignment guides 26, where alignment are mapping between).
Cheverton teaches all the subject matter above, but not the following:
applying the spatial transform to the first region in the first image to calculate a transformed first region; and training the machine learning model using the transformed first image.
Liu et al teaches the following subject matter: applying the spatial transform to the first region in the first image to calculate a transformed first region; and training the machine learning model using the transformed first image (figure 3 step 310 and 0070, and 0082 teaches using of machine learning as well as OPC correction 999 of target to matches (spatial transform)).
Cheverton and Liu et al are both in the field of image analysis in the field of target/sample analysis using machine learning such that the combine outcome is predictable.
Therefore it would have been obvious to one having ordinary skill before the effective filing date to modify Cheverton by Liu et al such analysis accurately position the patterning device a feature into classes to target feature as disclosed by Liu et al in paragraph 0008.
Claim 9:
Cheverton teaches:
The system of claim 1, wherein the sample holder comprises a first plate, a second plate, and the patterned structural elements, and wherein the patterned structural elements comprise pillars embedded at the predetermined positions on at least one of the first plate or the second plate (figure 1 and 3 part 140, and paragraph 0021-0024).
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Cheverton (US 2007/0116350) in view of Liu et al (US 2017/0357911).
Claim 15:
Cheverton (US 2007/0116350) teaches the following subject matter:
A method for converting an assay image using a machine learning model, the method comprising:
receiving a first image, captured by a first optical sensor, of a sample holder containing a sample, wherein the sample holder is fabricated with a standard of patterned structural elements at predetermined positions (figure 1 cameras 12 and 14 with sample holder 2 and 4 and paragraph 0021-0024 with mold that are cylindrical or flat with alignment guides 26 (predetermined positions));
identifying a first region in the first image based on locations of one or more structural elements of the patterned structural elements in the first image (0021-0024 teaches mold that are cylindrical or flat with alignment guides 26);
determining a spatial transform associated with the first region based on a mapping between the locations of the one or more structural elements in the first image and predetermined positions of one or more structural elements in the sample holder (0021-0024 teaches mold that are cylindrical or flat with alignment guides 26, where alignment are mapping between).
Cheverton teaches all the subject matter above, but not the following:
applying the spatial transform to the first region in the first image to calculate a transformed first region; and applying the machine learning model to the transformed first region in the first image to generate a second region.
Liu et al teaches the following subject matter: applying the spatial transform to the first region in the first image to calculate a transformed first region; and applying the machine learning model to the transformed first region in the first image to generate a second region (figure 3 step 310 and 0070, and 0082 teaches using of machine learning as well as OPC correction 999 of target to matches (spatial transform)).
Cheverton and Liu et al are both in the field of image analysis in the field of target/sample analysis using machine learning such that the combine outcome is predictable.
Therefore it would have been obvious to one having ordinary skill before the effective filing date to modify Cheverton by Liu et al such analysis accurately position the patterning device a feature into classes to target feature as disclosed by Liu et al in paragraph 0008.
Claims 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Cheverton (US 2007/0116350) in view of Liu et al (US 2017/0357911).
Claim 18:
Cheverton (US 2007/0116350) teaches the following subject matter:
An image-based assay system, comprising:
a database system to store images (0024 teaches memory to storage of data); and
a processing device, communicatively coupled to the database system (figure 1 and paragraph 0022 teaches system 16 with computer/processor), to:
receive a first image, captured by a first optical sensor, of a sample holder containing a sample, wherein the sample holder is fabricated with a standard of patterned structural elements at predetermined positions (figure 1 cameras 12 and 14 with sample holder 2 and 4 and paragraph 0021-0024 with mold that are cylindrical or flat with alignment guides 26 (predetermined positions));
identify a first region in the first image based on locations of one or more structural elements of the patterned structural elements in the first image (0021-0024 teaches mold that are cylindrical or flat with alignment guides 26);
determine a spatial transform associated with the first region based on a mapping between the locations of the one or more structural elements in the first image and predetermined positions of one or more structural elements in the sample holder (0021-0024 teaches mold that are cylindrical or flat with alignment guides 26, where alignment are mapping between).
Cheverton teaches all the subject matter above, but not the following:
apply the spatial transform to the first region in the first image to calculate a transformed first region; and train the machine learning model using the transformed first image.
Liu et al teaches the following subject matter: apply the spatial transform to the first region in the first image to calculate a transformed first region; and train the machine learning model using the transformed first image (figure 3 step 310 and 0070, and 0082 teaches using of machine learning as well as OPC correction 999 of target to matches (spatial transform)).
Cheverton and Liu et al are both in the field of image analysis in the field of target/sample analysis using machine learning such that the combine outcome is predictable.
Therefore it would have been obvious to one having ordinary skill before the effective filing date to modify Cheverton by Liu et al such analysis accurately position the patterning device a feature into classes to target feature as disclosed by Liu et al in paragraph 0008.
Claim 19:
Cheverton teaches:
The system of claim 18, wherein the sample holder comprises a first plate, a second plate, and the patterned structural elements, and wherein the patterned structural elements comprise pillars embedded at the predetermined positions on at least one of the first plate or the second plate (figure 1 and 3 part 140, and paragraph 0021-0024).
Allowable Subject Matter
Claim 6 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, and overcoming the rejections above.
Claim 10, and dependent claims 13 and 16-17, are 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, and overcoming the rejections above.
Claim 11, and dependent claim 14, are 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, and overcoming the rejections above.
Claim 12 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, and overcoming the rejections above.
Claim 20 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, and overcoming the rejections above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lalpuria et al (US 2009/0257632) teaches Method For Measuring The Area Of A Sample Disposed Within An Analysis Chamber - area of an analysis chamber covered by a biologic fluid sample quiescently residing within the chamber is provided. The chamber has a first panel with an interior surface, and a second panel with an interior surface, both of which panels are transparent. The method includes the steps of: a) illuminating the sample residing within the analysis chamber at one or more wavelengths operable to highlight interfaces between the sample and air, and to highlight a constituent within the sample; b) imaging the sample along the one or more wavelengths, and producing image signals representative of the interaction of the one or more wavelengths with the sample; c) determining a location of at least one interface between the sample and air, using the image signals; d) determining a location of one or more constituents within the sample relative to the at least one sample-air interface using the image signals; and e) determining an area of the chamber containing the sample, using the location of the one or more constituents and the at least one sample-air interface.
Chou et al (US 2018/0202903) teaches BIO/CHEMICAL ASSAY DEVICES AND METHODS FOR SIMPLIFIED STEPS, SMALL SAMPLES, ACCELERATED SPEED, AND EASE-OF-USE – 0008 teaches a liquid sample can be placed in between two plates that are separated by spacers and analyzed. In theory, the volume of sample analyzed can be calculated by multiplying the area of the sample that is analyzed by the thickness of the sample that is analyzed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TSUNG-YIN TSAI whose telephone number is (571)270-1671. The examiner can normally be reached 7am-4pm.
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, Bhavesh Mehta can be reached at (571) 272-7453. 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.
/TSUNG YIN TSAI/Primary Examiner, Art Unit 2656