DETAILED ACTION
Claims 17-18 are pending. Claims 1-16 and 19-20 are cancelled.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments, filed 12/12/25, have been fully considered but are not persuasive, except where noted below.
Applicant’s arguments regarding the rejections of claims 1-16 under 35 U.S.C. § 112 and 35 U.S.C. § 101 (page 4) are persuasive and these claims are no longer rejected under those statutes.
Applicant’s arguments regarding the rejections of claims 17-18 under 35 U.S.C. § 112 (page 4) are persuasive and the claims are no longer rejected under that statute.
Applicant’s arguments regarding 35 U.S.C. § 102 (page 4) are moot as the claims are not rejected under that statute.
Applicant’s arguments regarding 35 U.S.C. § 103 and claims 17-18 (page 4) are not persuasive in view of the new grounds of rejection for these claims detailed below and that include the newly cited reference Martinez.
For at least these reasons, the rejection of the claims is maintained.
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.
Claim(s) 17-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because the claimed invention is directed to the abstract idea (mental process) of predicting a shutdown alarm based on data.
Claim 18 recites a system for anticipating shutdown alarms with respect to a boiler, i.e. a machine, which is a statutory category of invention. The claim recites:
generating at least one prediction of one or more of the shutdown alarms that may be performed in the human mind, or by a human using a pen and paper. Thus the claim recites an abstract idea (mental processes), see MPEP 2106.04(a).
This judicial exception is not integrated into a practical application because the additional elements, i.e. a boiler system having a controller and a plurality of sensors associated with a plurality of internet of things (IoT) devices/sensors comprising a first controller supported on or proximate to the boiler, wherein the boiler is a lead boiler that operates with one or more lag boilers; a plurality of sensors associated with the plurality of internet of things (IoT) devices and also supported on or positioned proximate to the boiler (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), wherein the sensors are configured to sense a plurality of parameters regarding the boiler and to provide a plurality of first signals regarding the sensed parameters to the controller; a gateway device of the boiler, wherein either the first signals or second signals based at least indirectly upon the first signals are sent to the gateway device; at least one communications device by which either the first signals, the second signals, or third signals based at least indirectly upon the first signals or second signals, are sent for receipt by a cloud computing system (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d) and applying the exception with generic computer technology, see MPEP 2106.04(a)(2) III C)), for use in either developing the one or more machine learning models (intended use), using machine learning models (applying the exception with generic computer technology using a known algorithm, see MPEP 2106.04(a)(2) III C), and a display configured to receive at least one fourth signal indicative of the at least one prediction of the one or more of the shutdown alarms, and to display either the at least one prediction or one or more alerts in response to the at least one prediction, by way of an application programming interface (API) (insignificant extra-solution elements – merely using generic computer technology, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d), MPEP 2106.04(a)(2) III e.g. receiving or transmitting data over a network, and see MPEP 2106.04(a)(2) III A regarding displaying information and MPEP 2106.05(d)) does not impose any meaningful limits on practicing the abstract idea. The claim is therefore directed to an abstract idea.
Note that a boiler system having a controller and a plurality of sensors is well-understood, routine and conventional, see Bohan and Michaud previously cited and the other references cited in the rejection under 35 U.S.C. § 103. In addition, machine learning, including LSTM and random forest machine learning, is well-understood, routine and conventional, see Tai et al. U.S. Patent Publication No. 20200334516 [0142] and Chen et al. U.S. Patent Publication No. 20200106788 [0032] previously cited. Also note that lead/lag boiler systems are well-understood, routine and conventional, see Bader U.S. Patent No. 4598668 [abstract, cols. 1-2], Christiansen U.S. Patent No. 5172654 [col. 1, lines 13-36] and Kovalcik et al. U.S. Patent Publication No. 20130099014 [0020] previously cited.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, a boiler system having a controller and a plurality of sensors associated with a plurality of internet of things (IoT) devices/sensors comprising a first controller supported on or proximate to the boiler, wherein the boiler is a lead boiler that operates with one or more lag boilers; a plurality of sensors associated with the plurality of internet of things (IoT) devices and also supported on or positioned proximate to the boiler (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), wherein the sensors are configured to sense a plurality of parameters regarding the boiler and to provide a plurality of first signals regarding the sensed parameters to the controller; a gateway device of the boiler, wherein either the first signals or second signals based at least indirectly upon the first signals are sent to the gateway device; at least one communications device by which either the first signals, the second signals, or third signals based at least indirectly upon the first signals or second signals, are sent for receipt by a cloud computing system (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d) and applying the exception with generic computer technology, see MPEP 2106.04(a)(2) III C)), for use in either developing the one or more machine learning models (intended use), using machine learning models (applying the exception with generic computer technology using a known algorithm, see MPEP 2106.04(a)(2) III C), and a display configured to receive at least one fourth signal indicative of the at least one prediction of the one or more of the shutdown alarms, and to display either the at least one prediction or one or more alerts in response to the at least one prediction, by way of an application programming interface (API) (insignificant extra-solution elements – merely using generic computer technology, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d), MPEP 2106.04(a)(2) III e.g. receiving or transmitting data over a network, and see MPEP 2106.04(a)(2) III A regarding displaying information and MPEP 2106.05(d)) does not impose any meaningful limits on practicing the abstract idea and are not considered significantly more. Considering the additionally elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. Thus the claim is not patent eligible.
Claim 17 recites the at least one communications device includes at least one wireless communications device (applying the exception with generic computer technology, see MPEP 2106.04(a)(2) III C). Thus this claim recites an abstract idea.
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 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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Khalate et al. U.S. Patent Publication No. 20180373234 (hereinafter Khalate) in view of Park et al. U.S. Patent Publication No. 20180232459 (hereinafter Park) and further in view of Bohan U.S. Patent Publication No. 20100298980 (hereinafter Bohan) and Martinez U.S. Patent No. 4966127 (hereinafter Martinez).
Regarding claim 17, the combination of Khalate, Park, Bohan and Martinez teaches all the limitations of the base claims as outlined just below.
Further, Khalate teaches the at least one communications device includes at least one wireless communications device [0051, Fig. 4 — communications interfaces 407 and/or BMS interface 409 can be direct (e.g., local wired or wireless communications) or via a communications network 446 (e.g., a WAN, the Internet, a cellular network, etc.); 0098 — Communications via interface 710 can be direct (e.g., local wired or wireless communications) or via an intermediate communications network 446 (e.g., a WAN, the Internet, a cellular network, etc.).; 0136-0138, Fig. 13 — Communications via interface 1310 can be direct (e.g., local wired or wireless communications) or via an intermediate communications network 446 (e.g., a WAN, the Internet, a cellular network, etc.)… variable monitor 1318 may receive temperature data from one or more temperature sensors of HVAC subsystem 440 of building subsystems 428… monitored variables 1306; 0080-0086, Fig. 5 — predictive diagnostics system 502 can be a component of a remote computing system or cloud-based computing system configured to receive and process data from one or more building management systems].
Regarding claim 18, Khalate teaches a system for anticipating shutdown alarms with respect to a boiler by way of machine learning model processing of information [0004-0005, Figs. 1-7 — The building management system includes connected equipment configured to measure a plurality of monitored variables and a predictive diagnostics system; 0033, Fig. 2 — a plurality of heating elements 220 (e.g., boilers, electric heaters, etc.); 0080 — Connected equipment 610 can include connected chillers 612, connected AHUs 614, connected actuators 616, connected controllers 618, or any other type of equipment in a building HVAC system (e.g., boilers, economizers, valves, dampers, cooling towers, fans, pumps, etc.); 0083-0085 — The control panel can use the sensor data to shut down the device if the control panel determines that the device is operating under unsafe conditions. For example, the control panel can compare the sensor data (or a value derived from the sensor data) to predetermined thresholds. If the sensor data or calculated value crosses a safety threshold, the control panel can shut down the device and/or operate the device at a derated setpoint. The control panel can generate a data point when a safety shut down or a derate occurs. The data point can include a safety fault code which indicates the reason or condition that triggered the shut down; 0087 -0090, Fig. 6 — If the current operating state is identified as a faulty state or moving toward a faulty state, predictive diagnostics system 502 may generate an alert (alarm) or notification for service technicians 606 to repair the fault or potential fault before it becomes more severe. In some embodiments, predictive diagnostics system 502 uses the current operating state to determine an appropriate control action for connected equipment 610… predictive diagnostics system 502 can predict when connected equipment 610 (including boilers) will next report a safety fault code that triggers a device shut down (that is associated with an alert/alarm); 0123-0130, Figs. 11-12 — At step 1110, predictive diagnostics system 502 is configured to create a machine learning model. By way of example, predictive diagnostics system 502 may be configured to utilize supervised machine learning to produce a model or function from the big data (e.g., the monitored variables history, probability distribution, etc.)… At step 1116, predictive diagnostics system 502 is configured to monitor data (e.g., the monitored variables, etc.) regarding the current operation of connected equipment 610 to predict whether operation of connected equipment 610 is trending towards a fault condition or remaining in a normal condition. At step 1118, predictive diagnostics system 502 is configured to predict a diagnosis for connected equipment 610 in response to the operation of connected equipment trending towards the fault condition] obtained by way of a plurality of internet connected devices [0051, Fig. 4 — communications interfaces 407 and/or BMS interface 409 can be direct (e.g., local wired or wireless communications) or via a communications network 446 (e.g., a WAN, the Internet, a cellular network, etc.); 0098 — Communications via interface 710 can be direct (e.g., local wired or wireless communications) or via an intermediate communications network 446 (e.g., a WAN, the Internet, a cellular network, etc.).; 0136-0138, Fig. 13 — Communications via interface 1310 can be direct (e.g., local wired or wireless communications) or via an intermediate communications network 446 (e.g., a WAN, the Internet, a cellular network, etc.)… variable monitor 1318 may receive temperature data from one or more temperature sensors of HVAC subsystem 440 of building subsystems 428… monitored variables 1306], the system comprising:
a first controller of the boiler [0026, Figs. 1-7 — HVAC system 100 is shown to include a chiller 102, a boiler 104; 0039-0043, Fig. 3 — Actuators 324-328 may receive control signals from AHU controller 330 and may provide feedback signals to AHU controller 330. Feedback signals can include, for example, an indication of a current actuator or damper position, an amount of torque or force exerted by the actuator, diagnostic information… AHU controller 330, by BMS controller 366… AHU controller 330 receives a measurement of the supply air temperature from a temperature sensor 362 positioned in supply air duct 312 (e.g., downstream of cooling coil 334 and/or heating coil 336). AHU controller 330 may also receive a measurement of the temperature of building zone 306 from a temperature sensor 364 located in building zone 306.; 0049, Figs. 4 and 7 — HVAC subsystem 440 can include a chiller, a boiler, any number of air handling units, economizers, field controllers, supervisory controllers, actuators, temperature sensors, thermostats, and other devices for controlling the temperature, humidity, airflow, or other variable conditions within building 10; 0080 — Connected equipment 610 can include connected chillers 612, connected AHUs 614, connected actuators 616, connected controllers 618, or any other type of equipment in a building HVAC system (e.g., boilers, economizers, valves, dampers, cooling towers, fans, pumps, etc.); 0113, Fig. 7 — Building controller 744 may receive inputs from sensory devices (e.g., temperature sensors, pressure sensors, flow rate sensors, humidity sensors, electric current sensors, cameras, radio frequency sensors, microphones, etc.)… monitored variables 706];
a plurality of sensors associated with the plurality of internet connected devices for the boiler, wherein the sensors are configured to sense a plurality of parameters regarding the boiler and to provide a plurality of first signals regarding the sensed parameters to the controller [0026, Figs. 1-7 — HVAC system 100 is shown to include a chiller 102, a boiler 104; 0039-0043, Fig. 3 — Actuators 324-328 may receive control signals from AHU controller 330 and may provide feedback signals to AHU controller 330. Feedback signals can include, for example, an indication of a current actuator or damper position, an amount of torque or force exerted by the actuator, diagnostic information… AHU controller 330, by BMS controller 366… AHU controller 330 receives a measurement of the supply air temperature from a temperature sensor 362 positioned in supply air duct 312 (e.g., downstream of cooling coil 334 and/or heating coil 336). AHU controller 330 may also receive a measurement of the temperature of building zone 306 from a temperature sensor 364 located in building zone 306.; 0049, Figs. 4 and 7 — HVAC subsystem 440 can include a chiller, a boiler, any number of air handling units, economizers, field controllers, supervisory controllers, actuators, temperature sensors, thermostats, and other devices for controlling the temperature, humidity, airflow, or other variable conditions within building 10; 0080 — Connected equipment 610 can include connected chillers 612, connected AHUs 614, connected actuators 616, connected controllers 618, or any other type of equipment in a building HVAC system (e.g., boilers, economizers, valves, dampers, cooling towers, fans, pumps, etc.); 0113, Fig. 7 — Building controller 744 may receive inputs from sensory devices (e.g., temperature sensors, pressure sensors, flow rate sensors, humidity sensors, electric current sensors, cameras, radio frequency sensors, microphones, etc.)… monitored variables 706];
a device of the boiler, wherein either the first signals or second signals based at least indirectly upon the first signals are sent to the device [0050-0052, Fig. 4 — BMS controller 366 is shown to include a communications interface 407 (device) and a BMS interface 409. Communications interface 407 may facilitate communications between BMS controller 366 and external applications (e.g., monitoring and reporting applications 422, enterprise control applications 426, remote systems and applications 444… for allowing user control, monitoring, and adjustment to BMS controller 366 and/or subsystems 428; 0080-0086, Figs. 5-6 — BMS 600 is shown to include building 10, network 446, client devices 448, and predictive diagnostics system 502… predictive diagnostics system 502 can be a component of a remote computing system or cloud-based computing system configured to receive and process data from one or more building management systems];
at least one communications device by which either the first signals, the second signals, or third signals based at least indirectly upon the first signals or second signals, are sent for receipt by a cloud computing system [0050-0052, Figs. 4 and 6-7 — BMS controller 366 is shown to include a communications interface 407 (device) and a BMS interface 409. Communications interface 407 may facilitate communications between BMS controller 366 and external applications (e.g., monitoring and reporting applications 422, enterprise control applications 426, remote systems and applications 444… for allowing user control, monitoring, and adjustment to BMS controller 366 and/or subsystems 428; 0080-0086, Fig. 5 — predictive diagnostics system 502 can be a component of a remote computing system or cloud-based computing system configured to receive and process data from one or more building management systems. For example, predictive diagnostics system 502 can be implemented as part of a PANOPTIX® brand building efficiency platform, as sold by Johnson Controls Inc], for use in either developing one or more machine learning models for predicting the shutdown alarms or generating at least one prediction of one or more of the shutdown alarms by way of the one or more machine learning models [0123-0130, Figs. 11-12 — At step 1110, predictive diagnostics system 502 is configured to create a machine learning model. By way of example, predictive diagnostics system 502 may be configured to utilize supervised machine learning to produce a model or function from the big data (e.g., the monitored variables history, probability distribution, etc.)… At step 1116, predictive diagnostics system 502 is configured to monitor data (e.g., the monitored variables, etc.) regarding the current operation of connected equipment 610 to predict whether operation of connected equipment 610 is trending towards a fault condition or remaining in a normal condition. At step 1118, predictive diagnostics system 502 is configured to predict a diagnosis for connected equipment 610 in response to the operation of connected equipment trending towards the fault condition]; and
a display configured to receive at least one fourth signal indicative of the at least one prediction of the one or more of the shutdown alarms, and to display either the at least one prediction or one or more alerts in response to the at least one prediction [0090 — web interface can be used to… view the results of the predictive diagnostics, identify which equipment is in need of preventative maintenance, and otherwise interact with predictive diagnostics system 502. Service technicians 606 can access the web interface to view a list of equipment for which faults are predicted by predictive diagnostics system 502].
But Khalate fails to clearly specify IoT devices, a controller and sensors supported on or proximate to the boiler and sending data via a gateway device and using an application programming interface (API) and wherein the boiler is a lead boiler that operates with one or more lag boilers.
However, Park teaches IoT devices [0329-0331, Fig. 14 — Internet-of-Things (IoT)… . The IoT environment may include a plurality of devices 1402, 1404, 1406, a cloud-based service 1408… the devices 1402, 1404, 1406 can be sensors, controllers, actuators, sub-systems, thermostats, or any other component within the BMS system capable of communicating to the cloud-based service 1408] and sending data via a gateway device [0331-0335 , Fig. 15 — devices 1402, 1404, 1406 are connected to the Internet via one or more gateways, routers, modems, or other internet connected devices, which provide communication to and from the internet… collator 1512 may be a software element within a local device, such as an internet gateway] and using an application programming interface (API) [0336-0339 — The multi-modal data processing service 1600 includes a timeseries microservice API 1602… The processing layer 1604 may further include a processing service API 1628; 0355-0357 — The mapping used in FIG. 20 can require maintaining mappings and building custom ACID services for each application, which can be expensive and tedious to maintain. These issues can be resolved by building a set of abstractions that provide APIs for application developers and data management applications… telemetry data is received by the service via one or more APIs].
Khalate and Park are analogous art. They relate to HVAC and building management systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to simply substitute the known IoT devices of Park for the known devices of Khalate for the predictable result of a system using IoT devices. In addition, it would be obvious to one having ordinary skill in the art to utilize IoT to facilitate communication with the remote/cloud internet connected infrastructure. Furthermore, it would be obvious to one having ordinary skill in the art to utilize a gateway, as taught by Park, to facilitate connecting with the internet and hence the remote/cloud internet connected infrastructure, as suggested by Park [0331-0335]. And one of ordinary skill in the art would have been motivated to perform these functions by way of an API in order to reduce cost and ease maintenance, as suggested by Park [0355-0357].
But the combination of Khalate and Park fails to clearly specify a controller and sensors supported on or positioned proximate to the boiler and wherein the boiler is a lead boiler that operates with one or more lag boilers.
However, Bohan teaches a controller and sensors supported on or positioned proximate to the boiler [0035-0037, Figs. 2-3 — exemplary multi-sensor component 208 is also known herein as TPPS 208, to represent the temperature, pressure and presence sensor functions which this device may perform within a single device housing… multi-sensor component 208, for example, may be threaded into the boiler tank (e.g., 302 of boiler 300 of FIG. 3), while the HVAC controller 200 may be mounted onto sensor TPPS 208, and the case 204 of HVAC controller 200 secured to the exterior of the boiler enclosure (e.g., 305 of boiler 300 of FIG. 3). In this way, TPPS 208 is adapted to make direct contact with the medium (e.g., medium 310, water, water-glycol mix within the boiler 300). TPPS 208, for example, may then utilize a modular plug to electrically interconnect the sensor/detector functions into the HVAC controller 200 as shown in FIG. 2D].
Khalate, Park and Bohan are analogous art. They relate to HVAC and building management systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to modify the above system, as taught by the combination of Khalate and Park, by incorporating the above limitations, as taught by Bohan.
One of ordinary skill in the art would have been motivated to do this modification so that the sensors are in direct contact with the medium being heated, thus facilitating more direct/accurate measurements, and to enable easy direct connection with the controller, thus facilitating improved communication, as suggested by Bohan [0037]. In addition, the locating the controller proximate to the boiler is an obvious matter of design choice, see MPEP 2144.04.
But the combination of Khalate, Park and Bohan fails to clearly specify that a boiler is a lead boiler that operates with one or more lag boilers.
However, Martinez teaches that a boiler is a lead boiler that operates with one or more lag boilers [col. 4 lines 11-44, Drawing — The direct fired boiler to be turned off is referred to as the lag boiler and the direct fired boiler to be left on is referred to as the lead boiler. For purposes of illustration, direct fired boiler 12 will be the lag boiler, and direct fired boiler 10 will be referred to as the lead boiler].
Khalate, Park, Bohan and Martinez are analogous art. They relate to HVAC and boiler systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to modify the above system, as taught by the combination of Khalate, Park, and Bohan by incorporating the above limitations, as taught by Martinez.
One of ordinary skill in the art would have been motivated to do this modification in order to save energy, as suggested by Martinez [col. 1 lines 9-11, col. 4 lines 52-60]. In addition, it would have been obvious to a person of ordinary skill in the art to simply substitute the known lead-lag boilers of Martinez for the known boilers of Khalate for the predictable result of a system using a lead-lag boiler arrangement.
Note that any citations to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP 2123.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BERNARD G. LINDSAY whose telephone number is (571)270-0665. The examiner can normally be reached Monday through Friday from 8:30 AM to 5:30 PM EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mohammad Ali can be reached on (571)272-4105. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BERNARD G LINDSAY/
Primary Examiner, Art Unit 2119