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 .
Election/Restrictions
Applicant’s election without traverse of Group I (claims 1-6 and 12-18) in the reply filed on 06/30/2026 is acknowledged.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-6 and 12-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea (i.e., mental processes and mathematical steps of evaluating ion intensity values against a threshold and classifying them, and producing event values and combining or weighing numerical datasets to calculate another value), and the claims do not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than the judicial exception.
Step 2A, Prong One – Judicial exception (Abstract Idea)
The courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper” to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, “methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’” 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same). Further, the courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer").
In the instant case, the independent claims recite limitations that, when considered in their broadest reasonable interpretation, fall within the abstract idea of (i) mental process (concepts formed in the human mind such as observation, evaluation, and judgment) and/or (ii) mathematical concepts (relationships, comparisons, classifications, and mathematical operations such as weighted sum). For instance, the independent claim 1 recites (independent claim 12 recites similar limitations):
receiving an intensity measurement for at least one ion made by an ADC detector subsystem for each of m extractions of an ion beam, producing m intensities for the ion;
receiving m event realizations for the ion, wherein, for each intensity of the m intensities, an event realization of 1 is produced for an intensity greater than an intensity threshold and an event realization of less than 1 is produced for an intensity less than or equal to the filtered intensity threshold, producing the m event realizations; and
calculating a filtered intensity for the ion that is a combination of them intensities and them event realizations.
These limitations collectively recite mental processes, including evaluating and classifying measured information, and mathematical concepts, including numerical comparison and evaluations for combining datasets. Such collection, evaluation and comparison of data are fundamentally a form of data analysis and mathematical evaluation, activities that have long been performed by humans mentally or with pen and paper, and therefore can be characterized as an abstract idea.
Step 2A, Prong Two – Integration into a Practical Application
The claims are not integrated into a practical application because in practice, executing all of the steps is indistinguishable from: (i) mere data acquisition from a conventional instrument environment, and (ii) generic computer implementation of the abstract analysis. That is to say that integration into a practical application is lacking where, as here, the abstract idea has no effect on the material world or the execution of the process.
Although the claims include additional elements, these additional elements do not integrate the abstract idea into a practical application. For example, the ADC detector subsystem and ion-beam extractions merely provide the numerical data upon which the abstract analysis is performed. The claims terminate with calculation of a filtered intensity and do not require using the calculated intensity to modify operation of the ADC detector subsystem, control an ion-beam extraction, operate the TOF mass analyzer, or otherwise effect a physical or technological result. Thus, the additional limitations merely link the abstract ideas to the technological environment of mass spectrometry and generally apply the abstract calculations using conventional computer components.
Therefore, the claims as a whole are directed to an abstract idea.
Step 2B– Significant More (Inventive Concept)
The claims do not include additional elements, either individually or as an ordered combination, that amount to significant more than the abstract idea. The additional elements, including the ADC detector subsystem, memory device, processor, and TOF mass analyzer, are recited at a high level of generality and perform their ordinary functions of measuring, storing, transmitting, and processing data, considered individually and as an ordered combination, these elements do not provide an inventive concept because they merely implement the abstract threshold classification and numerical combination using conventional mass spectrometry and computer components.
Dependent claims 2-6 and 13-16 merely refine the abstract numerical and analysis by specifying a zero value, a weighted sum, rate-dependent weighing, and a probability-based threshold; these are additional mathematical rules and do not add an inventive concept. Dependent claim 17 adds only conventional memory-based post-processing, and claim 18 adds conventional real-time processing of data received from a TOF mass analyzer. None of these limitations changes detector operation or produces a further physical result, either individually or as an ordered combination.
Taken alone or as ordered combination, claims 1-6 and 12-18 fail to recite patent eligible subject matter.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-6 and 12-18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 and 12 each recites “an event realization of 1 is produced for an intensity greater than an intensity threshold and an event realization of less than 1 is produced for an intensity less than or equal to the filtered intensity threshold.” There is insufficient antecedent basis for “the filtered intensity threshold” limitation in the claim, and it is unclear whether this term refers to the previously recited “intensity threshold” or identifies a separate threshold. The specification repeats the same inconsistent terminology rather than clearly resolving it (See Spec. paras. [0098, 0106]). If separate thresholds are intended, the claims do not specify their relationship or the event realization produced for an intensity falling between the thresholds, and depending on the relative threshold values, a given intensity may satisfy either neither condition or both conditions.
Claims 2-6 and 13-18 are vague and indefinite by virtue of their dependencies on respective rejected claims 1 and 12.
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.
Claims 1-5 and 12-18 are rejected under 35 U.S.C. 103 as being unpatentable over US 2013/0268212 A1 [hereinafter Makarov]
Regarding Claims 1 and 12:
Makarov teaches a method and a system for filtering ion intensities measured by an analog-to-digital converter (ADC) detector subsystem (Abstract and paras. [0036-0037]: data acquisition method for detecting ions in a mass spectrometer with ADC), comprising a processor (para. [0048]: “The threshold or noise removal module may be implemented on a dedicated processor”) that:
receiving an intensity measurement for at least one ion made by an ADC detector subsystem for each of m extractions of an ion beam, producing m intensities for the ion (paras. [0003, 0049]: a TOF mass spectrometer in which “ions are emitted from a pulsed source in the form of a short packet of ions, and are directed along the fixed flight path through an evacuated region to an ion detector,” where the “detection signals each comprise a sequence of data points in time (i.e. a transient), each point having an intensity value”);
receiving m event realizations for the ion, wherein, for each intensity of the m intensities, an event realization of 1 is produced for an intensity greater than an intensity threshold and an event realization of less than 1 is produced for an intensity less than or equal to the filtered intensity threshold, producing the m event realizations (paras. [0049, 0269]: applying threshold functions to the detected signals, to “removes points which have intensity values less than a threshold. The removed points are effectively replaced by a zero in the data. Accordingly, it only transfers points of the detection signals for merging of the detections signals which are not less than the threshold.” That is, when each measured intensity receives the functional equivalent of a binary threshold result, event realization =1 when intensity no less than threshold (point retained), and event realization = 0 when intensity less than threshold (point replaced by zero). The number of threshold-positive data points are counted); and
calculating a filtered intensity for the ion that is a combination of the m intensities and the m event realizations (paras. [0050, 0269]: the filtered signals (including data points represent m intensities that above the threshold) are used to construct the mass spectrum and also counts the number of threshold-positive data points (“m event realization”)).
Although Makarov classifies an intensity equal to the threshold as qualifying, whereas claim1 classifies an intensity equal to the threshold as non-qualifying, it would have been obvious for one of ordinary skill in the art to include the threshold value itself in the non-passing class, because assigning equality to either the passing or non-passing class represents one of finite and predictable threshold-boundary conventions and would merely require selecting whether the comparator is implemented using “greater than” or “greater than to equal to.” Such a selection would have predictably preserved Makarov’s noise-filtering function while adopting a more conservative criterion in which only intensities strictly exceeding the selected noise threshold are retained.
Regarding Claims 2 and 13:
Makarov teaches the method of claim 1 and the system of claim 12, respectively. Makarov further teaches wherein the event realization of less than 1 is 0 (para. [0049]: Makarov expressly teaches that measured intensity points below the threshold are replaced by zero and transfers intensity points meeting the threshold criterion, therefore, Makarov teaches that the event realization of less than 1 is 0).
Regarding Claims 3 and 14:
Makarov teaches the method of claim 1 and the system of claim 12, respectively. Makarov further teaches wherein the filtered intensity is calculated as a weighted sum of the m intensities and the m event realizations (para. [0049]: Makarov applies a binary weighting to every measured intensity, the resulting filter intensity is therefore the sum of the measured intensity weighted according to their corresponding threshold-derived event realizations (i.e., weight=1 when intensity passes the threshold; weight =0 when intensity fails the threshold)).
Regarding Claims 4 and 15:
Makarov teaches the method of claim 3 and the system of claim 14, respectively. Makarov teaches distinguishing a low-ion-rate regime using a predetermined threshold for a low number of ions and, in that regime, employing highly sensitive, low-noise detection capable of single-particle counting (paras. [0033 and [0289]. Makarov further teaches suppressing measured intensity values by threshold filtering (paras. [0048-0050]). Therefore, it would have been obvious to an ordinarily skilled person in the art, to assign greater relative weight to the threshold-derived event information than to the raw intensity information at low ion rate, since Makarov demonstrates that event-sensitive, low-noise detection is more reliable in that regime and that reducing the contribution of low-level intensity noise improves the resulting spectrum.
Regarding Claims 5 and 16:
Makarov teaches the method of claim 4 and the system of claim 15, respectively. Makarov teaches that at high incoming-ion rates the detector output may saturate and therefore uses a lower-gain intensity detector to detect high particle rates before saturation and achieve a larger dynamic range (paras. [0030, 0033]). Therefore, it would have been obvious for an ordinarily skilled person in the art, in that high-rate regime, to assign less weight to the threshold-derived event information and greater weight to the measured intensity information, because the event information provides limited discrimination once most measurements satisfy the threshold, whereas the measured intensity contributes to represent signal magnitude. Such relative weighting would further Makarov’s express objective of detecting high ion rates without saturation and increasing dynamic range.
Regarding Claim 17:
Makarov teaches the system of claim 12. Makarov further teaches a memory device and wherein the processor receives the m intensities and m event realizations from the memory device and calculates the filtered intensity in a post-processing step (para. [0100]: “The processed detection signals and/or mass spectrum constructed by the data processing system and/or data derived therefrom … may be transferred to a data system, i.e. a mass data storage system or memory…to allow for spectra output…and/or further processing of the spectra by computer programs.”).
Regarding Claim 18:
Makarov teaches the system of claim 12. Makarov further teaches comprising a memory device and a time-of-flight (TOF) mass analyzer of a mass spectrometer and wherein the processor receives them intensities and m event realizations from the TOF mass analyzer and calculates the filtered intensity in real-time during a sample acquisition by the mass spectrometer (paras. [0018, 0036-0037, 0048, 0054]: Makarov expressly teaches application to a TOF mass spectrometer having a pulsed ion source, TOF mass analyzer, ion detector, ADC and processor. “The dedicated processor is preferably for applying the threshold to remove noise on-the-fly.” Makarov also teaches calculating a new threshold/LUT for each detection signal when scan-to-scan noise varies and comparing the acquired points with that threshold during acquisition).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Makarov in view of US20160189943A1 [hereinafter Bloomfield].
Regarding Claim 6:
Makarov teaches the method of claim 5. However, Makarov does not expressly teach wherein the threshold rate is a rate at which a probability that an ADC detector subsystem detection of the ion is a single ion event falls below a probability threshold level.
Bloomfield teaches wherein the threshold rate is a rate at which a probability that an ADC detector subsystem detection of the ion is a single ion event falls below a probability threshold level (paras. [0050-0051]: Bloomfield teaches determining whether an ADC detector response represents a single-ion event based on ion statistics. Specially, it teaches for an ion having an equivalent TDC ion count K over N ion-beam extractions, calculates, using a Poisson distribution, a probability P that a single ion hits the detector and compares P with a threshold probability level. When P exceeds the threshold, the ADC response is regarded with high confident as representing a single-ion event).
Therefore, it would have been obvious for an ordinary skilled person in the art, before the effective time of filing, to modify Makarov’s rate-dependence processing by using Bloomfield’s Poisson-based single-ion probability criterion to define the threshold rate. Makarov already teaches that, at low signal intensities, the random varying number of detected ions may be modeled using Poisson statistics and that the number of ions corresponding to a measured intensity may be determined from calibration or statistics analysis (para. [0270]), and apply Bloomfield’s single-ion probability threshold to Makarov’s disclosed Poisson analysis of detected-ion statistics would provide an objective statistical criterion form defining the ion-rate boundary between reliable single-ion counting and higher-rate intensity detection.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JING WANG whose telephone number is (571)272-2504. The examiner can normally be reached M-F 7:30-17:00.
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/JING WANG/Examiner, Art Unit 2881
/DAVID E SMITH/Examiner, Art Unit 2881
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