DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114 was filed in this application after a decision by the Patent Trial and Appeal Board, but before the filing of a Notice of Appeal to the Court of Appeals for the Federal Circuit or the commencement of a civil action. Since this application is eligible for continued examination under 37 CFR 1.114 and the fee set forth in 37 CFR 1.17(e) has been timely paid, the appeal has been withdrawn pursuant to 37 CFR 1.114 and prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant’s submission filed on 12/22/2025 has been entered.
Status of Claims
Claims 1, 8, and 15 are independent claims and are amended.
Claims 1-20 are pending in this application.
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 .
Continuity
This instant application is a continuation (CON.) of application no. 15/647,870 filed on 07/12/2017, which is patented number 10,740,294, and has provisional no. 62/445,668 filed on 01/12/2017.
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 1-20 are rejected under 35 U.S.C. 101 because the claims do not amount to significantly more than an abstract idea.
Regarding claim 1, the claim recites language of:
“receive, from two or more of the plurality of storage devices, a plurality of characteristics associated with valid data stored at a plurality of erase blocks of the plurality of storage devices, wherein the plurality of erase blocks are indicated as ready to be garbage collected; and
perform a garbage collection process, wherein to perform the garbage collection process the processing device is to:
group valid data from the plurality of erase blocks based on a similarity of the plurality of characteristics between the valid data stored at the plurality of erase blocks, and
store the grouped valid data at erase blocks of the plurality of storage devices, the erase blocks for storage selected based on the characteristics associated with the valid data from the plurality of erase blocks.”
a/ Analysis under Step 2A, Prong I:
Accordingly, the steps of “perform a garbage collection process…”, “group valid data from the plurality of erase blocks …”, and “store the grouped valid data at erase blocks of the plurality of storage devices,…” as drafted, are mental processes that, under its broadest reasonable interpretation, cover performance of the limitations in mind (e.g., an observation, evaluation, judgment, option, etc.) but for the recitation of generic computer’s component(s) (e.g., a plurality of storage devices, a storage controller and/or a processing device). Therefore, if a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in mind (e.g., “perform a garbage collection process” and “group valid data”) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas (see MPEP 2106.04(a)(2), Part III).
(Similar above analysis is applied to independent claims 8 and 15, respectfully).
b/ Analysis under Step 2A, Prong II:
The remaining limitations in claims 1, 8 and 15 do not integrate the judicial exception into a practical application. For instance, the additional elements, e.g., “a plurality of storage devices”, “a storage controller”, and “a processing device” are known as generic computing components/units used as tools for performing the computing functions of the above indicated steps of “receiving”, “perform”, “group”, and “store” which amount no more than mere instructions to apply the exception using the generic computing component/unit having at least a processing device and storage devices, see Mayo, 566 U.S. AT 84.
In addition, the additional limitations of “receive, from two or more of the plurality of storage devices, a plurality of characteristics associated with valid data stored…” represent an insignificant extra solution activities because these additional steps including in the claim as the computing functions that do not integrate into a practical application because these steps do not specify of how the characteristics is received and how the grouped valid data is stored in such the perform practically data processing (see MPEP 2106.04(a)-(h)).
c/ Analysis under Step 2B:
Furthermore, independent claims 1, 8, and 15 do not include additional elements/limitations beyond the judicial exception that, alone or in combination, are not “well-understood, routine, conventional” (see MPEP 2106.05(d)).
As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using “a plurality of storage devices”, “a storage controller”, and “a processing device” are known as generic computing components/units used as tools. Next, the additional limitations of “receive,…, a plurality of characteristics associated with valid data stored…”, represent an insignificant extra solution activities because these additional steps including in the claims as the computing functions to apply the exception using a generic computer components that are well-understood, routine, conventional activity to a skill artisan in the relevant technical field of gathering and transmitting data via network, see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362, and storing/retrieving information in memory, see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
For the at least above reasons, the limitations in claims 1, 8, and 15 as considered both individually and/or in combination, do not amount to significantly more than the abstract idea.
Claims 2-7, 9-14, and 16-20 depend on claims 1, 8, and 15 and include all the limitations of claims 1, 8, and 15; thus, claims 2-7, 9-14, and 16-20 recite the same as being the above abstract idea as under the Step 2A (Prong I, Prong II), and Step 2B as following:
Regarding claim 2, the claim recites additional limitations of “wherein the plurality of storage devices comprise a plurality of direct-mapped solid-state storage devices” which do not integrate the judicial exception into a practical application. The claim language provides further definition of the plurality of storage devices, which does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use as tools. Thus, the claim does not include any additional limitations or elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered both individually and as an ordered combination, do not amount to significantly more than the abstract idea.
Regarding claim 3, the claim recites further additional limitation of “wherein the garbage collection process is performed based on a capacity of the plurality of storage devices being used for storage”, which do not integrate the judicial exception into a practical application. Accordingly, the activity of “is performed” the garbage collection, as drafted, is mental process. The using of additional elements of “a capacity” of the “storage devices” are used as tools for gathering data in well-known step of storing (see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015)). Thus, the claim does not include additional limitation/element that is sufficient to amount to significantly more than the judicial exception because the additional limitations/elements, when consider both individually and as an ordered combination, do not amount to significantly more than the abstract idea.
Regarding claim 4, the claim recites further additional limitation of “wherein the processing device is further to: determine an expected longevity associated with each of the valid data based on the plurality of characteristics, wherein the valid data is grouped based on a similarity of the expected longevity between the valid data” in which the steps of “determine” and “is grouped”, as drafted, are mental processes as performing in mind that falls within the “Mental Processes” grouping of abstract idea (see MPEP 2106.04 (a)(2), part III). Plus, the additional elements of “longevity” and “characteristics” do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. Thus, the claim does not include additional limitation/element that is sufficient to amount to significantly more than the judicial exception because the additional limitations/elements, when consider both individually and as an ordered combination, do not amount to significantly more than the abstract idea.
Regarding claim 5, the claim recites further additional limitation of “wherein the plurality of characteristics comprise an age associated with each of the valid data” which do not integrate the judicial exception into a practical application. The claim language provides further definition of “age” as a partial feature/element of the plurality of characteristics, which does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. Thus, the claim does not include any additional limitations or elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered both individually and as an ordered combination, do not amount to significantly more than the abstract idea.
Regarding claim 6, the claim recites further additional limitation of “wherein the plurality of characteristics comprise a type of data associated with each of the valid data” which do not integrate the judicial exception into a practical application. The claim language provides further definition of “a type of data” as a partial feature/element of the plurality of characteristics, which does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. Thus, the claim does not include any additional limitations or elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered both individually and as an ordered combination, do not amount to significantly more than the abstract idea.
Regarding claim 7, the claim recites further additional limitation of “wherein the plurality of characteristics specifies a deduplication importance associated with each valid data, the deduplication importance corresponding to a number of times that a respective valid data was associated with a deduplication operation” which do not integrate the judicial exception into a practical application. The claim language provides further definition of “a deduplication importance” as specified as a partial feature/element of the plurality of characteristics, and the “deduplication importance corresponding to “a number of times” does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use.
Thus, the claim does not include any additional limitations or elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered both individually and as an ordered combination, do not amount to significantly more than the abstract idea.
Similar above indicated analysis and rejections of claims 2-7 are applied to dependent claims 9-14 and 16-20, respectively.
For at least above reasons, claims 1-20 are not drawn to eligible subject matter as they are directed to an abstract idea without significant more.
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 1-6, 8-13, 15-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kimmel et al., US Patent No. 8,621,145 B1 (hereinafter as “Kimmel”), in view of Ebsen et al., US Patent No. 10,739,996 B1 (hereinafter as “Ebsen”) and further in view of Singhai et al., US Pub. No. 20170123676 (hereinafter as “Singhai”).
Regarding claim 1, Kimmel teaches: a system (see Figs. 2-3), comprising:
a plurality of storage devices (Fig. 3 is shown the plurality of storage devices at elements 34-35, 38; and col. 3, lines 38-42: discloses a solid-state secondary cache, and flash memory; and col. 5, lines 35-42); and
a storage controller operatively coupled to the plurality of storage devices (see Fig. 3, element 31; and col. 6, lines 28-33: wherein the “storage server” is interpreted as the storage controller as well), the storage controller comprising a processing device (see again in col. 6, lines 28-33: “a network storage server in which the techniques described above can be implemented (e.g., storage server 2 in FIG. 1). In the illustrated embodiment, the storage server 2 includes one or more processors 21 and memory 22 coupled to an interconnect 29.”), the processing device to:
receive, from two or more of the plurality of storage devices, a plurality of characteristics associated with valid data stored at a plurality of erase blocks of the plurality of storage devices (col. 5, lines 9-19: “classification and localization of cache lines with similar cache aging and invalidation behaviors within erase block boundaries, allowing efficient reuse of flash locations while improving effective cache capacity. After erase block fill using these methods, the slow-turn, fast-turn or no-turn designation for an erase block or stripe can be forgotten, using line-granular tracking of line use and invalidation to inform subsequent reuse of the erase block or stripe. Alternatively, the slow-turn, fast-turn or no-turn designation can be retained and inform subsequent replacement policy”, wherein the “aging” and/or “invalidation behaviors” are/is interpreted as the characteristic(s); and col. 10, lines 37-40: “receives data blocks from the EC layer 36 in the form of write units. As illustrated in FIG. 4, a write unit 49 is a group of several queued data blocks 50 of the same data class (e.g., slow-turn, fast-turn or no-turn)…”; and col. 12, line 37: wherein the “valid entries in the erase block/stripe is interpreted as valid data associated with the characteristic(s)).
Kimmel teaches classifying and locating the valid/invalid entries in the erase blocks/stripes in the groups of slow-turn, fast-turn or no-turn according the similar aging (col. 5, lines 9-19, col. 10 and col. 12). However, Kimmel does not explicitly teach “wherein the plurality of erase blocks are indicated as ready to be garbage collected;” and “perform a garbage collection process, wherein to perform the garbage collection process the processing device is to: group valid data from the plurality of erase blocks based on a similarity of the plurality of characteristics between the valid data stored at the plurality of erase blocks, and store the grouped valid data at erase blocks of the plurality of storage devices, the erase blocks for storage selected based on the characteristics associated with the valid data from the plurality of erase blocks.”
In the same field of endeavor (i.e., data processing), Ebsen teaches enhanced garbage collection technique including that: “
wherein the plurality of erase blocks are indicated as ready to be garbage collected (see col. 1, lines 31-33: “The garbage collection operation may include selecting a plurality of blocks on which to perform the garbage collection operation,…” wherein the technique of “selecting” is interpreted as “are indicated”, and see further in Fig. 3 for indicating the erase blocks as ready to be garbage collected);
perform a garbage collection process (col. 2, lines 9-13: “perform garbage collection operation …”), wherein to perform the garbage collection process the processing device (col. 3, lines 14-25, e.g., “DSD 104 may include garbage collection module (GCM) 110... A module may include one or more physical components of a computing device (e.g., circuits, processors, etc.), may include instructions that, when executed, can cause a processor to perform a particular task or job, or any combination thereof. The GCM 110 may perform the methods and processes described herein to select data and blocks for collection”) is to:
group valid data from the plurality of erase blocks based on a similarity of the plurality of characteristics between the valid data stored at the plurality of erase blocks (Fig. 3, col. 4, lines 7-14, and col. 10, lines 15-46 via the grouping of plurality of blocks to specify a garbage collection unit, wherein group the blocks comprise the valid data, and group the blocks having invalid data, e.g., “stale” or “staleness” that need to be erased, and col. 11, lines 4-17: “Efficiency metrics for blocks may also be based on characteristics of the block itself, such as how many program & erase cycles the block has undergone, or whether the block is exhibiting high wear or frequent errors. Data and statistics may also be maintained according to data streams, rather than or in addition to data maintained for particular blocks, GCUs, or data segments. Factors such as the staleness of a block may still be considered and factored into the efficiency metrics. Information used to determine access efficiency metrics, such as statistical access patterns, may be stored to addressing tables, or in separate data structures and accessible by the GCM. The different factors and access efficiency metrics may be weighted in any number of ways when selecting blocks for garbage collection”, and col. 11, lines 65-67 to col. 12, lines 1-5: “The GCM may collect and combine data with similar update patterns or frequency and store them together, so that frequently updated data is combined together and infrequently updated data is stored separately. For example, infrequently updated data may be combined and stored to blocks having higher wear or lower reliability, while frequently updated data may be combined and stored to blocks with less wear or greater reliability” wherein the technique of “collect and combine” is interpreted as group/grouping. And also col. 12, lines 7-12), and
(wherein) the erase blocks for storage selected based on the characteristics associated with the valid data from the plurality of erase blocks (see col. 1, lines 31-33: “The garbage collection operation may include selecting a plurality of blocks on which to perform the garbage collection operation,…” wherein the technique of “selecting” is interpreted as “are indicated”, and see further in Fig. 3 for indicating the erase blocks as ready to be garbage collected; and col. 10, lines 15-46: wherein “stale” or “staleness” is interpreted as characteristic, and col. 11, lines 4-17, e.g., “Efficiency metrics for blocks may also be based on characteristics of the block itself, such as how many program & erase cycles the block has undergone, or whether the block is exhibiting high wear or frequent errors. Data and statistics may also be maintained according to data streams, rather than or in addition to data maintained for particular blocks, GCUs, or data segments. Factors such as the staleness of a block may still be considered and factored into the efficiency metrics…”).
Accordingly, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the instant application to combine the teachings of the cited references because the teachings of Ebsen would have provided Kimmel with the above indicated limitations for allowing a skilled artisan in motivation to improve the grouping valid data in erase blocks based on the similar characteristics for performing the garbage collection to efficiently free space of storage device(s) (Ebsen: Abstract, Figs. 2-3, and cols. 2-3)
Kimmel teaches the optimization for a non-volatile solid-state cache including the erase blocks and valid data/entries having the characteristic, e.g., similar “aging”, and grouping of valid and invalid data/entries of erase blocks (col. 3, lines 44-67; and cols. 4-5). Ebsen, in the same field of endeavor, teaches enhanced garbage collection processing operations include selecting, combining and grouping the valid and invalid data of the blocks (Figs. 1-3 and cols. 4, 10-12, for instance). However, Kimmel and Ebsen do not explicitly teach: “store the grouped valid data at erase blocks of the plurality of storage devices.”
In the same field of endeavor (i.e., data processing), Singhai teaches: “store the grouped valid data at erase blocks of the plurality of storage devices” (see [0047] “aggregating data blocks that rely on a reference data set into a segment. The segment refers to a chunk of flash storage that can be filled sequentially and erased as a unit” and [0083] “data blocks and update one or more identifiers associated with the data block in a records table stored in a data store (e.g. data storage repository 110/220)”, wherein the data storage repository 110 comprises data storage devices 112a and 112n as shown in Fig. 1).
Accordingly, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the instant application to combine the teachings of the cited references because the teachings of Singhai would have provided Kimmel and Ebsen with the storing the grouped of valid data at erase blocks of the plurality of storage devices for allowing a skilled artisan in motivation to improve the storing of the grouped valid data in erase blocks in the plurality of storage devices enhancing the garbage collection efficiently (Singhai: Fig. 1 and par. [0038]: “The endurance reduction in flash storage devices is associated with the tolerance for write-erase cycles by the flash storage device, while performance of the flash storage device is impacted by the availability of free writeable data blocks in the flash storage device”).
Regarding claim 2, Kimmel, Ebsen, and Singhai, in combination, teach: wherein the plurality of storage devices comprise a plurality of direct-mapped solid-state storage devices (Kimmel: Fig. 3, and col. 3, lines 28-39; Ebsen: Fig. 1 and Fig. 2 at element 203, 206, and 209, and col. 2, lines 20-31, e.g., “a solid state drive (SSD)”, and lines 54-64; and Singhai: Fig. 17 as shown the directed mapped solid-state storage devices, pars. [0004] “perform data block aggregation by comparing each corresponding data block of an incoming data set to a stored data block in storage…”, [0034] “managing sets of reference data blocks in storage devices”).
Regarding claim 3, Ebsen and Singhai teach: wherein the garbage collection process is performed (Ebsen: col. 1, lines 27-38, e.g., “to perform the garbage collection operation”) based on a capacity of the plurality of storage devices being used for storage (Ebsen: see col. 3, lines 1-13, e.g., “a storage drive’s capacity is filled with invalid data, the drive may perform garbage collection operations to recapture blocks for storage. Garbage collection may include copying the valid data from one or more blocks, and then erasing or resetting those blocks so that they can be made available for storing additional data”; and Singhai: pars. [0038] “…storage capacity limitations and endurance reduction over the life span. The endurance reduction in flash storage devices is associated with the tolerance for write-erase cycles by the flash storage device, while performance of the flash storage device is impacted by the availability of free writeable data blocks in the flash storage device.” and [0049-50] “Garbage Collection for Reference Sets in Flash Storage Systems” and “…garbage collection can be performed as described below…”, [0055] “ [0189] “… amount of memory used for associated with a data set… a reference data set meets retirement based on the amount of memory used in a storage device…”, wherein the amount of memory is illustrated as the capacity of the storage device(s) as known by a skilled artisan).
Regarding claim 4, Singhai teaches wherein the processing device (Fig. 2 at element 204 – Processor) is further to:
-66-Docket No.: P70479 11840US.C1determine an expected longevity associated with each of the valid data based on the plurality of characteristics, wherein the valid data is grouped based on a similarity of the expected longevity between the valid data (pars.[0010] and [0042] “the reference data sets may have the following characteristics: 1)… a period of time and 2)… Next, 3)… Lastly, 4)…it can be retired after the use count drops to zero…” and [0049-52], “Garbage Collection” algorithm, “valid data blocks” which storing valid data to be moved=erased, “if a reference data set (e.g., reference data set R) is expected to be retired soon, then reconstruct original data blocks using the reference data set (e.g., R) and newly deduplicate it using a newer reference data set(s).”, wherein the “expected to be retired soon” is interpreted as an expected longevity in the claim, and the reconstruct=generate group of original data blocks and group of newer reference data sets, see further in pars. [0143] “the new reference data set may satisfy for retirement …” and [0162], “In some embodiments, reference blocks are grouped into a subset based on a degree of similarity associated with content of each reference data block” wherein herein the data blocks contain the valid data).
Regarding claim 5, Kimmel, Ebsen, and Singhai, in combination, teach: wherein the plurality of characteristics comprise an age associated with each of the valid data (Kimmel: col. 5, lines 9-19: “classification and localization of cache lines with similar cache aging and invalidation behaviors within erase block boundaries, allowing efficient reuse of flash locations while improving effective cache capacity. After erase block fill using these methods, the slow-turn, fast-turn or no-turn designation for an erase block or stripe can be forgotten, using line-granular tracking of line use and invalidation to inform subsequent reuse of the erase block or stripe.”; Ebsen: col. 10, lines 15-46 via the grouping of plurality of blocks to specify a garbage collection unit, wherein group the blocks comprise the valid data, and group the blocks having invalid data, e.g., “stale” or “staleness” that need to be erased, and col. 11, lines 4-17: “… Factors such as the staleness of a block may still be considered and factored into the efficiency metrics.”; and Singhai: pars. [0050-52] “retirement”/”retire older…” inherit to age, and [0189] e.g., “retirement criteria…amount of times, … a predetermined duration (e.g., minutes, hours, days, weeks, etc. “ which equivalent to “age” of the reference data sets storing in blocks of storage device(s), Fig. 2).
Regarding claim 6, Singhai teaches: wherein the plurality of characteristics comprise a type of data associated with each of the valid data (Singhai: par. [0154] “…receives a set of data blocks from one or more client devices (e.g. client devices 102). The set of data blocks can be associated with, but not limited to, document files of a type such as, but not limited to, word doc, pdfs, jpegs, etc., rendered by applications of the client devices (e.g. client devices 102). Next, the method 800 may continue by performing 804 a similarity analysis of the set of data blocks.”, wherein the “a type such as, but not limited to, word doc, pdfs, jpegs, etc.,” is interpreted as type of data which associated with the valid data in data blocks of storage device(s)).
Claims 8-13, 15-20 are rejected in the analysis of above claims 1-6; and therefore, the claims are rejected on that basis.
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Kimmel, Ebsen, and Singhai, and further in view of Huang et al., US Pub. No. 20150019797 (hereinafter as “Huang”).
Regarding claim 7, the claim is rejected by the same reasons set forth above to claim 1. However, Kimmel, Ebsen, and Singhai do not explicitly teach “wherein the plurality of characteristics specifies a deduplication importance associated with each valid data,” and “the deduplication importance corresponding to a number of times that a respective valid data was associated with a deduplication operation.”
In the same field of endeavor (i.e., data processing), Huang teaches:
wherein the plurality of characteristics specifies a deduplication importance associated with each valid data (pars. [0034-37] teaches the duplicate pages/data found in block(s) during the garbage collection processing or performing), the deduplication importance corresponding to a number of times that a respective valid data was associated with a deduplication operation (Fig. 5 element 512 checking for “De-dupe” data, and pars. [0035-37] and [0050-51] teaches exceeding threshold implies to detecting a number of times the valid/invalid pages/data were associated with the duplicate operation).
Therefore, it would have been obvious to one of ordinary skill in the data processing art before the effective filing date of the claimed invention to combine the teachings of the cited references because the teachings of Huang would have provided Kimmel, Ebsen, and Singhai with the above indicated limitations for facilitating data deduplication to perform garbage collection to save/reduce storage.
Claim 14 is rejected in the analysis of above claim 7; and therefore, the claim is rejected on that basis.
Response to Arguments
Referring to claim rejections under 35 USC. 103, Applicant’s arguments (see Remarks, page 7) to the claim limitations including amended limitation in claim 1 (similar to claims 8 and 15) have been fully considered, but are moot in view of the new grounds of rejection necessitated by applicant's amendment to the claims. Applicant's newly amended features are taught implicitly, expressly, or impliedly by the prior art of record.
Prior Arts
The prior art made of record on form PTO-892 and not relied upon is considered pertinent to applicant's disclosure. Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
It is noted that any citation to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the references 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 In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275,277 (CCPA 1968)); Merck & Co. v. Biocraft Laboratories, 874 F.2d 804, 10 USPQ2d 1843 (Fed. Cir.), cert. denied, 493 U.S. 975 (1989).
Conclusion
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/Jessica N Le/Examiner, Art Unit 2169 /MD I UDDIN/ Primary Examiner, Art Unit 2169