cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14272/usgaesjtvoshev-uhfffaoysa-n/chmo0000630
title: infrared absorption spectroscopy (IR) (4-(5-tricyclo[8.2.2.24,7]hexadeca-1(13),4,6,10(14),11,15-hexaenyl)benzonitrile)
title: InChI=1S/C23H19N/c24-16-20-9-13-22(14-10-20)23-15-19-6-5-17-1-3-18(4-2-17)7-11-21(23)12-8-19/h1-4,8-10,12-15H,5-7,11H2

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 2924, 2873, 2850, 2227, 1604, 1591, 1500, 1476, 1456, 1435, 1414, 1392, 1367, 1354, 1320, 1305, 1278, 1258, 1238, 1213, 1183, 1177, 1163, 1108, 1092, 1017, 990, 953, 941, 907, 881, 850, 837, 822, 795, 775, 765, 755, 737, 718, 691, 676, 671, 654, 639, 595, 567, 530, 509, 494, 473, 455, 449, 431, 414, 402, 388, 380 cm–1.
DOI: 10.7910/dvn/il0lue/2vid9l
title: product_process_patents_2_ind_100_us_Analysis of biological materials.png

description: :unav
DOI: 10.7910/dvn/il0lue/5k8hzh
title: product_process_patents_abstr_us_airplanes.png

description: :unav
DOI: 10.7910/dvn/il0lue/jo2ycq
title: product_process_patents_abstr_ep_nanotech.png

description: :unav
DOI: 10.7910/dvn/il0lue/kejick
title: product_process_patents_pred_100_us_Analysis of biological materials.png

description: :unav
DOI: 10.7910/dvn/il0lue/kjgvzq
title: product_process_patents_pred_ind_100_us_Medical technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/lljnbl
title: product_process_patents_pred_100_us_Macromolecular chemistry, polymers.png

description: :unav
DOI: 10.7910/dvn/il0lue/tltnoy
title: product_process_patents_abstr_us_Organic fine chemistry.png

description: :unav
DOI: 10.7910/dvn/il0lue/tyktkr
title: product_process_patents_pred_ind_100_ep_Mechanical elements.png

description: :unav
DOI: 10.7910/dvn/il0lue/w9qrpl
title: product_process_patents_abstr_ep_Medical technology.png

description: :unav
DOI: 10.5281/zenodo.3588276
title: Human Methylene- tetrahydrofolate reductase (MTHFR) A Target Enabling Package (TEP)

description: The folate and methionine cycles are essential metabolic pathways for life, involved respectively in DNA synthesis and generation of the ubiquitous methyl donor S-adenosylmethionine (SAM). The enzyme 5,10-methylenetetrahydrofolate reductase (MTHFR) represents a key regulatory connection between these cycles, hence exerting a strong influence on an array of diseases. This TEP presents the first structures for any eukaryotic MTHFR, revealing a novel SAM-binding fold. The TEP provides additional mass spectrometry, activity assay and biophysical binding methods yielding mechanistic insights into how phosphorylation and allosteric binding of SAM act in concert to inhibit MTHFR activity. This work further provides the starting point for the design of tool molecules (e.g. SAM-analogues) aimed at disrupting the SAM-induced inhibition of MTHFR activity.
DOI: 10.7910/dvn/il0lue/0ceo6i
title: product_process_patents_abstr_us_C05.png

description: :unav
DOI: 10.7910/dvn/il0lue/6lqa4v
title: product_process_patents_pred_100_ep_F02B.png

description: :unav
DOI: 10.7910/dvn/il0lue/fdn7mv
title: product_process_patents_2_ind_100_ep_Civil engineering.png

description: :unav
DOI: 10.7910/dvn/il0lue/hnnzfr
title: product_process_patents_abstr_us_Transport.png

description: :unav
DOI: 10.7910/dvn/il0lue/j7kreo
title: product_process_patents_2_ind_100_us_Basic materials chemistry .png

description: :unav
DOI: 10.7910/dvn/il0lue/nrmgsg
title: product_process_patents_2_ind_100_ep_Computer technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/sfkk49
title: product_process_patents_2_100_ep_Chemical engineering.png

description: :unav
DOI: 10.7910/dvn/il0lue/spls97
title: product_process_patents_abstr_us_Computer technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/w9kwtq
title: product_process_patents_2_ind_100_us_Micro-structural and nano-technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/wtswle
title: product_process_patents_abstr_ep_Digital communication.png

description: :unav
DOI: 10.5281/zenodo.3588277
title: Phenological metrics for Protected Area "DanubeDelta", MODIS terra tile h20v04

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.5281/zenodo.3588278
title: Phenological metrics for Protected Area "DanubeDelta", MODIS terra tile h20v04

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.5281/zenodo.3588281
title: Phenological metrics for Protected Area "Donana", MODIS terra tile h17v05

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.5281/zenodo.3588282
title: Phenological metrics for Protected Area "Donana", MODIS terra tile h17v05

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.7910/dvn/il0lue/3opcba
title: product_process_patents_pred_ind_100_ep_Computer technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/6usraf
title: product_process_patents_2_100_us_robotics.png

description: :unav
DOI: 10.7910/dvn/il0lue/aq9dxs
title: product_process_patents_pred_ind_100_ep_Other consumer goods.png

description: :unav
DOI: 10.7910/dvn/il0lue/ax0raz
title: product_process_patents_pred_ind_100_us_Textile and paper machines.png

description: :unav
DOI: 10.7910/dvn/il0lue/g30vsv
title: product_process_patents_2_100_ep_Control.png

description: :unav
DOI: 10.7910/dvn/il0lue/nqlrvh
title: product_process_patents_abstr_ep_Materials, metallurgy.png

description: :unav
DOI: 10.7910/dvn/il0lue/ohecpn
title: product_process_patents_pred_ind_100_us_Other special machines.png

description: :unav
DOI: 10.7910/dvn/il0lue/u7aq1x
title: product_process_patents_pred_100_us_Textile and paper machines.png

description: :unav
DOI: 10.17632/ydcr7mcrtp.6
title: TabbyXL: Dataset for the Performance Evaluation of a Software Platform for Rule-Based Spreadsheet Data Extraction and Transformation

description: This dataset is designed to evaluate TabbyXL (version 1.1.0), a software platform for the rule-based transformation of spreadsheet data from arbitrary to relational tables, that is freely available at [GitHub](https://github.com/tabbydoc/tabbyxl/releases/tag/v1.1.0). The dataset provides all required data to reproduce the performance evaluation including the program running and automatic performance evaluation of TabbyXL. The performance evaluation confirms the applicability of the implemented rulesets to process a bunch of different arbitrary tables of the same genre (government statistical websites). This demonstrates that TabbyXL can be used for developing programs for the transformation of spreadsheet data into the relational form. README.md file included in this dataset provides a detail description of the data and steps to reproduce the experiment.
DOI: 10.5281/zenodo.3588283
title: Phenological metrics for Protected Area "SierraNevadaEcosystem", MODIS aqua tile h17v05

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.5281/zenodo.3588284
title: Phenological metrics for Protected Area "SierraNevadaEcosystem", MODIS aqua tile h17v05

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.7910/dvn/il0lue/9jlu73
title: product_process_patents_pred_ind_100_ep_nanotech.png

description: :unav
DOI: 10.7910/dvn/il0lue/budqp8
title: product_process_patents_2_ind_100_ep_C05.png

description: :unav
DOI: 10.7910/dvn/il0lue/jzzy5z
title: product_process_patents_pred_100_ep_Handling.png

description: :unav
DOI: 10.7910/dvn/il0lue/wl1nk7
title: product_process_patents_2_100_us_H01M.png

description: :unav
DOI: 10.7910/dvn/il0lue/xbxjok
title: product_process_patents_2_100_us_Medical technology.png

description: :unav
DOI: 10.7910/dvn/il0lue/ywzyau
title: product_process_patents_pred_ind_100_ep_Thermal processes and apparatus.png

description: :unav
DOI: 10.7910/dvn/il0lue/zn080l
title: product_process_patents_abstr_us_nanotech.png

description: :unav
DOI: 10.17632/wcvcctfxhh.1
title: Data for: Bilateral comparison of the absorbed dose to water in high energy X-ray beams between the KRISS and the NMIJ

description: The data sets are (1) the technical protocol prepared for the comparison study and (2) the results reported by the KRISS.
DOI: 10.5281/zenodo.3585730
title: 87Rb MAS NMR Spectrum of RbClO4

description: <sup>87</sup>Rb MAS echo NMR spectrum of RbClO<sub>4</sub>.
description: Dead link in CSDFE file updated
DOI: 10.5281/zenodo.3585731
title: 87Rb MAS NMR Spectrum of RbClO4

description: <sup>87</sup>Rb MAS echo NMR spectrum of RbClO<sub>4</sub>.
DOI: 10.5281/zenodo.3588287
title: Phenological metrics for Protected Area "Samaria", MODIS terra tile h19v05

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.5281/zenodo.3588288
title: Phenological metrics for Protected Area "Samaria", MODIS terra tile h19v05

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.5281/zenodo.3588293
title: Phenological metrics for Protected Area "OhridPrespa", MODIS aqua tile h19v04

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.5281/zenodo.3588294
title: Phenological metrics for Protected Area "OhridPrespa", MODIS aqua tile h19v04

description: Phenological metrics derived from satellite data by use of R-package "phenex" (Lange (2017)). NDVI is filtered by modified BISE algorithm (see Viovy (1992)). NDVI curve is modelled with method DLogistic (see Doktor (2017), Lange (2017)). Phenological metrics include: (1) Start of season / green-up (GU); (2) End of season / senescence (SEN); (3) Length of vegetation period (VP); (4) GPP proxy (integral over vegetation period, GSIVI); (5) minimum NDVI (MinNDVI); (6) maximum NDVI (MaxNDVI); (7) day of minimum NDVI as julian date (MinDOY); (8) day of maximum NDVI as julian date (MaxDOY); (9) r-square of modelled NDVI curve; (1)-(4) are derived by using local threshold (LT) and global threshold (GT) method (see Doktor (2017), Lange (2017)). (1)-(6) include mean and standard deviation; References: [Viovy 1992]: Viovy N, Arino O, Belward A (1992) The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13(8):1585–1590; [Doktor 2017]: Doktor D, Lange M (2017) Disparate applicability and broad spatio-temporal satellite resolution affects extracted trends of European spring phenology for 1989-2007. In preparation for Global Ecology and Biogeographie; [Lange 2017]: Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex, Last accessed on 2017-05-29;
DOI: 10.7910/dvn/il0lue/1ddjmc
title: product_process_patents_2_ind_100_us_Handling.png

description: :unav
DOI: 10.7910/dvn/il0lue/ffvgxt
title: product_process_patents_2_100_ep_smartphones.png

description: :unav
DOI: 10.7910/dvn/il0lue/mt4wqw
title: product_process_patents_pred_ind_100_ep_semiconductors.png

description: :unav
DOI: 10.7910/dvn/il0lue/qumrji
title: product_process_patents_abstr_ep_Macromolecular chemistry, polymers.png

description: :unav
DOI: 10.7910/dvn/il0lue/sf5xjb
title: product_process_patents_pred_100_us_Optics.png

description: :unav
DOI: 10.7910/dvn/il0lue/tasbm0
title: product_process_patents_pred_ind_100_us_Mechanical elements.png

description: :unav
DOI: 10.7910/dvn/il0lue/u7f0xk
title: product_process_patents_pred_100_ep_Micro-structural and nano-technology.png

description: :unav