cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14457/tu.the.2019.58
title: Long-term food waste management in Phnom Penh utilizing the system dynamics modelling approach: a case study of Chamkamon and Daun penh districts, Phnom Penh, Cambodia

description: Phnom Penh, the capital city of Cambodia, has high population growth that leads to high amount of food waste. This creates a number of environmental impacts, such as global warming, methane emission, and ground water contamination. To properly manage food waste, it is necessary to identify key factors affecting food waste management. Moreover, the interactions among key food waste factors are required to effectively plan for the long-term food waste management. This study develops the dynamics model of food waste management, utilizing the system dynamics modelling approach, to investigate trend of food waste in Phnom Penh, and plan for food waste management in the long-term. The developed dynamics model considers two major sources of waste, namely household and retailer wastes with a total of 12 key factors affecting food waste management. The simulation results reveal that majority of food wastes come from households, and that they are mainly from inappropriate preparation processes, inappropriate packing sizes, and unfinished promotion packs. Policy analyses, performed through the developed dynamics model, suggest to reduce waste during preparation processes, use packing sizes that match with customer requirement, and consider promotions that are suitable for short-life products, including vegetables. Those strategies assist for long-term food waste management, and mitigate landfill and environmental problems in Phnom Penh. Cooperation among households, retailers, local authority, and government are crucial to sustain the implementation plan in the long-term. The developed dynamics model of food waste management raises concerns of food waste and landfill problems, and suggest a number of plans for households, retailers, local authority, and government to be used to manage food waste in the long-term.
DOI: 10.5523/bris.1hg5f7mlbumld2rqnaov5dyn26
title: On the Use of the Geometric Median in Delay-and-Sum Ultrasonic Array Imaging - This dataset is superseded by 10.5523/bris.1k3uq7c27gzm52qqijhbhmu3ux

description: Supporting data for the paper in IEEE Trans. Ultrason. Ferroelect. Freq. Contr., "On the Use of the Geometric Median in Delay-and-Sum Ultrasonic Array Imaging" *** This dataset is superseded by a later dataset under DOI 10.5523/bris.1k3uq7c27gzm52qqijhbhmu3ux
DOI: 10.21227/0btt-mm59
title: Fault-Tolerant Fractional-Slot PMSMs with One Coil Parallel Branches Made Phases. Part 2: Circulating Harmonic Current Rejection Potential

description: The paper is aimed at a class of fractionalslotpermanentmagnet synchronousmachines (FSPMSMs)equipped with phases made up of one coil parallelbranches, with emphasis on their potential to reject theharmonic currents circulating in the loops created by theparallel branches. Following the identification and topologicalcharacterization of this class of machines in Part 1,the star of slots approach is extended to the analysis ofthe back-EMF harmonic content. This makes it possible theinvestigation of the possible circulating harmonic currentsby checking the phase shifts between the different back-EMF harmonics induced in the coils belonging to eachphase. It is shown that all candidates identified in Part1 exhibit the potential to reject circulating harmonic currents.The paper is achieved by a case study dedicated toa candidate equipped with three phases made up of sixparallel branches including a single coil each. Its featuresare predicted by a 2D finite element analysis. Selected noandon-load features are experimentally-validated.
DOI: 10.21227/37sv-2848
title: Fault-Tolerant Fractional-Slot PMSMs with One Coil Parallel Branches Made Phases. Part 2: Circulating Harmonic Current Rejection Potential

description: The paper is aimed at a class of fractionalslotpermanentmagnet synchronousmachines (FSPMSMs)equipped with phases made up of one coil parallelbranches, with emphasis on their potential to reject theharmonic currents circulating in the loops created by theparallel branches. Following the identification and topologicalcharacterization of this class of machines in Part 1,the star of slots approach is extended to the analysis ofthe back-EMF harmonic content. This makes it possible theinvestigation of the possible circulating harmonic currentsby checking the phase shifts between the different back-EMF harmonics induced in the coils belonging to eachphase. It is shown that all candidates identified in Part1 exhibit the potential to reject circulating harmonic currents.The paper is achieved by a case study dedicated toa candidate equipped with three phases made up of sixparallel branches including a single coil each. Its featuresare predicted by a 2D finite element analysis. Selected noandon-load features are experimentally-validated.
DOI: 10.15161/oar.it/23550
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.14272/xhfjihlnmpupee-uhfffaoysa-l/chmo0000739
title: 31P nuclear magnetic resonance spectroscopy (31P NMR) ()
title: InChI=1S/2C18H12F3P.C18H16NP.2Cu.2HI/c2*19-13-1-7-16(8-2-13)22(17-9-3-14(20)4-10-17)18-11-5-15(21)6-12-18;1-15-12-13-19-18(14-15)20(16-8-4-2-5-9-16)17-10-6-3-7-11-17;;;;/h2*1-12H;2-14H,1H3;;;2*1H/q;;;2*+1;;/p-2

description: dataset for 31P nuclear magnetic resonance spectroscopy (31P NMR) 31P NMR (162 MHz, DMSO-d6) δ [ppm] = −4.98 (bs, 1P, PMePyrPhos), −14.13 (bs, 2P, P(F-Ph)3P). Impurities: 1% phosphine oxide of the ligands, note that the complex was not completely dissolved in the deuterated solvent.
DOI: 10.14272/xhfjihlnmpupee-uhfffaoysa-l.1
title: C54H40Cu2F6I2NP3
title: InChI=1S/2C18H12F3P.C18H16NP.2Cu.2HI/c2*19-13-1-7-16(8-2-13)22(17-9-3-14(20)4-10-17)18-11-5-15(21)6-12-18;1-15-12-13-19-18(14-15)20(16-8-4-2-5-9-16)17-10-6-3-7-11-17;;;;/h2*1-12H;2-14H,1H3;;;2*1H/q;;;2*+1;;/p-2

description: This dataset contains experimental data from a sample (InChI=1S/2C18H12F3P.C18H16NP.2Cu.2HI/c2*19-13-1-7-16(8-2-13)22(17-9-3-14(20)4-10-17)18-11-5-15(21)6-12-18;1-15-12-13-19-18(14-15)20(16-8-4-2-5-9-16)17-10-6-3-7-11-17;;;;/h2*1-12H;2-14H,1H3;;;2*1H/q;;;2*+1;;/p-2). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) 31P nuclear magnetic resonance spectroscopy (31P NMR) 19F nuclear magnetic resonance spectroscopy (19F NMR) infrared absorption spectroscopy (IR) mass spectrometry (MS) single crystal X-ray diffraction (single-crystal X-ray diffraction)
DOI: 10.14272/xhfjihlnmpupee-uhfffaoysa-l/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/2C18H12F3P.C18H16NP.2Cu.2HI/c2*19-13-1-7-16(8-2-13)22(17-9-3-14(20)4-10-17)18-11-5-15(21)6-12-18;1-15-12-13-19-18(14-15)20(16-8-4-2-5-9-16)17-10-6-3-7-11-17;;;;/h2*1-12H;2-14H,1H3;;;2*1H/q;;;2*+1;;/p-2

description: dataset for infrared absorption spectroscopy (IR) IR (ATR) 𝜈̃ [cm–1] = 3053 (vw), 2958 (vw), 2923 (vw), 2856 (vw), 1585 (m), 1494 (m), 1433 (w), 1393 (w), 1300 (w), 1225 (w), 1158 (m), 1093 (w), 1013 (w), 825 (m), 742 (w), 693 (w), 635 (vw), 518 (m), 494 (w), 463 (w), 442 (w), 430 (w).
DOI: 10.14272/xhfjihlnmpupee-uhfffaoysa-l/chmo0000159
title: single crystal X-ray diffraction (single-crystal X-ray diffraction) ()
title: InChI=1S/2C18H12F3P.C18H16NP.2Cu.2HI/c2*19-13-1-7-16(8-2-13)22(17-9-3-14(20)4-10-17)18-11-5-15(21)6-12-18;1-15-12-13-19-18(14-15)20(16-8-4-2-5-9-16)17-10-6-3-7-11-17;;;;/h2*1-12H;2-14H,1H3;;;2*1H/q;;;2*+1;;/p-2

description: dataset for single crystal X-ray diffraction (single-crystal X-ray diffraction)
DOI: 10.14272/xhfjihlnmpupee-uhfffaoysa-l/chmo0000470
title: mass spectrometry (MS) ()
title: InChI=1S/2C18H12F3P.C18H16NP.2Cu.2HI/c2*19-13-1-7-16(8-2-13)22(17-9-3-14(20)4-10-17)18-11-5-15(21)6-12-18;1-15-12-13-19-18(14-15)20(16-8-4-2-5-9-16)17-10-6-3-7-11-17;;;;/h2*1-12H;2-14H,1H3;;;2*1H/q;;;2*+1;;/p-2

description: dataset for mass spectrometry (MS) MS (FAB, 3-NBA) m/z [%] = 1351 (4) [M+Cu]+, 1161 (2) [M-I]+, 1074 (1) [Cu3I2P2]+, 1035 (2) [Cu3I2LP]+, 996 (6) [Cu3I2L2]+, 884 (8) [Cu2IP2]+, 845 (13) [Cu2ILP]+, 719 (19) [Cu3I2L]+, 695 (23) [CuP2]+, 568 (5) [Cu2IP]+, 529 (35) [Cu2IL]+, 378 (4) [CuP]+, 340 (38) [CuL]+, 278 (13) [L+H]+.
DOI: 10.14272/xhfjihlnmpupee-uhfffaoysa-l/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/2C18H12F3P.C18H16NP.2Cu.2HI/c2*19-13-1-7-16(8-2-13)22(17-9-3-14(20)4-10-17)18-11-5-15(21)6-12-18;1-15-12-13-19-18(14-15)20(16-8-4-2-5-9-16)17-10-6-3-7-11-17;;;;/h2*1-12H;2-14H,1H3;;;2*1H/q;;;2*+1;;/p-2

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, DMSO-d6) δ [ppm] = 8.51 (bs, 1H, HPyr), 7.47–7.20 (m, 36H), 2.27 (s, 3H, HMe). Impurities: 1% DCM, 3% H-grease, 4% THF, 10% EE, 1% phosphine oxide of the ligands according to the 31P-NMR, note that the complex was not completely dissolved in the deuterated solvent.
DOI: 10.14272/xhfjihlnmpupee-uhfffaoysa-l/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/2C18H12F3P.C18H16NP.2Cu.2HI/c2*19-13-1-7-16(8-2-13)22(17-9-3-14(20)4-10-17)18-11-5-15(21)6-12-18;1-15-12-13-19-18(14-15)20(16-8-4-2-5-9-16)17-10-6-3-7-11-17;;;;/h2*1-12H;2-14H,1H3;;;2*1H/q;;;2*+1;;/p-2

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C-NMR (400 MHz, DMSO-d6) δ [ppm] = 164.4 (s), 162.0 (s), 136.0 (dd, J = 15.6 Hz, J = 8.4 Hz), 133.4 (d, J = 13.3 Hz), 130.0 (s), 129.0 (d, J = 28.3 Hz), 128.6 (d, J = 7.6 Hz), 115.9 (dd, J = 21.2 Hz, J = 9.4 Hz), 20.6 (s, 1C, CMe), resonances could not be assigned due to low resolution even at 8192 ns (45C). Impurities: 1% DCM, 3% H-grease, 4% THF, 10% EE, 1% phosphine oxide of the ligands according to the 31P-NMR, note that the complex was not completely dissolved in the deuterated solvent.
DOI: 10.14272/xhfjihlnmpupee-uhfffaoysa-l/chmo0000597
title: 19F nuclear magnetic resonance spectroscopy (19F NMR) ()
title: InChI=1S/2C18H12F3P.C18H16NP.2Cu.2HI/c2*19-13-1-7-16(8-2-13)22(17-9-3-14(20)4-10-17)18-11-5-15(21)6-12-18;1-15-12-13-19-18(14-15)20(16-8-4-2-5-9-16)17-10-6-3-7-11-17;;;;/h2*1-12H;2-14H,1H3;;;2*1H/q;;;2*+1;;/p-2

description: dataset for 19F nuclear magnetic resonance spectroscopy (19F NMR) 19F NMR (376 MHz, DMSO-d6) δ [ppm] = −114.87 (s, 6F, F(F-Ph)3P). Impurities: 1% phosphine oxide of the ligands according to the 31P-NMR, note that the complex was not completely dissolved in the deuterated solvent.
DOI: 10.18112/openneuro.ds002692.v1.0.0
title: my study
DOI: 10.5281/zenodo.3746068
title: Presencia y Producción en Scopus de los Titulares y Catedráticos de Comunicación (2000-19)

description: Para la obtención del presente set de datos se han buscado los perfiles de los titulares y catedráticos en Comunicación (2000-2019) en Scopus. Scopus es una base de datos bibliográfica de Elsevier que asigna un perdil a los autores de sus trabajos bajo el cual se agrupan los posteriores trabajos. ERRORES. Si algún profesor que aparece como AUSENTE en el listado realmente sí está indexado en Scopus, háganos llegar su número de identificación de Scopus y lo agregaremos sin más problemas. Dada la sensibilidad de algunos compañeros esta búsqueda la han hecho por separado dos personas, para tratar de ser lo más exhaustivo posible, en el proceso se han corregido y unificado más de 80 perfiles de profesores que aparecían divididos en dos o más perfiles (un mismo profesor tenía varios perfiles que han sido unificados, de nada...).
DOI: 10.5281/zenodo.3746067
title: Presencia y Producción en Scopus de los Titulares y Catedráticos de Comunicación (2000-19)

description: Para la obtención del presente set de datos se han buscado los perfiles de los titulares y catedráticos en Comunicación (2000-2019) en Scopus. Scopus es una base de datos bibliográfica de Elsevier que asigna un perdil a los autores de sus trabajos bajo el cual se agrupan los posteriores trabajos. ERRORES. Si algún profesor que aparece como AUSENTE en el listado realmente sí está indexado en Scopus, háganos llegar su número de identificación de Scopus y lo agregaremos sin más problemas. Dada la sensibilidad de algunos compañeros esta búsqueda la han hecho por separado dos personas, para tratar de ser lo más exhaustivo posible, en el proceso se han corregido y unificado más de 80 perfiles de profesores que aparecían divididos en dos o más perfiles (un mismo profesor tenía varios perfiles que han sido unificados, de nada...).
DOI: 10.15468/w74476
title: Comment on “ Protein Sequences from Mastodon and Tyrannosaurus rex Revealed by Mass Spectrometry ”

description: This dataset contains the digitized treatments in Plazi based on the original journal article Mike Buckley, Ange 1 la Walker, Simon Y. W. Ho, Yue Yang, Colin Smith, Peter Ashton, Jane Thomas Oates, Enrico Cappellini, Hannah Koon, Kirsty Penkman, Ben Elsworth, Dave Ashford, Caroline Solazzo, Phillip Andrews, John Strahler, Beth Shapiro, Peggy Ostrom, Hasand Gandhi, Webb Miller, Brian Raney, Maria Ines Zylber, M. Thomas P. Gilbert, Richard V. Prigodich, Michael Ryan, Kenneth F. Rijsdijk, Anwar Janoo, Matthew J. Collins (2008): Comment on “ Protein Sequences from Mastodon and Tyrannosaurus rex Revealed by Mass Spectrometry ”. Science 319: 33, DOI: 10.1126/science.1147046
DOI: 10.25345/c5mm7z
title: MassIVE MSV000085262 - Streptomyces noursei liquid fermentation in ISP2
title: Streptomyces noursei crude extract. Grown in liquid ISP2 medium (room temperature and 180 RPM). Extracted using Diaion HP20 resin and subsequent methanol extraction (3 x 24hr). Prepared at 0.3 mg/mL, injection vol. = 10 microliters.
DOI: 10.14457/mu.res.2019.2
title: Novel approach for combating a clique of multi-drug resistant “ESKAPE”: a Pseudomonas aeruginosa model
DOI: 10.14457/mu.res.2019.3
title: Neutrophil activation and NETosis in patients infected with dengue virus
DOI: 10.17632/7jnr3g75cj.2
title: The Role of Blueschist Stored in Shallow Lithosphere in the Generation of Post-collisional Orogenic Magmas

description: Eight figures and eighteen tables relevant to this study.
DOI: 10.15468/2fummq
title: Comment on “ Protein Sequences from Mastodon and Tyrannosaurus rex Revealed by Mass Spectrometry ”

description: This dataset contains the digitized treatments in Plazi based on the original journal article Pavel A. Pevzner, Sangtae Kim, Julio Ng (2008): Comment on “ Protein Sequences from Mastodon and Tyrannosaurus rex Revealed by Mass Spectrometry ”. Science 321: 1040, DOI: 10.1126/science.1155006
DOI: 10.5281/zenodo.3738380
title: Dataset from "Subsurface Structure at the InSight landing site from compliance measurements by seismic and meteorological experiments"

description: This document describes the data available in this folder. These data include both modeling data and derived data obtained from the raw data of the InSight SEIS and APSS experiments. For the raw data, we acknowledge : InSight Mars SEIS Data Service. (2019). SEIS raw data, Insight Mission. IPGP, JPL, CNES, ETHZ, ICL, MPS, ISAE-Supaero, LPG, MFSC. https://doi.org/10.18715/SEIS.INSIGHT.XB_2016 The dataset described was used to produce all the Figures and Table 3 of the following paper (referred to as Kenda et al., 2020, in the rest of this document): B. Kenda, M. Drilleau, R. Garcia, T. Kawamura, N. Murdoch, N. Compaire, P. Lognonné, A. Spiga, R. Widmer-Schnidrig, P. Delage, V. Ansan, C. Vrettos, S. Rodriguez, W. B. Banerdt, D. Banfield, D. Antonangeli, U. Christensen, D. Mimoun, A. Mocquet, T. Spohn, Subsurface structure at the InSight landing site from compliance measurements by seismic and meteorological experiments. Journal of Geophysical Research: Planets. The folder is subdivided into the following folders (in alphabetical order): Compliance_models_and_sensitivity this folder contains structural models of the near surface and the corrseponding calculated ground compliance as a function of frequency. These were used to illustrate the theory described in the paper and to exhibit the sensitivity of ground compliance to a variety of parameters. In particular, the data were used to produce Figures 1, 2, 3, 4, 5 and 9 of Kenda et al. (2020). Mars_data contains a series of data derived from the InSight SEIS and APSS observations, including examples of coherence between seismic and pressure measurements, and compliance observations based on two different techniques. These data are represent in Kenda et al. 2020 in Figures 6, 7 and 8. Mars_inversion contains the results of the inversion of Martian data performed in our study and used to guide our interpretations. These data were used to produce Figures 15, 16, 17 and 18, and Table 3 of Kenda et al. (2020). Synthetic_inversion presents the data relative to the inversion scheme and to a series of synthetic tests (Figures 10, 11, 12, 13 and 14 of Kenda et al., 2020). All data are provided in ASCII format, with a detailed description in the README.txt file in each of the subfolders.
DOI: 10.5281/zenodo.3738379
title: Dataset from "Subsurface Structure at the InSight landing site from compliance measurements by seismic and meteorological experiments"

description: This document describes the data available in this folder. These data include both modeling data and derived data obtained from the raw data of the InSight SEIS and APSS experiments. For the raw data, we acknowledge : InSight Mars SEIS Data Service. (2019). SEIS raw data, Insight Mission. IPGP, JPL, CNES, ETHZ, ICL, MPS, ISAE-Supaero, LPG, MFSC. https://doi.org/10.18715/SEIS.INSIGHT.XB_2016 The dataset described was used to produce all the Figures and Table 3 of the following paper (referred to as Kenda et al., 2020, in the rest of this document): B. Kenda, M. Drilleau, R. Garcia, T. Kawamura, N. Murdoch, N. Compaire, P. Lognonné, A. Spiga, R. Widmer-Schnidrig, P. Delage, V. Ansan, C. Vrettos, S. Rodriguez, W. B. Banerdt, D. Banfield, D. Antonangeli, U. Christensen, D. Mimoun, A. Mocquet, T. Spohn, Subsurface structure at the InSight landing site from compliance measurements by seismic and meteorological experiments. Journal of Geophysical Research: Planets. The folder is subdivided into the following folders (in alphabetical order): Compliance_models_and_sensitivity this folder contains structural models of the near surface and the corrseponding calculated ground compliance as a function of frequency. These were used to illustrate the theory described in the paper and to exhibit the sensitivity of ground compliance to a variety of parameters. In particular, the data were used to produce Figures 1, 2, 3, 4, 5 and 9 of Kenda et al. (2020). Mars_data contains a series of data derived from the InSight SEIS and APSS observations, including examples of coherence between seismic and pressure measurements, and compliance observations based on two different techniques. These data are represent in Kenda et al. 2020 in Figures 6, 7 and 8. Mars_inversion contains the results of the inversion of Martian data performed in our study and used to guide our interpretations. These data were used to produce Figures 15, 16, 17 and 18, and Table 3 of Kenda et al. (2020). Synthetic_inversion presents the data relative to the inversion scheme and to a series of synthetic tests (Figures 10, 11, 12, 13 and 14 of Kenda et al., 2020). All data are provided in ASCII format, with a detailed description in the README.txt file in each of the subfolders.
DOI: 10.5281/zenodo.3746119
title: Modeling plate and spring reverberation using a DSP-informed deep neural network

description: Accompanying audio samples for the paper: Martínez Ramírez M. A., Benetos, E. and Reiss J. D., “Modeling plate and spring reverberation using a DSP-informed deep neural network” in the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 2020. Dry and wet bass and guitar recordings. Bass and Guitar dry notes are taken from the IDMT-SMT-Audio-Effects dataset. Author: Michael Stein (Fraunhofer IDMT) https://www.idmt.fraunhofer.de/en/business_units/m2d/smt/audio_effects.html Plate Reverb - Bass - recordings are taken from the IDMT-SMT-Audio-Effects dataset. Plate settings are the following: <strong>Smaertelectronix ambience</strong>: ’Gating Amount - 0’, ’Gating Attack" - 10 ms’, ’Gating Release - 10 ms’, ’Decay Time - 2225 ms’, ’Decay Diffusion - 50%’, ’Decay Hold - off’, ’Shape Size - 16%’, ’Shape Predelay - 0 ms’, ’Shape Width - 100%’, ’Shape Quality - 100%’, ’Shape Variation - 0’, ’EQ Bass Frequency - 43 Hz’, ’EQ Bass Gain - −7.8 dB’, ’EQ Treble Frequency - 5044 Hz’, ’EQ Treble Gain - −3.7 dB’, ’Damping Bass Frequency - 158 Hz’, ’Damping Bass Amount - 87%’, ’Damping Treble Frequency - 8127 Hz’, ’Damping Treble Amount - 32%’, ’Dry - −Inf’, ’Wet - 0dB’. Spring Reverb - Bass and Guitar - recorded from the spring reverb tank<strong>: Accutronics </strong><strong>4</strong><strong>EB</strong><strong>2</strong><strong>C</strong><strong>1</strong><strong>B</strong>: ’Dry Mix - 0%’, ’Wet Mix - 100%’ Plate<em> </em>reverb samples correspond to a VST audio plug-in, while spring<em> </em>reverb samples are recorded using an analog reverb tank which is based on 2 springs placed in parallel. The recordings are downsampled to 16 kHz. Also, since the plate reverb samples have a fade-out applied in the last 0.5 seconds of the recordings, we process the spring reverb samples accordingly.
DOI: 10.5281/zenodo.3746118
title: Modeling plate and spring reverberation using a DSP-informed deep neural network

description: Accompanying audio samples for the paper: Martínez Ramírez M. A., Benetos, E. and Reiss J. D., “Modeling plate and spring reverberation using a DSP-informed deep neural network” in the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 2020. Dry and wet bass and guitar recordings. Bass and Guitar dry notes are taken from the IDMT-SMT-Audio-Effects dataset. Author: Michael Stein (Fraunhofer IDMT) https://www.idmt.fraunhofer.de/en/business_units/m2d/smt/audio_effects.html Plate Reverb - Bass - recordings are taken from the IDMT-SMT-Audio-Effects dataset. Plate settings are the following: <strong>Smaertelectronix ambience</strong>: ’Gating Amount - 0’, ’Gating Attack" - 10 ms’, ’Gating Release - 10 ms’, ’Decay Time - 2225 ms’, ’Decay Diffusion - 50%’, ’Decay Hold - off’, ’Shape Size - 16%’, ’Shape Predelay - 0 ms’, ’Shape Width - 100%’, ’Shape Quality - 100%’, ’Shape Variation - 0’, ’EQ Bass Frequency - 43 Hz’, ’EQ Bass Gain - −7.8 dB’, ’EQ Treble Frequency - 5044 Hz’, ’EQ Treble Gain - −3.7 dB’, ’Damping Bass Frequency - 158 Hz’, ’Damping Bass Amount - 87%’, ’Damping Treble Frequency - 8127 Hz’, ’Damping Treble Amount - 32%’, ’Dry - −Inf’, ’Wet - 0dB’. Spring Reverb - Bass and Guitar - recorded from the spring reverb tank<strong>: Accutronics </strong><strong>4</strong><strong>EB</strong><strong>2</strong><strong>C</strong><strong>1</strong><strong>B</strong>: ’Dry Mix - 0%’, ’Wet Mix - 100%’ Plate<em> </em>reverb samples correspond to a VST audio plug-in, while spring<em> </em>reverb samples are recorded using an analog reverb tank which is based on 2 springs placed in parallel. The recordings are downsampled to 16 kHz. Also, since the plate reverb samples have a fade-out applied in the last 0.5 seconds of the recordings, we process the spring reverb samples accordingly.
DOI: 10.25405/data.ncl.12102492.v1
title: Preese Hall-1 and Becconsall-1Z

description: Geochemistry Preese Hall-1 Becconsall-1Z
DOI: 10.5281/zenodo.3746126
title: RegionalVC

description: Test
DOI: 10.5281/zenodo.3746127
title: RegionalVC

description: Test