cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21225029.v1
title: SHARAD Surface Reflectivity Data for McGlasson et al. (submitted to JGR Planets)

description: SHARAD surface reflectivity maps for Martian PLDs and outlying crater deposits. <br> Both reflectivity maps are in equicylindrical projection using the Mars 2000 geographic coordinate system (GCS_Mars_2000_Sphere, 3396190.0 radius). Data covers poleward of 60 degrees in each hemisphere, and areas outside of the outlying deposits and PLDs are set to NoData. <br> Data are 20 ppd resolution, 64 bit pixel format. NoData pixels are represented by a value of -9999. Units are in meters. <br> <br>
DOI: 10.5281/zenodo.8169676
title: Assisted Extraction with Cyclodextrins as a Way of Improving the Antidiabetic Activity of Actinidia Leaves

description: Data includes source data and the publication to which it is related
DOI: 10.5281/zenodo.8169675
title: Assisted Extraction with Cyclodextrins as a Way of Improving the Antidiabetic Activity of Actinidia Leaves

description: Data includes source data and the publication to which it is related
DOI: 10.5281/zenodo.7529545
title: aipv dataset

description: The data that support the findings of this study are openly available in Github, at https://doi.org/10.5281/zenodo.7528885. Physical models can help improve solar cell efficiency during the design phase as well as quality control after the fabrication process. We present a data-driven approach to inverse modeling that can predict the underlying parameters of a finite element method (FEM) solar cell model based on an electroluminescence (EL) image of the solar cell. For training the inverse model, 75,000 synthetic EL images were generated with randomized parameters of the physical cell model. We combine 17 deep convolutional neural networks (CNNs) based on a modified VGG19 architecture into a deep ensemble to add uncertainty estimates. Using the silicon solar cell model, we show that such a novel approach to data-driven statistical inverse modeling can help apply recent developments in deep learning to new engineering applications that require real-time parameterizations of physical models augmented by confidence intervals. The trained network was tested on four different physical solar cell samples and the estimated parameters were used to create the corresponding model representations. Resimulations of the measurements yielded relative deviations of the calculated from the measured junction voltage values of 0.2\% on average with a maximum of 10\%, demonstrating the validity of the approach.
DOI: 10.5281/zenodo.7529544
title: aipv dataset

description: The data that support the findings of this study are openly available in Github, at https://doi.org/10.5281/zenodo.7528885. Physical models can help improve solar cell efficiency during the design phase as well as quality control after the fabrication process. We present a data-driven approach to inverse modeling that can predict the underlying parameters of a finite element method (FEM) solar cell model based on an electroluminescence (EL) image of the solar cell. For training the inverse model, 75,000 synthetic EL images were generated with randomized parameters of the physical cell model. We combine 17 deep convolutional neural networks (CNNs) based on a modified VGG19 architecture into a deep ensemble to add uncertainty estimates. Using the silicon solar cell model, we show that such a novel approach to data-driven statistical inverse modeling can help apply recent developments in deep learning to new engineering applications that require real-time parameterizations of physical models augmented by confidence intervals. The trained network was tested on four different physical solar cell samples and the estimated parameters were used to create the corresponding model representations. Resimulations of the measurements yielded relative deviations of the calculated from the measured junction voltage values of 0.2\% on average with a maximum of 10\%, demonstrating the validity of the approach.
DOI: 10.48432/bfddex
title: Competição de Clones de Cajueiro Anão-precoce em Pacajus-CE, Paraipaba-CE e Ribeira de Pombal-BA no período 1998-2001

description: Dados obtidos de experimentos de competição de clones de caju, implantados em 1997 nas estações experimentais de Pacajus e Paraipaba, no Ceará e em área de produtor em Ribeira de Pombal-Bahia. No acompanhamento realizados nos anos de 1998 a 2001, foram coletados e comparados dados de produção de castanhas, número de castanhas, peso de castanha, altura de planta e diâmetro da copa das plantas e indicadores tecnológicos do beneficamento de castanha.
DOI: 10.5281/zenodo.7991022
title: Water in the terrestrial planet-forming zone of the PDS 70 disk

description: This release includes the portion of the JWST-MIRI MRS spectrum of the PDS 70 disk analysed in the paper by Perotti et al. (2023). The original observational data are part of the Guaranteed Time Observation (GTO) program 1282 (PI: Th. Henning) with observation number 66 and will become public on 2 August, 2023 on the MAST database (https://archive.stsci.edu/). This release contains:<br> <br> 1) the full rebinned (4.9-22.5 μm) JWST-MIRI MRS spectrum of PDS 70 presented in Fig. 2 of Perotti et al. (2023);<br> 2) the JWST-MIRI MRS spectrum of PDS 70 in the 6.78-7.36 μm region used for the water line analysis shown in Fig. 3 of Perotti et al. (2023);<br> 3) the Spitzer-IRS low-resolution spectrum observed as part of the Spitzer-IRS GTO program 40679 (PI: G. Rieke) shown in Fig.1 of Perotti et al. (2023). The first dataset consists of one .csv file (1_PDS70_fig2_MIRI_Perotti23.csv) which contains the the 4.9-22.5 μm JWST-MIRI MRS spectrum of PDS 70 presented in Fig. 2 of Perotti et al. (2023). The spectrum is rebinned by averaging 15 spectral points and assign errors σ to the rebinned spectral points assuming a normal error distribution with equal weights for each individual spectral element.<br> <br> The second dataset consists of one .dat file and one python script. One .dat file contains the JWST-MIRI spectrum of PDS 70 in the 6.78-7.36 μm region shown in Fig. 3 of Perotti et al. (2023) where the brightest water emission lines are observed (2_PDS70_fig3_MIRI_Perotti23.dat). The JWST-MIRI continuum-subtracted spectrum and the best-fit water LTE slab model are included. The Python script used to reproduce Figure 3 of Perotti et al. (2023) is also provided (2_script_plot_fig3.py). <br> <br> The third dataset consists of one .dat file (3_PDS70_fig1_IRS_Perotti23.dat) which represents the Spitzer-IRS low-resolution spectrum of PDS 70 shown in Figure 1 of Perotti et al. (2023).
description: {"references": ["Perotti et al. 2023"]}
DOI: 10.5281/zenodo.7991021
title: Water in the terrestrial planet-forming zone of the PDS 70 disk

description: This release includes the portion of the JWST-MIRI MRS spectrum of the PDS 70 disk analysed in the paper by Perotti et al. (2023). The original observational data are part of the Guaranteed Time Observation (GTO) program 1282 (PI: Th. Henning) with observation number 66 and will become public on 2 August, 2023 on the MAST database (https://archive.stsci.edu/). This release contains:<br> <br> 1) the full rebinned (4.9-22.5 μm) JWST-MIRI MRS spectrum of PDS 70 presented in Fig. 2 of Perotti et al. (2023);<br> 2) the JWST-MIRI MRS spectrum of PDS 70 in the 6.78-7.36 μm region used for the water line analysis shown in Fig. 3 of Perotti et al. (2023);<br> 3) the Spitzer-IRS low-resolution spectrum observed as part of the Spitzer-IRS GTO program 40679 (PI: G. Rieke) shown in Fig.1 of Perotti et al. (2023). The first dataset consists of one .csv file (1_PDS70_fig2_MIRI_Perotti23.csv) which contains the the 4.9-22.5 μm JWST-MIRI MRS spectrum of PDS 70 presented in Fig. 2 of Perotti et al. (2023). The spectrum is rebinned by averaging 15 spectral points and assign errors σ to the rebinned spectral points assuming a normal error distribution with equal weights for each individual spectral element.<br> <br> The second dataset consists of one .dat file and one python script. One .dat file contains the JWST-MIRI spectrum of PDS 70 in the 6.78-7.36 μm region shown in Fig. 3 of Perotti et al. (2023) where the brightest water emission lines are observed (2_PDS70_fig3_MIRI_Perotti23.dat). The JWST-MIRI continuum-subtracted spectrum and the best-fit water LTE slab model are included. The Python script used to reproduce Figure 3 of Perotti et al. (2023) is also provided (2_script_plot_fig3.py). <br> <br> The third dataset consists of one .dat file (3_PDS70_fig1_IRS_Perotti23.dat) which represents the Spitzer-IRS low-resolution spectrum of PDS 70 shown in Figure 1 of Perotti et al. (2023).
description: {"references": ["Perotti et al. 2023"]}
DOI: 10.5281/zenodo.8169694
title: Pomegranate Flower Extract—The Health-Promoting Properties Optimized by Application of the Box–Behnken Design

description: Data includes source data and the publication to which it is related
DOI: 10.5281/zenodo.8169693
title: Pomegranate Flower Extract—The Health-Promoting Properties Optimized by Application of the Box–Behnken Design

description: Data includes source data and the publication to which it is related
DOI: 10.3886/e144721
title: Data and Code for: "Who Benefits from State Corporate Tax Cuts? A Local Labor Markets Approach with Heterogeneous Firms: Comment"

description: Suárez Serrato and Zidar (2016) identify state corporate tax incidence in a spatial equilibrium model with imperfectly mobile firms. Their identification argument rests on comparative-statics omitting a channel implied by their model: the link between common determinants of a location’s attractiveness and the average idiosyncratic productivity of firms choosing that location. This compositional margin causes the labor demand elasticity to be independent from the product demand elasticity, impeding the identification of incidence from reduced-form estimates. Assigning consensual values to the unidentified parameters, we find that the incidence share born by firm-owners is closer to 25% than the 40% initially reported. The null associated with the ``conventional view'' that the share on workers is 1 and that on firm owners is 0 is still rejected.
description: Population.
description: Smallest Geographic Unit: Public- use micro- data areas (PUMAs)
description: Data is from Suárez Serrato and Zidar (2016) replication archive. It can be downloaded at: https://doi.org/10.3886/E113026V1.
DOI: 10.3886/e144721v1
title: Data and Code for: "Who Benefits from State Corporate Tax Cuts? A Local Labor Markets Approach with Heterogeneous Firms: Comment"

description: Suárez Serrato and Zidar (2016) identify state corporate tax incidence in a spatial equilibrium model with imperfectly mobile firms. Their identification argument rests on comparative-statics omitting a channel implied by their model: the link between common determinants of a location’s attractiveness and the average idiosyncratic productivity of firms choosing that location. This compositional margin causes the labor demand elasticity to be independent from the product demand elasticity, impeding the identification of incidence from reduced-form estimates. Assigning consensual values to the unidentified parameters, we find that the incidence share born by firm-owners is closer to 25% than the 40% initially reported. The null associated with the ``conventional view'' that the share on workers is 1 and that on firm owners is 0 is still rejected.
description: Population.
description: Smallest Geographic Unit: Public- use micro- data areas (PUMAs)
description: Data is from Suárez Serrato and Zidar (2016) replication archive. It can be downloaded at: https://doi.org/10.3886/E113026V1.
DOI: 10.25934/pr00008844.1
title: Available datapackage for study 'Comparison of the Efficacy and Safety of Human Coronavirus Immune Plasma (HCIP) vs. Control (SARS-CoV-2 Non-immune) Plasma Among Outpatients With Symptomatic COVID-19'

description: To assess the efficacy and safety of Human coronavirus immune plasma (HCIP) to reduce the risk of hospitalization or death, the duration of symptoms and duration of nasopharyngeal or oropharyngeal viral shedding.
DOI: 10.5067/n4aehy0kphgo
title: CMS GOSAT and ObsPack L4 Top-down methane emissions for individual years (2010-2017) and sectors at 0.5x0.625 degrees for North America
DOI: 10.6084/m9.figshare.23720961
title: Kidney Dataset

description: This dataset is taken from McGilchrist and Aisbett (1991). It describes the first and second recurrence times of infection in kidney patients together with information on risk variables such as age, sex, and disease type. <br> Source <br> McGilchrist, C. A., & Aisbett, C. W. (1991). Regression with frailty in survival analysis. <em>Biometrics</em>, 47(2), 461-466
DOI: 10.22002/d1.20198
title: Caltech Fish Counting Dataset 2022

description: A full instructional guide is provided here: https://github.com/visipedia/caltech-fish-counting The Caltech Fish Counting Dataset is a large-scale dataset for detecting, tracking, and counting fish in sonar videos.
DOI: 10.6084/m9.figshare.20516432.v1
title: 2D-QSAR, docking, molecular dynamics, studies of PF-07321332 analogues to identify alternative inhibitors against 3CL<sup>pro</sup> enzyme in SARS-CoV disease

description: Given the results of the Pfizer-developed inhibitor PF-07321332 in the treatment of the SARS-Covid-19 epidemic, we aimed to identify potential alternatives to this compound by utilizing various methods; we developed 2 D-QSAR models to predict the therapeutic activity of 78 analogues of PF-07321332, three statistical learning techniques including (MLP-ANN), (SVR), and (MLR) were exploited. Various validation approaches were applied to the three models developed following the use of five most relevant descriptors. The study of the characteristics of these descriptors proved that the inhibitory activity of PF-07321332 analogues is specifically affected by the structure of the molecule, its polarizability, and by the hydrogen bonds. The best model, named MLP-ANN (with a 5-3-1 architecture), was selected on the basis of the following statistical parameters: r2 = 0.922, Q2 = 0.921. In addition, we performed a molecular docking and a molecular dynamics analysis of these compounds. The obtained results confirm that compound 8 can be a good alternative for compound PF-07321332. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.20516430
title: Repurposing small molecules of <i>Tephrosia purpurea</i> against SARS-CoV-2 main protease

description: Coronavirus infection is a communicable disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged as a global pandemic with deteriorating effect on the world’s population. Main protease (M<sup>pro</sup>) of SARS-CoV-2 plays a significant role in the viral replication, transcription and disease propagation as well as a potential candidate for drug discovery and development for COVID-19 infection. The current study employed state of art structure-based drug discovery to decipher the role of phytochemicals of <i>Tephrosia purpurea</i> against M<sup>pro</sup>. <i>Tephrosia purpurea</i> is being used as a traditional medicinal plant for the treatment of cough, breathlessness and fever as per the Indian Materia Medica. Screening of the phytochemicals of <i>Tephrosia purpurea</i> against M<sup>pro</sup> was performed using molecular docking approach to identify the top 5 hits (+)-tephrorin B, deguelin, vitamin p, lanceolarin and 3beta-hydroxy-20(29)-lupene with binding energy of −8.4, −8.1, −8.0, −7.8, and −7.8 kcal/mol, respectively. Furthermore, identified top 5 hits were subjected to drug-likeness and toxicity prediction as well as MM-GBSA calculation. Out of the five molecules four molecules were predicted not to comprise any mutagenic and carcinogenic effects. Top two molecules based on the drug-likeness properties for oral bio-availability were further analysed by molecular dynamics simulation at 100 ns timescale. It was observed from the dynamic behaviour of the two complexes that the addition of these molecules changed the conformation and stability of the apo protein; thus may act as inhibitors for M<sup>pro</sup>. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.20516430.v1
title: Repurposing small molecules of <i>Tephrosia purpurea</i> against SARS-CoV-2 main protease

description: Coronavirus infection is a communicable disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged as a global pandemic with deteriorating effect on the world’s population. Main protease (M<sup>pro</sup>) of SARS-CoV-2 plays a significant role in the viral replication, transcription and disease propagation as well as a potential candidate for drug discovery and development for COVID-19 infection. The current study employed state of art structure-based drug discovery to decipher the role of phytochemicals of <i>Tephrosia purpurea</i> against M<sup>pro</sup>. <i>Tephrosia purpurea</i> is being used as a traditional medicinal plant for the treatment of cough, breathlessness and fever as per the Indian Materia Medica. Screening of the phytochemicals of <i>Tephrosia purpurea</i> against M<sup>pro</sup> was performed using molecular docking approach to identify the top 5 hits (+)-tephrorin B, deguelin, vitamin p, lanceolarin and 3beta-hydroxy-20(29)-lupene with binding energy of −8.4, −8.1, −8.0, −7.8, and −7.8 kcal/mol, respectively. Furthermore, identified top 5 hits were subjected to drug-likeness and toxicity prediction as well as MM-GBSA calculation. Out of the five molecules four molecules were predicted not to comprise any mutagenic and carcinogenic effects. Top two molecules based on the drug-likeness properties for oral bio-availability were further analysed by molecular dynamics simulation at 100 ns timescale. It was observed from the dynamic behaviour of the two complexes that the addition of these molecules changed the conformation and stability of the apo protein; thus may act as inhibitors for M<sup>pro</sup>. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.20516432
title: 2D-QSAR, docking, molecular dynamics, studies of PF-07321332 analogues to identify alternative inhibitors against 3CL<sup>pro</sup> enzyme in SARS-CoV disease

description: Given the results of the Pfizer-developed inhibitor PF-07321332 in the treatment of the SARS-Covid-19 epidemic, we aimed to identify potential alternatives to this compound by utilizing various methods; we developed 2 D-QSAR models to predict the therapeutic activity of 78 analogues of PF-07321332, three statistical learning techniques including (MLP-ANN), (SVR), and (MLR) were exploited. Various validation approaches were applied to the three models developed following the use of five most relevant descriptors. The study of the characteristics of these descriptors proved that the inhibitory activity of PF-07321332 analogues is specifically affected by the structure of the molecule, its polarizability, and by the hydrogen bonds. The best model, named MLP-ANN (with a 5-3-1 architecture), was selected on the basis of the following statistical parameters: r2 = 0.922, Q2 = 0.921. In addition, we performed a molecular docking and a molecular dynamics analysis of these compounds. The obtained results confirm that compound 8 can be a good alternative for compound PF-07321332. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.20528773
title: Absolute binding free energies of mucroporin and its analog mucroporin-M1 with the heptad repeat 1 domain and RNA-dependent RNA polymerase of SARS-CoV-2

description: The peptide Mucroporin and its analog Mucroporin-M1 were studied using the molecular docking and molecular dynamics simulation of their complexation with two protein targets, the Heptad Repeat 1 (HR1) domain and RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. The molecular docking of the peptide-protein complexes was performed using the glowworm swarm optimization algorithm. The lowest energy poses were submitted to molecular dynamics simulation. Then, the binding free energies of Mucroporin and its analog Mucroporin-M1 with these two protein targets were calculated using the Multistate Bennett Acceptance Ratio (MBAR) method. It was verified that the peptides/HR1 domain complex showed stability in the interaction site determined by molecular docking. It was also found that Mucroporin-M1 has a much higher affinity than Mucroporin to the HR1 protein target. The peptides showed similar stability and affinity at the NTP binding site in the RdRp protein. Additional experimental studies are needed to confirm the antiviral activity of Mucroporin-M1 and a possible mechanism of action against SARS-CoV-2. However, here we indicate that Mucroporin-M1 may have potential antiviral activity against the HR1 domain with the possibility for further peptide optimization. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.20528773.v1
title: Absolute binding free energies of mucroporin and its analog mucroporin-M1 with the heptad repeat 1 domain and RNA-dependent RNA polymerase of SARS-CoV-2

description: The peptide Mucroporin and its analog Mucroporin-M1 were studied using the molecular docking and molecular dynamics simulation of their complexation with two protein targets, the Heptad Repeat 1 (HR1) domain and RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. The molecular docking of the peptide-protein complexes was performed using the glowworm swarm optimization algorithm. The lowest energy poses were submitted to molecular dynamics simulation. Then, the binding free energies of Mucroporin and its analog Mucroporin-M1 with these two protein targets were calculated using the Multistate Bennett Acceptance Ratio (MBAR) method. It was verified that the peptides/HR1 domain complex showed stability in the interaction site determined by molecular docking. It was also found that Mucroporin-M1 has a much higher affinity than Mucroporin to the HR1 protein target. The peptides showed similar stability and affinity at the NTP binding site in the RdRp protein. Additional experimental studies are needed to confirm the antiviral activity of Mucroporin-M1 and a possible mechanism of action against SARS-CoV-2. However, here we indicate that Mucroporin-M1 may have potential antiviral activity against the HR1 domain with the possibility for further peptide optimization. Communicated by Ramaswamy H. Sarma