Find research datasets worth reusing

opencc-by-4.0Mar 2023View details →

Crime Reduction by the NBS during the UrbanGreenUP project in Valladolid city

This indicator is included in the list of indicators Challenge 8. Social Justice and Social Cohesion. According to Oxford dictionary, crime is an action or omission which constitutes an offence and is punishable by law. The installation of urban furniture as a measure of protection against crime, vandalism and terrorist acts has been developing successfully since the 70s and it is called “Crime Prevention Through Environmental Design (CPTE)”. The main technique is to reduce crime opportunities through modification and manipulation of the built environment that make it more difficult (Massoomeh et al, 2016). Green Infrastructures can help to reduce the causes and opportunities crime and vandalism because the structures that look well cared for discourage crime and increase social justice and cohesion. It is a measure that through well planning, designing and managing of the built environment (Massoomeh et al, 2016).

opencc-by-4.0Apr 2023View details →

Data for Coupling Covariance Matrix Adaptation with Continuum Modeling for Determination of Kinetic Parameters Associated with Electrochemical CO2 Reduction

This data set contains digitized and tagged polarization and partial current density data for 18 datasets of CO2 reduction to H2 and CO over Ag catalysts, as well as 8 datasets of CO2 reduction to HCOO-, CO, and H2 over Sn catalysts. We analyze this data using a coupled continuum modeling and covariance matrix adaptation approach for which the codebase is provided in DOI: 10.5281/zenodo.7866195.

opencc-by-4.0May 2023View details →

Lung nodule CT false positive reduction

This data set is part of the public development data for the <a href="http://auc23.grand-challenge.org/">2023 Automated Universal Classification Challenge</a> (AUC23). The data set concerns the classification of lung nodules on screening thoracic computed tomography (CT) scans and was derived from the <a href="https://luna16.grand-challenge.org/Data/">2016 Lung Nodule Analysis (LUNA) challenge</a>. The data set was previously introduced and described by <a href="https://www.sciencedirect.com/science/article/pii/S1361841517301020?via%3Dihub">Setio et al. (2017)</a> and no images or patient information were added. Only the "false positive reduction" track was considered, where a provided set of nodule candidates should be classified. Data was restructured in compliance with the <a href="https://auc23.grand-challenge.org/">AUC23</a> challenge format. The data set was collected from the largest publicly available reference database for lung nodules: <a href="https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=1966254">The Lung Image Database Consortium image collection</a>. Images are 3D tensors: <ul> <li>0: 3D axial screening CT scan (cropped to candidate nodule's region of interest)</li> </ul> Classification labels: <ul> <li>0: Is a nodule</li> <li>1: Is not a nodule</li> </ul> Folder structure: imagesTr (root folder with all patients and studies)     ├── LUNA16_0000_0000.mha  (axial CT imaging for nodule 0000)     ├── LUNA16_0000_0002.mha  (axial CT imaging for nodule 0002)     ├── ...   Please cite the following article if you are using the <a href="https://luna16.grand-challenge.org/Data/">2016 Lung Nodule Analysis (LUNA) challenge</a> false positive reduction track data set: <pre><code>Setio AAA, Traverso A, de Bel T, Berens MSN, Bogaard CVD, Cerello P, Chen H, Dou Q, Fantacci ME, Geurts B, Gugten RV, Heng PA, Jansen B, de Kaste MMJ, Kotov V, Lin JY, Manders JTMC, Sóñora-Mengana A, García-Naranjo JC, Papavasileiou E, Prokop M, Saletta M, Schaefer-Prokop CM, Scholten ET, Scholten L, Snoeren MM, Torres EL, Vandemeulebroucke J, Walasek N, Zuidhof GCA, Ginneken BV, Jacobs C. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge. Med Image Anal. 2017 Dec;42:1-13. doi: 10.1016/j.media.2017.06.015. Epub 2017 Jul 13. PMID: 28732268.</code></pre>

Fig. 3 in Reduction Of The Breeding Population Of The Rook, Corvus Frugilegus (Aves, Corvidae), In Ukraine: The Example Of The Eastern Part Of The Kyiv Region

Fig. 3. Kernel Density Estimation of number of the rook breeding group in the research area in 1983–1985 (A), and in 2021 (B). The highest density areas are highlighted in red; the lowest density areas are green.

Fig. 2 in Reduction Of The Breeding Population Of The Rook, Corvus Frugilegus (Aves, Corvidae), In Ukraine: The Example Of The Eastern Part Of The Kyiv Region

Fig. 2. The location of Rook colonies and their number in the research area in 1983–1985 (A), and in 2021 (B).

Fig. 4 in Reduction Of The Breeding Population Of The Rook, Corvus Frugilegus (Aves, Corvidae), In Ukraine: The Example Of The Eastern Part Of The Kyiv Region

Fig. 4. Standard Deviational Ellipses for the location of rook colonies and their number in the research area in 1983–1985 and 2021.

Fig. 1 in Reduction Of The Breeding Population Of The Rook, Corvus Frugilegus (Aves, Corvidae), In Ukraine: The Example Of The Eastern Part Of The Kyiv Region

Fig. 1. Geographical location of the study area. The circle is a research territory with an area of 1850 km².

opencc-by-4.0Jul 2023View details →

Let There Be Light: Genome-reduction Enables Bacillus subtilis to Produce Disulfide-bonded Gaussia Luciferase

Supplemental Material: <ul> <li>Plasmid Maps in PNG format</li> <li>Plasmid Sequences in GB format</li> <li>Plasmid Sequences in DNA format (SnapGene)</li> </ul>

Theory-guided development of homogeneous catalysts for the reduction of CO2 to formate, formaldehyde, and methanol derivatives

The stepwise catalytic reduction of carbon dioxide (CO2) to formic acid, formaldehyde, and methanol opens non-fossil pathways to important platform chemicals. The present article aims at identifying molecular control parameters to steer the selectivity to the three distinct reduction levels using organometallic catalysts of earth-abundant first-row metals. A linear scaling relationship was developed to map the intrinsic reactivity of 3d transition metal pincer complexes to their activity and selectivity in CO2 hydrosilylation. The hydride affinity of the catalysts was used as a descriptor to predict activity/selectivity trends in a composite volcano picture, and the outstanding properties of cobalt complexes bearing bis(phosphino)triazine PNP-type pincer ligands to reach the three reduction levels selectively under different reaction conditions could thus be rationalized. The implications of the composite volcano picture were successfully experimentally validated with selected catalysts, and the challenging intermediate level of formaldehyde could be accessed in over 80% yield with the cobalt complex 6. The results underpin the potential of tandem computational-experimental approaches to propel catalyst design for CO2-based chemical transformations.

Hepatitis B surface antigen reduction is associated with hepatitis B core-specific CD8+ T cell quality

The file containing post QC, count matrix, containing 6 samples as following. (S01:CHBN001, S02:CHBN002, S03:CHBN003, S04:CHBN004, S12:CHBN005, S14:CHBN006.) scRNAseq Libraries generated by 10xGenomics 5'-kit were read by NovaSeq 6000 platform.  After sequencing, raw reads were mapped to human generated by cellranger 6.1.2, then generated count matrix were subjected to QC according to Seurat manual (mitochondrial genes <10%, ribosomal genes > 0.05%), then SCT-transformed and integrated with 3000 features. Detail of QC/integration will be described in our manuscript.

Reduction in the Tropical High Cloud Fraction in Response to an Indirect Weakening of the Hadley Cell

NetCDF files for figures in "Reduction in the Tropical High Cloud Fraction in Response to an Indirect Weakening of the Hadley Cell" submitted to Journal of Advances in Modeling Earth Systems. Figure 1: Prescribed SST for control and perturbed simulations:  <ul> <li>sst_ctrl_annualzonalmeans.nc</li> <li>sst_pert_annualzonalmeans.nc</li> </ul> Figure 2: Mass meridional stream function data for control and perturbed simulations: Figure 2a: PC2 cloud scheme + Gregory-Rowntree mass-flux convection scheme <ul> <li>mmsf_pc2gr_ctrl_annualmeans.nc</li> <li>mmsf_pc2gr_pert_annualmeans.nc</li> </ul> Figure 2b: Smith cloud scheme + Gregory-Rowntree mass-flux convection scheme <ul> <li>mmsf_smithgr_ctrl_annualmeans.nc</li> <li>mmsf_smithgr_pert_annualmeans.nc</li> </ul> Figure 3a: Ice cloud fraction data for control and perturbed simulations with PC2 cloud scheme (zonal and time-mean over 15 simulation years) <ul> <li>Cf_pc2gr_ctrl_annualzonalmeans.nc</li> <li>Cf_pc2gr_pert_annualzonalmeans.nc</li> </ul> Figure 3b: Ice cloud fraction data for control and perturbed simulations with Smith cloud scheme (zonal and time-mean over 15 simulation years) <ul> <li>Cf_smithgr_ctrl_annualzonalmeans.nc</li> <li>Cf_smithgr_pert_annualzonalmeans.nc</li> </ul> Figure 3c: Relative humidity data for control and perturbed simulations with PC2 cloud scheme (zonal and time-mean over 15 simulation years) <ul> <li>RH_pc2gr_ctrl_annualzonalmeans.nc</li> <li>RH_pc2gr_pert_annualzonalmeans.nc</li> </ul> Figure 3d: Relative humidity for control and perturbed simulations with Smith cloud scheme (zonal and time-mean over 15 simulation years) <ul> <li>RH_smithgr_ctrl_annualzonalmeans.nc</li> <li>RH_smithgr_pert_annualzonalmeans.nc</li> </ul> Figure 3e: Specific humidity data for control and perturbed simulations with PC2 cloud scheme (zonal and time-mean over 15 simulation years) <ul> <li>q_pc2gr_ctrl_annualzonalmeans.nc</li> <li>q_pc2gr_pert_annualzonalmeans.nc</li> </ul> Figure 3f: Specific humidity data for control and perturbed simulations with Smith cloud scheme (zonal and time-mean over 15 simulation years) <ul> <li>q_smithgr_ctrl_annualzonalmeans.nc</li> <li>q_smithgr_pert_annualzonalmeans.nc</li> </ul> Figure 3g: Temperature data for control and perturbed simulations with PC2 cloud scheme (zonal and time-mean over 15 simulation years) <ul> <li>T_pc2gr_ctrl_annualzonalmeans.nc</li> <li>T_pc2gr_pert_annualzonalmeans.nc</li> </ul> Figure 3h: Temperature data for control and perturbed simulations with Smith cloud scheme (zonal and time-mean over 15 simulation years) <ul> <li>T_smithgr_ctrl_annualzonalmeans.nc</li> <li>T_smithgr_pert_annualzonalmeans.nc</li> </ul>  Figure 5: Control and perturbed simulation data for ice cloud fraction and mass fraction of ice cloud condensates meaned over the tropical ascent region for PC2 scheme <ul> <li>Cf_pc2gr_ctrl_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>Cf_pc2gr_pert_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>qcf_pc2gr_ctrl_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>qcf_pc2gr_pert_annualzonalmeans_15yrs_tropicalascent.nc</li> </ul>  Figure 6a,b: Monthly-mean data of convective mass flux for control and perturbed simulations over the tropics between \(\pm\) 31 \(^\circ\)N for PC2 cloud scheme <ul> <li>convmassflux_pc2gr_ctrl_monthlymean_15yrs_tropics.nc</li> <li>convmassflux_pc2gr_pert_monthlymean_15yrs_tropics.nc</li> </ul>  Figure 6c,d: Monthly-mean data of net convective detrainment for control and perturbed simulations over the tropics between \(\pm\) 31 \(^\circ\)N for PC2 cloud scheme <ul> <li>netconvdetrain_pc2gr_ctrl_monthlymean_15yrs_tropics.nc</li> <li>netconvdetrain_pc2gr_pert_monthlymean_15yrs_tropics.nc</li> </ul>  Figure 6e,f: Monthly-mean data of tendency of ice cloud condensates due to convection for control and perturbed simulations over the tropics between \(\pm\) 31 \(^\circ\)N for PC2 cloud scheme <ul> <li>dqcfdtconv_pc2gr_ctrl_monthlymean_15yrs_tropics.nc</li> <li>dqcfdtconv_pc2gr_pert_monthlymean_15yrs_tropics.nc</li> </ul>  Figure 7: Annual and zonal-mean data of net convective detrainment for control and perturbed simulations over the tropical ascent regoin between \(\pm\) 7 \(^\circ\)N for PC2 cloud scheme <ul> <li>netconvdetrain_pc2gr_ctrl_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>netconvdetrain_pc2gr_pert_annualzonalmeans_15yrs_tropicalascent.nc</li> </ul>  Figure 8: Annual and zonal-mean data of net convective detrainment and ice cloud fraction for control and perturbed simulations over the tropical ascent regoin between \(\pm\) 7 \(^\circ\)N for PC2 cloud scheme <ul> <li>netconvdetrain_pc2gr_ctrl_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>netconvdetrain_pc2gr_pert_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>Cf_pc2gr_ctrl_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>Cf_pc2gr_pert_annualzonalmeans_15yrs_tropicalascent.nc</li> </ul>  Figure 9: Annual and zonal-mean data of convective tendency of mass fraction of ice cloud condensates for control and perturbed simulations over the tropical ascent regoin between \(\pm\) 7 \(^\circ\)N for PC2 cloud scheme <ul> <li>dqcfdtconv_pc2gr_ctrl_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>dqcfdtconv_pc2gr_pert_annualzonalmeans_15yrs_tropicalascent.nc</li> </ul>  Figure 10: Annual and zonal-mean data of net depositional tendency of mass fraction of ice cloud condensates for control and perturbed simulations over the tropical ascent regoin between \(\pm\) 7 \(^\circ\)N for PC2 cloud scheme <ul> <li>dqcfdtnetdep_pc2gr_ctrl_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>dqcfdtnetdep_pc2gr_pert_annualzonalmeans_15yrs_tropicalascent.nc</li> </ul>  Figure 11: Monthly-mean data of net depositional tendency of mass fraction of ice cloud condensates for control and perturbed simulations over the tropics between \(\pm\) 31\(^\circ\)N for PC2 cloud scheme <ul> <li>dqcfdtnetdep_pc2gr_ctrl_monthlymean_15yrs_tropics.nc</li> <li>dqcfdtnetdep_pc2gr_pert_monthlymean_15yrs_tropics.nc</li> </ul>  Figure 12: Annual and zonal-mean data of specific humidity and advective tendency for specific humidity for control and perturbed simulations over the tropical ascent regoin between \(\pm\) 7 \(^\circ\)N for PC2 cloud scheme <ul> <li>q_pc2gr_ctrl_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>q_pc2gr_pert_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>dqdtadv_pc2gr_ctrl_annualzonalmeans_15yrs_tropicalascent.nc</li> <li>dqdtadv_pc2gr_pert_annualzonalmeans_15yrs_tropicalascent.nc</li> </ul> Figure 13: Control and perturbed simulation data for mean vertical advection of moisture, mean vertical moisture convergence, total advection of moisture, and total moisture convergence (meaned over the tropical ascent region for PC2 scheme for 15 simulation years) <ul> <li>MeanVerticalAdvectionOfMoisture_pc2gr_ctrl_15yrmean_tropicalascent_vertprof.nc</li> <li>MeanVerticalAdvectionOfMoisture_pc2gr_pert_15yrmean_tropicalascent_vertprof.nc</li> <li>MeanVerticalMoistureConvergence_pc2gr_ctrl_15yrmean_tropicalascent_vertprof.nc</li> <li>MeanVerticalMoistureConvergence_pc2gr_pert_15yrmean_tropicalascent_vertprof.nc</li> <li>TotalMoistureAdvection_pc2gr_ctrl_15yrmean_tropicalascent_vertprof.nc</li> <li>TotalMoistureAdvection_pc2gr_pert_15yrmean_tropicalascent_vertprof.nc</li> <li>TotalMoistureConvergence_pc2gr_ctrl_15yrmean_tropicalascent_vertprof.nc</li> <li>TotalMoistureConvergence_pc2gr_pert_15yrmean_tropicalascent_vertprof.nc</li> </ul>

Why The Perfectly Symmetric Cobalt-Pentapyridyl Loses the H2 Production Challenge: Theoretical Insight into Reaction Mechanism and Reduction Free Energies

Abstract Researchers have extensively investigated photo-catalytic water reduction utilizing Cobalt-based catalysts with poly-pyridyl ligands. While catalysts exhibiting distorted poly-pyridyl ligand demonstrate higher H2 production yields, those with ideal octahedral coordination display poor performance. This outcome suggests the crucial role of ligand framework in catalytic activity, yet reasons behind the disparity in H2 production rates for catalysts with octahedral geometries remain unclear. We theoretically examined the water reduction mechanism of Co-based poly-pyridyl catalyst, CoPy5, having perfect octahedral coordination. We clarified the effect of octahedral coordination by utilizing each intermediate step of ECEC mechanism. We determined spin states, solvent response, electronic structures, and reduction free energies. CoPy5 with perfect octahedral coordination, alongside its distorted counterparts, exhibit similar spin states as the reaction progresses through each intermediate step. However, the first reduction free energy obtained for the CoPy5 is slightly higher than that of its distorted counterparts. Following the second protonation, resulting H2 molecule experiences limited diffusion from the Co center due to the compact structure of the CoPy5, which blocks the Co center for the next H2 production cycle. Catalysts having distorted octahedral geometries facilitate fast removal of H2 into the solvent. Thus, the reaction center becomes immediately available for subsequent H2 production. Computational Details AIMD simulations have been performed for modeling intermediate states of the ECEC mechanisms of H2 production through water splitting. Open source CP2K simulation package have been used in all simulations. PBE density functional in general gradient approximation (GGA) formalism was employed for the AIMD simulations. Goedecker-Teter-Hutter (GTH) potentials were applied for the estimation of core electron interactions with the valence shell and nucleus. Valence electrons were modeled explicitly and valence shells of Co, N, C, O and H contain 17, 5, 4, 6 and 1 electrons, respectively. DZVP-MOLOPT basis set was used for all atomic kinds. For auxiliary plane wave basis set, a cutoff of 400 Ry was utilized. Dispersion interactions were taken into consideration by applying Vydrov and Van Voorhis vdW density functional, in the revised form (rVV10). Periodic boundary conditions and spin polarization were always applied. For the CoPy5 complex, AIMD simulations were carried out in a box defined as cubic with explicit water environment. The CoPy5 catalyst was first solvated in 215 water molecules and the simulation volume was relaxed by performing AIMD simulations for approximately 20 ps in the isothermal-isobaric ensemble (NPT). Cubic simulation box volume was determined as 6163.28  ̊A3. Following the determination of the simulation box size, each intermediate step were modeled by applying AIMD simulations in the canonical ensemble (NVT) for approximately 20 ps. Time step was set to 0.5 fs. Canonical sampling through velocity rescaling (CSVR) thermostat with a time constant of 100 fs was applied in order to keep the simulation temperature at 300 K. Please see the corresponding article for more details.

opencc-by-4.0Jul 2023View details →

Surface Charge Boundary Condition Often Misused in CO2 Reduction Models (raw data for graphs)

This contains the raw data, in text file format, for the figures in the journal article "Surface Charge Boundary Condition Often Misused in CO2 Reduction Models" published in Journal of Physical Chemistry C, DOI 10.1021/acs.jpcc.3c05364. The files are in directories corresponding to their figure number, and the files are named with the capacitance.

Effect of LIK066 on Reduction of Fatty Content in Livers of Obese Patients

ClinicalTrials.gov study NCT03205150. IPD Sharing: YES. Countries: 8. Publications: 1.

A Stigma Reduction Intervention at Time of Entry Into Antenatal Care to Improve PMTCT Services in Tanzania

ClinicalTrials.gov study NCT03600142. IPD Sharing: YES. Countries: 1. Publications: 4.

closedIPD-NOFeb 2026View details →

Safety and Efficacy of Romidepsin and the Therapeutic Vaccine Vacc-4x for Reduction of the Latent HIV-1 Reservoir

ClinicalTrials.gov study NCT02092116. IPD Sharing: NO. Countries: 1. Publications: 2.

closedIPD-NOFeb 2026View details →

Cocaine Use Reduction and Health

ClinicalTrials.gov study NCT03224546. IPD Sharing: NO. Countries: 1. Publications: 3.

Evaluation of Medical Cannabis and Prescription Opioid Taper Support for Reduction of Pain and Opioid Dose in Patients With Chronic Non-Cancer Pain

ClinicalTrials.gov study NCT04827992. IPD Sharing: YES. Countries: 1. Publications: 1.

The Use of Cannabidiol (CBD) in Pain Reduction and Opioid Use After Shoulder Arthroscopy

ClinicalTrials.gov study NCT04672252. IPD Sharing: YES. Countries: 1. Publications: 2.