cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6914119
title: Remotely Sensing River Greenhouse Gas Exchange Velocity Using the SWOT Satellite

description: Scripts and results for our "Remotely Sensing River Greenhouse Gas Exchange Velocity Using the SWOT Satellite" manuscript. Consult the README file for a more detailed description of the data, results, and scripts.
DOI: 10.5281/zenodo.6416068
title: Remotely Sensing River Greenhouse Gas Exchange Velocity Using the SWOT Satellite

description: Scripts and results for our "Remotely Sensing River Greenhouse Gas Exchange Velocity Using the SWOT Satellite" manuscript. Consult the README file for a more detailed description of the data, results, and scripts.
DOI: 10.5281/zenodo.6900984
title: SMARTED: SMARTwatch Emotion Dataset

description: The SMARTED (SMARTwatch Emotion Dataset) dataset contains physiological data collected in three groups of people enrolled in a university research study. Refer to the README for further details.
DOI: 10.5281/zenodo.6900983
title: SMARTED: SMARTwatch Emotion Dataset

description: The SMARTED (SMARTwatch Emotion Dataset) dataset contains physiological data collected in three groups of people enrolled in a university research study. Refer to the README for further details.
DOI: 10.6084/m9.figshare.20383734
title: A New Uncertain Remanufacturing Scheduling Model with Rework Risk Using Hybrid Optimization Algorithm

description: As a resource-conserving and environmental-friendly manufacturing paradigm, remanufacturing with the potential to realize sustainability in production has been extensively investigated. Scheduling plays a significant role in achieving the remanufacturing benefits. However, the remanufacturing process involves intricate uncertainties because it takes end-of-life products with different qualities as workblanks, which increases the risk of rework and complicates remanufacturing scheduling. Though the traditional stochastic optimization methods or fuzzy theory have been employed to address uncertainties in the remanufacturing scheduling problem, they are constrained with the limited historical data which renders it difficult to describe uncertainties accurately and intuitively. Therefore, a new uncertain remanufacturing scheduling model with rework risk is proposed, in which, the interval grey numbers are applied to describe the uncertainty clearly and consider the rework risk in remanufacturing process. To solve this model, a hybrid optimization algorithm that combines differential evolution and particle swarm optimization algorithms through an efficient representation scheme is proposed. Besides, this algorithm integrates multiple improvements to maintain the diversity of the population and enhance its performance. Simulation experiments are given, demonstrating that the proposed algorithm provides a better optimal solution than other baseline algorithms for solving the remanufacturing scheduling problem.
DOI: 10.6084/m9.figshare.20383734.v1
title: A New Uncertain Remanufacturing Scheduling Model with Rework Risk Using Hybrid Optimization Algorithm

description: As a resource-conserving and environmental-friendly manufacturing paradigm, remanufacturing with the potential to realize sustainability in production has been extensively investigated. Scheduling plays a significant role in achieving the remanufacturing benefits. However, the remanufacturing process involves intricate uncertainties because it takes end-of-life products with different qualities as workblanks, which increases the risk of rework and complicates remanufacturing scheduling. Though the traditional stochastic optimization methods or fuzzy theory have been employed to address uncertainties in the remanufacturing scheduling problem, they are constrained with the limited historical data which renders it difficult to describe uncertainties accurately and intuitively. Therefore, a new uncertain remanufacturing scheduling model with rework risk is proposed, in which, the interval grey numbers are applied to describe the uncertainty clearly and consider the rework risk in remanufacturing process. To solve this model, a hybrid optimization algorithm that combines differential evolution and particle swarm optimization algorithms through an efficient representation scheme is proposed. Besides, this algorithm integrates multiple improvements to maintain the diversity of the population and enhance its performance. Simulation experiments are given, demonstrating that the proposed algorithm provides a better optimal solution than other baseline algorithms for solving the remanufacturing scheduling problem.
DOI: 10.14284/572
title: TIMBERS in-situ sensor dataset
title: TIMBERS in-situ sensor dataset

description: Dataset comprises in-situ sensor data that was collected in the Belgian Part of the North Sea (Kwinte and Westdiep areas) in the framework of the BELSPO-funded TIMBERS project, where an onset towards 3D turbidity monitoring was the main goal. The in-situ data was collected at the surface (WISP) and underwater in 1D stations (CTD and OBS profiles, Niskin water samples) and along 2D transects (CTD, OBS, LISST). The water samples were then further analysed in the lab (Hach measurements, filtration and gravimetric analyses).
description: Filtration and gravimetric analyses of the (niskin) water samples yielded suspended particle concentrations in mg/L. These laboratory analyses were performed by the Flanders Environment Agency (VMM), following their standard protocol (VMM/LAB/GBM/1.213 - Beproevingsmethode voor de kwantitatieve bepaling van zwevende stoffen in water, Johan Annys, 10/12/2021).
DOI: 10.6084/m9.figshare.20383872
title: adww

description: addddddddddddddddd
DOI: 10.6084/m9.figshare.20383872.v1
title: adww

description: addddddddddddddddd
DOI: 10.5517/ccdc.csd.cc2chhw8
title: CCDC 2189650: Experimental Crystal Structure Determination

description: Related Article: Chengmin Li|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25505/fiz.icsd.cc2chhx9
title: CSD 2189651: Experimental Crystal Structure Determination

description: Related Article: Chengmin Li|2022|ICSD Communication|||
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.19096019
title: Meteora 18S rRNA gene phylogenetic trees

description: Maximum Likelihood (ML) and Bayesian Inference (BI) phylogenetic trees of the 18S rRNA gene
DOI: 10.6084/m9.figshare.19096019.v2
title: Meteora 18S rRNA gene phylogenetic trees

description: Maximum Likelihood (ML) and Bayesian Inference (BI) phylogenetic trees of the 18S rRNA gene
DOI: 10.6084/m9.figshare.19096019.v1
title: Meteora 18S rRNA gene phylogenetic trees

description: Maximum Likelihood (ML) and Bayesian Inference (BI) phylogenetic trees of the 18S rRNA gene
DOI: 10.6084/m9.figshare.19096004
title: Meteora 18S rRNA gene phylogenetic alignment

description: Phylogenetic dataset of the 18S rRNA gene
DOI: 10.6084/m9.figshare.19096004.v1
title: Meteora 18S rRNA gene phylogenetic alignment

description: Phylogenetic dataset of the 18S rRNA gene
DOI: 10.14469/hpc/6011
title: Difluoropolysiphenol, atropisomerisation F...F

description: Gaussian Calculation
DOI: 10.5523/bris.2g2s2acy46mjg2padsk8ofcpo2
title: Daly et al. 2022_SOPHIE preconception health

description: This dataset contains the data for the 835 women who took part in the SOPHIE (Study Of Pregnancy Health In England) survey study, which assessed knowledge, attitudes and views on preconception health and intervention delivery methods
DOI: 10.6084/m9.figshare.20383917.v1
title: Appendix 3 Pre-COVID Studies BEME Virtual Interviews in Graduate Medical Education

description: <strong>Abstract:</strong> <strong>Background</strong> The COVID-19 pandemic caused graduate medical education (GME) programs to pivot to virtual interviews (VIs) for recruitment and selection. This systematic review synthesizes the rapidly expanding evidence base on VIs, providing insights into preferred formats, strengths and weaknesses. <strong>Methods</strong> PubMed/MEDLINE, Scopus, ERIC, PsycINFO, MedEdPublish and Google Scholar were searched from 2012 to February 21, 2022. Two authors independently screened titles, abstracts, full texts, performed data extraction and assessed risk of bias using the Medical Education Research Quality Instrument. Findings were reported according to Best Evidence in Medical Education guidance. <strong>Results</strong> One hundred ten studies were included. The majority (97%) were from North America. Fourteen were conducted before COVID-19 and 96 during the pandemic. Studies involved both medical students applying to residencies (61%) and residents applying to fellowships (39%). Procedural specialties were more represented than non-procedural specialties. Applicants preferred VI days that lasted 4-6 hours, with 3-5 interviews lasting 15-20 minutes each, with virtual tours and opportunities to connect with current faculty and trainees. Satisfaction with VIs was high, though both applicants and programs found VIs inferior to in-person interviews for assessing fit. Confidence in ranking applicants and programs was decreased. The distribution of match outcomes shifted, with home match rates increasing in some specialties, decreasing geographic diversity. Stakeholders universally noted significant cost and time savings with VIs, as well as equity gains and reduced carbon footprint due to eliminating travel. The optimal future state remains unclear, though a hybrid model (e.g., VIs followed by a limited number of in-person second looks) may optimize strengths and weaknesses. <strong>Conclusions</strong> The use of VIs for GME recruitment and selection has accelerated rapidly. The findings of this review offer early insights into preferred formats for VIs, as well as strengths and weaknesses that can guide future practice, policy and research.
DOI: 10.6084/m9.figshare.20383917
title: Appendix 3 Pre-COVID Studies BEME Virtual Interviews in Graduate Medical Education

description: <strong>Abstract:</strong> <strong>Background</strong> The COVID-19 pandemic caused graduate medical education (GME) programs to pivot to virtual interviews (VIs) for recruitment and selection. This systematic review synthesizes the rapidly expanding evidence base on VIs, providing insights into preferred formats, strengths and weaknesses. <strong>Methods</strong> PubMed/MEDLINE, Scopus, ERIC, PsycINFO, MedEdPublish and Google Scholar were searched from 2012 to February 21, 2022. Two authors independently screened titles, abstracts, full texts, performed data extraction and assessed risk of bias using the Medical Education Research Quality Instrument. Findings were reported according to Best Evidence in Medical Education guidance. <strong>Results</strong> One hundred ten studies were included. The majority (97%) were from North America. Fourteen were conducted before COVID-19 and 96 during the pandemic. Studies involved both medical students applying to residencies (61%) and residents applying to fellowships (39%). Procedural specialties were more represented than non-procedural specialties. Applicants preferred VI days that lasted 4-6 hours, with 3-5 interviews lasting 15-20 minutes each, with virtual tours and opportunities to connect with current faculty and trainees. Satisfaction with VIs was high, though both applicants and programs found VIs inferior to in-person interviews for assessing fit. Confidence in ranking applicants and programs was decreased. The distribution of match outcomes shifted, with home match rates increasing in some specialties, decreasing geographic diversity. Stakeholders universally noted significant cost and time savings with VIs, as well as equity gains and reduced carbon footprint due to eliminating travel. The optimal future state remains unclear, though a hybrid model (e.g., VIs followed by a limited number of in-person second looks) may optimize strengths and weaknesses. <strong>Conclusions</strong> The use of VIs for GME recruitment and selection has accelerated rapidly. The findings of this review offer early insights into preferred formats for VIs, as well as strengths and weaknesses that can guide future practice, policy and research.
DOI: 10.6084/m9.figshare.20383986
title: Appendix 4 Included Studies BEME Virtual Interviews in Graduate Medical Education

description: <strong>Abstract:</strong> <strong>Background</strong> The COVID-19 pandemic caused graduate medical education (GME) programs to pivot to virtual interviews (VIs) for recruitment and selection. This systematic review synthesizes the rapidly expanding evidence base on VIs, providing insights into preferred formats, strengths and weaknesses. <strong>Methods</strong> PubMed/MEDLINE, Scopus, ERIC, PsycINFO, MedEdPublish and Google Scholar were searched from 2012 to February 21, 2022. Two authors independently screened titles, abstracts, full texts, performed data extraction and assessed risk of bias using the Medical Education Research Quality Instrument. Findings were reported according to Best Evidence in Medical Education guidance. <strong>Results</strong> One hundred ten studies were included. The majority (97%) were from North America. Fourteen were conducted before COVID-19 and 96 during the pandemic. Studies involved both medical students applying to residencies (61%) and residents applying to fellowships (39%). Procedural specialties were more represented than non-procedural specialties. Applicants preferred VI days that lasted 4-6 hours, with 3-5 interviews lasting 15-20 minutes each, with virtual tours and opportunities to connect with current faculty and trainees. Satisfaction with VIs was high, though both applicants and programs found VIs inferior to in-person interviews for assessing fit. Confidence in ranking applicants and programs was decreased. The distribution of match outcomes shifted, with home match rates increasing in some specialties, decreasing geographic diversity. Stakeholders universally noted significant cost and time savings with VIs, as well as equity gains and reduced carbon footprint due to eliminating travel. The optimal future state remains unclear, though a hybrid model (e.g., VIs followed by a limited number of in-person second looks) may optimize strengths and weaknesses. <strong>Conclusions</strong> The use of VIs for GME recruitment and selection has accelerated rapidly. The findings of this review offer early insights into preferred formats for VIs, as well as strengths and weaknesses that can guide future practice, policy and research.
DOI: 10.6084/m9.figshare.20383986.v1
title: Appendix 4 Included Studies BEME Virtual Interviews in Graduate Medical Education

description: <strong>Abstract:</strong> <strong>Background</strong> The COVID-19 pandemic caused graduate medical education (GME) programs to pivot to virtual interviews (VIs) for recruitment and selection. This systematic review synthesizes the rapidly expanding evidence base on VIs, providing insights into preferred formats, strengths and weaknesses. <strong>Methods</strong> PubMed/MEDLINE, Scopus, ERIC, PsycINFO, MedEdPublish and Google Scholar were searched from 2012 to February 21, 2022. Two authors independently screened titles, abstracts, full texts, performed data extraction and assessed risk of bias using the Medical Education Research Quality Instrument. Findings were reported according to Best Evidence in Medical Education guidance. <strong>Results</strong> One hundred ten studies were included. The majority (97%) were from North America. Fourteen were conducted before COVID-19 and 96 during the pandemic. Studies involved both medical students applying to residencies (61%) and residents applying to fellowships (39%). Procedural specialties were more represented than non-procedural specialties. Applicants preferred VI days that lasted 4-6 hours, with 3-5 interviews lasting 15-20 minutes each, with virtual tours and opportunities to connect with current faculty and trainees. Satisfaction with VIs was high, though both applicants and programs found VIs inferior to in-person interviews for assessing fit. Confidence in ranking applicants and programs was decreased. The distribution of match outcomes shifted, with home match rates increasing in some specialties, decreasing geographic diversity. Stakeholders universally noted significant cost and time savings with VIs, as well as equity gains and reduced carbon footprint due to eliminating travel. The optimal future state remains unclear, though a hybrid model (e.g., VIs followed by a limited number of in-person second looks) may optimize strengths and weaknesses. <strong>Conclusions</strong> The use of VIs for GME recruitment and selection has accelerated rapidly. The findings of this review offer early insights into preferred formats for VIs, as well as strengths and weaknesses that can guide future practice, policy and research.
DOI: 10.34740/kaggle/dsv/3993193
title: Mahanagar Yatayat Dataset
DOI: 10.6084/m9.figshare.19069604
title: Plas-5k dataset

description: This CSV file contains the Binding Affinity and other important features obtained by simulating 5000 protein-ligand complexes. The calculations were performed using MM-PBSA. <br>It should be noted that all the energy values are in kcal/mol unit.
DOI: 10.5281/zenodo.6914265
title: Sebastian+Simmons-High-frequency quantitative ultrasound to assess the acoustic properties of engineered tissues in vitro

description: This dataset includes raw acquired ultrasound data, processing scripts, and statistical data for acoustic property characterization of cell-free and cell-seeded fibrin hydrogels.
DOI: 10.5281/zenodo.6914264
title: Sebastian+Simmons-High-frequency quantitative ultrasound to assess the acoustic properties of engineered tissues in vitro

description: This dataset includes raw acquired ultrasound data, processing scripts, and statistical data for acoustic property characterization of cell-free and cell-seeded fibrin hydrogels.
DOI: 10.6084/m9.figshare.19069595
title: Plas-5k Initial Structures

description: The 7zip file contains the initial structure of all the 5000 protein-ligand complexes in pdb format. For inorganic ligand the residue name is "LIG". For peptide ligand, the sequence will be bound by last OXT and 2nd last OXT atom. Also the water molecules and Na+ and Cl- ions were removed, as they will mostly be unnecessary for ML training and it will save storage space.
DOI: 10.3886/e166881
title: Data and Code for: Expected and Realized Inflation in Historical Perspective

description: These are the replication files to produce the figures and table in our Journal of Economic Perspectives paper about the relationship between actual and expected inflation in historical perspective.
description: United States. Smallest Geographic Unit: United States
DOI: 10.3886/e169781
title: Data and Code for: The Subjective Inflation Expectations of Households and Firms: Measurement, Determinants, and Implications

description: Households’ and firms’ subjective inflation expectations play a central role in macroeconomic and intertemporal microeconomic models. We discuss how subjective inflation expectations are measured, the patterns they display, their determinants, and how they shape households’ and firms’ economic choices in the data and help us make sense of the observed heterogeneous reactions to business-cycle shocks and policy interventions. We conclude by highlighting the relevant open questions and why tackling them is important for academic research and policy making.
DOI: 10.5281/zenodo.5920664
title: Data files for "Hybrid quantum-classical approach for coupled-cluster Green's function theory"

description: Source code and data files for the manuscript "Hybrid quantum-classical approach for coupled-cluster Green's function theory." Reference: Quantum 6, 675 (2022); https://doi.org/10.22331/q-2022-03-30-675. Title: Hybrid quantum-classical approach for coupled-cluster Green's function theory Authors: Trevor Keen, Bo Peng, Karol Kowalski, Pavel Lougovski, and Steven Johnston. Abstract: The three key elements of a quantum simulation are state preparation, time evolution, and measurement. While the complexity scaling of dynamics and measurements are well known, many state preparation methods are strongly system-dependent and require prior knowledge of the system’s eigenvalue spectrum. Here, we report on a quantum-classical implementation of the coupled-cluster Green’s function (CCGF) method, which replaces explicit ground state preparation with the task of applying unitary operators to a simple product state. While our approach is broadly applicable to a wide range of models, we demonstrate it here for the Anderson impurity model (AIM). The method requires a number of T gates that grow as $O(N^5)$ per time step to calculate the impurity Green’s function in the time domain, where N is the total number of energy levels in the AIM. For comparison, a classical CCGF calculation of the same order would require computational resources that grow as $O(N^6)$ per time step.
DOI: 10.5281/zenodo.5920663
title: Data files for "Hybrid quantum-classical approach for coupled-cluster Green's function theory"

description: Source code and data files for the manuscript "Hybrid quantum-classical approach for coupled-cluster Green's function theory." Reference: Quantum 6, 675 (2022); https://doi.org/10.22331/q-2022-03-30-675. Title: Hybrid quantum-classical approach for coupled-cluster Green's function theory Authors: Trevor Keen, Bo Peng, Karol Kowalski, Pavel Lougovski, and Steven Johnston. Abstract: The three key elements of a quantum simulation are state preparation, time evolution, and measurement. While the complexity scaling of dynamics and measurements are well known, many state preparation methods are strongly system-dependent and require prior knowledge of the system’s eigenvalue spectrum. Here, we report on a quantum-classical implementation of the coupled-cluster Green’s function (CCGF) method, which replaces explicit ground state preparation with the task of applying unitary operators to a simple product state. While our approach is broadly applicable to a wide range of models, we demonstrate it here for the Anderson impurity model (AIM). The method requires a number of T gates that grow as $O(N^5)$ per time step to calculate the impurity Green’s function in the time domain, where N is the total number of energy levels in the AIM. For comparison, a classical CCGF calculation of the same order would require computational resources that grow as $O(N^6)$ per time step.
DOI: 10.5281/zenodo.6394852
title: Data Files for "Quadrupolar magnetic excitations in an isotropic spin-1 antiferromagnet"

description: Data files for the manuscript "Quadrupolar magnetic excitations in an isotropic spin-1 antiferromagnet". Reference: A. Nag, A. Nocera, S. Agrestini, M. Garcia-Fernandez, A. C. Walters, Sang-Wook Cheong, S. Johnston, and Ke-Jin Zhou, "Quadrupolar magnetic excitations in an isotropic spin-1 antiferromagnet". Nature Communications 13, 2327 (2022). Preprint: arXiv:2111.03625 (2021), URL: https://arxiv.org/abs/2111.03625