cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10472507
title: Very high resolution of Jakarta's urban green space data

description: Very high resolution of Jakarta’s urban green space data was produced using fusion of three different earth observation data (Planet, Sentinel-1 SAR, and Sentinel-2 MSI). Planet data was first transformed into Red Edge Triangulated Vegetation Index (RTVI) and the Red Edge Triangulated Wetness Index (RTWI) spectral indices before classification. Training and testing data were gathered from Google Street View. Two machine learning algorithms were used (Random Forest (RF) and Classification and Regression Tree (CART)) within the Google Earth Engine (GEE) cloud computing platform. To refine the data, Google's Open Building Data was used, the data was accessible through the GEE data catalog.
DOI: 10.6084/m9.figshare.24419938.v6
title: The South China Sea metagenome dataset

description: MAGs and other files generated using <b>the </b><b>South China Sea</b> microbial dataset.
DOI: 10.6084/m9.figshare.24964689
title: Instruments and supplemental material

description: Manuscript: The loving reciprocity scale: Internal structure, factorial invariance, reliability, and convergent validity
DOI: 10.5281/zenodo.10472484
title: Data and Code for Modeling Raton Basin

description: Data and Code for Modeling Raton Basin. Includes Abaqus files, post-processing files, analysis of SI model, optimization code, and scripts to generate figures.
DOI: 10.6084/m9.figshare.24964665
title: <b>Effect of microplastics on the soil-plant system: A perspective </b><b>on</b><b> rhizosphere microbial community and soil element cycling</b>

description: Data for figure construction
DOI: 10.6084/m9.figshare.24964665.v1
title: <b>Effect of microplastics on the soil-plant system: A perspective </b><b>on</b><b> rhizosphere microbial community and soil element cycling</b>

description: Data for figure construction
DOI: 10.6084/m9.figshare.24964710
title: supply chain

description: supply chain data
DOI: 10.6084/m9.figshare.24233317.v1
title: UKR Resilience Project

description: Data for submission to Science (2023)
DOI: 10.34740/kaggle/dsv/7366498
title: The Infrared Thermography Temperature Dataset
DOI: 10.18141/2223108
title: IDAES-PSE 2.2.0 Release

description: The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. New features in the 2.2 release include: DiagnosticsToolbox DiagnosticsToolbox (idaes.core.util.model_diagnostics. DiagnosticsToolbox is a new self-guiding toolbox for assisting with diagnosing modeling issues. The toolbox contains a wide range of tools for identifying common modeling issues and conveying these to the user, and more features will be added in the coming months. To try the new toolbox, use the following steps: from idaes.core.util import DiagnosticsToolbox Build an instance of your model Ensure your models has zero degrees of freedom (as best you can) dt = DiagnosticsToolbox(model) dt.report_structural_issues() Follow the prompts Deprecations DegeneracyHunter is being deprecated in favor of the new DiagnosticsToolbox. The features and capabilities of DegeneracyHunter will be moved over to the DiagnositcsToolbox in the coming months. Removal of usage of Pyomo's expr.current due to deprecation upstream. Removed support for radial basis functions in ALAMOpy as these did not work in the current implementation. Those wishing to use radial basis functions should use Pysmo instead. New Capabilities MSContactor model for unit operations involving mass transfer between 2 or more streams, such as membrane, solvent extraction and solids leaching operations. Other Improvements Improved formulation for solubility products with additional parameters for better scaling of terms Better backward compatibility, verification and robustness testing of core models and APIs Added support for Separator models without energy balances
DOI: 10.21947/2228905
title: MVCO site - NREL Thermodynamic profiler (Assist II-11) / TROPoe retrieval

description: This dataset contains thermodynamic profiles retrieved through TROPoe.
DOI: 10.21947/2229145
title: WFIP3 RHOD site - NREL Scanning Lidar (upgraded Galion SN: 60) / Derived Data - High-Frequency Wind Profiles

description: Wind profiles from ground-based Doppler lidar at site RHOD were calculated for each 6-beam profiling scan (one point every ~20 s). The wind speed retrieval uses the Sathe et al., 2015, paper in the references.
DOI: 10.21947/2229418
title: WFIP3 - RHOD site - NREL Scanning Lidar (upgraded Galion SN: 60) / Derived Data - Wind Statistics

description: The 10-min wind statistics from ground-based Doppler lidar at the RHOD site were calculated using the Sathe et al., 2015, paper in the references.
DOI: 10.26179/h5h3-w279
title: At-sea seabird observations and effort during the TEMPO voyage of the RV Investigator (Jan-Mar 2021)
DOI: 10.6084/m9.figshare.24961485
title: MOL_LMDB

description: The pcqm molecular files used for fractional denoising pre-training
DOI: 10.6084/m9.figshare.24964668.v1
title: Microbial Communities and Metagenomes in Methane-Rich Deep Coastal Sediments

description: Coastal sediments are rich in embedded recalcitrant organic carbons that are biotransformed into methane. In this study, bacterial 16S rRNA community composition, gas composition (carbon dioxide, methane, nitrogen) and chemical indicators (total nitrogen, total carbon and total sulfate) were examined in five deep sediment cores (over 130 m in length) obtained from the Hangzhou Bay. The V3-V4 region of the 16S rRNA gene amplicons was amplified and sequenced for the community analysis. We conducted a metagenomic sequencing of the two sediment samples, with a high methane content and enrichment of methanogenic Bathyarchaeota. A total of 27 draft genomes were retrieved through metagenomic binning methodologies and were classified into Bathyarchaeota, Asgard archaea, Planctomycetes and other microbial groups. The species composition, along with the physicochemical factors of the core sediments, revealed a strong correlation with methane content, particularly in sample S-2. The data provided are significant for revealing the relationship between methane generation and microbial community composition in deep sediment core samples from coastal to marine environments.
DOI: 10.6084/m9.figshare.24947634
title: Chemical indicators in Hangzhou Bay sediments

description: Coastal sediments are rich in embedded recalcitrant organic carbons that are biotransformed into methane. In this study, bacterial 16S rRNA community composition, gas composition (carbon dioxide, methane, nitrogen) and chemical indicators (total nitrogen, total carbon and total sulfate) were examined in five deep sediment cores (over 130 m in length) obtained from the Hangzhou Bay. The V3-V4 region of the 16S rRNA gene amplicons was amplified and sequenced for the community analysis. We conducted a metagenomic sequencing of the two sediment samples, with a high methane content and enrichment of methanogenic Bathyarchaeota. A total of 27 draft genomes were retrieved through metagenomic binning methodologies and were classified into Bathyarchaeota, Asgard archaea, Planctomycetes and other microbial groups. The species composition, along with the physicochemical factors of the core sediments, revealed a strong correlation with methane content, particularly in sample S-2. The data provided are significant for revealing the relationship between methane generation and microbial community composition in deep sediment core samples from coastal to marine environments.
DOI: 10.3886/e183610v1-144841
title: Data and Code for: The impact of large-scale social media advertising campaigns on COVID-19 vaccination: Evidence from two randomized controlled trials

description: COVID-19 vaccines are widely available in wealthy countries, yet many remain unvaccinated. We report on two studies (U.S. and France) with millions of Facebook users that tested strategies central to vaccination outreach: (1) health professionals addressing common concerns and (2) motivating “ambassadors” to encourage vaccination in their social networks. We can reject very small effects of any intervention on new first doses (0.16pp - U.S., 0.021pp - France), with similar results for second doses and boosters (U.S.). During the Omicron wave, messaging aimed at the unvaccinated or those tasked with encouraging others did not change vaccination decisions.
DOI: 10.6084/m9.figshare.24964821
title: Understory bamboo removal impacts on woody seedlings regeneration in forest ecosystems: a meta-analysis

description: Tree seedling regeneration in forests is often impeded by the competitive influence of dense understory bamboo competition. While localized studies have investigated the ecological effects of understory bamboo removal on tree seedlings, but a comprehensive analysis at a global scale is lacking. In this meta-analysis, we synthesized data from 32 experimental studies to assess the overall effect of understory bamboo removal on tree seedling regeneration and identify key influencing factors. Our findings demonstrated that understory bamboo removal enhanced tree seedling survival, emergence, and height growth. However, the response of tree seedlings to bamboo removal varied depending on regeneration characteristics, forest types, and bamboo removal methods. Specifically, understory bamboo removal increased the survival rate of deciduous seedlings but had no significant effect on evergreen seedlings. Regarding regeneration stages, bamboo removal had a significant positive effect on the survival rate of saplings but not on seedlings. In different forest types, bamboo removal significantly increased the emergence density of seedlings in deciduous broadleaf forest but had a significant negative influence in evergreen and mixed evergreen-deciduous forests. Additionally, natural removal of bamboo (i.e., bamboo flowering) showed a greater positive effect on seedlings than bamboo removal by artificial or animal gnawing methods. Furthermore, we found that the duration of bamboo removal, mean annual temperature, precipitation of seasonality, and soil pH strongly influenced the response ratios of tree seedling regeneration. Our findings offer valuable insights into the ecological implications of understory bamboo removal on tree seedlings regeneration, providing guidance for effective understory bamboo management to promote forest succession and biodiversity conservation.
DOI: 10.6084/m9.figshare.24964821.v1
title: Understory bamboo removal impacts on woody seedlings regeneration in forest ecosystems: a meta-analysis

description: Tree seedling regeneration in forests is often impeded by the competitive influence of dense understory bamboo competition. While localized studies have investigated the ecological effects of understory bamboo removal on tree seedlings, but a comprehensive analysis at a global scale is lacking. In this meta-analysis, we synthesized data from 32 experimental studies to assess the overall effect of understory bamboo removal on tree seedling regeneration and identify key influencing factors. Our findings demonstrated that understory bamboo removal enhanced tree seedling survival, emergence, and height growth. However, the response of tree seedlings to bamboo removal varied depending on regeneration characteristics, forest types, and bamboo removal methods. Specifically, understory bamboo removal increased the survival rate of deciduous seedlings but had no significant effect on evergreen seedlings. Regarding regeneration stages, bamboo removal had a significant positive effect on the survival rate of saplings but not on seedlings. In different forest types, bamboo removal significantly increased the emergence density of seedlings in deciduous broadleaf forest but had a significant negative influence in evergreen and mixed evergreen-deciduous forests. Additionally, natural removal of bamboo (i.e., bamboo flowering) showed a greater positive effect on seedlings than bamboo removal by artificial or animal gnawing methods. Furthermore, we found that the duration of bamboo removal, mean annual temperature, precipitation of seasonality, and soil pH strongly influenced the response ratios of tree seedling regeneration. Our findings offer valuable insights into the ecological implications of understory bamboo removal on tree seedlings regeneration, providing guidance for effective understory bamboo management to promote forest succession and biodiversity conservation.
DOI: 10.58080/dvzy-1z98
title: A single arm phase II study using magnetic resonance imaging (MRI) to select patients with early breast cancer for omission of post-operative radiotherapy (ANZ 1002 PROSPECT)

description: HeSANDA 1.0.0
description: Dataset of 201 women with histologically confirmed, unifocal, unilateraly invasive early breast cancer selected to omit radiotherapy by MRI before trial entry. The primary objective was ipsilateral invasive recurrence rate in the breast at 5 years.
DOI: 10.58080/rfsh-9s54
title: Randomised phase II trial of neoadjuvant chemotherapy +/- concurrent aromatase inhibitor endocrine therapy to down-stage large oestrogen receptor positive breast cancer (ANZ 1401 ELIMINATE)

description: HeSANDA 1.0.0
description: * Dataset of 134 women with ER-positive, HER2-negative grade 2/3 invasive breast cancer greater than 20mm. *Randomised 2:1 to receive either standard neoadjuvant chemotherapy concurrently with aromatase inhibitor (89 patients) or standard neoadjuvant chemotherapy only (45 patients) for 18-24 weeks. * Rate of downstaging to pathologic stage 0 or 1A, pCR at time of surgery data. * Median breast tumour volume percentage decrease, rate of breast conserving surgery, SAE rates data.
DOI: 10.6084/m9.figshare.24964932.v1
title: Information of Genomes from Methane-Rich Deep Coastal Sediments

description: Information of Genomes from Methane-Rich Deep Coastal Sediments
DOI: 10.6084/m9.figshare.24964932
title: Information of Genomes from Methane-Rich Deep Coastal Sediments

description: Information of Genomes from Methane-Rich Deep Coastal Sediments
DOI: 10.6084/m9.figshare.24961908
title: Data from: Comparative analysis of models in predicting the effects of SNPs on TF-DNA binding using large-scale in vitro and in vivo data

description: Noncoding variants associated with complex traits can alter the motifs of transcription factor (TF)-DNA binding. Although many computational models have been developed to predict the effects of noncoding variants on TF binding, their predictive power lacks systematic evaluation. Here we have evaluated 14 different models built on position weight matrices (PWMs), support vector machine (SVM), ordinary least squares (OLS) and deep neural networks (DNN), using large-scale in vitro (i. e. SNP-SELEX) and in vivo (i. e. allele-specific binding, ASB) TF binding data. The SNP-SELEX data used in this study were collected from the GVAT database (http://renlab.sdsc.edu/GVATdb/), and the ASB data were collected from the ADASTRA database (https://adastra.autosome.org/bill-cipher/downloads). This dataset contains following files.SNP-SELEX_firstbatch_evaldata_positive_data.txt.gz: SNP-SELEX, first batch, positive setSNP-SELEX_firstbatch_evaldata_negative_data.txt.gz: SNP-SELEX, first batch, negative setSNP-SELEX_novelbatch_evaldata_positive_data.txt.gz: SNP-SELEX, novel batch, positive setSNP-SELEX_novelbatch_evaldata_negative_data.txt.gz: SNP-SELEX, novel batch, negative setASB_evaldata_positive_data.txt.gz: ASB, positive setASB_evaldata_negative_data.txt.gz: ASB, negative setSNP-SELEX_AUROC_AUPRC.xlsx: AUROC and AUPRC of 14 models based on SNP-SELEXASB_AUROC_AUPRC.xlsx: AUROC and AUPRC of 14 models based on ASB<br>
DOI: 10.6084/m9.figshare.24964938
title: alpha-diversity metrics of samples from methane-rich deep coastal sediments

description: alpha-diversity metrics of samples from methane-rich deep coastal sediments
DOI: 10.26179/45qw-j927
title: Data to support Zooplankton abundance and distribution along the Mawson coast, East Antarctica - collected on the TEMPO voyage of the RV Investigator
DOI: 10.26183/a9de-xp42
title: Phosphorus Recovery from Hydroponics Waste Solutions and its Economic Potential – Supplementary Material

description: This dataset contains precipitation of nutrients present in hydroponic waste nutrient solution. Tables and figures contained in a word document to support the publication of the article titled Phosphorus Recovery from Hydroponics Waste Nutrient Solutions and its Economic Potential. 
<p>
Nutrient management, particularly phosphorus, is crucial for global food security due to its limited availability. This study investigates the extraction of phosphorus from hydroponic waste nutrient solutions (HWNS) using samples from various hydroponic farms. The results display elevated phosphorus levels, peaking at 70mg/L and a median of 20mg/L, in conjunction with a high median calcium concentration of 220 mg/L. This combination enhances the potential for efficient calcium phosphate precipitation. At a pH of 9.5, phosphorus removal reached consistently high levels, exceeding 94% and achieving a median value of 97.6%. The economic value of the recovered phosphorus was then compared to rock phosphates. Through chemical precipitation with micro-calcium phosphate, economic evaluations determined that to achieve production costs comparable to or below the market value of calcium phosphate, HWNS should contain a phosphorus concentration of at least 16 mg P/L.
DOI: 10.6084/m9.figshare.24941527
title: Dataset from Flour beetles prefer corners over walls and are slowed down with increasing habitat complexity

description: Movement affects all key behaviours in which animals engage, including dispersal and habitat use. The red flour beetle, known as a cosmopolitan pest of stored products, was the subject of our study. We examined whether the beetles preferred corners, walls or open areas, and how turns or obstacles in corridors delayed the beetles' arrival at a target cell. Beetles spent significantly more time in corners than expected by chance, while they spent considerably less time in open areas than expected. However, no significant difference was observed between areas with two or three surrounding walls. This could be attributed to the beetles' stronger attraction to corners than crevices or the insufficient proximity of the third wall to the other two. Movement through the corridor was delayed by turns or obstacles, expressed in arrival probabilities, arrival times, time in the corridor or movement speed. Obstacles on the corridor's perimeter had a stronger effect on the beetle movement than those in the corridor's centre owing to the beetles' tendency to follow walls. The research is important also for applied purposes, such as better understanding beetle movement, how to delay their arrival to new patches, and where to place traps.
DOI: 10.6084/m9.figshare.24941527.v1
title: Dataset from Flour beetles prefer corners over walls and are slowed down with increasing habitat complexity

description: Movement affects all key behaviours in which animals engage, including dispersal and habitat use. The red flour beetle, known as a cosmopolitan pest of stored products, was the subject of our study. We examined whether the beetles preferred corners, walls or open areas, and how turns or obstacles in corridors delayed the beetles' arrival at a target cell. Beetles spent significantly more time in corners than expected by chance, while they spent considerably less time in open areas than expected. However, no significant difference was observed between areas with two or three surrounding walls. This could be attributed to the beetles' stronger attraction to corners than crevices or the insufficient proximity of the third wall to the other two. Movement through the corridor was delayed by turns or obstacles, expressed in arrival probabilities, arrival times, time in the corridor or movement speed. Obstacles on the corridor's perimeter had a stronger effect on the beetle movement than those in the corridor's centre owing to the beetles' tendency to follow walls. The research is important also for applied purposes, such as better understanding beetle movement, how to delay their arrival to new patches, and where to place traps.
DOI: 10.5281/zenodo.8215107
title: A machine learning-based high-precision density functional method for drug-like molecules

description: Models
The repo contains the models and test datasets for our aticles. The energy unit is in Hartree, The coordinate unit is in Bohr.
## DeePHF
you need first prepare the `dm_eig.npy` in data_test and do predict `l_e_delta.npy`, you can use
```
deepks test -m model.pth -o test/test -d data_test/* -D dm_eig -G
```
## DeePKS
first you should prepare the `atom.npy`, and `energy.npy` in data_test. you can test the datasets by command. 
```
deepks scf scf_input.yaml -m model.pth -s data_test -d test_out
```
# Datasets
All datasets only have `atom.npy` and `energy.npy`. The coordinate unit is `bohr`, and energy unit is `Hartree`.
## small molecules torsion
Contains 62 small molecules with 36 conformation for each under CCSD(T)/def2-TZVP.
 
[1] B. D. Sellers, N. C. James, A. Gobbi, A comparison of quantum and molecular mechanical methods to estimate strain energy in druglike fragments, Journal of chemical information and modeling 57 (6) (2017) 1265–127
 
## MPCONF91
Contains 6 molecules with 91 conformations under LNO-CCSD(T)/def2-TZVP.
 
[1] J. Rezac, D. Bím, O. Gutten, L. Rulisek, Toward accurate conformational energies of smaller peptides and medium-sized macrocycles: Mpconf196 benchmark energy data set, Journal of chemical theory and computation 14 (3) (2018) 1254–1
 
## torsionNet206
Contains 206 molecules with 4494 conformations under CCSD(T)/def2-TZVP.
 
[1] B. K. Rai, V. Sresht, Q. Yang, R. Unwalla, M. Tu, A. M. Mathiowetz,G. A. Bakken, Torsionnet: A deep neural network to rapidly predict small-molecule torsional energy profiles with the accuracy of quantum mechanics, Journal of Chemical Information and Modeling 62 (4) (2022) 785–80
 
## Out-of-plane bending
Contains 242 molecules with 3315 conformations under CCSD(T)/def2-TZVP.
 
[1] X. Yang, C. Liu, P. Ren, High order ab initio valence force field with chemical pattern based parameter assignment., Journal of Computational Biophysics and Chemistry 21 (4) (2021) 43
 
## DrugBank-T
Contains 165 molecules with 1155 conformations under CCSD(T)/def2-TZVP.
 
[1] V. Law, C. Knox, Y. Djoumbou, T. Jewison, A. C. Guo, Y. Liu, A. Maciejewski, D. Arndt, M. Wilson, V. Neveu, et al., Drugbank
4.0: shedding new light on drug metabolism, Nucleic acids research 42 (D1) (2014) D1091–D1097  
[2] Z. Qiao, M. Welborn, A. Anandkumar, F. R. Manby, T. F. Miller III, Orbnet: Deep learning for quantum chemistry using symmetry adapted atomic-orbital features, The Journal of chemical physics 153 (12) (2020) 124111
## Notice
if you use above datasets, please cite the original articals too