cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23675661.v1
title: Untit Can the digital economy effectively contribute to the clean energy transition? Evidence from China led Item

description: As our digital economy rapidly evolves and digital technology becomes more pervasive, there's growing interest in digital transformation for clean energy. Accordingly, this study discusses the impact of digital economy on clean energy transformation from multi-dimensional, multi-level and multi-regional perspective through spatial econometric model based on the panel data of 30 provinces in China from 2000 to 2021. It is proved that the positive effects of digital economy on local clean energy transformation are much greater than those of neighboring areas, which further proves that ecological environment, technological innovation, FDI, financial development, city size and economic growth are also the main action paths for the sustainable development of clean energy transformation. Secondly, when government intervention and market-driven conditions are taken into account, both limit the positive impact of the digital economy on clean energy transformation, but the impact of the digital economy differs across regions. Finally, the digital economy has the largest impact in the western region, the smallest in the eastern region and the second largest in the central region, taking into account the existence of spatial regional heterogeneity. Our research can provide theoretical support for China and other emerging developing countries to promote the deep integration of the digital economy and clean energy, as these facts show that the sustainable development of the digital economy is an important way to promote the transformation of clean energy.
DOI: 10.17632/3b72vrw589.1
title: Probability Language-Njiku and Chacha

description: The data file contains scores of secondary school students scores in probability language and achievement in probability. The file also includes demographic data. The analysis of the data shows a significant correlation between probability language skills and achievement in probability.
DOI: 10.17632/g6jkmk666s.1
title: Integrating a choice experiment into an agent-based model to simulate climate-change induced migration: The case of the Mekong River Delta, Vietnam

description: Stata files for the data used in Integrating a choice experiment into an agent-based model to simulate climate-change induced migration: The case of the Mekong River Delta, Vietnam by Tra Thi Trinh and Alistair Munro.  Please note that this is part of a larger dataset used by researchers at our institute (National Graduate Institute for Policy Studies or GRIPS), and that only parts of the dataset relevant to our results are posted here. NetLogo code of our simulations is attached.  Some part of the STATA code that is essential to replicate our estimation is also posted. Other data and code that are not posted here will be made available on request.
DOI: 10.17632/k3cg6kzfyy.1
title: POPULATION GENETIC STRUCTURE OF TWO CRYPTIC DUCKWEED SPECIES

description: The data presented in this study, titled "Population Genetic Structure of Two Cryptic Duckweed Species (Lemna minor & L. turionifera) in Alberta Using a Genotyping-by-Sequencing Approach," is about to be published in the Journal Aquatic Botany. Our research utilized genotyping-by-sequencing to investigate the population genetic structure of two duckweed species, Lemna minor and L. turionifera Landolt, in Alberta.

For this analysis, we employed four distinct datasets, each represented by a .vcf file:

    Lemna_minor_&_turionifera_lm550refgenom: This dataset includes samples of both L. minor and L. turionifera, with the reference genome being L. minor 5500 (An et al., 2018).

    Lemna_minor_lm550refgenom: This dataset comprises solely L. minor samples, and the reference genome used is L. minor 5500 (An et al., 2018).

    Lemna_turionifera_lm550refgenom: This dataset contains only L. turionifera samples, with the reference genome being L. minor 5500 (An et al., 2018).

    Lemna_minor_lm8627refgenom: This dataset consists exclusively of L. minor samples, and the reference genome utilized is L. minor 8627 (An et al., 2018).

The samples of Lemna minor and L. turionifera were collected from various locations across six watersheds and 12 river basins in Alberta.

This comprehensive study aims to shed light on the population genetic structure of these cryptic duckweed species in Alberta using advanced genotyping-by-sequencing techniques.

For more information please contact the corresponding author Kanishka M. Senevirathna, kanishkamadushanka12191@gmail.com
DOI: 10.17632/8zhm255378.1
title: Property crime in the South Caucasus 

description: Among property crimes, three main types- robbery, burglary and theft, and, accordingly, their clear-up rate are discussed. The data source on crime is the annual reports published by the official statistics offices of Georgia, Azerbaijan and Armenia (https://www.geostat.ge/en ; https://www.armstat.am/en/ ; https://www.stat.gov.az/?lang=en ). In the case of Georgia, additionally, the data for the years 1997-2012 were requested from the Ministry of Internal Affairs ( https://police.ge/en ). Data on the number of prisoners, real wages, divorce rates and urbanisation were also obtained from the mentioned sources. Other demographic variables - total population, age and gender are obtained from the database prepared by the UN Population Division (https://population.un.org/wpp/  ). Changes in the consumer prices index and the GDP per capita (at constant prices, PPP) are from the WEO database of the International Monetary Fund (https://www.imf.org/en/data ). The employment rate and education level are from the databases of the International Labor Organisation and the UNESCO Institute for Statistics (https://ilostat.ilo.org/ ; http://uis.unesco.org/ ).
DOI: 10.17632/bk8p8b3548.1
title: Waste collector's perception

description: Waste collectors' perceptions of the internal service quality of the Denpasar waste management system. The data collected on November 2022
DOI: 10.17632/bk8p8b3548.2
title: Waste collector's perception

description: Waste collectors' perceptions of the internal service quality of the Denpasar waste management system. The data collected on November 2022
DOI: 10.17632/8k97yxxghm.2
title: Immune activation and other risk factors for HIV acquisition

description: Immune activation and other risk factors for HIV acquisition.
DOI: 10.17632/8k97yxxghm.3
title: Immune activation and other risk factors for HIV acquisition

description: Immune activation and other risk factors for HIV acquisition.
DOI: 10.17632/d2j939k88t.1
title: Kurdish Standard Characters EMNIST-like Dataset

description: The Kurdish Character dataset is a comprehensive collection of the Kurdish alphabet, providing detailed information about each letter used in the Kurdish writing system. This dataset serves as a valuable resource for learning and studying the Kurdish language, as well as for developing language processing applications and educational tools.
The dataset includes all letters of the Kurdish alphabet, encompassing both the Arabic-based Sorani script and the Latin-based Kurmanji script. The collection mostly consists of (58) characters and was created with the assistance of about (3500) native people. This work is an enormous collection of individual handwritten Central Kurdish character representations. totally with 7000 photos for each character, it has (406000) total images. Preprocessing and subsequent preparation of the dataset used in this work were done in accordance with EMINST standards.
the dataset aims to capture the natural handwriting styles and variations that exist in the Kurdish language. This allows for a more authentic representation of the Kurdish alphabet, considering the different ways individuals may write each letter. The collected dataset can be used for various purposes such as developing handwriting recognition systems, analyzing handwriting patterns, improving the accuracy of optical character recognition (OCR) algorithms, and enhancing the overall understanding and study of the Kurdish script.
DOI: 10.5281/zenodo.8141666
title: EuroSAT Model Zoo: A Dataset of Diverse Populations of Neural Network Models - EuroSAT

description: <strong>Abstract</strong> In the last years, neural networks have evolved from laboratory environments to the state-of-the-art for many real-world problems. Our hypothesis is that neural network models (i.e., their weights and biases) evolve on unique, smooth trajectories in weight space during training. Following, a population of such neural network models (refereed to as “model zoo”) would form topological structures in weight space. We think that the geometry, curvature and smoothness of these structures contain information about the state of training and can be reveal latent properties of individual models. With such zoos, one could investigate novel approaches for (i) model analysis, (ii) discover unknown learning dynamics, (iii) learn rich representations of such populations, or (iv) exploit the model zoos for generative modelling of neural network weights and biases. Unfortunately, the lack of standardized model zoos and available benchmarks significantly increases the friction for further research about populations of neural networks. With this work, we publish a novel dataset of model zoos containing systematically generated and diverse populations of neural network models for further research. In total the proposed model zoo dataset is based on six image datasets, consist of 27 model zoos with varying hyperparameter combinations are generated and includes 50’360 unique neural network models resulting in over 2’585’360 collected model states. Additionally, to the model zoo data we provide an in-depth analysis of the zoos and provide benchmarks for multiple downstream tasks as mentioned before. <strong>Dataset</strong> This dataset is part of a larger collection of model zoos and contains the zoos trained on EuroSAT. All zoos with extensive information and code can be found at www.modelzoos.cc. This repository contains two types of model populations: the base model zoo ("eurosat_cnn_kaiming_uniform.zip"), as well as a collection of sparsified model zoos (filenames ending in "magn_XX.zip" or "ard.zip"). Zoos are trained with CNN models in configurations varying the seed only (seed), and sparsification is done through magnitude-based weight pruning ("magn_XX.zip") or varational dropout ("ard.zip"). For more information on the zoos and code to access and use the zoos, please see www.modelzoos.cc.
description: This dataset is part of a larger collection of model zoo datasets. Further information and references to all zoos can be found on www.modelzoos.cc
DOI: 10.5281/zenodo.8141667
title: EuroSAT Model Zoo: A Dataset of Diverse Populations of Neural Network Models - EuroSAT

description: <strong>Abstract</strong> In the last years, neural networks have evolved from laboratory environments to the state-of-the-art for many real-world problems. Our hypothesis is that neural network models (i.e., their weights and biases) evolve on unique, smooth trajectories in weight space during training. Following, a population of such neural network models (refereed to as “model zoo”) would form topological structures in weight space. We think that the geometry, curvature and smoothness of these structures contain information about the state of training and can be reveal latent properties of individual models. With such zoos, one could investigate novel approaches for (i) model analysis, (ii) discover unknown learning dynamics, (iii) learn rich representations of such populations, or (iv) exploit the model zoos for generative modelling of neural network weights and biases. Unfortunately, the lack of standardized model zoos and available benchmarks significantly increases the friction for further research about populations of neural networks. With this work, we publish a novel dataset of model zoos containing systematically generated and diverse populations of neural network models for further research. In total the proposed model zoo dataset is based on six image datasets, consist of 27 model zoos with varying hyperparameter combinations are generated and includes 50’360 unique neural network models resulting in over 2’585’360 collected model states. Additionally, to the model zoo data we provide an in-depth analysis of the zoos and provide benchmarks for multiple downstream tasks as mentioned before. <strong>Dataset</strong> This dataset is part of a larger collection of model zoos and contains the zoos trained on EuroSAT. All zoos with extensive information and code can be found at www.modelzoos.cc. This repository contains two types of model populations: the base model zoo ("eurosat_cnn_kaiming_uniform.zip"), as well as a collection of sparsified model zoos (filenames ending in "magn_XX.zip" or "ard.zip"). Zoos are trained with CNN models in configurations varying the seed only (seed), and sparsification is done through magnitude-based weight pruning ("magn_XX.zip") or varational dropout ("ard.zip"). For more information on the zoos and code to access and use the zoos, please see www.modelzoos.cc.
description: This dataset is part of a larger collection of model zoo datasets. Further information and references to all zoos can be found on www.modelzoos.cc
DOI: 10.17632/mrvmsrn9r6.1
title: MICRO-GO study: transcriptional profiling of orbital tissues in Graves’ orbitopathy & microbiome composition

description: Background: Graves’ disease (GD) and Graves’ orbitopathy (GO) result from ongoing stimulation of the TSH receptor due to autoantibodies acting as persistent agonists. Orbital pre-adipocytes and fibroblasts also express the TSH receptor, resulting in expanded retro-orbital tissue and causing exophthalmos and limited eye movement. Recent studies have shown that GD/GO patients have a disturbed gut microbiome composition, which has been associated with increased intestinal permeability. We hypothesize that enhanced intestinal permeability may aggravate orbital inflammation and, thus, increase myofibroblast differentiation and the degree of fibrosis. 
Methods: We used 2 distinct cohorts of GO patients to study intestinal permeability and its connection to inflammatory/fibrotic processes in the orbital tissues of GO patients. Intestinal permeability was assessed by measuring serum lipopolysaccharide-binding protein (LBP), zonulin, TLR5, and TLR9 ligands. The influx of macrophages and accumulation of T-cells and myofibroblast were quantified in orbital connective tissue. The NanoString digital spatial profiler RNA panel was used to determine the transcriptional profile of active fibrotic areas within orbital sections.
Results: GO patients displayed significantly higher LBP serum concentrations than healthy controls. Within the MicroGO cohort, patients with high serum LBP levels also showed higher levels of zonulin and TLR5 and TLR9 ligands in their circulation. The increased intestinal permeability was accompanied by augmented expression of genes marking immune cell infiltration and encoding key proteins for immune cell adhesion, antigen presentation, and cytokine signaling in the orbital tissue. Macrophage influx was positively linked to the extent of T cell influx and fibroblast activation within GO-affected orbital tissues. Moreover, serum LBP levels significantly correlated with the abundance of specific Gram-negative gut bacteria, linking the gut to local orbital inflammation. 
Conclusion: These results indicate that GO patients have enhanced intestinal permeability. The subsequent translocation of bacterial compounds to the systemic circulation may aggravate inflammatory processes within the orbital tissue and, as a consequence, augment the proportion of activated myofibroblasts, which actively secrete extracellular matrix leading to retro-orbital tissue expansion. 

Here, we share our data on fecal microbiota composition (assessed by 16S rRNA sequencing) and the transcriptional data obtaining with the GeoMx digital spatial profiling technology.
DOI: 10.6084/m9.figshare.23675517
title: scCUTseq source data

description: Source data used for the analysis of the manuscript titled 'High clonal diversity and spatial genetic admixture in early prostate cancer and surrounding normal tissue'
DOI: 10.17632/n2jy2hck2n.1
title: Data and Code for: The Federal Reserve’s Response to the Global Financial Crisis and its Effects: An Interrupted Time-Series Analysis of the Impact of its Quantitative Easing Programs

description: This file contains the data and code for the publication "The Federal Reserve’s Response to the Global Financial Crisis and its Effects: An Interrupted Time-Series Analysis of the Impact of its Quantitative Easing Programs" by A. C. Kamkoum, 2023.
DOI: 10.17632/sjyf9kncs9.1
title: Novel misos shape distinct microbial ecologies

description: From the 38 metagenomic samples of novel misos, 90 prokaryotic and 10 A. oryzae metagenome-assembled genomes (MAGs) of high quality were recovered.
DOI: 10.5281/zenodo.8143400
title: Machine Learning-Assisted Discovery of Hidden States in Expanded Free Energy Space

description: Collective variables (CVs) are crucial parameters in enhanced sampling calculations and strongly impact the quality of the obtained free energy surface. However, many existing CVs are unique to and dependent on the system they are constructed with, making the developed CV non-transferable to other systems. Herein, we develop a non-instructor-led deep autoencoder neural network (DAENN) for discovering general-purpose CVs. The DAENN is used to train a model by learning molecular representations upon unbiased trajectories that contain only the reactant conformers. The prior knowledge of nonconstraint reactants coupled with the here-introduced topology variable and loss-like penalty function are only required to make the biasing method able to expand its configurational (phase) space to unexplored energy basins. Our developed autoencoder is efficient and relatively inexpensive to use in terms of <em>a priori</em> knowledge, enabling one to automatically search for hidden CVs of the reaction of interest.
DOI: 10.5281/zenodo.8143399
title: Machine Learning-Assisted Discovery of Hidden States in Expanded Free Energy Space

description: Collective variables (CVs) are crucial parameters in enhanced sampling calculations and strongly impact the quality of the obtained free energy surface. However, many existing CVs are unique to and dependent on the system they are constructed with, making the developed CV non-transferable to other systems. Herein, we develop a non-instructor-led deep autoencoder neural network (DAENN) for discovering general-purpose CVs. The DAENN is used to train a model by learning molecular representations upon unbiased trajectories that contain only the reactant conformers. The prior knowledge of nonconstraint reactants coupled with the here-introduced topology variable and loss-like penalty function are only required to make the biasing method able to expand its configurational (phase) space to unexplored energy basins. Our developed autoencoder is efficient and relatively inexpensive to use in terms of <em>a priori</em> knowledge, enabling one to automatically search for hidden CVs of the reaction of interest.
DOI: 10.17632/ddntr48m83.1
title: Data for: Japanese macaques exhibit pessimistic judgment bias after seeing snake pictures

description: Datasets and R codes necessary to reproduce the analysis in the manuscript.
DOI: 10.17632/ddntr48m83.2
title: Data for: Japanese macaques exhibit pessimistic judgment bias after seeing snake pictures

description: Datasets and R codes necessary to reproduce the analysis in the manuscript.
DOI: 10.6084/m9.figshare.23675595.v1
title: General data about 22 Chinese lakes.xlsx

description: In this study, we analyzed the contents and isotopic compositions of BC in surface sediments from 22 lakes across China. The BC contents ranged from 0.02 to 0.70% and the BC/TOC ratio ranged from 3.1% to 24.6%. Our findings based on δ13C and Δ14C data indicate that fossil fuel combustion is the primary source of sediment BC, contributing 28% to 91% (average 73%), with the highest in in the most developed eastern China and the lowest in the less developed southwestern and northwestern China (QTP and IMXP). The highest BC burial rates were observed in the NEP and YGP, followed by the EP and QTP, with the IMXP exhibiting the lowest rates. As of 2014, the total BC burial flux in Chinese lakes was estimated to be 122.2 Gg yr-1, which is comparable to the BC burial fluxes in China's offshore regions. However, due to the smaller lake area, Chinese lakes exhibit substantially higher BC burial rates per unit area than marginal seas and deep oceans, making them an important sink for BC.
DOI: 10.6084/m9.figshare.23675595
title: General data about 22 Chinese lakes.xlsx

description: In this study, we analyzed the contents and isotopic compositions of BC in surface sediments from 22 lakes across China. The BC contents ranged from 0.02 to 0.70% and the BC/TOC ratio ranged from 3.1% to 24.6%. Our findings based on δ13C and Δ14C data indicate that fossil fuel combustion is the primary source of sediment BC, contributing 28% to 91% (average 73%), with the highest in in the most developed eastern China and the lowest in the less developed southwestern and northwestern China (QTP and IMXP). The highest BC burial rates were observed in the NEP and YGP, followed by the EP and QTP, with the IMXP exhibiting the lowest rates. As of 2014, the total BC burial flux in Chinese lakes was estimated to be 122.2 Gg yr-1, which is comparable to the BC burial fluxes in China's offshore regions. However, due to the smaller lake area, Chinese lakes exhibit substantially higher BC burial rates per unit area than marginal seas and deep oceans, making them an important sink for BC.
DOI: 10.17632/cs4v2bh24t.1
title: The effects of transcranial electrical stimulation of the left dorsolateral prefrontal cortex on tactile spatial discrimination performance

description: The hypothesis is that the application of tRNS and anodal tPCS to the left DLPFC may improve tactile orientation discrimination performance. Our data show that tRNS application on the left DLPFC tended to enhance tactile perceptual discrimination performance, but not anodal tPCS over the left DLPFC. These findings indicate that transcranial electrical stimulation to the left DLPFC may improve tactile perceptual discrimination performance, with effects that depend on stimulus modality.
DOI: 10.17632/yd9ztgg3n7.1
title: Praise and Cooperation

description: data for praise and cooperation project
DOI: 10.17632/mbmj2ymjmg.1
title: Data of mud and sand sediment transport by the 2011 Tohoku-oki tsunami at Sendai Plain, Japan

description: This dataset contains simulation data using Delft3D-FLOW. 

We put the following two data in the folder "Main results".  In the folder "Sensitivity analysis", we only put "erosion_sedimentation.mat"
erosion_sedimentation.mat; The distribution of sedimentation and erosion in domain 6 after the simulation.
wd.mat; The distribution of water depth with an interval of 5 min in domain 6.

We put our simulation data as follows.
Main results/Sand sediment transport; the simulation results in Table. 2.
Main results/Mud sediment transport; the simulation results in Table. 3.
Main results/Sand sediment transport; the simulation results in Table. 4.
Main results/Sand sediment transport; the simulation results in Table. 5.