cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive6075.20230509.8.1
title: Halomonas stevensii Kim et al. 2010

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6076.20230509.8.1
title: Halomonas titanicae Mann et al. 2010

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6077.20230509.8.1
title: Halomonas vilamensis Menes et al. 2011

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6078.20230509.8.1
title: Halomonas caseinilytica Wu et al. 2008

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6079.20230509.8.1
title: Halomonas qijiaojingensis Chen et al. 2012

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6080.20230509.8.1
title: Salinicola salarius (Kim et al. 2007) de la Haba et al. 2010

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6081.20230509.8.1
title: Salinicola socius Anan'ina et al. 2008 emend. de la Haba et al. 2010

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6082.20230509.8.1
title: Kushneria marisflavi (Yoon et al. 2001) Sánchez-Porro et al. 2009

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6083.20230509.8.1
title: Kushneria avicenniae (Soto-Ramírez et al. 2007) Sánchez-Porro et al. 2009

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6084.20230509.8.1
title: Kushneria aurantia Sánchez-Porro et al. 2009

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6085.20230509.8.1
title: Kushneria sinocarnis Zou and Wang 2010

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6086.20230509.8.1
title: Aidingimonas halophila Wang et al. 2009

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6087.20230509.8.1
title: Aidingimonas halophila Wang et al. 2009

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6088.20230509.8.1
title: Halothiobacillus neapolitanus (Parker 1957) Kelly and Wood 2000 emend. Boden 2017

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.6084/m9.figshare.27053038.v1
title: Supplementary Material for: Lysinuric Protein Intolerance: not only a disorder for pediatric nephrologists. Case report.

description: Introduction. Lysinuric Protein Intolerance (LPI) is a multisystemic inborn error of metabolism with a variable clinical expressivity, that usually begins in childhood with growth failure and gastroenterological/neurological problems related to the altered urea cycle and later complications involving the renal, pulmonary and immuno-hematological systems. 
Case report: We present the case of a 40-year-old woman suffering from chronic kidney disease in the context of a LPI, whose diagnosis was challenging because the signs of the disease were always blurred and the patient never manifested critical episodes typical of this multisystemic disease. In addition to renal disease, splenomegaly, thrombocytopenia, elevated lactate dehydrogenase (LDH), hyperferritinemia and hypertriglyceridemia were also present. A thorough investigation of the patient’s food preferences revealed her spontaneous aversion to protein-containing foods and excessive drowsiness during the occurrence of infectious episodes or on the rare occasions of excessive protein intake, although without ever coming to medical attention. These nuanced signs led us to suspect an impairment of the urea cycle and ultimately allowed us to narrow down the diagnosis to LPI through biochemical and genetic investigations. 
Conclusion. Nephrologists should consider LPI in the differential diagnosis, whenever a patient presents with mixed proteinuria, tubular dysfunction and/or chronic kidney failure of unknown origin. In these circumstances, we suggest looking for other signs such as growth failure, signs and symptoms ascribed to urea-cycle impairment, pulmonary involvement, hepatosplenomegaly and laboratory alterations such as pancytopenia, hyperferritinemia, lipid abnormalities, elevated LDH.
DOI: 10.13145/bacdive6089.20230509.8.1
title: Halothiobacillus neapolitanus (Parker 1957) Kelly and Wood 2000 emend. Boden 2017

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6090.20230509.8.1
title: Halothiobacillus neapolitanus (Parker 1957) Kelly and Wood 2000 emend. Boden 2017

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6091.20230509.8.1
title: Guyparkeria halophila (Wood and Kelly 1995) Boden 2017

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6092.20230509.8.1
title: Guyparkeria hydrothermalis (Durand et al. 1997) Boden 2017

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6093.20230509.8.1
title: Halothiobacillus kellyi Sievert et al. 2000

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6094.20230509.8.1
title: Halothiobacillus sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6095.20230509.8.1
title: Halothiobacillus sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6096.20230509.8.1
title: Thioalkalibacter halophilus Banciu et al. 2009

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6097.20230509.8.1
title: Thiofaba tepidiphila Mori and Suzuki 2008

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6098.20230509.8.1
title: Helicobacter cinaedi (Totten et al. 1988) Vandamme et al. 1991

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6099.20230509.8.1
title: Helicobacter pylori (Marshall et al. 1985) Goodwin et al. 1989

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6101.20230509.8.1
title: Helicobacter pylori (Marshall et al. 1985) Goodwin et al. 1989

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6102.20230509.8.1
title: Helicobacter pylori (Marshall et al. 1985) Goodwin et al. 1989

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.11073674
title: Global gridded scenarios of residential cooling energy demand to 2050

description: # ggACene (global gridded Air Conditioning energy) projections

## Output AC and AC electricity gridded data

This repository hosts output data for SSPs126, 245, 370 and 585 on the estimated and future projected ownership of residential air conditioning (% of households), the related energy consumption (TWh/yr.), and the underlying population counts (useful to quantify the per-capita average consumption or the headcount of people affected by the cooling gap).

### Input data and analysis replication

The repository also hosts input data to replicate the data generating process. A twin Github repository hosts code (https://github.com/giacfalk/ggACene) to run the model generating the ggACene (global gridded Air Conditioning energy) projections dataset.

## InstructionsTo reproduce the model and generate the dataset from scratch, please refer to the following steps:- Download input data "replication_package_input_data.7z" by cloning the repository- Decompress the folder using 7-Zip (https://www.7-zip.org/download.html)- Open RStudio and adjust the path folder in the sourcer.R script- Run the sourcer.R script to train the ML model, make projections, and represent result files

### ReferencesFalchetta, G., De Cian, E., Pavanello, F., & Wing, I. S. Inequalities in global residential cooling energy use to 2050. Forthcoming at Nature Communications
DOI: 10.5281/zenodo.13740681
title: Global gridded scenarios of residential cooling energy demand to 2050

description: # ggACene (global gridded Air Conditioning energy) projections

### Output AC and AC electricity gridded data

This repository hosts output data for SSPs126, 245, 370 and 585 on the estimated and future projected ownership of residential air conditioning (% of households), the related energy consumption (TWh/yr.), and the underlying population counts (useful to quantify the per-capita average consumption or the headcount of people affected by the cooling gap). These data are contained in the multi-layer .nc (NCDF) files, which can be opened and processed in any GIS software/library, or visualised in softwares such as Panoply.

### Input data and analysis replication

The repository also hosts input data to replicate the entire data generating process. A twin Github repository hosts code (https://github.com/giacfalk/ggACene) to run the model generating the ggACene (global gridded Air Conditioning energy) projections dataset.

## InstructionsTo reproduce the model and generate the dataset from scratch, please refer to the following steps:- Download input data "replication_package_input_data.7z" by cloning the repository- Decompress the folder using 7-Zip (https://www.7-zip.org/download.html)- Open RStudio and adjust the path folder in the sourcer.R script- Run the sourcer.R script to train the ML model, make projections, and represent result files

### Figures replication package

Finally, the source_code_data_replication_figures.zip archive contains an R script and processed input data to replicate all the figures contained in the manuscript.

### ReferenceFalchetta, G., De Cian, E., Pavanello, F., & Wing, I. S. Inequalities in global residential cooling energy use to 2050. Nature Communications. https://www.nature.com/articles/s41467-024-52028-8
DOI: 10.5281/zenodo.7845126
title: Global gridded scenarios of residential cooling energy demand to 2050

description: # ggACene (global gridded Air Conditioning energy) projections This data repository hosts output data for SSPs126, 245, 370 and 585 on the estimated and future projected ownership of residential air conditioning, its energy consumption, and the underlying population (useful to quantify the per-capita average consumption or the headcount of people affected by the cooling gap). The repository also hosts input data to replicate the data generating process. A twin Github repository hosts code (https://github.com/giacfalk/ggACene) to run the model generating the ggACene (global gridded Air Conditioning energy) projections dataset. ## Running the model<br> To reproduce the model and generate the dataset from scratch, please refer to the following steps:<br> - Download input data by cloning the repository<br> - Adjust the path folder in the sourcer.R script<br> - Run the sourcer.R script to train the ML model and make projections ## References<br> Falchetta, G., De Cian, E., Pavanello, F., & Wing, I. S. Inequalities in global residential cooling energy use to 2050 *Under review*
DOI: 10.5281/zenodo.8386094
title: Global gridded scenarios of residential cooling energy demand to 2050

description: # ggACene (global gridded Air Conditioning energy) projections

## Output AC and AC electricity gridded data

This repository hosts output data for SSPs126, 245, 370 and 585 on the estimated and future projected ownership of residential air conditioning, its energy consumption, and the underlying population (useful to quantify the per-capita average consumption or the headcount of people affected by the cooling gap).

### Input data and analysis replication

The repository also hosts input data to replicate the data generating process. A twin Github repository hosts code (https://github.com/giacfalk/ggACene) to run the model generating the ggACene (global gridded Air Conditioning energy) projections dataset.

## InstructionsTo reproduce the model and generate the dataset from scratch, please refer to the following steps:- Download input data "replication_package_input_data.7z" by cloning the repository- Decompress the folder using 7-Zip (https://www.7-zip.org/download.html)- Open RStudio and adjust the path folder in the sourcer.R script- Run the sourcer.R script to train the ML model, make projections, and represent result files

### ReferencesFalchetta, G., De Cian, E., Pavanello, F., & Wing, I. S. Inequalities in global residential cooling energy use to 2050. Forthcoming at Nature Communications
DOI: 10.5281/zenodo.10726561
title: Global gridded scenarios of residential cooling energy demand to 2050

description: # ggACene (global gridded Air Conditioning energy) projections

## Output AC and AC electricity gridded data

This repository hosts output data for SSPs126, 245, 370 and 585 on the estimated and future projected ownership of residential air conditioning, its energy consumption, and the underlying population (useful to quantify the per-capita average consumption or the headcount of people affected by the cooling gap).

### Input data and analysis replication

The repository also hosts input data to replicate the data generating process. A twin Github repository hosts code (https://github.com/giacfalk/ggACene) to run the model generating the ggACene (global gridded Air Conditioning energy) projections dataset.

## InstructionsTo reproduce the model and generate the dataset from scratch, please refer to the following steps:- Download input data "replication_package_input_data.7z" by cloning the repository- Decompress the folder using 7-Zip (https://www.7-zip.org/download.html)- Open RStudio and adjust the path folder in the sourcer.R script- Run the sourcer.R script to train the ML model, make projections, and represent result files

### ReferencesFalchetta, G., De Cian, E., Pavanello, F., & Wing, I. S. Inequalities in global residential cooling energy use to 2050. Forthcoming at Nature Communications
DOI: 10.5281/zenodo.12541994
title: Global gridded scenarios of residential cooling energy demand to 2050

description: # ggACene (global gridded Air Conditioning energy) projections

## Output AC and AC electricity gridded data

This repository hosts output data for SSPs126, 245, 370 and 585 on the estimated and future projected ownership of residential air conditioning (% of households), the related energy consumption (TWh/yr.), and the underlying population counts (useful to quantify the per-capita average consumption or the headcount of people affected by the cooling gap).

### Input data and analysis replication

The repository also hosts input data to replicate the data generating process. A twin Github repository hosts code (https://github.com/giacfalk/ggACene) to run the model generating the ggACene (global gridded Air Conditioning energy) projections dataset.

## InstructionsTo reproduce the model and generate the dataset from scratch, please refer to the following steps:- Download input data "replication_package_input_data.7z" by cloning the repository- Decompress the folder using 7-Zip (https://www.7-zip.org/download.html)- Open RStudio and adjust the path folder in the sourcer.R script- Run the sourcer.R script to train the ML model, make projections, and represent result files

### ReferencesFalchetta, G., De Cian, E., Pavanello, F., & Wing, I. S. Inequalities in global residential cooling energy use to 2050. Forthcoming at Nature Communications
DOI: 10.5281/zenodo.12697821
title: Global gridded scenarios of residential cooling energy demand to 2050

description: # ggACene (global gridded Air Conditioning energy) projections

### Output AC and AC electricity gridded data

This repository hosts output data for SSPs126, 245, 370 and 585 on the estimated and future projected ownership of residential air conditioning (% of households), the related energy consumption (TWh/yr.), and the underlying population counts (useful to quantify the per-capita average consumption or the headcount of people affected by the cooling gap). These data are contained in the multi-layer .nc (NCDF) files, which can be opened and processed in any GIS software/library, or visualised in softwares such as Panoply.

### Input data and analysis replication

The repository also hosts input data to replicate the entire data generating process. A twin Github repository hosts code (https://github.com/giacfalk/ggACene) to run the model generating the ggACene (global gridded Air Conditioning energy) projections dataset.

## InstructionsTo reproduce the model and generate the dataset from scratch, please refer to the following steps:- Download input data "replication_package_input_data.7z" by cloning the repository- Decompress the folder using 7-Zip (https://www.7-zip.org/download.html)- Open RStudio and adjust the path folder in the sourcer.R script- Run the sourcer.R script to train the ML model, make projections, and represent result files

### Figures replication package

Finally, the source_code_data_replication_figures.zip archive contains an R script and processed input data to replicate all the figures contained in the manuscript.

### ReferenceFalchetta, G., De Cian, E., Pavanello, F., & Wing, I. S. Inequalities in global residential cooling energy use to 2050. Nature Communications
DOI: 10.13145/bacdive6103.20230509.8.1
title: Helicobacter fennelliae (Totten et al. 1988) Vandamme et al. 1991

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6104.20230509.8.1
title: Helicobacter muridarum Lee et al. 1992

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6105.20230509.8.1
title: Helicobacter hepaticus Fox et al. 1994

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6107.20230509.8.1
title: Helicobacter marmotae Fox et al. 2006

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6108.20230509.8.1
title: Helicobacter mastomyrinus Shen et al. 2006

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6109.20230509.8.1
title: Helicobacter suis Baele et al. 2008

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6110.20230509.8.1
title: Helicobacter heilmannii Smet et al. 2012

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.6084/m9.figshare.27052702
title: supplementary.zip

description: This research explores the impact of thefoveal load on preview in Chinese reading, with a particular focus on the discrepancies observed in prior studies that employed single- or two-character words as parafoveal stimuli. Two experiments were conducted, utilizing single-character and two-character words as parafoveal stimuli, while manipulating foveal word frequency (high, low) and three preview types (identical, similar pseudocharacter, dissimilar pseudocharacter).<br>
DOI: 10.6084/m9.figshare.27052702.v1
title: supplementary.zip

description: This research explores the impact of thefoveal load on preview in Chinese reading, with a particular focus on the discrepancies observed in prior studies that employed single- or two-character words as parafoveal stimuli. Two experiments were conducted, utilizing single-character and two-character words as parafoveal stimuli, while manipulating foveal word frequency (high, low) and three preview types (identical, similar pseudocharacter, dissimilar pseudocharacter).<br>
DOI: 10.13145/bacdive6111.20230509.8.1
title: Helicobacter heilmannii Smet et al. 2012

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6112.20230509.8.1
title: Sulfuricurvum kujiense Kodama and Watanabe 2004

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6113.20230509.8.1
title: Sulfurimonas denitrificans (Timmer-ten Hoor 1975) Takai et al. 2006

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6114.20230509.8.1
title: Sulfurimonas autotrophica Inagaki et al. 2003

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6115.20230509.8.1
title: Sulfurimonas paralvinellae Takai et al. 2006

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6116.20230509.8.1
title: Wolinella succinogenes (Wolin et al. 1961) Tanner et al. 1981

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6117.20230509.8.1
title: Sulfurovum lithotrophicum Inagaki et al. 2004

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.