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11,718 results for “life”
Edward FitzGerald Life and Letters – Analysis of writing and reading
<p>These files form part of an archive of research material relating to the Life and Letters of Edward FitzGerald. The data have been compiled by independent researchers W H (Bill) Martin and Sandra Mason; their contact details are below. The files comprise a number of searchable listings of information contained in FitzGerald’s letters. The information formed input to a book on Edward FitzGerald which is referenced below.</p> <p>This section of the archive contains a database, <em>efgliterature</em>, which analyses the letters in terms of their comments on FitzGerald’s writings and the books and other material that he read. It also shows the dating of the letters, the people to whom FitzGerald wrote, and his location at the time of writing. The letters are those contained in the collection published by A M Terhune and A B Terhune in 1980 – see reference below. The database contains all the letters published by the Terhunes, including some which have no literary references. An explanatory README text file contains a table showing the fields included in the database and giving definitions of them and of the codings used where relevant. </p> <p> </p>
Edward FitzGerald Life and Letters – Analysis of other interests and views
<p>These files form part of an archive of research material relating to the Life and Letters of Edward FitzGerald. The data have been compiled by independent researchers W H (Bill) Martin and Sandra Mason; their contact details are below. The files comprise a number of searchable listings of information contained in FitzGerald’s letters. The information formed input to a book on Edward FitzGerald which is referenced below.</p> <p>This section of the archive contains a number of databases which analyse the letters in terms of their comments on FitzGerald’s interests and activities, and his views on a variety of topics. The databases cover current affairs (<em>efgctaffairs</em>), religion (<em>efgreligion</em>), travel (<em>efgtravel</em>), leisure activities (<em>efgactivities</em>), nature and countryside (<em>efgnature</em>), food and drink (<em>efgfood</em>), and personal matters (<em>efgcharacter</em>). They also show the dating of the letters, the people to whom FitzGerald wrote, and his location at the time of writing. The letters are those contained in the collection published by A M Terhune and A B Terhune in 1980 – see reference below. An explanatory README text file contains tables showing the fields included in the databases and giving definitions of them and of the codings used where relevant. </p>
Edward FitzGerald Life and Letters – Analysis of family and friends
<p>These files form part of an archive of research material relating to the Life and Letters of Edward FitzGerald. The data have been compiled by independent researchers W H (Bill) Martin and Sandra Mason; their contact details are below. The files comprise a number of searchable listings of information contained in FitzGerald’s letters. The information formed input to a book on Edward FitzGerald which is referenced below.</p> <p>This section of the archive contains a database, <em>efgpeople</em>, which analyses the letters in terms of their comments on FitzGerald’s family and a wide range of his friends. It also shows the dating of the letters, the people to whom FitzGerald wrote, and his location at the time of writing. The letters are those contained in the collection published by A M Terhune and A B Terhune in 1980 – see reference below. The database contains all the letters published by the Terhunes, including some which have no references to family and friends. An explanatory README text file contains a table showing the fields included in the database and giving definitions of them and of the codings used where relevant. </p>
Edward FitzGerald Life and Letters – Analysis of books and other material
<p>These files form part of an archive of research material relating to the Life and Letters of Edward FitzGerald. The data have been compiled by independent researchers W H (Bill) Martin and Sandra Mason; their contact details are below. The files comprise a number of searchable listings of information about FitzGerald’s letters and other aspects of his life. The information formed input to a book on Edward FitzGerald which is referenced below.</p> <p>This section of the archive contains three databases relating to FitzGerald’s library of books and other literary papers. The first of these, <em>efgbooks</em>, lists books known to have been in his possession from catalogues of sales of his effects after his death and a listing made by John Glyde (see references below). The second database, <em>efgtrinitycatal</em>, documents the holdings of books and other material owned by FitzGerald that are currently held in the Library of Trinity College, Cambridge. The third database, <em>efgtrinitydetail</em>, provides further details of the elements in the Trinity College FitzGerald holdings that we examined in more detail. An explanatory README text file contains tables showing the fields included in the databases and giving definitions of them and of the codings used where relevant. </p>
Supporting Material for article "The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences"
<p>This data set is the Supporting Material referred to in the Supplementary Data for the article "The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences" (Drysdale, et al.) submitted for publication in April 2019.</p> <p> </p>
The terrestrial carnivorous plant Utricularia reniformis sheds light on environmental and life-form genome plasticity: Annotation, Gene Ontology and raw data
<p><strong>Description:</strong> In this work, we deeply sequenced (genome and transcriptome of different organs), assembled, and analyzed the 311-Mbp genome of the terrestrial carnivorous plant <em>U. reniformis</em> (Lentibulariaceae). This project presents great importance to the understanding of genomic, evolutive and functional aspects of<em> U. reniformis</em>, which may, with the next-generation sequencing and computational biology approaches shed light to a better understanding not only for the biology and evolution of <em>Utricularia</em> genus, but also for other genera and lineages of the Lentibulariaceae family. Here we present all the raw data generated, including annotation and gene ontology files.</p> <p><strong>External Information</strong></p> <p><a href="https://genomevolution.org/coge/GenomeInfo.pl?gid=54799">Genome Browser</a> avaliable at CoGe Portal (https://genomevolution.org/coge/GenomeInfo.pl?gid=54799)</p> <p><a href="http://https://www.ncbi.nlm.nih.gov/bioproject/290588">GenBank </a><a href="http://https://www.ncbi.nlm.nih.gov/bioproject/290588">Bioproject</a> (https://www.ncbi.nlm.nih.gov/bioproject/290588) for raw genomic and transcriptomic reads</p> <p><a href="https://bv.fapesp.br/en/auxilios/84264/genomics-and-transcriptomics-of-utricularia-reniformis-lentibulariaceae-an-evolutive-and-function/">FAPESP grant website</a> contaning the project abstract and other information.</p> <p><strong>Papers published related to <em>Utricularia reniformis</em> genome</strong></p> <pre><strong>[1]</strong> Silva SR, Diaz YC, Penha HA, Pinheiro DG, Fernandes CC, Miranda VF, MichaelTP, Varani AM. <strong>The Chloroplast Genome of Utricularia reniformis Sheds Light on the Evolution of the ndh Gene Complex of Terrestrial Carnivorous Plants from the Lentibulariaceae Family</strong>. PLoS One. 2016 Oct 20;11(10):e0165176. doi:<strong><a href="https://www.ncbi.nlm.nih.gov/pubmed/27764252">10.1371/journal.pone.0165176</a></strong>. </pre> <pre><strong>[2] </strong>Silva SR, Alvarenga DO, Aranguren Y, Penha HA, Fernandes CC, Pinheiro DG, Oliveira MT, Michael TP, Miranda VFO, Varani AM. <strong>The mitochondrial genome of the terrestrial carnivorous plant Utricularia reniformis (Lentibulariaceae): Structure, comparative analysis and evolutionary landmarks.</strong> PLoS One. 2017 Jul19;12(7):e0180484. doi: <strong><a href="https://www.ncbi.nlm.nih.gov/pubmed/28723946">10.1371/journal.pone.0180484</a></strong>.</pre> <pre><strong>[3] </strong>Silva SR, Moraes AP, Penha HA, Julião MHM, Domingues DS, Michael TP, Miranda VFO, Varani AM. <strong>The Terrestrial Carnivorous Plant Utricularia reniformis Sheds Light on Environmental and Life-Form Genome Plasticity.</strong> Int J Mol Sci. 2019 Dec 18;21(1). pii: E3. doi: <strong><a href="https://www.ncbi.nlm.nih.gov/pubmed/31861318">10.3390/ijms21010003</a></strong>.</pre> <p><strong>Acknowledgements</strong></p> <p>This work was supported by Sao Paulo Research Foundation FAPESP, Grant ID: [1325164-6]</p> <p> </p> <p><strong>---------------------------------------------------------</strong><br> <strong>FILES DESCRIPTION</strong><br> <strong>---------------------------------------------------------</strong><br> <br> ----------------<br> <strong>ANNOT-vFinal.sql: </strong>MySQL database containing all integrated annotation information of Urenif and Ugibba<br> ----------------<br> <strong>TABLE fields description</strong><br> gene_name gene name generated by EVidence Modeler + PASA<br> length gene lenght<br> status duplicate_gene_classifier status (0:singleton, 1:dispersed, 2:proximal, 3: tandem, 4:WGD)<br> product gene product <br> GOterms Blast2GO/OmicsBox GOterms<br> GO_mapping Blast2GO/OmicsBox GOterms derived from direct mapping (UniProt)<br> GO_annotation Blast2GO/OmicsBox annotated GOterms<br> GO_interpro Blast2GO/OmicsBox derived from InterProScan<br> EC Blast2GO/OmicsBox EC number<br> EC_name Blast2GO/OmicsBox enzyme name<br> NOG_annot EggNOG annotation description<br> NOG_EC EggNOG EC number<br> NOG_GO EggNOG GOterms<br> NOG_class EggNOG COG/KOG classfication<br> KEGG_Pathway EggNOG KEGG pathyways<br> KEGG_ko EggNOG KEGG ko<br> CAZy EggNOG CAZy enzymes<br> TAIR_gene Closest A. thaliana gene name (homologous) TAIR database lasted version<br> TAIR_annot Closest A. thaliana gene product (homologous) TAIR database lasted version <br> ortho MCL clustering among Vvinifera, Athaliana, and Slycopersicum (S:singleton, C: clustered, Y: shared)<br> ortho_two MCL clustering among Urenif and Ugibba (S:singleton, C: clustered, Y: shared)<br> -<br> -<br> ----------------<br> <strong>CEGs.zip </strong> 336 shared and concatenated CEGs from Urenif, U. gibba, Genlisea nigrocaulis, G. hispidula, G. aurea, G. pygmaea, and G. repens.<br> ----------------</p> <p><strong>ProcessRepeats_mod</strong> Modified version of RepeatMasker, ProcessRepeats script for detection of plant evolutionary lineages<br> ----------------</p> <p><strong>----------------------------------------------------------------------------------------------------------------------------------------------<br> <em>Utricularia gibba</em> files<br> ----------------------------------------------------------------------------------------------------------------------------------------------</strong><br> <strong>Ugibba</strong><strong>-no-masked.fa </strong> Ugibba genome excluding organellar genomes (provided by Lan et al., 2017)<br> <strong>Ugibba-softmasked.fa</strong> Ugibba genome RepeatMasker softmasked and excluding organellar genomes (provided by Lan et al., 2017)<br> <strong>Ug.collinearity </strong> MCScanX collinearity file<br> <strong>Ug-duplicates.txt</strong> MCScanX duplicate_gene_classifier short report<br> <strong>Ug.gene_type </strong> MCScanX duplicate_gene_classifier full report<br> <strong>Ug.tandem </strong> Ugibba tandem genes generated by MCScanX tool<br> <strong>Ugibba_annot.annot </strong> Blast2GO/OmicsBox annotation file (eudicotyledons filtered and Viridiplantae GOSlim) <strong>Ugibba_annot-</strong><strong>noclean</strong><strong>.</strong><strong>annot</strong><strong> </strong> Blast2GO/OmicsBox annotation file (not filtered)<br> <strong>Ugibba</strong><strong>.cDNA</strong> Ugibba cDNAs fasta file<br> <strong>Ugibba</strong><strong>.CDS </strong> Ugibba CDSs fasta file<br> <strong>Ugibba</strong><strong>-EVM.all-no-TEs-PASA-ANNOTATED.gff3</strong> Ugibba GFF3 file fully annotated (including gene products and GO terms)</p> <p><strong>Ugibba</strong><strong>-EVM.all-no-TEs-PASA.gff3</strong> Ugibba GFF3 file fully annotated (genes only)<br> <strong>Ugibba_export.txt</strong> Blast2GO/OmicsBox full exported table<br> <strong>Ugibba_fasta.fasta</strong> Blast2GO/OmicsBox Ugibba fasta proteins containg annotation (product and GO terms)<br> <strong>ugibba_frozen_cleaned-validated.box</strong> Full Blast2GO/OmicsBox file</p> <p><strong>ugibba_frozen.box</strong> Full Blast2GO/OmicsBox file (containing TEs genes annotation)</p> <p><strong>ugibba_nogs_emapper_annotations.box</strong> Full Blast2GO/OmicsBox EggNOG file (containing TEs genes annotation)</p> <p><strong>Ugibba_GAF.txt</strong> GAF file<br> <strong>Ugibba</strong><strong>.gene</strong> Ugibba gene fasta file<br> <strong>Ugibba_GOstat.txt </strong> GOstat file<br> <strong>Ugibba</strong><strong>-PASA-assemblies.fasta </strong> Ugibba PASA assemblies<br> <strong>Ugibba</strong><strong>-PASA.stats </strong> Ugibba annotation STATS<br> <strong>Ugibba</strong><strong>.</strong><strong>prot</strong><strong> </strong> Ugibba protein fasta file<br> <strong>Ugibba</strong><strong>-RepeatMasker.gff </strong> Ugibba RepeatMasker gff file<br> <strong>Ugibba</strong><strong>-RepeatMasker.gff3 </strong> Ugibba RepeatMasker gff3 file<br> <strong>Ugibba</strong><strong>-RepeatMasker.tbl </strong> Ugibba RepeatMasker results<br> <strong>Ugibba</strong><strong>-RepeatMasker-v2.gff3</strong> Ugibba RepeatMasker gff3 second version file<br> <strong>Ugibba</strong><strong>-RNAseq-assembled.fasta </strong> Ugibba RNAseq assembled transcriptome (Trinity)<br> <strong>Ugibba_TEs_DANTE_2019.fa </strong> Ugibba TEs library, detected by REPET and annotated by PASTEC and DANTE<br> <strong>Ugibba_WEGO.txt </strong> WEGO file</p> <p><strong>----------------------------------------------------------------------------------------------------------------------------------------------<br> <em>Utricularia reniformis</em> files<br> ----------------------------------------------------------------------------------------------------------------------------------------------</strong><br> <strong>Urenif</strong><strong>-no-masked.fa </strong> Urenif genome excluding organellar genomes<br> <strong>Urenif</strong><strong>-</strong><strong>softmasked</strong><strong>.fa</strong> Urenif genome RepeatMasker softmasked and excluding organellar genomes<br> <strong>Ur.collinearity </strong> MCScanX collinearity file<br> <strong>Ur-duplicates.txt </strong> MCScanX duplicate_gene_classifier short report<br> <strong>Ur.gene_type</strong> MCScanX duplicate_gene_classifier full report<br> <strong>Ur.tandem</strong> Urenif tandem genes generated by MCScanX tool<br> <strong>Urenif_annot.annot</strong> Blast2GO/OmicsBox annotation file (eudicotyledons filtered and Viridiplantae GOSlim)<br> <strong>Urenif_annot-</strong><strong>noclean</strong><strong>.</strong><strong>annot</strong> Blast2GO/OmicsBox annotation file (not filtered)<br> <strong>Urenif</strong><strong>.cDNA</strong> Urenif cDNAs fasta file<br> <strong>Urenif</strong><strong>.CDS </strong> Urenif cDNAs fasta file<br> <strong>Urenif</strong><strong>-EVM.all-no-TEs-PASA-ANNOTATED.gff3</strong> Urenif GFF3 file fully annotated (including gene products and GO terms)</p> <p><strong>Urenif</strong><strong>-EVM.all-no-TEs-PASA.gff3</strong> Urenif GFF3 file fully annotated (genes only)<br> <strong>Urenif_export.txt</strong> Blast2GO/OmicsBox full exported table<br> <strong>Urenif_fasta.fasta</strong> Blast2GO/OmicsBox Urenif fasta proteins containg annotation (product and GO terms)<br> <strong>urenif_frozen_cleaned-validated.box</strong> Full Blast2GO/OmicsBox file</p> <p><strong>urenif_frozen.box</strong> Full Blast2GO/OmicsBox file (containing TEs genes annotation)</p> <p><strong>urenif_nogs_emapper_annotations.box</strong> Full Blast2GO/OmicsBox EggNOG file (containing TEs genes annotation)<br> <strong>Urenif_GAF.txt </strong> GAF file<br> <strong>Urenif</strong><strong>.gene</strong> Urenif gene fasta file<br> <strong>Urenif_GOStat.txt </strong> GOstat file<br> <strong>Urenif</strong><strong>-PASA-assemblies.fasta</strong> Urenif PASA assemblies<br> <strong>Urenif</strong><strong>-PASA.stats </strong> Urenif annotation STATS<br> <strong>Urenif</strong><strong>.</strong><strong>prot</strong><strong> </strong> Urenif protein fasta file<br> <strong>Urenif</strong><strong>-RepeatMasker.gff </strong> Urenif RepeatMasker gff file<br> <strong>Urenif</strong><strong>-RepeatMasker.gff3 </strong> Urenif RepeatMasker gff3 file<br> <strong>Urenif</strong><strong>-RepeatMasker.tbl </strong> Urenif RepeatMasker results<br> <strong>Urenif</strong><strong>-RepeatMasker-v2.gff3 </strong> Urenif RepeatMasker gff3 second version file<br> <strong>Urenif</strong><strong>-RNAseq-assembled.fasta </strong> Urenif RNAseq assembled transcriptome (Trinity)<br> <strong>Urenif_TEs_DANTE_2019.fa </strong> Urenif TEs library, detected by REPET and annotated by PASTEC and DANTE<br> <strong>Urenif_WEGO.txt </strong> WEGO file<br> <strong>----------------------------------------------------------------------------------------------------------------------------------------------<br> ----------------------------------------------------------------------------------------------------------------------------------------------</strong></p>
Mesquita et al, 2015: Life History Data
Daniel O. Mesquita, Guarino R. Colli, Gabriel C. Costa, Taís B. Costa, Donald B. Shephard, Laurie J. Vitt, and Eric R. Pianka. 2015. Life history data of lizards of the world. Ecology 96:594. <p></p>http://dx.doi.org/10.1890/14-1453.1<p></p>
Mesquita et al, 2015: Life history data of lizards of the world (1014) DwCA
Daniel O. Mesquita, Guarino R. Colli, Gabriel C. Costa, Taís B. Costa, Donald B. Shephard, Laurie J. Vitt, and Eric R. Pianka. 2015. Life history data of lizards of the world. Ecology 96:594. <p></p>http://dx.doi.org/10.1890/14-1453.1<p></p>Daniel O. Mesquita, Guarino R. Colli, Gabriel C. Costa, Taís B. Costa, Donald B. Shephard, Laurie J. Vitt, and Eric R. Pianka. 2015. Life history data of lizards of the world. Ecology 96:594. <p></p>http://dx.doi.org/10.1890/14-1453.1
Morgan Ernest, 2003: Life history characteristics of placental non-volant mammals
S. K. Morgan Ernest. 2003. Life history characteristics of placental non-volant mammals. Ecology 84:3402.<p></p>S. K. Morgan Ernest. 2003. Life history characteristics of placental non-volant mammals. Ecology 84:3402.
Data-driven model enhancement of late-life lithium-ion batteries
<p>Suplement dataset for the paper "Data-driven model enhancement of late-life lithium-ion batteries"</p>
BeBOD estimates of mortality, years of life lost, prevalence, years lived with disability, and disability-adjusted life years for 38 causes, 2013-2021
<p><strong>Belgian National Burden of Disease Study</strong></p> <p><strong>Estimates of the burden of disease</strong></p> <p><em>Causes of death</em></p> <p>Our estimates are based on the official causes of death database compiled by <a href="https://statbel.fgov.be/en/themes/population/mortality-life-expectancy-and-causes-death/causes-death">Statbel</a>. We first map the ICD-10 codes of the underlying causes of death to the Global Burden of Disease cause list, consisting of 131 unique causes of deaths. Next, we perform a probabilistic redistribution of ill-defined deaths to specific causes, to obtain a specific cause of death for each deceased person.</p> <p><em>Years of Life Lost</em></p> <p>In addition to counting the number of deaths, we also calculate Years of Life Lost (YLLs) as a measure of premature mortality. YLLs correspond to the life expectancy at the age of death, and therefore give a higher weight to deaths occurring at younger ages. We calculate YLLs using the Global Burden of Disease reference life table, which represents the theoretical maximum number of years that people can expect to live.</p> <p><em>Prevalence</em></p> <p>Our estimates are based on the GBD cause list for morbidity by <a href="https://www.healthdata.org/">IHME</a>. We first select for each of the 38 causes, the most suitable local data source as described in the <a href="https://www.sciensano.be/en/biblio/belgian-national-burden-disease-study-guidelines-calculation-dalys-belgium-2">protocol</a>. Next, we calculate the prevalence by year, region, age, and sex, to obtain a prevalence for each of the included diseases.</p> <p><em>Years Lived with Disability</em></p> <p>In addition to calculating the number of prevalent cases, we also calculate Years Lived with Disability (YLDs) as a measure of morbidity. YLDs are calculated as the product of the number of prevalent cases with the disability weight (DW), averaged over the different health states of the disease. The DWs reflect the relative reduction in quality of life, on a scale from 0 (perfect health) to 1 (death). We calculate YLDs using the Global Burden of Disease DWs.</p> <p><em>Disability-Adjusted Life Years</em></p> <p>Disability-Adjusted Life Years (DALYs) are a measure of overall disease burden, representing the healthy life years lost due to morbidity and mortality. DALYs are calculated as the sum of YLLs and YLDs for each of the considered diseases.</p>
BeBOD estimates of mortality and years of life lost for 131 causes of death, 2004-2021
<p><strong>Belgian National Burden of Disease Study</strong></p> <p><strong>Estimates of the fatal burden of disease</strong></p> <p><em>Causes of death</em></p> <p>Our estimates are based on the official causes of death database compiled by <a href="https://statbel.fgov.be/en/themes/population/mortality-life-expectancy-and-causes-death/causes-death">Statbel</a>. We first map the ICD-10 codes of the underlying causes of death to the Global Burden of Disease cause list, consisting of 131 unique causes of deaths. Next, we perform a probabilistic redistribution of ill-defined deaths to specific causes, to obtain a specific cause of death for each deceased person.</p> <p><em>Years of Life Lost</em></p> <p>In addition to counting the number of deaths, we also calculate Years of Life Lost (YLLs) as a measure of premature mortality. YLLs correspond to the life expectancy at the age of death, and therefore give a higher weight to deaths occurring at younger ages. We calculate YLLs using the Global Burden of Disease reference life table, which represents the theoretical maximum number of years that people can expect to live.</p> <p><em>More information</em></p> <p>For additional background on BeBOD, please visit <a href="https://www.sciensano.be/en/projects/belgian-national-burden-disease-study">https://www.sciensano.be/en/projects/belgian-national-burden-disease-study</a>.</p> <p>Explore the estimates via <a href="https://burden.sciensano.be/shiny/mortality">https://burden.sciensano.be/shiny/mortality</a>.</p>
Powering the Circular Future: Climate Change and Economic Perspectives on Second-Life Batteries in the Belgian Context - Supporting Information S2 and S3
<p>The data contains the databases used to calculate the climate change impacts of second-life batteries including full Life Cycle Inventory data published in the article entitled "Powering the Circular Future: Climate Change and Economic Perspectives on Second-Life Batteries in the Belgian Context".</p> <p>The second file S3 contains the economic data and the climate change impacts of the same article.</p> <p>In version 2.0 of S2, a sensitivity analysis and more detail is added in the results.</p> <p> </p>
Survey on the social impact of the citizen science in the projects LIFE MIPP and InNat
<p>The present dataset consists in a sociological survey addressed to the volunteers involved in MIPP and InNat projects, a citizen science initiative aimed at the collection of distribution data of protected species and habitats all over Italian national territory. In particular, two different files are provided: </p> <ol> <li>the original survey (questions and answers) addressed to the volunteers in Italian</li> <li>the English translation of the questionnaire </li> </ol> <p>The survey covers different topics: socio-demographic data (section 1), opinions on the role of volunteering in a citizen science project (section 2), possible previous citizen science experience (section 3), test on the acquired skills on the monitored insect species with MIPP/InNat (section 4), opinions concerning the ecological crisis and the trust in the ability of humankind to solve environmental issues (section 5), possibility to be further contacted for additional interviews (section 6).</p> <p>A total of 364 completed questionnaires have been collected and relative results are provided here. Moreover, the above-mentioned results are thoroughly investigated and analysed in a scientific paper which also explores drivers that might keep volunteers active in a biodiversity monitoring project. Indeed, the engagement of volunteers in citizen science projects is a remarkable issue to address in order to ensure long-term sustainability, scientific relevance and public participation.</p> <p>The MIPP/InNat initiative started in 2012, with the project MIPP “Monitoring of insects with public participation” (LIFE11 NAT/IT/000252) which ended in 2017, and was then continued by the InNat project thanks to Italian National fundings. Data gathered in both projects converged in the same database. This research was supported by the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4 - Call for tender No. 3138 of 16 December 2021, rectified by Decree n.3175 of 18 December 2021 of Italian Ministry of University and Research funded by the European Union – 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research, CUP B83D21014060006, Project title “National Biodiversity Future Center” – NBFC.</p>
Dataset for "Sustainable Disposal and End-of-Life Treatment of Battery Energy Storage Systems: An Environmental and Economic Case Study"
This study investigates the environmental and economic impacts of end-of-life (EOL) treatment for a 2.8 MWh/2.5 MW battery energy storage system (BESS) based on lithium-ion batteries (LIBs). It focuses on recycling pre-treatment processes for battery systems and recycling procedures for components like cooling systems, fire extinguishing systems, inverters, and the reuse of BESS containers and substations. A life cycle assessment (LCA) was employed to evaluate key environmental impacts, including climate change, eutrophication, and resource use. The study reveals substantial environmental benefits, particularly from recovering secondary materials like aluminium and copper, with recycling pre-treatment contributing significantly to overall benefits. Additionally, the economic analysis projects profits, emphasizing the advantages of locally sourcing critical raw materials. The research highlights the need for more sustainable recycling practices and provides insights for improving environmental and economic strategies in BESS management, offering guidance for future research and policy development in battery waste processing.
PhasAGE Training School 1 -Overview of bioinformatics tools for the life sciences & Classification and evolution of non-globular proteins- LECTUREs
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
"I have been born, raised, and lived my whole life here"
<p>This dataset completes an article on the story of Einar, a Faroese man who always lived within a 500-meters radius on the island of Suðuroy, who never felt “stuck” or “immobile” in the literal sense of the word. Studies have shown that staying is a process, as much as mobility; yet while mobility studies mainly show that imagination is an incentive to move, we argue that imagination may also actively support staying. Combining sociocultural psychology with mobility studies, we propose to explore the entanglement of symbolic mobility (a form of imagination) and various forms of geographical (im)mobility. Based on ethnographic fieldwork and hours of conversation, we present the case study of Einar's life on his island. We follow the sociogenetic development of the island, and the expansion and contraction of the imaginative horizon over time. On this background, we then retrace the life of Einar and show how, within this transforming context, his imagination developed thanks to resources he could use from the mobility of technologies, ideas, and other people. Interestingly, at different bifurcation points, his symbolic mobility almost led him to move away but, at another point, helped him to refuse geographical mobility. Hence, he was always symbolically mobile while staying. We finally propose directions for generalising from this case study, and implications for cultural psychology and for mobility and migration studies.</p>
Data for: The structure of evolutionary model space for proteins across the tree of life
<p>Supporting data for "The structure of evolutionary model space for proteins across the tree of life," submitted by GE Scolaro and EL Braun. The data files correspond to three gzipped tarballs including protein multiple sequence alignments, PAML format models of protein evolution, and model fit data; see included README for details.</p>
Data for "Ecosystem size filters life-history strategies to shape community assembly in lakes"
<p>Dataset 1. List of 71 fish species collected from north temperate lakes in Wisconsin USA. Data include critical life-history data used for strategy classifications according to Winemiller and Rose (1992), principal component scores, and strategy classification according to the cluster analysis.</p> <p>Dataset 2. Species occurrence data in all study lakes along with results from the 'soft classification" according to Euclidean distance.</p> <p>Dataset 3. Limnological and fish community characteristics of study lakes including species richness, lake area, estimated lake volume, and convex hull statistics for the overall fish community and each life-history strategy type.</p>
BeBOD estimates of mortality and years of life lost, 2004-2019
<p><strong>Belgian National Burden of Disease Study</strong></p> <p><strong>Estimates of the fatal burden of disease</strong></p> <p><em>Causes of death</em></p> <p>Our estimates are based on the official causes of death database compiled by <a href="https://statbel.fgov.be/en/themes/population/mortality-life-expectancy-and-causes-death/causes-death">Statbel</a>. We first map the ICD-10 codes of the underlying causes of death to the Global Burden of Disease cause list, consisting of 130 unique causes of deaths. Next, we perform a probabilistic redistribution of ill-defined deaths to specific causes, to obtain a specific cause of death for each deceased person.</p> <p><em>Years of Life Lost</em></p> <p>In addition to counting the number of deaths, we also calculate Years of Life Lost (YLLs) as a measure of premature mortality. YLLs correspond to the life expectancy at the age of death, and therefore give a higher weight to deaths occurring at younger ages. We calculate YLLs using the Global Burden of Disease reference life table, which represents the theoretical maximum number of years that people can expect to live.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.