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18,658 results for “impacts”
Linked collectors and determiners for: Tropical epiphyte diversity under human impact ? Comparing primary forests, secondary forests, and forest fragments in Ecuador - Otonga.
Natural history specimen data linked to collectors and determiners held within, "Tropical epiphyte diversity under human impact ? Comparing primary forests, secondary forests, and forest fragments in Ecuador - Otonga". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/08a79618-374c-4014-9e71-3194ef3cf69a">https://bionomia.net/dataset/08a79618-374c-4014-9e71-3194ef3cf69a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/08a79618-374c-4014-9e71-3194ef3cf69a">https://gbif.org/dataset/08a79618-374c-4014-9e71-3194ef3cf69a</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Mammals in MZNA-VERT: project Human impacts in rivers of Navarra.
Natural history specimen data linked to collectors and determiners held within, "Mammals in MZNA-VERT: project Human impacts in rivers of Navarra". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/d436cc89-f949-436a-a4c9-4b12552f760d">https://bionomia.net/dataset/d436cc89-f949-436a-a4c9-4b12552f760d</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/d436cc89-f949-436a-a4c9-4b12552f760d">https://gbif.org/dataset/d436cc89-f949-436a-a4c9-4b12552f760d</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Tropical epiphyte diversity under human impact ? Comparing primary forests, secondary forests, and forest fragments in Ecuador - Bilsa.
Natural history specimen data linked to collectors and determiners held within, "Tropical epiphyte diversity under human impact ? Comparing primary forests, secondary forests, and forest fragments in Ecuador - Bilsa". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/42962fd5-34ee-4666-abdb-04e8ba4d23b0">https://bionomia.net/dataset/42962fd5-34ee-4666-abdb-04e8ba4d23b0</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/42962fd5-34ee-4666-abdb-04e8ba4d23b0">https://gbif.org/dataset/42962fd5-34ee-4666-abdb-04e8ba4d23b0</a>. Formatted as a Frictionless Data package.
Analyzing the Impact of Copying-and-Pasting Vulnerable Solidity Code Snippets from Question-and-Answer Websites
<p>This data comprises all input and output, including intermediate results for the evaluation of the tool cpg-contract-checker(CCC) and the crawled data and results for the study published under the name "Analyzing the Impact of Copying-and-Pasting Vulnerable Solidity Code Snippets from Question-and-Answer Websites".<br>We conducted a study on the impact of vulnerable code reuse from Q&A websites during the development of smart contracts and provided tools uniquely fit to detect vulnerable code patterns in complete and incomplete Smart Contract code. The paper proposes a pattern-based vulnerability detection tool that is able to analyze code snippets (i.e., incomplete code) as well as full smart contracts based on the concept of code property graphs. We also propose a methodology that leverages fuzzy hashing to quickly detect code clones of vulnerable snippets among deployed smart contracts. Our results show that our vulnerability search, as well as our code clone detection, are comparable to state-of-the-art while being applicable to code snippets. The tools are used to realize a study pipeline for which the dataset and (intermediate) results are contained in this archive.</p>
The Dynamics of Self-Disclosure on Social Media: Analyzing the Impact of Benefits, Concerns, and Experiences
<p><span>In the digital age, social media platforms have become integral to daily communication, providing users with unprecedented opportunities to share personal information and connect with others. This phenomenon, known as self-disclosure, involves the voluntary sharing of personal information, thoughts, and feelings with others. This study investigates the factors influencing self-disclosure behavior on social media, employing Social Cognitive Theory (SCT) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) as theoretical frameworks</span>.</p>
Socio-economic impact of digitization survey
<p><span>Database containing the results of the survey: "The social impact of internet-based content for young people," posted on the Google Forms platform in October 2023 available to students for the next six months. Respondents were students studying in Poland, Montentegro. The data used is the material for the publication for IEEE journal.</span></p> <p>This dataset is an affect of research conducted as a part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (Project ID: HORIZON MSCA-SE 101086381). </p>
Impact of prenatal THC exposure on mouse brain development; a lifespan approach with MRI
<p>Prenatal cannabis exposure has been demonstrated to impact neurodevelopment in offspring at different ages. To date, to our knowledge, no study has longitudinally examined the effects from embryos to adulthood. Here we collected and analyzed data to explore how prenatal exposure to delta-9-tetrahydrocannabinol (5 mg/kg subcutaneous injections, gestational dat [GD] 3-10) in mice impacts trajectories of brain development with structural magnetic resonance imaging. We supplement these findings with behavioural analyses and electron microscopy as described below.</p> <p>In the first cohort (embryos) embryos were extracted on GD 17 and scanned with MRI postnatally, as described in the methods of the accompanying paper. Electron microscopy was used to investigate dark neural and glial cells, apoptotic cells, and dividing cells in the hippocampus. In the second cohort (neonates) pups were born and scanned postnatally with manganese enhanced MRI on postnatal day (PND) 3, 5, 7, and 10. Separation-induced ultrasonic vocalizations were acquired on PND 12 and pups were perfused on PND 13. EM analyses were repeated in the neonatal hippocampi. In the third cohort (adults) pups were scanned on PND 25, 35, 60, and 90. Behavioral assessments for anxiety-like behavior with open-field test and sensorimotor gating with prepulse inhibition were performed on PND 35 and 37 respectively. </p> <p>Findings showed altered prenatal body volumes and weight-trajectories, altered brain volumes (especially sustained in females until adulthood), and indications of changes to behavior, including anxiety-like phenotypes in neonates and adolescents. Evidence from electron microscopy suggests increased cell division in the embryo hippocampus. Together these data suggest a profound and sustained impact of early gestation prenatal THC exposure on brain development. For further details on the methods, approach, and results, please see the forthcoming publication.</p> <p>In this dataset you will find the following data:</p> <p>Pregnancy/dam-level outcomes can be found in maternal_outcomes.zip</p> <ul> <li><a href="../api/records/13820978/draft/files/zenodo_pregnancy_README.txt/content" target="_blank" rel="noopener noreferrer">zenodo_pregnancy_README.txt</a>: includes description of the data and fields available in each csv.</li> <li>dam_weights.csv: A spreadsheet including the information related to each dam pooled across the studies</li> <li>nest_quality.csv: A spreadsheet including the manually-rated nest quality from a pilot and the full experiment</li> <li>master_maternal_observations_old_thc.csv: A spreadsheet including data for time spent on and off nest extracted automatically and manually from Ethovision</li> </ul> <p>Embryo outcomes:</p> <ul> <li>zenodo_embryos_README.txt: includes description of the data and fields available in each csv.</li> <li>demographics_for_analysis.csv: A spreadsheet with relevant information for each embryo sample.</li> <li>raw_embryo_mincs.zip: includes 84 embryo scans, full body</li> <li>embryo_heads.zip: includes 57 embryo scans that all passed qc, head only niftis </li> <li>squish_qc.csv: QC of whether the embryos were squished or not</li> <li>em_embryo_hc_mm2csv.csv: cells per mm^2 from electron microscopy</li> </ul> <p>Neonate outcomes:</p> <ul> <li>zenodo_neonates_README.txt: includes description of data and fields available in each csv</li> <li>demographics.csv: A spreadsheet with the demographic information for each pup and timepoint in the study</li> <li>raw_neonate_niftis.zip: 172 scans from neonates in nifti format</li> <li>agreement_qc.csv: quality control file with assessments of raw images</li> <li>milestones_999_as_NA.csv: Record of which milestones were tested and whether they were obtained</li> <li>master_usv.csv: Spreadsheet including data for ultrasonic vocalizations from all tested pups</li> <li>neo_cell_counts_mm2.csv: cells per mm^2 from electron microscopy for the neonates</li> </ul> <p>Adult outcomes: </p> <ul> <li>zenodo_adult_README.txt: includes description of the data and fields available in each csv.</li> <li>demographics.csv: A spreadsheet with the demographic information for each mouse and timepoint in the study</li> <li>adult_raw_niftis.zip: The raw data (before preprocessing) in nifti format</li> <li>master_qc.csv: Quality control assessment of the raw images</li> <li>master_oft.csv: Values for open field test extracted from Ethovision</li> <li>avg_trials_ppi.csv: Data from prepulse inhibition trials, average startle of 100 ms following pulse</li> <li>max_trials_ppi.csv Dat afrom prepulse inhibition trials, maximum startle of 100 ms following pulse</li> </ul>
Research integrity practices and environmental impact of research: Questionnaire of the survey conducted at two French institutions
<p>This dataset is a questionnaire designed to evaluate researchers' understanding, application, and perception of responsible research principles, and to identify strengths and weaknesses in their implementation.<br>It contains about thirty questions and covers various and sometimes complex topics: responsible and inclusive research practices, public trust in science, climate crisis, reduction of GHG emissions caused by research activities, research integrity, researchers' engagement in the public sphere.</p> <p>It is divided into 6 sections:<br>- Relations between science and society <br>- Conducting research in a changing world <br>- Ethics and research integrity <br>- Engaged research <br>- Science communication </p> <p>To enable comparative analysis, it incorporates questions from other surveys which are cited as references.</p>
Usage and Impact Vocabularies Peer Review Dataset
<p>This dataset reflects responses received via the Qualtrics data collection instrument provided to usage and impact vocabulary stakeholders to solicit peer review on a draft version of the glossary and crosswalk spreadsheet developed for the "EAGER: Secure Research Impact Metric Data Exchange: Data Supply Chain" project funded by The National Science Foundation (Award # 2335827).</p>
THE IMPACT OF PAEDIATRIC EMERGENCY MANAGEMENT SKILLS ON PATIENT OUTCOMES IN ZARIA
<p><span>Paediatric emergencies represent a critical challenge in Nigeria, where approximately 2,300 children under the age of five die daily, predominantly from preventable and treatable conditions such as pneumonia, malaria, and diarrheal diseases. Mortality rates are disproportionately higher in rural areas, where primary health care (PHC) centers often serve as the only point of access to medical services. The effectiveness of these centers is largely dependent on the emergency management skills of their healthcare workers. Despite their importance, there has been limited research on how the skills of PHC workers in managing paediatric emergencies impact patient outcomes.</span></p> <p><span>This study aimed to assess the proficiency of healthcare workers in primary healthcare centers in Zaria in managing common paediatric emergencies. A cross-sectional descriptive study was conducted among 139 health workers selected through a multi-stage sampling technique in Sabon Gari and Zaria Local Government Areas. Data collection was carried out using a pre-tested semi-structured self-administered questionnaire. The data were analyzed using SPSS version 21, and associations were tested using the chi-square test, with results presented in tables and charts.</span></p> <p><span>The findings revealed a significant deficiency in the emergency management skills of healthcare workers. A majority of respondents demonstrated inadequate skills in handling paediatric emergencies, with 66 (48.5%) exhibiting very poor competency in the management of common paediatric emergencies, and 32 (23.5%) displaying poor competency. Only a small fraction, 4 (2.9%) of respondents, demonstrated excellent skills in emergency management. Similarly, 46.7% of the respondents had very poor skills in the treatment of common paediatric emergencies, while only 3.0% exhibited excellent treatment skills. A statistically significant relationship was observed between the level of academic qualification and emergency management skills (p < 0.05).</span></p> <p><span>The results underscore the critical need to enhance the skill levels of healthcare workers in PHCs through continuous professional development. This could be achieved through collaborative efforts between the Department of Paediatrics at Ahmadu Bello University Teaching Hospital and the Primary Health Care Departments of Zaria and Sabon Gari local governments, focusing on regular training and workshops. Improving the skills of healthcare workers in managing paediatric emergencies is essential for reducing child mortality and improving health outcomes in the region.</span></p>
IMPACT World+ / a globally regionalized method for life cycle impact assessment
<p><strong>IMPACT World+</strong> is a life cycle impact assessment method which characterizes thousands of substances spanning across various compartments and sub-compartments of the environment. It differentiates 19 impact categories at midpoint level and 34 impact categories at damage level. For more information on IW+, refer to our <a href="https://www.impactworldplus.org/">website</a> and <a href="https://doi.org/10.1007/s11367-019-01583-0">scientific article</a>. For information on the updates of IMPACT World+, you can register to the <a href="http://eepurl.com/dEeeJL">newsletter</a> of CIRAIG.</p> <p>The v2.1 update is the biggest update of the IMPACT World+ method in many years as it introduces new impact categories and updates many models with the latest available research.</p> <p>IMPACT World+ comes in three interpretation levels: <em><strong>midpoint</strong></em>, <em><strong>expert</strong></em> and <em><strong>footprint</strong></em>. You can find explanations for these three interpretation levels <a href="https://www.impactworldplus.org/version-2-0-1/">here</a>.</p> <p>The <em><strong>expert</strong></em> and <em><strong>midpoint</strong></em> versions of IMPACT World+ also come with two different implementations regarding how to account for <strong>biogenic carbon</strong>. One with the traditional biogenic <em>carbon neutrality approach</em> (e.g., where biogenic carbon dioxide is set at 0 and biogenic methane is set at 27kgCO2eq for GWP100) and one including the uptake of biogenic carbon dioxide, where the release of biogenic carbon is therefore set at the same CFs as fossil carbon, but the uptake is with a negative sign, i.e., a <em>-1/+1 approach</em> for biogenic carbon (look for the files marked “(incl. CO2 uptake)”).</p> <p>While we provide the -<em>/+1 approach</em>, we must make it clear to the users that this approach is heavily dependent on the quality of the inventory you are using, and that there are still <strong>issues </strong>currently with the LCI databases (even in ecoinvent 3.10). Furthermore, if you are using this approach, you either <strong>MUST </strong>adopt a <em>cradle-to-grave </em>approach to both account for the uptake and release of biogenic carbon (otherwise you will only account for the uptake of the carbon and have skewed results) or if you adopt a <em>cradle-to-gate</em> approach because you need to provide results to someone downstream of your supply chain you <strong>MUST </strong>communicate with that downstream user to tell them that they should account for the release of biogenic carbon in a <em>-1/+1 approach</em> also, otherwise, you and your downstream user will <strong>double count the benefits</strong> of using biogenic products, which is incorrect. This is especially true is the case of food products where the carbon emissions post consumption are typically not included in the inventories, which could result in a substantial under estimation of the impacts of this product over its life cycle.</p> <h3>Description of the files</h3> <p>- The dev file is a file useful for developers and maintainers of databases/datasets who wish to link IW+ 2.1 to their databases/datasets. It regroups all existing characterization factors of the IW+ LCIA method in an Excel format, using the terminology of IW+.</p> <p>- The "ecoinvent" files are Excel files matching with "pure" ecoinvent and its flow name terminology (as in unaltered by various software) in an Excel table. This is useful if you are using ecoinvent outside of LCA software.</p> <p>- The exiobase file links IW+ to the <a href="https://doi.org/10.5281/zenodo.5589597">Exiobase GMRIO database</a>. Once the file is read through pandas (pandas.read_excel()), the resulting matrix can directly be multiplied to the environmental extensions of exiobase (S, F or F_Y if using the pymrio package).</p> <p>- The openLCA file can be directly imported in the openLCA software as a JSON-LD file.</p> <p>- The SimaPro file can be directly imported in the SimaPro software as a CSV file.</p> <p>- The brightway2 files are ecoinvent-version dependent, so you need to select the correct file to work with the correct version of ecoinvent. Else, some of the ecoinvent flows which name did change in between versions of ecoinvent would not be characterized, leading to underestimated results. To import a file, you need to pass through brightway2 itself (it cannot be done through the activity-browser for now). The function to import a .bw2package file is bw2.BW2Package.import_file().</p> <p>- Finally, the source file regroups all the native information used by IW+ to derive the characterization factors. This file is primarily useful for the IW+ internal team. It is provided for transparency, as well as for curious users or users who wish to generate all these files themselves through the <a href="https://github.com/CIRAIG/IWP_Reborn">open-access code of IW+</a>.</p> <h3>New indicators</h3> <p>- <em>Plastic physical effect on biota</em></p> <p>This new indicator measures the effect of plastic resins emitted in the water environments (both freshwater and marine) on biota, in PDF.m2.yr. It also comes with a midpoint indicator in CTUe. This indicator is the result of the work of the <a href="https://marilca.org/characterization-factors/">MariLCA working group</a>.</p> <p>- <em>Fisheries impact</em></p> <p>This new indicator measures the impact on biodiversity of fisheries activities. It is only assessed at the ecosystem quality damage level (in PDF.m2.yr). This is based on the work of <a href="https://doi.org/10.3390/su16093870">Stanford-Clark et al.</a></p> <p>- <em>Marine ecotoxicity</em></p> <p>In the v2.1 we decided to finally integrate these two ecotoxicity indicators, at the damage level only. These are based on an old version of Usetox (v2.02). As the v3 of Usetox is on the verge of being released, all ecotoxicity and toxicity categories will be updated in the next version of IW+.</p> <p>- <em>Terrestrial ecotoxicity</em></p> <p>In the v2.1 we decided to finally integrate these two ecotoxicity indicators, at the damage level only. These are based on an old version of Usetox (v2.02). As the v3 of Usetox is on the verge of being released, all ecotoxicity and toxicity categories will be updated in the next version of IW+.</p> <p>- <em>Photochemical ozone formation</em></p> <p>For this impact category, IW+ adopts what the ReCiPe methodology recommends. In their <a href="https://doi.org/10.1007/s11367-016-1246-y">2016 update</a>, ReCiPe renamed the indicator "Photochemical oxidant formation" to "Photochemical ozone formation". In addition, they calculated the impact of this category on ecosystem quality. There are thus two corresponding impact categories at damage level: "Photochemical ozone formation, human health" and "Photochemical ozone formation, ecosystem quality"</p> <h3>Updated indicators</h3> <p>- <em>All climate change indicators</em></p> <p>IMPACT World+ v2.1 proposes the carbon neutrality approach (i.e., CO2-bio = 0) as well as the -1/+1 approach (CO2-bio uptake = -1 / CO2-bio release = +1). However, the latter is only available in the expert and midpoint versions. In the footprint version, the carbon neutrality assumption is still being used.</p> <p>Furthermore, we added CFs for temporary storage of biogenic carbon that can be used (e.g., Correction for delayed emissions, carbon dioxide, biogenic).</p> <p>- <em>Climate change, human health</em></p> <p>In the v2.0.1, we updated the GWP100 and GTP100 indicators following the recommendations of the AR6 from the IPCC2021. Now in the v2.1, we are also updating our damage indicators for climate change to follow the AR6 recommendations. Notably, the cumulative AGTP500 used in the derivation of these CFs was recalculated with updated equations (which we obtained thanks to Yue He and Thomas Gasser from the International Institute for Applied Systems Analysis - IIASA). In addition, the effect factors were also updated. Previously it was based on data from the World Health Organization from 2003, it is now based on the WHO 2014 report as well as the <a href="https://backend.orbit.dtu.dk/ws/portalfiles/portal/329521472/PhD_Thesis_Lea_Rupcic.pdf">work of L</a><a href="https://backend.orbit.dtu.dk/ws/portalfiles/portal/329521472/PhD_Thesis_Lea_Rupcic.pdf">. </a><a href="https://backend.orbit.dtu.dk/ws/portalfiles/portal/329521472/PhD_Thesis_Lea_Rupcic.pdf">Rupcic</a>.</p> <p>- <em>Climate change, ecosystem quality</em></p> <p>Similarly to the human health indicator the cumulative AGTP500 were recalculated. However, the effect factor was not updated yet for this impact category.</p> <p>- <em>Particulate matter formation</em></p> <p>Those CFs were updated to the latest model from Fantke, et al. This is composed of a series of articles on updates to <a href="https://doi.org/10.1021/acs.est.7b02589">fate</a> and <a href="https://doi.org/10.1021/acs.est.9b01800">effect</a> factors</p> <p>This model now provides regionalized characterization factors per town of more than 100,000 inhabitants. The CFs at the town-level are available in the source file, but in the dev file and in the different software versions, we only provide national/regional (e.g., RER) as well as global values, aggregated from the town-level factors.</p> <p>- <em>Water availability, human health</em></p> <p>Those CFs were updated to the latest model of L. Debarre (2024) [<em>publication in review, link will be added once published</em>]. This model includes a harmonization of methodology between the domestic and agriculture water use, updates the exposition factors using the latest Gross National Income data and updates the EF. Overall, the values of the characterization factors of this category have dramatically decreased, by a minimum of 65%.</p> <p>- <em>Water availability, terrestrial ecosystems</em></p> <p>While the original value of the characterization was not updated (e.g., 0.21 PDF.m2.yr in Netherlands), the regionalization was updated based on an estimation of depths of groundwater, based on <a href="https://doi.org/10.1126/science.abc2755">Jasechko (2021)</a>.</p> <p>- <em>Water scarcity</em></p> <p>Those CFs were updated to the latest update of the AWARE model Seitfudem (2024) [<em>publication in review, link will be added once published</em>].</p> <p>- <em>Fossil and nuclear energy use</em></p> <p>The HHV values were updated to match the updated HHVs in ecoinvent.</p> <p>- <em>Ozone layer depletion</em></p> <p>Those CFs were adapted to match the latest data from the <a href="https://ozone.unep.org/sites/default/files/2023-02/Scientific-Assessment-of-Ozone-Depletion-2022.pdf">World Meteorological Organization (2022)</a>. In addition, the time horizon has now been extended to the infinite instead of limiting it to 500 years.</p> <h3>Methodology</h3> <p>For more detail on the methodology behind each impact category, refer to our <a href="https://github.com/CIRAIG/IWP_Reborn/tree/master/Methodology">Github</a>, in the future it will be available directly on our website.</p> <h3>Corrections</h3> <p>In this section we only provide information on the major corrections that were made. For a full report of all the changes please refer to out <a href="https://github.com/CIRAIG/IWP_Reborn/tree/master/Report_changes">Github</a>.</p> <p>- There are challenges associated with using IMPACT World+ files across databases or software for which they were not specifically designed. For instance, this is why we now provide files adapted to particular ecoinvent versions in brightway2. Similarly, both SimaPro and openLCA periodically update the names of their elementary flows. When an impact assessment method has previously been imported into one of these tools, an embedded procedure in their update processes is supposed to adjust the characterization factor names in line with the new flow names, ensuring compatibility with the updated list. However, we lack detailed knowledge of this procedure, meaning we cannot guarantee that the updated versions of IW+ in these tools would align with our specific modeling choices. Likewise, the IW+ versions we provide for a given release of SimaPro or openLCA might be incompatible with previous or subsequent versions due to discrepancies in flow names and characterization factors. Consequently, users of these software should verify which flows are characterized and make adjustments if necessary.</p> <p>- Harmonization of regionalized flows</p> <p>Regionalized impact model do not operate at the same geographical granularity. In the previous version, some flows were characterized in one impact category but not in the other. For instance, the flow "Water, lake, US-TRE" was characterized for the "water scarcity" indicator but not for "Water availability, human health". All regionalized flows are now characterized for all the impact categories they affect. This is also true for the newest regionalized impact category (Particulate matter formation) where SO<sub>2</sub> for example is regionalized at a much more granular level than in the freshwater acidification impact category.</p> <p>- Fossil and nuclear energy use</p> <p>For the SimaPro version of the v2.0.1, some flows that only exist in SimaPro were not characterized, such as "Oil, crude, 43.4 MJ per kg". Now they are properly characterized using the energy content value specified in the name. Results obtained with SimaPro will thus differ from results obtained with brightway2 and openLCA, since the latter do not use such flows and only use flow such as "Oil, crude".</p> <p>- Thermally polluted water</p> <p>In the v2.0.1, the flows "Water, turbine use, unspecified natural origin" were not linked to the correct proxy, which meant they did not impact the Thermally polluted water category, which underestimated the impact of this category.</p> <p>- The problem of "Nitrogen"</p> <p>"Nitrogen" can mean two different things. It can literally mean the "N" element, but it can also mean the "N2" molecule. The issue is that it is not clear in the LCI databases, which meaning does "Nitrogen" have. Previously, our understanding was that "Nitrogen" meant "N" but since then, ecoinvent notably, added formulas to the elementary flows they provide and associated the formula "N2" to their "Nitrogen" flows, indicating that they understand it as "N2" and not "N". Furthermore, in SimaPro and openLCA, the associated CAS number is generally "7727-37-9" which again corresponds to "N2". Thus, we now consider that “Nitrogen” represents dinitrogen, and thus does not impact the "Marine eutrophication" impact category anymore. We also corrected a previous mistake: N<sub>2</sub>O is not characterized anymore for this impact category.</p>
Data sets - The attitude of computer science teachers to inclusive education, Motivation to teach, Perception of the possible impact of computer science on students with mental disabilities
<p>Data sets </p> <p>The attitude of computer science teachers to inclusive education, Motivation to teach, Perception of the possible impact of computer science on students with mental disabilities. <br>In the period from February to October 2024, a survey of 112 computer science teachers in Kazakhstan (Pavlodar region) was conducted to determine attitudes to inclusive education, motivation to teach, and perception of the possible impact of computer science on students with mental disabilities.</p> <p>Questionnaire <br>https://docs.google.com/document/d/1LzukKSqW_mHMZXbMtN0ecmmU4cKJiwgf0laTWBHQSng/edit?usp=sharing</p> <p><strong>This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP14872400).</strong></p>
Data set: Modeling of Ion Agglomeration in Magnesium Electrolytes and its Impacts on Battery Performance
<p>Dataset of the continuum simulations generated and used within the paper "Modeling of Ion Agglomeration in Magnesium Electrolytes and its Impacts on Battery Performance", published in ChemSusChem (<span>2020</span><span>, </span><span>13 (14)</span><span>, 3599-3604, </span>DOI: 10.1002/cssc.202001034).</p> <p><br>The choice of electrolyte has a crucial influence on the performance of rechargeable magnesium batteries. In multivalent electrolytes an agglomeration of ions to pairs or bigger clusters may affect the transport in the<br>electrolyte and the reaction at the electrodes. In this work the formation of clusters is included in a general model for magnesium batteries. In this model, the effect of cluster formation on transport, thermodynamics and kinetics is consistently taken into account. The model is used to analyze the effect of ion clustering in magnesium tetrakis(hexafluoroisopropyloxy)borate in dimethoxyethane as electrolyte. It becomes apparent that ion agglomeration is able to explain experimentally observed phenomena at high salt concentrations. </p>
Data from: A tale of two studies: detection and attribution of the impacts of invasive plants in observational surveys
1.Short-term experiments cannot characterize how long-lived, invasive shrubs influence ecological properties that can be slow to change, including native diversity and soil fertility. Observational studies are thus necessary, but often suffer from methodological issues. 2.To highlight ways of improving the design and interpretation of observational studies that assess the impacts of invasive plants, we compare two studies of nutrient cycling and earthworms along two separate gradients of invasive shrub abundance. By considering the divergent sampling strategies and statistical analyses of these two studies, and interpreting their contradictory results in the context of other studies, we also aim to better describe the impacts of the focal invader, Rhamnus cathartica. 3.In a new study of a single site in Minnesota, we observed positive correlations between buckthorn abundance and soil pH, soil nutrient pools, nutrient fluxes through leaf litterfall, earthworm abundance, and root biomass. Multiple regression models showed these relationships persisted after accounting for variability in soil texture and tree species composition. For a separate, more expansive study in Illinois, other authors reported little to no correlation between buckthorn abundance and 10 soil properties, including earthworm abundance, pH, and nutrient concentrations. However, like many other studies, their regression models only assessed predictors related to invader abundance. R2 values for models of ecosystem properties ranged from 0-0.79 (adjusted-R2) for our study in Minnesota and from <0.05-0.16 (unadjusted) for the prior study in Illinois. 4.Differences in sampling error and use of predictor variables between the two studies likely explain the contrasting results. 5.Synthesis and applications. To reduce the uncertainty of conclusions from observational studies of invasive plants, future studies must ensure that heterogeneity of soils and vegetation is adequately accounted for in the sampling strategy and statistical analyses (e.g., analysis of covariance, multiple regression). Particular attention should be given to ecosystem properties with variability that likely predates the invader (e.g., geophysical features and tree community composition). In our study, effects of buckthorn on ecosystem properties were not only robust to the inclusion of potentially confounding predictors, but also consistent with expectations based on ecological stoichiometry and mass balance of element flow.
Data from ATTRICI 1.1 - counterfactual climate for impact attribution
<p>Data as produced and presented in the publication</p> <pre><strong>ATTRICI v1.1 - counterfactual climate for impact attribution</strong></pre> <p>in Geoscientific Model Development.</p> <p>Abstract:</p> <p>Attribution in its general definition aims to quantify drivers of change in a system. According to IPCC WGII a change in a natural, human or managed system is attributed to climate change by quantifying the difference between the observed state of the system and a counterfactual baseline that characterizes the system’s behavior in the absence of climate change, where “climate change refers to any long-term trend in climate, irrespective of its cause". Impact attribution following this definition remains a challenge because the counterfactual baseline cannot be observed. Process-based and empirical impact models can fill this gap as they allow to simulate the counterfactual climate impact baseline. In those simulations, the models are forced by observed direct (human) drivers such as land use changes, changes in water or agricultural management but a counterfactual climate without long-term changes. We here present ATTRICI (ATTRIbuting Climate Impacts), an approach to construct the required counterfactual stationary climate data from observational (factual) climate data. Our method identifies the long-term shifts in the considered daily climate variables that are correlated to global mean temperature change assuming a smooth annual cycle of the associated scaling coefficients for each day of the year. The produced counterfactual climate datasets are used as forcing data within the impact attribution set-up of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). Our method preserves the internal variability of the observed data in the sense that factual and counterfactual data for a given day have the same rank in their respective statistical distributions. The associated impact model simulations allow for quantifying the contribution of climate change to observed long-term changes in impact indicators and for quantifying the contribution of the observed trend in climate to the magnitude of individual impact events. Attribution of climate impacts to anthropogenic forcing would need an additional step separating anthropogenic climate forcing from other sources of climate trends, which is not covered by our method.</p>
FOCI model output used in the study by Ivanciu et al. - Twenty-first century Southern Hemisphere impacts of ozone recovery and climate change from the stratosphere to the ocean
<p>This dataset comprises the output from simulations with the coupled climate model FOCI (Flexible Ocean and Climate Infrastructure, Matthes et al., 2020) used in the analysis presented in the study by Ivanciu et al., 2021 “Twenty-first century Southern Hemisphere impacts of ozone recovery and climate change from the stratosphere to the ocean”. Four ensembles of three simulations each were performed: FixODS (II012, II014, II016), FixGHG (II013, II015, II017), INTERACT_O3 (SW128, II010, II011) and PRESC_O3 (JH027, II037, JH039). A detailed description of the simulations can be found in the above-mentioned manuscript.</p>
Data for Quantifying the Impact of Parametric Uncertainty on Automatic Mechanism Generation for CO2 Hydrogenation on Ni(111)
<p>Data, scripts, and all generated mechanisms for the preprint and article "Quantifying the Impact of Parametric Uncertainty on Automatic Mechanism Generation for CO<sub>2</sub> Hydrogenation on Ni(111)"</p>
Larval nutrition impacts survival to adulthood, body size, and the allometric scaling of metabolic rate in adult honeybees
<p>Resting metabolic rate (RMR) is a fundamental physiological measure linked to numerous aspects of organismal function, including lifespan. Although dietary restriction in insects during larval growth/development affects adult RMR, the impact of larval diet <i>quality</i> on adult RMR has not been studied. Using <i>in vitro</i> rearing to control larval diet quality, we determined the effect of dietary protein and carbohydrate on honeybee survival-to-adulthood, time-to-eclosion, body mass/size and adult RMR. High carbohydrate larval diets increased survival-to-adulthood and time-to-eclosion compared to both low carbohydrate and high protein diets. Upon emergence, bees reared on the high protein diet were smaller and lighter than those reared on other diets, whilst those raised on the high carbohydrate diet varied more in body mass. Newly emerged adult bees' reared on the high carbohydrate diet showed a significantly steeper increase in allometric scaling of RMR compared to those reared on other diets. This suggests that diet quality influences survival-to-adulthood, time-to-eclosion, and the allometric scaling of RMR. Given that agricultural intensification and increasing urbanisation have led to a decrease in both forage availability and dietary diversity for bees, our results are critical to improving understanding of the impacts of poor developmental nutrition on bee growth/development and physiology.</p>
Data_Figure S4_Impact on Bile Acid Concentrations by Alveolar Echinococcosis and Treatment with Albendazole in Mice
<p> </p> <p>Data of Figure S4 from Impact on Bile Acid Concentrations by Alveolar Echinococcosis and Treatment with Albendazole in Mice.</p> <p>The Dataset (doi: 10.3390_metabo11070442) contains the original figures as PNG-format (10.3390_metabo11070442_FigS4.PNG). Corresponding raw data and subsequent data analysis obtained from LC-MS/MS analysis provided as a file in CSV format (31003A_179400_10.3390_metabo11070442_CGC_AE-BileAcids_4_2_1.csv). All further experiment related information provided as one meta-data-file (31003A_179400_10.3390_metabo11070442_CGC_AE-BileAcids_4_2_M_1.txt) in txt format, a file containing further related information in CSV format (31003A_179400_10.3390_metabo11070442_CGC_AE-BileAcids_4_2_2.csv), and one file containing further related information on the analysis method (31003A_179400_10.3390_metabo11070442_CGC_AE-BileAcids_4_2_3.pdf) PDF format.</p>
Data_Table 1_Impact on Bile Acid Concentrations by Alveolar Echinococcosis and Treatment with Albendazole in Mice
<p> </p> <p>Data of Table1 from Impact on Bile Acid Concentrations by Alveolar Echinococcosis and Treatment with Albendazole in Mice”</p> <p>The Dataset (doi: 10.3390_metabo11070442) contains the original figures as PNG-format (10.3390_metabo11070442_Tab1.PNG). Corresponding raw data and subsequent data analysis obtained from LC-MS/MS analysis provided as one file in CSV format (31003A_179400_10.3390_metabo11070442_CGC_AE-BileAcids_4_1_1.csv). All further experiment related information provided as one meta-data-file (31003A_179400_10.3390_metabo11070442_CGC_AE-BileAcids_4_1_M_1.txt) in txt format, one file containing further related information in CSV format (31003A_179400_10.3390_metabo11070442_CGC_AE-BileAcids_4_1_2.csv), and one file containing further related information on the analysis method (31003A_179400_10.3390_metabo11070442_CGC_AE-BileAcids_4_1_3.pdf) PDF format.</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.