Dataset Card for escher-human-edit

Human Edit dataset

  Dataset Structure





  Data Instances

Each instance contains:

source_image: The original image edited_image: The edited version of the image edit_instruction: The instruction used to edit the image source_image_caption: Caption for the source image target_image_caption: Caption for the edited image Additional metadata fields

  Data Splits

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The serotonin 2C receptor (5-HT2CR)–a key regulator of diverse neurological processes–exhibits functional variability derived from editing of its pre-mRNA by site-specific adenosine deamination (A-to-I pre-mRNA editing) in five distinct sites. Here we describe a statistical technique that was developed for analysis of the dependencies among the editing states of the five sites. The statistical significance of the observed correlations was estimated by comparing editing patterns in multiple individuals. For both human and rat 5-HT2CR, the editing states of the physically proximal sites A and B were found to be strongly dependent. In contrast, the editing states of sites C and D, which are also physically close, seem not to be directly dependent but instead are linked through the dependencies on sites A and B, respectively. We observed pronounced differences between the editing patterns in humans and rats: in humans site A is the key determinant of the editing state of the other sites, whereas in rats this role belongs to site B. The structure of the dependencies among the editing sites is notably simpler in rats than it is in humans implying more complex regulation of 5-HT2CR editing and, by inference, function in the human brain. Thus, exhaustive statistical analysis of the 5-HT2CR editing patterns indicates that the editing state of sites A and B is the primary determinant of the editing states of the other three sites, and hence the overall editing pattern. Taken together, these findings allow us to propose a mechanistic model of concerted action of ADAR1 and ADAR2 in 5-HT2CR editing. Statistical approach developed here can be applied to other cases of interdependencies among modification sites in RNA and proteins.

SEED-Data-Edit

SEED-Data-Edit is a hybrid dataset for instruction-guided image editing with a total of 3.7 image editing pairs, which comprises three distinct types of data: Part-1: Large-scale high-quality editing data produced by automated pipelines (3.5M editing pairs). Part-2: Real-world scenario data collected from the internet (52K editing pairs). Part-3: High-precision multi-turn editing data annotated by humans (95K editing pairs, 21K multi-turn rounds with a maximum… See the full description on the dataset page: https://huggingface.co/datasets/AILab-CVC/SEED-Data-Edit-Part1-Unsplash.

The Gene-Editing Tools For Non-Human Primates Market report segments the industry into By Technology (CRISPR/Cas9, Transcription Activator-Like Effectror Nucleases (TALENs), Zinc Finger Nucleases (ZFNs), Others), By Application (Biomedical Research, Transgenic Model Development, Pharmaceutical Development, Gene Therapy Research), By End User (Research Institutions, and more), and Geography.

BackgroundThe strong familiality of living to extreme ages suggests that human longevity is genetically regulated. The majority of genes found thus far to be associated with longevity primarily function in lipoprotein metabolism and insulin/IGF-1 signaling. There are likely many more genetic modifiers of human longevity that remain to be discovered.Methodology/Principal FindingsHere, we first show that 18 single nucleotide polymorphisms (SNPs) in the RNA editing genes ADARB1 and ADARB2 are associated with extreme old age in a U.S. based study of centenarians, the New England Centenarian Study. We describe replications of these findings in three independently conducted centenarian studies with different genetic backgrounds (Italian, Ashkenazi Jewish and Japanese) that collectively support an association of ADARB1 and ADARB2 with longevity. Some SNPs in ADARB2 replicate consistently in the four populations and suggest a strong effect that is independent of the different genetic backgrounds and environments. To evaluate the functional association of these genes with lifespan, we demonstrate that inactivation of their orthologues adr-1 and adr-2 in C. elegans reduces median survival by 50%. We further demonstrate that inactivation of the argonaute gene, rde-1, a critical regulator of RNA interference, completely restores lifespan to normal levels in the context of adr-1 and adr-2 loss of function.Conclusions/SignificanceOur results suggest that RNA editors may be an important regulator of aging in humans and that, when evaluated in C. elegans, this pathway may interact with the RNA interference machinery to regulate lifespan.

This update to the Human Footprint (HFP) provides a measure of the direct and indirect human pressures on the environment globally in years 2000, 2005, 2010, and 2013. Per the orinal Human Footprint, this dataset is derived from remotely-sensed and bottom-up survey information compiled on eight measured variables. This represents not only the most current information of its type, but also the first temporally-consistent set of Human Footprint maps. Data on human pressures were acquired or developed for: 1) built environments, 2) population density, 3) electric infrastructure, 4) crop lands, 5) pasture lands, 6) roads, 7) railways, and 8) navigable waterways. This update incorporates updated and higher resolution population, nightlights, pasture, road, and railway input datasets. The Human Footprint maps find a range of uses as proxies for human disturbance of natural systems and can provide an increased understanding of the human pressures that drive macro-ecological patterns, as well as for tracking environmental change and informing conservation science and application. HFP values range from 0 (no human impact) to 50 (heavily human impacted).

See: Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11.

This dataset can be downloaded uniquly from UN Biodiversity Lab.
Updated data is made available only to FIP pilot countires at present - rasters are clipped to other FIP data extents.

Around 38.5 percent of people interviewed in 24 European countries stated that they think climate change is caused mainly by human activities. During the same interview, 42.7 percent agreed that such change was caused about equally by natural and human processes. When it comes to specific examples, Sweden got the highest number of respondents, with more than half believing that the current climate change is being caused mainly by humans.

The human evaluation (HE) dataset created for English to German (EnDe) and English to French (EnFr) MT tasks was a subset of one of the official test sets of the IWSLT 2016 evaluation campaign. The resulting HE sets are composed of 600 segments for both EnDe and EnFr, each corresponding to around 10,000 words. Human evaluation was based on Post-Editing, i.e. the manual correction of the MT system output, which was carried out by professional translators. Nine and five primary runs submitted to the evaluation campaign were post-edited for the two tasks, respectively.

Data are publicly available through the WIT3 website wit3.fbk.eu. 600 segments for both EnDe and EnFr (10K tokens each). Respectively, 9 and 5 different automatic translations post-edited by professional translators (for Analysis of MT quality and Quality Estimation components).

The WikiPrefs dataset is a human preferences dataset for Large Language Models alignment. It was built using the EditPrefs method from historical edits of Wikipedia featured articles

A survey held on AI and journalism in January 2024 in the United Kingdom found that just ** percent of respondents would trust an online news article written by an AI journalist and edited by an AI editor. This is contrast to ** percent who said the same about content both created and edited by humans. Whilst the results suggest a lack of readiness for news content entirely generated and edited by AI, the data also highlights the general lack of trust in journalists and editors, with close to ** percent saying they would not trust human journalists or editors either.

Human post-edited test sentences for the WMT 2017 Automatic post-editing task. This consists in 2,000 English sentences belonging to the IT domain and already tokenized. Source and target segments can be downloaded from: https://lindat.mff.cuni.cz/repository/xmlui/handle/11372/LRT-2132. All data is provided by the EU project QT21 (http://www.qt21.eu/).

This dataset contains modeled temperature, ozone, and PM2.5 data for the United States over the 21st century, using two global climate model scenarios and two emissions datasets.

The Gene-Editing Tools For Non-Human Primates report features an extensive regional analysis, identifying market penetration levels across major geographic areas. It highlights regional growth trends and opportunities, allowing businesses to tailor their market entry strategies and maximize growth in specific regions.

Overview

This dataset contains 20000 pieces of text collected from Wikipedia, Gutenberg, and CNN/DailyMail. The text is cleaned by replacing symbols such as (.*?/) with a white space using automatic scripts and regex.

Data Source Distribution

1. 10,000 Wikipedia Articles: From the 20220301 dump.
2. 3,000 Gutenberg Books: Via the GutenDex API.
3. 7,000 CNN/DailyMail News Articles: From the CNN/DailyMail 3.0.0 dataset.

Why These Sources

The data was collected from these source to ensure the highest level of integrity against AI generated text. * Wikipedia: The 20220301 dataset was chosen to minimize the chance of including articles generated or heavily edited by AI. * Gutenberg: Books from this source are guaranteed to be written by real humans and span various genres and time periods. * CNN/DailyMail: These news articles were written by professional journalists and cover a variety of topics, ensuring diversity in writing style and subject matter.

Dataset Structure

The dataset consists of 5 CSV files. 1. CNN_DailyMail.csv: Contains all processed news articles. 2. Gutenberg.csv: Contains all processed books. 3. Wikipedia.csv: Contains all processed Wikipedia articles. 4. Human.csv: Combines all three datasets in order. 5. Shuffled_Human.csv: This is the randomly shuffled version of Human.csv.

Each file has 2 columns: - Title: The title of the item. - Text: The content of the item.

Uses

This dataset is suitable for a wide range of NLP tasks, including: - Training models to distinguish between human-written and AI-generated text (Human/AI classifiers). - Training LSTMs or Transformers for chatbots, summarization, or topic modeling. - Sentiment analysis, genre classification, or linguistic research.

Disclaimer

While the data was collected from such sources, the data may not be 100% pure from AI generated text. Wikipedia articles may reflect systemic biases in contributor demographics. CNN/DailyMail articles may focus on specific news topics or regions.

For details on how the dataset was created, click here to view the Kaggle notebook used.

Licensing

This dataset is published under the MIT License, allowing free use for both personal and commercial purposes. Attribution is encouraged but not required.

Post-transcriptional events play an important role in human development. The question arises as to whether Adenosine to Inosine RNA editing, catalyzed by the ADAR (Adenosine Deaminase acting on RNA) enzymes, differs in human embryogenesis and in adulthood. We tested the editing of various target genes in coding (FLNA, BLCAP, CYFIP2) and non-coding sequences at their Alu elements (BRCA1, CARD11, RBBP9, MDM4, FNACC), as well as the transcriptional levels of the ADAR1 enzymes. This analysis was performed on five fetal and adult human tissues: brain, heart, liver, kidney, and spleen, as well as on human embryonic stem cells (hESCs), which represent the blastocyst stage in early human development. Our results show substantially greater editing activity for most adult tissue samples relative to fetal ones, in six of the eight genes tested. To test the effect of reduced A-to-I RNA editing activity in early human development we used human embryonic stem cells (hESCs) as a model and tried to generate hESC clones that overexpress the ADAR1–p110 isoform. We were unable to achieve overexpression of ADAR1–p110 by either transfection or lentiviral infection, though we easily generated hESC clones that expressed the GFP transgene and overexpressed ADAR1-p110 in 293T cells and in primary human foreskin fibroblast (HFF) cells. Moreover, in contrast to the expected overexpression of ADAR1-p110 protein following its introduction into hESCs, the expression levels of this protein decreased dramatically 24–48 hr post infection. Similar results were obtained when we tried to overexpress ADAR1-p110 in pluripotent embryonal carcinoma cells. This suggests that ADAR1 protein is substantially regulated in undifferentiated pluripotent hESCs. Overall, our data suggest that A-to-I RNA editing plays a critical role during early human development.

We developed datasets on the human modification of global terrestrial ecosystems for 2022. The methods and data sources associated with these data are fully described in:

Theobald, D.M., Oakleaf, J.R., Moncrieff, G., Voigt, M., Kiesecker, J., and Kennedy, C.M.

For 2022, raster datasets are provided in cloud-optimized GeoTIFF format at 300 m resolution (EPSG:4326). The naming convention is as follows: HMv2024080101_

Note that these data are available as Google Earth Engine assets via this script (including 90 m): https://code.earthengine.google.com/1b7b5976fdd6189c6533ca00a46386d1

The Google Earth Engine script to clip out custom extents and export to GeoTIFF is here: https://code.earthengine.google.com/44c9f092472edb9bac3c45096aa5091d

Please see companion repo here for datasets for 1990-2020: https://zenodo.org/uploads/14449495.

This Special Issue of the Journal of South Pacific Law aims to provide insight into the role of international law in addressing the short-term and long-term challenges posed by climate change to Pacific Island States and their populations. It focuses on the two international legal frameworks that were designed to protect the Earth’s climate system and the human person: international climate change law on the one hand, and international human rights law on the other.

Background: Multiple surveys of the general public and experts on human genome editing have been conducted. However, many focused only on editing in clinical applications, with few regarding its use for basic research. Given that genome editing for research purposes is indispensable for the realization of clinical genome editing, understanding lay attitudes toward genome editing in research, particularly using human embryos, which is likely to provoke ethical concerns, is helpful for future societal discussion.Methods: An online survey was conducted with Japanese laypeople and researchers to ascertain their views regarding human genome editing for research purposes. Participants were queried about their acceptance as a function of the target of genome editing (germ cells, surplus IVF embryos, research embryos, somatic cells); then, those who answered “acceptable depending on the purpose” were asked about their acceptance in the context of specific research purposes of genome editing. Participants were also asked about their expectations and concerns regarding human genome editing.Results: Replies were obtained from 4,424 laypeople and 98 researchers. Approximately 28.2–36.9% of the laypeople exhibited strong resistance to genome editing for research purposes regardless of their applications. In contrast, 25.5% of the researchers demonstrated resistance only to genome editing in research embryos; this percentage was substantially higher than those concerning the other three targets (5.1–9.2%). Approximately 50.4–63.4% of laypeople who answered “acceptable depending on the purpose” approved germline genome editing for disease research; however, only 39.3–42.8% approved genome editing in basic research to obtain biological knowledge. In contrast, the researchers displayed a lower degree of acceptance of germline genome editing for research purposes related to chronic diseases (60.9–66.7%) than for other research purposes (73.6–90.8%). Analysis of responses concerning expectations and concerns indicated that laypeople who would not accept genome editing of human embryos did not necessarily worry about “instrumentalization of the embryo.” They also had substantially low expectations for recognized advantages of genome editing, including “advances in science” and “reduction of intractable diseases,” compared with other groups of respondents.Conclusion: The assumptions shared among experts in conventional bioethical debates and policy discussions on human genome editing are not self-evident to laypeople.

Human post-edited and reference test sentences for the En-De PBSMT WMT 2018 Automatic post-editing task. This consists of 2,000 German sentences for each file belonging to the IT domain and already tokenized. All data is provided by the EU project QT21 (http://www.qt21.eu/).

Review of Economics and Statistics: Forthcoming.. Visit https://dataone.org/datasets/sha256%3A92185cc49ab18ad5dc23232f4746982ccf9ac71f2651be35c842f5ba360eb7b2 for complete metadata about this dataset.