Private Dataset, Internal use only

This package contains the data and code necessary to run the experiments for our paper "The Value of Human Data Annotation for Machine Learning1based Anomaly Detection in Environmental Systems".

The total mean values of all parameters measured in each of the three minipig age groups and the corresponding data of humans from the scientific literature. The three different colors identify the differences between the age-group values of the minipigs and the mean values of human data, presented as a minipig/human ratio (MP:H). Ratios lower than 0.85 and higher than 1.15 were defined as substantial anatomical deviations (in red) between the two species where no comparability is present. Parameters with ratios within the range of 0.85 and 1.15 were considered to have a moderate (>0.85 and 0.9 and

Dataset Card for "meta-shepherd-human-data"

Original Dataset: https://github.com/facebookresearch/Shepherd

  Example

Question: Where on the planet would you expect a bald eagle to live?

Here are the options: Option 1: colorado Option 2: outside Option 3: protection Option 4: zoo exhibit Option 5: world

Please choose the correct option and justify your choice:

Answer: Bald eagles are found throughout most of North America, from Alaska and Canada south to… See the full description on the dataset page: https://huggingface.co/datasets/philschmid/meta-shepherd-human-data.

Data S1. Structure Dataset for Homo sapiensData S2. Structure Dataset for Escherichia coliData S3. Structure Dataset for Saccharomyces cerevisiaeData S4. Human co-complex subunit pairsData S5. Delta-MeltingTemperature matrix for humanData S6. MeltingCurve-Dissimilarity matrix for humanData S7. ProteinAbundance-correlation matrix for humanData S8. Delta-ProteinDegradationRate matrix for humanData S9. Delta-TranscriptionRate matrix for humanData S10. GeneExpression-correlation matrix for humanData S11. Delta-Translation-Initiation-Efficiency matrix for humanData S12. Delta-Translation-Elongation-Speed matrix for humanData S13. Fluorescent probe sequences used for smFISH experimentsData S14. Plasmids generated for genetic perturbation experimentsData S15. Yeast strains generated for genetic perturbation experiments

De-identified participant responses from the two psychophysics experiments

Human data obtained from the Kyotango cohort study

This data captures the health survey responses reported by participants.

Dataset Card for Evaluation run of OpenLLM-France/Lucie-7B-Instruct-human-data

Dataset automatically created during the evaluation run of model OpenLLM-France/Lucie-7B-Instruct-human-data The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/OpenLLM-France_Lucie-7B-Instruct-human-data-details.

Human data

Dataset relating to manuscript: Disruptive colouration and binocular disparity: Breaking camouflage Adams, Graf & Anderson. The .zip file includes psychophysics data for all participants. There are two files for each numbered participant; one file with raw reaction time data and another with summarised data for each condition used for the ANOVA, for each of the 30 participants in the paper: The seven columns in the raw data .csv (i.e. 1.csv) correspond to different aspects of each trial; with each row containing data from one trial. The values in each cell are explicable from the heading label. For example, in the MonoStereo column, a value of 1 corresponds to Monocular presentation for that trial, 2 would indicate Stereo presentation. The Summary file for each participant combines repetitions into single values for each of the conditions used in further analysis. The dataset relates to work conducted as part of the EPSRC-funded grant EP/K005952/1

The embedded touch screen display (ETSD) market is experiencing robust growth, driven by increasing demand across diverse sectors. The market's expansion is fueled by several key factors. The proliferation of smart devices, particularly in the consumer electronics and industrial automation sectors, is a major catalyst. Furthermore, advancements in display technologies, such as the transition towards higher resolution and improved touch sensitivity, are enhancing user experience and driving adoption. The rising integration of ETSD in medical equipment for improved user interfaces and diagnostic capabilities is also significantly contributing to market growth. While the precise market size in 2025 is unavailable, considering a potential CAGR of 10% (a reasonable estimate for this rapidly evolving technology), and assuming a 2024 market size of $15 billion (a conservative estimate based on industry reports and the listed companies' activities), we can project a 2025 market size of approximately $16.5 billion. This growth trajectory is expected to continue through 2033, albeit at a potentially moderating pace. However, certain challenges remain. The high initial investment costs associated with adopting ETSD technology, particularly in cost-sensitive sectors, can serve as a restraint. Furthermore, the technological complexities involved in manufacturing high-quality, reliable displays, along with potential supply chain disruptions, could impact market growth. Segmentation analysis reveals that the medical care and industrial control applications are projected to witness the highest growth rates due to increasing demand for advanced features and functionalities in these sectors. The liquid crystal display (LCD) segment currently holds a significant market share; however, the organic light-emitting diode (OLED) segment is poised for rapid growth due to its superior image quality and energy efficiency. The competitive landscape is marked by a mix of established players and emerging companies, leading to innovation and price competition. This dynamic interplay of factors will ultimately shape the future trajectory of the embedded touch screen display market.

See ReadMe file for details.

Human behavior in a VI task as described by paper "Choice history effects improve reward harvesting efficiency in mice and humans" in Figure 2.

We explored the effects of 12 weeks of NR supplementation on the gut microbiota in humans.