No description was included in this Dataset collected from the OSF

Land use change and biological invasions collectively threaten biodiversity. Yet, few studies have addressed how altering the landscape structure and nutrient supply can promote biological invasions and particularly invasive spread (the spread of an invader from the place of introduction), or asked whether and how these factors interact with biotic interactions and invader properties. We here bridge this knowledge gap by providing a holistic network-based approach. Our approach combines a trophic network model with a spatial network model allowing us to test which combinations of abiotic and biotic factors can facilitate invasions and in particular invasive spread in food webs. We numerically simulated 6300 single-species invasions in clustered and random landscapes at different levels of nutrient supply. In total, our simulation experiment yielded 69\% successful invasions---71% in clustered landscapes and 66% in random landscapes, with the proportion of successful invasions increasing...

User-specified parameters.

This dataset contains the spatiotemporal data used to train the spatiotemporal deep neural networks described in "Modeling the Spread of a Livestock Disease With Semi-Supervised Spatiotemporal Deep Neural Networks". The dataset consists of two sets of NumPy arrays. The first set: X_grid.npy and Y_grid.npy were used to train the convolutional LSTM, while the second set: X_graph.npy, Y_graph.npy, and edge_index.npy were used to train the graph convolutional LSTM. The data consists of spatiotemporally varying environmental and anthropogenic variables along with case reports of vesicular stomatitis. Resources in this dataset:Resource Title: NumPy Arrays of Spatiotemporal Features and VS Cases. File Name: vs_data.zipResource Description: This is a ZIP archive containing five NumPy arrays of spatiotemporal features and geotagged VS cases.Resource Software Recommended: NumPy,url: https://numpy.org/

This Excel spreadsheet contains the data used in Tan and Schultz (2023).

These data consist of 289 peer-reviewed empirical journal articles on the relationship between weather and COVID-19 during 2020 and 2021. These data also include 24 review articles on the same topic.

Tan, L., and D. M. Schultz, 2023: Weather effects on the spread of COVID-19: Characteristics and critical analysis of the first and second years of scientific research. Bull. Amer. Meteor. Soc., https://doi.org/10.1175/BAMS-D-23-0071.1.

Observations used in the study "Rodrigues, F. S., Zhan, W., Milla, M. A., Fejer, B. G., de Paula, E. R., Neto, A. C., et al ( 2019). MELISSA: System description and spectral features of pre‐ and post‐midnight F‐region echoes. Journal of Geophysical Research: Space Physics, 124. https://doi.org/10.1029/2019JA027445."

The uploaded files include the RTI maps measured by the MELISSA radar system between 2014 and 2018 (.tif files). They also include values of SNR versus local time and height and the spectra presented in the manuscript (.mat files).

Please, see README.txt for additional details.

We performed systematic mapping of EPC data applications by time, geographical spread, data features & auxiliary data used, problem domains addressed and complexity of employed data analysis. This mapping work was intended to answer the following questions: Q1. Which research studies have used EPC data (hereafter “applications”)? Q2. What input data were used by the EPC data applications? Q3. Which problem domains were addressed by the EPC data applications? Q4. How did the EPC data applications change within the study period?

Purpose:

To understand how the energy performance certificates (EPC) data has been used since introduction of the first national EPC registers.

This dataset provides information about the number of properties, residents, and average property values for Spread Eagle Drive cross streets in Westcliffe, CO.

This dataset is about book series. It has 1 row and is filtered where the books is A spread of sail. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

This dataset provides information about the number of properties, residents, and average property values for Spread Oak Lane cross streets in Waterbury, CT.

Understanding how epidemics spread in a system is a crucial step to prevent and control outbreaks, with broad implications on the system’s functioning, health, and associated costs. This can be achieved by identifying the elements at higher risk of infection and implementing targeted surveillance and control measures. One important ingredient to consider is the pattern of disease-transmission contacts among the elements, however lack of data or delays in providing updated records may hinder its use, especially for time-varying patterns. Here we explore to what extent it is possible to use past temporal data of a system’s pattern of contacts to predict the risk of infection of its elements during an emerging outbreak, in absence of updated data. We focus on two real-world temporal systems; a livestock displacements trade network among animal holdings, and a network of sexual encounters in high-end prostitution. We define the node’s loyalty as a local measure of its tendency to maintain contacts with the same elements over time, and uncover important non-trivial correlations with the node’s epidemic risk. We show that a risk assessment analysis incorporating this knowledge and based on past structural and temporal pattern properties provides accurate predictions for both systems. Its generalizability is tested by introducing a theoretical model for generating synthetic temporal networks. High accuracy of our predictions is recovered across different settings, while the amount of possible predictions is system-specific. The proposed method can provide crucial information for the setup of targeted intervention strategies.

The Reddit Subreddit Dataset by Dataplex offers a comprehensive and detailed view of Reddit’s vast ecosystem, now enhanced with appended AI-generated columns that provide additional insights and categorization. This dataset includes data from over 2.1 million subreddits, making it an invaluable resource for a wide range of analytical applications, from social media analysis to market research.

Dataset Overview:

This dataset includes detailed information on subreddit activities, user interactions, post frequency, comment data, and more. The inclusion of AI-generated columns adds an extra layer of analysis, offering sentiment analysis, topic categorization, and predictive insights that help users better understand the dynamics of each subreddit.

2.1 Million Subreddits with Enhanced AI Insights: The dataset covers over 2.1 million subreddits and now includes AI-enhanced columns that provide: - Sentiment Analysis: AI-driven sentiment scores for posts and comments, allowing users to gauge community mood and reactions. - Topic Categorization: Automated categorization of subreddit content into relevant topics, making it easier to filter and analyze specific types of discussions. - Predictive Insights: AI models that predict trends, content virality, and user engagement, helping users anticipate future developments within subreddits.

Sourced Directly from Reddit:

All data in this dataset is sourced directly from Reddit, ensuring accuracy and authenticity. The dataset is updated regularly, reflecting the latest trends and user interactions on the platform. This ensures that users have access to the most current and relevant data for their analyses.

Key Features:

• Subreddit Metrics: Detailed data on subreddit activity, including the number of posts, comments, votes, and user participation.
• User Engagement: Insights into how users interact with content, including comment threads, upvotes/downvotes, and participation rates.
• Trending Topics: Track emerging trends and viral content across the platform, helping you stay ahead of the curve in understanding social media dynamics.
• AI-Enhanced Analysis: Utilize AI-generated columns for sentiment analysis, topic categorization, and predictive insights, providing a deeper understanding of the data.

Use Cases:

• Social Media Analysis: Researchers and analysts can use this dataset to study online behavior, track the spread of information, and understand how content resonates with different audiences.
• Market Research: Marketers can leverage the dataset to identify target audiences, understand consumer preferences, and tailor campaigns to specific communities.
• Content Strategy: Content creators and strategists can use insights from the dataset to craft content that aligns with trending topics and user interests, maximizing engagement.
• Academic Research: Academics can explore the dynamics of online communities, studying everything from the spread of misinformation to the formation of online subcultures.

Data Quality and Reliability:

The Reddit Subreddit Dataset emphasizes data quality and reliability. Each record is carefully compiled from Reddit’s vast database, ensuring that the information is both accurate and up-to-date. The AI-generated columns further enhance the dataset's value, providing automated insights that help users quickly identify key trends and sentiments.

Integration and Usability:

The dataset is provided in a format that is compatible with most data analysis tools and platforms, making it easy to integrate into existing workflows. Users can quickly import, analyze, and utilize the data for various applications, from market research to academic studies.

User-Friendly Structure and Metadata:

The data is organized for easy navigation and analysis, with metadata files included to help users identify relevant subreddits and data points. The AI-enhanced columns are clearly labeled and structured, allowing users to efficiently incorporate these insights into their analyses.

Ideal For:

• Data Analysts: Conduct in-depth analyses of subreddit trends, user engagement, and content virality. The dataset’s extensive coverage and AI-enhanced insights make it an invaluable tool for data-driven research.
• Marketers: Use the dataset to better understand your target audience, tailor campaigns to specific interests, and track the effectiveness of marketing efforts across Reddit.
• Researchers: Explore consumer behavior data of online communities, analyze the spread of ideas and information, and study the impact of digital media on public discourse, all while leveraging AI-generated insights.

This dataset is an essential resource for anyone looking to understand the intricacies of Reddit's vast ecosystem, offering the data and AI-enhanced insights needed to drive informed decisions and strategies across various fields. Whether you’re tracking emerging trends, analyzing user behavior, or conducting acade...

This dataset provides information about the number of properties, residents, and average property values for Spread Oak Road cross streets in Keysville, GA.

This data publication contains the results from 45 experimental burns and 48 smoldering tests on masticated materials from mixed-conifer forests. These data were collected from 15 study locations from 2012 through 2016 as part of the MASTIDON project. The MASTIDON project was a four-year study to describe the phyical characteristics of masticated materials that were treated with four different cutting heads in xeric and mesic environments. The main focus of the project was to evaluate how leaving the particles on the ground for varying lengths of time affected the burnability of the particles. The project was funded by the Joint Fire Sciences Program (JFSP) and RMRS between 2013 and 2016. The masticated particles were created by four different machines, including a vertical rotating head, horizontal drum, chipper, and mower. They had been decomposing in situ in wet and dry areas of Idaho, and dry areas of Colorado, New Mexico, and South Dakota since their initial treatment and were between 0 and 10 years old. The materials were burned at the RMRS Missoula Fire Sciences lab, Missoula, MT. The experimental burns were conducted in a combustion facility on a large fuel bed 0.68 square meters in size. The smoldering tests were conducted on beds 497 square centimeters in size under a fume hood in the soils laboratory. This download includes (1) data on fire behavior within the experimental burns, including rate of spread, flame height, flame duration, consumption, heat flux, moisture content, and more; (2) temperature data, burn durations, duff moistures and thicknesses from the smoldering tests; (3) photos of the experimental burn beds and smoldering beds; and (4) files describing the MASTIDON project and its goals.

Test accuracy for early stopping with patience setting of 20, 40, 60, 80, and 100 on three FCNs models.

Explore our meticulously curated Movies dataset and TV shows dataset, designed to cater to diverse analytical and research needs. Whether you're a data scientist, a student, or a business professional, these datasets provide valuable insights into the entertainment industry.

Key Features of the Movies Dataset:

1. Extensive collection of global movies across various genres and languages.

2. Detailed metadata, including titles, release dates, genres, directors, cast, and ratings.

3. Regularly updated to ensure relevance and accuracy.

Why Choose Our TV Shows Dataset?

Our TV shows dataset is your gateway to understanding trends in episodic content. It includes:

• Comprehensive details about popular and niche TV shows.

• Information on episode counts, seasons, ratings, and networks.

• Insights into audience preferences and regional programming.

Applications of These Datasets

These datasets are perfect for:

• Machine learning models for recommendation systems.

• Academic research on media trends and audience behavior.

• Business strategies for entertainment platforms.

Unlock the power of TV show data with our Crawl Feeds TV Shows Dataset. Start analyzing today and gain valuable insights into your favorite shows!

Resource Description: This is a ZIP archive containing five NumPy arrays of spatiotemporal features and geotagged VS cases.Resource Software Recommended: NumPy,url: https://numpy.org/

Donuka offers a simple, reliable property data solution to power innovation and create seamless business solutions for companies of all sizes. Our data covers more than 37 million properties spread out across the U.S. that can be accessed in bulk-file format or through our APIs.

We offer access to data ONLY in selected states and counties

DATA SOURCES:

1. ONLY state sources (city/county/state administration, federal agencies, ministries, etc.). We DO NOT use unverified databases
2. Over 2300 sources. We use even the smallest sources, because they contain valuable data. This allows us to provide our users with the most complete data

DATA RELEVANCE:

1. Our data is updated daily, weekly, monthly depending on the sources
2. We collect, process and store all data, regardless of their relevance. Historical data is also valuable

DATA TYPES:

1. Specifications
2. Owners
3. Permits
4. Sales
5. Inspections
6. Violations
7. Assessed values
8. Taxes
9. Risks
10. Foreclosures
11. Property Tax Liens
12. Deed Restrictions

NUMBERS:

1. 2300+ data sources in total
2. 4 billion records (listed in the "data types" block above) in total
3. 2 million new records every day

DATA USAGE:

1. Property check, investigation (even the smallest events are stored in our database)
2. Prospecting (more than 100 parameters to find the required records)
3. Tracking (our data allows us to track any changes)

Two short exposures of the bright, radioquiet Seyfert1.2 galaxy UGC3973 wereconducted with XMM as part of an AGN snapshot survey. During one of theseobservations a narrow 8keV (rest frame) linelike emission feature was detectedwith the pn instrument. An instrumental origin was ruled out. The detection wasseriously scrutinised and found to be significant at 96.098.4% confidence,depending what a priori assumptions were made. We propose three, 20ksobservations (60ks total) of UGC3973 spread over AO5. The proposed programmewill allow investigation of the significance of the feature, its variability,and its origin. In addition, UGC3973 has demonstrated significant flux andspectral variability over similar time periods as proposed here. This will allow truncated!, Please see actual data for full text [truncated!, Please see actual data for full text]

This dataset provides information about the number of properties, residents, and average property values for Spread Oak Lane cross streets in East Hampton, NY.