Huzaifah0/audio-splitting-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

An Open Context "predicates" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Variables" record is part of the "Çatalhöyük Area TP Zooarchaeology" data publication.

The shear-wave splitting (SWS) databases data product provides the geosciences community with an easy access to two published databases:

• "The Géosciences Montpellier SplitLab sShear-wave splitting database":http://ds.iris.edu/ds/products/sws-db/
• "The Missouri University of Science and Technology (Missouri S&T) shear-wave splitting database":http://ds.iris.edu/ds/products/sws-db-mst/ for western and central United States

✓ ☁️ The SWS files are also available from the "EarthScope Data Archive":https://data.earthscope.org/archive/seismology/products/swsdb/README.html.

https://ds.iris.edu/spud/resources/images/spud.png" style="width:30px;"/> A query for the Splitlab Shear-wave splitting database is available on "SPUD":https://ds.iris.edu/spud/swsmeasurement

Huzaifah0/audio-splitting-dataset-v6 dataset hosted on Hugging Face and contributed by the HF Datasets community

Node classification on PubMed with 60%/20%/20% random splits for training/validation/test.

Basic Animal Incident Dataset (Manual Splitting)

## Overview

Basic Animal Incident Dataset (Manual Splitting) is a dataset for object detection tasks - it contains Dog And Cat Wu8I L3Az 3iVz JoTF annotations for 913 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Basic Animal Incident Dataset (Manual Splitting) Backup

## Overview

Basic Animal Incident Dataset (Manual Splitting) Backup is a dataset for object detection tasks - it contains Dog And Cat Wu8I L3Az 3iVz JoTF OAup annotations for 913 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The runtime benchmarks were obtained by running each algorithm on the seed and full multi-MSAs Pfam-A.seed and Pfam-A.full on 2 cores with 8 GB RAM for the seed alignments and on 3 cores with 12 GB RAM for the full alignments. We did not compute the maximum runtime of the Blue algorithm; the algorithm failed to terminate within 6 days for 34 families.

Dataset Split 2

## Overview

Dataset Split 2 is a dataset for object detection tasks - it contains Coffea Liberica annotations for 3,061 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This data file contains records from research participants in an empirical investigation of dysfunctional individuation and its association with ego splitting and with differentiation of self. College adjustment problems were also measured. The Dysfunctional Individuation Scale, the Splitting Index, the Differentiation of Self battery, along with measures of college adjustment were assessed. The general aim of the project was to provide further evidence for the construct validity of dysfunctional individuation

This dataset contains all source files, including Q.E. input files, of eight bilayer ferroelectric structures, 4 compounds with two antiparallel charge polarization each, of MX2 (M = Mo, W; X = S, Se) from which all figures inside the paper can be reproduced. Transition metal dichalcogenides (TMDs) exhibit giant spin-orbit coupling (SOC), and intriguing spin-valley effects, which can be harnessed through proximity in van der Waals (vdW) heterostructures. Remarkably, in hexagonal monolayers, the Zeeman-type band splitting of valence bands, which originate from the prismatic crystal field, can reach values of several hundreds of meV, offering significant potential for both fundamental and applied research. While this effect is suppressed in the commonly studied hexagonal (H)-stacked bilayers due to the presence of inversion symmetry, the recent discovery of sliding ferroelectricity in rhombohedral (R-)stacked MX2 bilayers (M=Mo, W; X=S, Se) suggest that the Zeeman effect could be present in these non-centrosymmetric configurations, making it even more intriguing to investigate how the spin-resolved bands would evolve during the phase transition. Here, we perform density functional theory calculations complemented by symmetry analysis to unveil the evolution of ferroelectricity during sliding and the behavior of Zeeman splitting along the transition path. While the evolution of the out-of-plane component of the electric polarization vector resembles the conventional ferroelectric transition, switching between positive and negative values, we observe significant in-plane components parallel to the sliding direction, reaching their maximum at the intermediate state. Moreover, we demonstrate that the R-stacked bilayers exhibit substantial Zeeman-type band splitting, akin to monolayers, which persists throughout the transition path, being allowed by the lack of inversion symmetry. Further analysis of different stacking configurations generated by sliding along various directions confirms that the Zeeman effect in MX2, primarily arising from the polarity of prismatic ligand coordination of the metal atom, is remarkably robust and completely governs the spin polarization of bands, independently of the sliding direction. This resilience promises to maintain robust spin transport in vdW heterostructures based on MX2 bilayers, opening new opportunities for ferroelectric spintronics.

(1) Photocatalysis databases.(2) Photocatalysis extraction models.(3) Photocatalysis extraction scripts.(4) Code for ChemDataExtractor v2.2 that was developed to auto-generate this database (static version).(5) A supporting CDEDatabase software package that was written to read/write ChemDataExtractor extracted files (static version).

Statistics illustrates market overview of splitting, slicing or paring machines in San Marino from 2007 to 2024.

Bill Splitting Apps Market Outlook

The global market size for bill-splitting apps was valued at approximately USD 1 billion in 2023 and is projected to grow to USD 3.5 billion by 2032, reflecting a robust CAGR of 14%. This impressive growth can be attributed to the increasing reliance on digital solutions for everyday tasks, driven by the convenience and efficiency that mobile and web-based applications offer. The rise of a cashless economy, coupled with the growing need for transparent and easy financial management tools, further propels the market's expansion.

One of the primary growth factors for the bill-splitting apps market is the proliferation of smartphones and the increasing penetration of the internet. As more people gain access to these technologies, the demand for applications that simplify daily tasks, such as splitting bills among friends or colleagues, rises significantly. The millennial and Gen Z demographics, known for their tech-savviness and preference for seamless digital experiences, are particularly driving the adoption of these apps. Additionally, the ongoing trend toward digitalization in various sectors, including finance and retail, complements the growth of bill-splitting applications.

Another significant factor contributing to the market's growth is the increasing globalization and mobility of the workforce. With more people working remotely or in different parts of the world, there is a growing need for efficient financial tools that can handle multiple currencies and payment methods. Bill-splitting apps cater to this need by providing features that allow users to split expenses accurately and conveniently, regardless of their geographical location. Moreover, the rise of shared economy services, such as carpooling and co-working spaces, further underscores the utility of these apps.

The growing emphasis on financial literacy and personal financial management also plays a crucial role in the market's expansion. As individuals become more aware of the importance of managing their finances effectively, they seek tools that offer transparency and ease of use. Bill-splitting apps often come with additional features, such as budgeting tools and expense tracking, making them valuable assets for users aiming to maintain healthy financial habits. Furthermore, partnerships between app developers and financial institutions can enhance the functionality of these apps, making them more appealing to a broader audience.

Regionally, North America holds a significant share of the market, driven by high smartphone penetration and a strong inclination towards digital financial solutions. However, the Asia Pacific region is expected to witness the fastest growth, thanks to its large millennial population, increasing disposable incomes, and rapid adoption of digital technologies. Europe also presents substantial opportunities, particularly in countries with high internet penetration and tech-savvy populations. Meanwhile, Latin America, the Middle East, and Africa are emerging regions that offer potential growth opportunities as digital infrastructure continues to improve.

Platform Analysis

The bill-splitting apps market can be segmented by platform into iOS, Android, and web-based applications. The iOS segment holds a significant share of the market due to the large user base of iPhone users who are known for their higher spending power and propensity to adopt new technologies. Apple's ecosystem and its seamless integration with other Apple devices make iOS a preferred platform for many app developers. Furthermore, the availability of a wide range of financial management apps in the Apple App Store contributes to the dominance of the iOS segment.

In contrast, the Android segment is expected to witness the fastest growth during the forecast period. This can be attributed to the widespread adoption of Android devices across the globe, particularly in emerging markets. The affordability and variety of Android smartphones make them accessible to a larger audience, thus driving the demand for Android-based bill-splitting apps. Additionally, the open-source nature of the Android platform allows developers to innovate and create customized solutions tailored to specific market needs, further boosting the segment's growth.

The web-based segment, although smaller compared to mobile platforms, remains a vital component of the market. Web-based bill-splitting applications offer the advantage of cross-platform compatibility, enabling users to access their accounts from any device with an internet conne

Overview

Source: https://huggingface.co/datasets/sayakpaul/nyu_depth_v2 (origin : fast-depth)

Train: 48k Test: 654 Image dtype: uint8 Depth dtype: uint16

Image to Depth Conversion

def image2depth(path):
  depth = cv2.imwrite(path, cv2.IMREAD_UNCHANGED)
  depth = depth.astype('float32')
  depth /= (2**16 - 1)
  depth *= 10.0
  return depth

Statistics illustrates market overview of splitting, slicing or paring machines in GCC from 2007 to 2024.

The sixth annual Advanced Water Splitting Pathways Benchmarking meeting was held on June 11-12, 2024 at the Arizona State University California Center- Los Angeles, CA. A total of 117 people participated (102 in person and 15 via Zoom). Attendance at most breakout sessions ranged from 10 - 25 attendees. The focus of many of the sessions was on developing plans to validate protocols written to date, defining future protocols to be written and aligning with international efforts. The plenary session provided perspectives on international activities in each technology area, as well as an overview of the ARCHES Hydrogen Hub.

75 25 Split

## Overview

75 25 Split is a dataset for object detection tasks - it contains 75 25 Split annotations for 900 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This dataset is about books. It has 1 row and is filtered where the book is The point of splitting. It features 7 columns including author, publication date, language, and book publisher.

For Dataset Split

## Overview

For Dataset Split is a dataset for instance segmentation tasks - it contains Instrument annotations for 3,193 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).