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130 results for “BITs”

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dryad36/100

Extended-variable probabilistic computing with probabilistic d-dimensional bits

Open the record for dataset details and reuse information.

publicSep 2025View details →
zenodo32/100

Fast Bit-Vector Satisfiability

<p>SMT-LIB2 queries from two symbolic analysis platforms and twenty programs</p> <ul> <li>pinpoint</li> <li>qsym</li> </ul>

opencc-byJun 2020View details →
zenodo32/100

Bits x la Marató: Looking for similar patients: the AI Doctor House conquers severe COVID-19!

<p>Clinical case reports for the task Looking for similar patients: the AI Doctor House conquers severe COVID-19! at the event Bits x la Marat&oacute;: https://www.fib.upc.edu/en/la-marato</p> <p>&nbsp;</p> <p>There is a pressing need by healthcare professionals to access information relevant to clinical practice in a more effective way. Over 80% of clinically relevant data is essentially unstructured, mainly images like MRI and clinical texts.</p> <p>One of the challenges faced by doctors is finding patients and clinical cases that show particular similarities to a given case (similar symptoms, diagnosis, treatments, or other characteristics) amongst the rapidly growing amount of clinical records and medical publications and the complexity of the data. Detection of similarities among patients or groups of patients is key for evidence-based clinical practice, the selection of patients for clinical trials, prioritizing patients for vaccination and for understanding the variability in clinical outcomes.</p> <p>From a COVID-19 point of view, AI tools should distinguish between patients with and with no risk of a severe outcome, so that clinicians could intervene promptly.&nbsp;<strong>Specifically, this task aims to promote the development of systems able to detect similarities among a collection of clinical case texts.</strong></p> <p>&nbsp;</p> <p><strong>Technology point of view:</strong></p> <p>The objective is to be able to compute and measure similarity between patients represented by their clinical case, that is, the text describing their medical condition, previous morbidities, medical tests and treatments performed, diagnosis or outcome. This very complex scenario can in principle be approached by a diversity of methodologies ranging from text similarity techniques used to detect plagiarism, clinical concept detection, or even more advanced semantic textual similarity strategies dealing with the meaning of natural language through AI.</p> <p>&nbsp;</p> <p><strong>Healthcare point of view:</strong></p> <p>Access to medically relevant information hidden in clinical texts is one of the principal&nbsp;challenges for healthcare professionals in the AI digital age. Questions such as which&nbsp;are the symptoms of patients with a worse outcome, given similar comorbidities,&nbsp;medications or procedures are very difficult to answer without systematically&nbsp;processing clinical texts. Even simpler, epidemiological questions like how many days&nbsp;have passed before COVID-19 symptoms started or if patients had travelled to certain&nbsp;geographical areas can only be answered efficiently by means of computational tools.&nbsp;Similarities between patients can aid prognosis, diagnosis and decision making, saving&nbsp;vital time to healthcare practitioners.</p> <p>&nbsp;</p> <p>If you need some help, <a href="https://medium.com/@adriensieg/text-similarities-da019229c894">here</a> is a helpful resource that will help you get started.</p> <p>&nbsp;</p> <p><a href="https://www.youtube.com/playlist?list=PL5uSCzf1azhBeVCHyswazImBNpIW8gYTD">YouTube playlist with our session at BITSXLAMARAT&Oacute;</a></p>

opencc-by-4.0Dec 2020View details →
zenodo32/100

Chisel with Polished Bit. XCB-105-1924

Chisel with Polished Bit. XCB-105-1924. 400 BCE-100 CE XCB-105 Adamagan (Aleut for place of walrus hunters) is at the head of Morzhovoi Bay, western Alaska Peninsula. It is a massive village with multiple occupations. When it was occupied 400 BCE-100 CE, it was the largest village in the Arctic with an estimated 1000 people. It also has limited occupations dated 2200-1700 BCE, 1000-600 BCE, and 900-1100 CE. The Western Alaska Peninsula artifacts are presented as a result of the research conducted under grants NSF 9630072, NSF 9814086, NSF 9996372, NSF 9996415, NSF 1139266, NSF 1321411. H. Maschner, Principal Investigator. These artifacts were scanned with either a Faro Edge Arm or a Minolta Vivid 9i. Processed in Geomagic or Polyworks. 2-8 photos were used for texture in Geomagic Wrap. Original digitizing work done at the IVL at Id. St. Univ. Subsequent processing and publication completed at Global Digital Heritage. Source: Objaverse 1.0 / Sketchfab

opencc-by-nc-1.0Jun 2020View details →
zenodo32/100

How Bit-Vector Logic Can Help Improve the Verification of First-Order LTL Specifications

<p>Experimental evaluation for the encoding presented in the paper &quot;How Bit-Vector Logic Can Help Improve the Verification of First-Order LTL Specifications&quot;.</p> <p>The encoding is implemented as a zot plugin entitled ae2bvzot.</p>

opencc-by-4.0Apr 2016View details →
zenodo32/100

Text generated by OPUS-MT and T5 models with single-bit errors in the parameters

<h2>Description</h2> <p>The dataset contains text generated using T5 and OPUS-MT model with and with single-bit errors in the parameters of the LLM. The T5 LLM used the&nbsp;<a href="https://huggingface.co/datasets/cnn_dailymail/viewer/3.0.0/test">CNN Daily Mail</a> dataset for summarization and OPUS-MT used the&nbsp;<a href="https://aclanthology.org/2017.iwslt-1.1/">IWSLT2017</a> dataset for Chinese-to-English translation.</p> <p>&nbsp;</p> <p>Folders:</p> <ul> <li>t5_fp32: T5 model with a quantified version of FP32</li> <li>t5_fp16: T5 model with a quantified version of FP16</li> <li>opus_fp32: OPUS-MT model with a quantified version of FP32</li> <li>opus_fp16: OPUS-MT model with a quantified version of FP16</li> </ul> <p>Files:</p> <ul> <li><strong>{cnn/iwslt2017}_input_text.txt</strong>: Input text, that is, text to summarize (cnn and T5) or Chinese text to translate (iwslt2017 and OPUS-MT).&nbsp; For each dataset in total there are&nbsp;<em>number_input_texts.</em></li> <li><strong>{cnn/iwslt2017}_output_reference.txt:</strong> Example of result expected for CNN (T5) and IWSLT2017 (OPUS-MT).&nbsp;For each dataset in total there are&nbsp;<em>number_input_texts.</em></li> <li><strong>{cnn/iwslt2017}_output_predict_fault_free:</strong> Example of predictions without single-bit errors. For each dataset in total there are&nbsp;<em>number_input_texts.</em></li> <li><strong>{cnn/iwslt2017}_output_predict_single_fi_bit_100times:</strong> Example of predictions with 100 different single-bit error. In each dataset in total there are <em>100*number input texts</em>.</li> </ul> <h2>Paper</h2> <ul> <li>Paper: <a href="https://doi.org/10.48550/arXiv.2403.16393">Concurrent Linguistic Error Detection (CLED) for Large Language Models</a></li> <li>Cite:</li> </ul> <p><code>@misc{zhu2024concurrent,</code><br><code>&nbsp; &nbsp; &nbsp; title={Concurrent Linguistic Error Detection (CLED) for Large Language Models},&nbsp;</code><br><code>&nbsp; &nbsp; &nbsp; author={Jinhua Zhu and Javier Conde and Zhen Gao and Pedro Reviriego and Shanshan Liu and Fabrizio Lombardi},</code><br><code>&nbsp; &nbsp; &nbsp; year={2024},</code><br><code>&nbsp; &nbsp; &nbsp; eprint={2403.16393},</code><br><code>&nbsp; &nbsp; &nbsp; archivePrefix={arXiv},</code><br><code>&nbsp; &nbsp; &nbsp; primaryClass={cs.AI}</code><br><code>}</code></p> <p>&nbsp;</p>

opencc-by-4.0Feb 2024View details →
zenodo32/100

Adze Bit. XCB-105-3731

Adze Bit. XCB-105-3731. 400 BCE-100 CE XCB-105 Adamagan (Aleut for place of walrus hunters) is at the head of Morzhovoi Bay, western Alaska Peninsula. It is a massive village with multiple occupations. When it was occupied 400 BCE-100 CE, it was the largest village in the Arctic with an estimated 1000 people. It also has limited occupations dated 2200-1700 BCE, 1000-600 BCE, and 900-1100 CE. The Western Alaska Peninsula artifacts are presented as a result of the research conducted under grants NSF 9630072, NSF 9814086, NSF 9996372, NSF 9996415, NSF 1139266, NSF 1321411. H. Maschner, Principal Investigator. These artifacts were scanned with either a Faro Edge Arm or a Minolta Vivid 9i. Processed in Geomagic or Polyworks. 2-8 photos were used for texture in Geomagic Wrap. Original digitizing work done at the IVL at Id. St. Univ. Subsequent processing and publication completed at Global Digital Heritage. Source: Objaverse 1.0 / Sketchfab

opencc-by-nc-1.0Jul 2020View details →
zenodo32/100

Adze Bit. XCB-105-1696

Ground, Chipped, and Polished Adze Bit. XCB-105-1696. 400 BCE-100 CE XCB-105 Adamagan (Aleut for place of walrus hunters) is at the head of Morzhovoi Bay, western Alaska Peninsula. It is a massive village with multiple occupations. When it was occupied 400 BCE-100 CE, it was the largest village in the Arctic with an estimated 1000 people. It also has limited occupations dated 2200-1700 BCE, 1000-600 BCE, and 900-1100 CE. The Western Alaska Peninsula artifacts are presented as a result of the research conducted under grants NSF 9630072, NSF 9814086, NSF 9996372, NSF 9996415, NSF 1139266, NSF 1321411. H. Maschner, Principal Investigator. These artifacts were scanned with either a Faro Edge Arm or a Minolta Vivid 9i. Processed in Geomagic or Polyworks. 2-8 photos were used for texture in Geomagic Wrap. Original digitizing work done at the IVL at Id. St. Univ. Subsequent processing and publication completed at Global Digital Heritage. Source: Objaverse 1.0 / Sketchfab

opencc-by-nc-1.0Jun 2020View details →
zenodo32/100

Concatenated SBWT bit vectors

<p><span>The concatenated bit vectors from the "plain matrix" of the SBWT pr</span><span>oposed by Alanko, Puglisi and Vuohtoniemi[1]</span><span>. The SBWT in question is built based&nbsp;</span><span>on a set of 17,336,887 Illumina HiSeq 2500 reads of length 502 sampled from the human&nbsp;</span><span>gut (SRAidentifier ERR5035349) in a study on irritable bowel syndrome and bile acid&nbsp;</span><span>malabsorption[2] with k-mer size 31.</span></p> <p><span><span>[1] Jarno N. Alanko, Simon J. Puglisi, and Jaakko Vuohtoniemi.</span><span> </span><span>Small searchable</span><span> </span><span>&kappa;</span><span>-spectra&nbsp;</span><span>via subset rank queries on the spectral burrows-wheeler transform. In Jonathan W. Berry,&nbsp;</span><span>David B. Shmoys, Lenore Cowen, and Uwe Naumann, editors,</span><span> </span><span>SIAM Conference on Applied&nbsp;</span><span>and Computational Discrete Algorithms, ACDA 2023, Seattle, WA, USA, May 31 - June 2,&nbsp;</span><span>2023</span><span>, pages 225&ndash;236. SIAM, 2023.</span><span> </span><span>doi:10.1137/1.9781611977714.20</span><span>.</span></span></p> <p><span><span><span>Ian B Jeffery, Anubhav Das, Eileen O&rsquo;Herlihy, Simone Coughlan, Katryna Cisek, Michael&nbsp;</span><span>Moore, Fintan Bradley, Tom Carty, Meenakshi Pradhan, Chinmay Dwibedi, et al. Differences&nbsp;</span><span>in fecal microbiomes and metabolomes of people with vs without irritable bowel syndrome&nbsp;</span><span>and bile acid malabsorption.</span><span> </span><span>Gastroenterology</span><span>, 158(4):1016&ndash;1028, 2020.</span></span></span></p>

opencc-by-4.0Apr 2024View details →
dryad32/100

Script and data used in: A lot of convergence, a bit of divergence: environment and interspecific interactions shape body color patterns in Lissotriton newts

<p>Coexistence with related species poses evolutionary challenges to which populations may react in diverse ways. When exposed to similar environments, sympatric populations of two species may adopt similar phenotypic trait values. However, selection may also favor trait divergence as a way to reduce competition for resources or mates. The characteristics of external body parts, such as coloration and external morphology, are involved to varying degrees in intraspecific signaling as well as in the adaptation to the environment, and consequently may be diversely affected by interspecific interactions in sympatry. Here, we studied the effect of sympatry on various color and morphological traits in males and females of two related newt species <i>Lissotriton helveticus</i> and <i>L. vulgaris</i>. Importantly, we did not only estimate how raw trait differences between species respond to sympatry, but also the marginal responses after controlling for environmental variation. We found that dorsal and caudal coloration converged in sympatry, likely reflecting their role in adaptation to local environments, especially concealment from predators. In contrast, aspects of male and female ventral coloration, which harbours sexual signals in both species, diverged in sympatry. This divergence may reduce opportunities for interspecific sexual interactions and the associated loss of energy, suggesting reproductive character displacement (RCD). Our study emphasizes the contrasting patterns of traits involved in different functions and calls for the need to consider this diversity in evolutionary studies.</p>

opencc-zeroJan 2022View details →
zenodo32/100

Unprotected AES furious 128 bit dataset

<p>2 round of unprotected AES furious 128 dataset containing 210k traces, labels and points of interest&nbsp;for multiples intermediates. Saved in NPY files for python3.&nbsp;</p> <p>- 200k traces with random keys&nbsp;</p> <p>- 10k traces with fixed keys. Plaintexts, Keys and Labels under the name &quot;extra . . .npy&quot;</p> <p>&nbsp;</p> <p>Main folders :</p> <p>- tracedata : Traces data split in two, fixed keys and random keys. Random keys are splitted in 10k chunk for memory reasons. Those files can be loaded using&nbsp;numpy.load(file,allow_pickle=True).</p> <p>- timepoints : Points of interest of all intermediates</p> <p>- realvalues : Labels for all intermediates each split in 2 files for training/validation and test.</p> <p>&nbsp;</p>

opencc-by-4.0Nov 2021View details →
zenodo32/100

Dataset and Additional Information for the paper A LINEAR-ALGEBRAIC MODEL FOR ESTIMATING ANTI-LEARNING WHEN A DECISION TREE SOLVES THE PARITY BIT PROBLEM, by ALEXEI LISITSA and ALEXEI VERNITSKI (submitted)

<p>This upload contains a dataset and additional information for the paper&nbsp;A LINEAR-ALGEBRAIC MODEL FOR ESTIMATING<br> ANTI-LEARNING WHEN A DECISION TREE SOLVES THE PARITY BIT PROBLEM, by ALEXEI LISITSA and &nbsp;ALEXEI VERNITSKI (submitted)&nbsp;</p>

opencc-by-4.0May 2022View details →
zenodo32/100

Preliminary experiment for inject-and-diffuse approach in BITS

<p>Preliminary experiment for inject-and-diffuse approach in BITS</p> <p>Data collection:&nbsp;Dec 23, 2021</p> <p>NCI experimental hutch at PAL-XFEL</p> <p>Dataset: Filtered images by Cheetah program.</p>

opencc-by-4.0Aug 2022View details →
zenodo32/100

Polished Wood Chisel Bit. XCB-105-1037

Polished Wood Chisel Bit. XCB-105-1037. 400 BCE-100 CE XCB-105 Adamagan (Aleut for place of walrus hunters) is at the head of Morzhovoi Bay, western Alaska Peninsula. It is a massive village with multiple occupations. When it was occupied 400 BCE-100 CE, it was the largest village in the Arctic with an estimated 1000 people. It also has limited occupations dated 2200-1700 BCE, 1000-600 BCE, and 900-1100 CE. The Western Alaska Peninsula artifacts are presented as a result of the research conducted under grants NSF 9630072, NSF 9814086, NSF 9996372, NSF 9996415, NSF 1139266, NSF 1321411. H. Maschner, Principal Investigator. These artifacts were scanned with either a Faro Edge Arm or a Minolta Vivid 9i. Processed in Geomagic or Polyworks. 2-8 photos were used for texture in Geomagic Wrap. Original digitizing work done at the IVL at Id. St. Univ. Subsequent processing and publication completed at Global Digital Heritage. Source: Objaverse 1.0 / Sketchfab

opencc-by-nc-1.0Jun 2020View details →
zenodo32/100

Hafted Drill Bit. XCB-105-1993

Hafted Drill Bit. XCB-105-1993. 400 BCE-100 CE XCB-105 Adamagan (Aleut for place of walrus hunters) is at the head of Morzhovoi Bay, western Alaska Peninsula. It is a massive village with multiple occupations. When it was occupied 400 BCE-100 CE, it was the largest village in the Arctic with an estimated 1000 people. It also has limited occupations dated 2200-1700 BCE, 1000-600 BCE, and 900-1100 CE. The Western Alaska Peninsula artifacts are presented as a result of the research conducted under grants NSF 9630072, NSF 9814086, NSF 9996372, NSF 9996415, NSF 1139266, NSF 1321411. H. Maschner, Principal Investigator. These artifacts were scanned with either a Faro Edge Arm or a Minolta Vivid 9i. Processed in Geomagic or Polyworks. 2-8 photos were used for texture in Geomagic Wrap. Original digitizing work done at the IVL at Id. St. Univ. Subsequent processing and publication completed at Global Digital Heritage. Source: Objaverse 1.0 / Sketchfab

opencc-by-nc-1.0Jul 2020View details →
zenodo32/100

FIGURE 15 in Contributions to the taxonomy of the Irano-Turanian genus Rhabdosciadium (Apiaceae): Nomenclatural notes, carpology, molecular phylogeny and the description of a new species from Bitlis (Turkey)

FIGURE 15. Mericarp cross-sections of Rhabdosciadium hizanense (A) and R. anatolyi (B). Pr: primary ridges make finger-like projections in R. hizanense (A), but only slightly protrude in R. anatolyi (B); bd: Vascular bundle; Vit: Vittae; P: Pericarp; S: Seed; Endsp: Endosperm; F: Funicle; Hc: Hypodermal collenchyma. Scale bar = 300 μm.

opennotspecifiedMar 2019View details →
zenodo32/100

FIGURE 17. Turkish Rhabdosciadium species R in Contributions to the taxonomy of the Irano-Turanian genus Rhabdosciadium (Apiaceae): Nomenclatural notes, carpology, molecular phylogeny and the description of a new species from Bitlis (Turkey)

FIGURE 17. Turkish Rhabdosciadium species R. hizanense (from the holotype, M. Fırat 32618): a1. Habit; a2. Basal leaves; a3. Fruit. R. anatolyi (from the epitype, M. Fırat 30400): b1. Habit; b2. Basal leaves; b3. Fruit. R. urusakii (topotype M. Fırat 31256): c1. Habit; c2. Basal leaves; c3. Fruit. R. microcalycinum (foto: A. Duran): d1. Habit; d2. Basal leaves; d3. Fruit. R. oligocarpum: e1. Habit (foto: A. Duran); e2. Basal leaves (foto: A. Duran); e3. Fruit (ISTE 99651).

opennotspecifiedMar 2019View details →
zenodo32/100

FIGURE 16 in Contributions to the taxonomy of the Irano-Turanian genus Rhabdosciadium (Apiaceae): Nomenclatural notes, carpology, molecular phylogeny and the description of a new species from Bitlis (Turkey)

FIGURE 16. Primary ridges of Rhabdosciadium hizanense (A) and R. anatolyi (B). e: Epidermis; bd: Vascular bundle; Vit: Vittae; Hc: Hypodermal collenchyma; ps: phloem sclerenchyma;. Xs: xylem sclerenchyma Scale bar = 50 μm.

opennotspecifiedMar 2019View details →
zenodo32/100

FIGURE 14. A in Contributions to the taxonomy of the Irano-Turanian genus Rhabdosciadium (Apiaceae): Nomenclatural notes, carpology, molecular phylogeny and the description of a new species from Bitlis (Turkey)

FIGURE 14. A proliferating umbel of Rhabdosciadium anatolyi at the fruiting stage. P: Peduncle; B: Bract; 1. First-degree umbel; 2. Second-degree umbellules; BR: bracteoles; M: Remains of the male flowers; MER: Mericarps that developed from the central hermaphrodite flower; C: Slightly curved fruit when one of the mericarps is not fully developed; S: Some mericarps, slightly stalked at the base (from the epitype, M. Fırat 30400).

opennotspecifiedMar 2019View details →
zenodo32/100

FIGURE 13. A in Contributions to the taxonomy of the Irano-Turanian genus Rhabdosciadium (Apiaceae): Nomenclatural notes, carpology, molecular phylogeny and the description of a new species from Bitlis (Turkey)

FIGURE 13. A proliferating umbel and umbellules of Rhabdosciadium anatolyi that form a second- or third-degree irregularly branched inflorescence. P: Peduncle; B: Bract; 1. First-degree umbel rays; 2. Second-degree umbellule rays; 3. Third-degree umbellule rays; 4. Pedicels (from the epitype, M. Fırat 30400).

opennotspecifiedMar 2019View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record