Dataset Card for STS-ca

  Dataset Summary

STS-ca corpus is a benchmark for evaluating Semantic Text Similarity in Catalan. This dataset was developed by BSC TeMU as part of Projecte AINA, to enrich the Catalan Language Understanding Benchmark (CLUB). This work is licensed under a Attribution-ShareAlike 4.0 International License.

  Supported Tasks and Leaderboards

This dataset can be used to build and score semantic similarity models in Catalan.… See the full description on the dataset page: https://huggingface.co/datasets/projecte-aina/sts-ca.

Spoken versions of the Semantic Textual Similarity dataset for testing semantic sentence level embeddings. Contains thousands of sentence pairs annotated by humans for semantic similarity. The spoken sentences can be used in sentence embedding models to test whether your model learns to capture sentence semantics. All sentences available in 6 synthetic Wavenet voices and a subset (5%) in 4 real voices recorded in a sound attenuated booth. Code to train a visually grounded spoken sentence embedding model and evaluation code is available at https://github.com/DannyMerkx/speech2image/tree/Interspeech21

Dataset

This dataset was created by terrychan

Contents

For Semantic Text Similarity, we collected the Spanish test sets from SemEval-2014 (Agirre et al., 2014) and SemEval-2015 (Agirre et al., 2015). Since no training data was provided for the Spanish subtask, we randomly sampled both datasets into 1,321 sentences for the train set, 78 sentences for the development set, and 156 sentences for the test set. To make the task harder for the models, we purposely made the development set smaller than the test set.

Note. The Δχ2 indicates a change in a χ2 from the modified hypothesized model. A significant Δ χ2 value indicates that the model was significantly different from the modified hypothesized model. STS = secondary traumatic stress; T1 = Time 1; T2 = Time 2.**p < .01*p < .05.Goodness-Of-Fit Statistics for Comparisons Between the Modified Hypothesized and the Nested Models in Two Studies.

For metabolomics study, tumor-bearing mice were starved for 6 hours before sarcoma and skeletal muscles were harvested.

This archive contains the data and models for Blue Brain Search.

They are in the format of a DVC remote.

Indeed, Blue Brain Search uses DVC to track machine learning models and datasets and to make them shareable and reproducible.

Each archive corresponds to a specific version of Blue Brain Search.

Please note that the archive for v0.1.0 is 4.3 GB once extracted.

The instructions to create an archive for a new version of Blue Brain Search is as follow:

git clone --depth 1 --branch 

For v0.1.0, this takes around ~3 mins 15 to create the archive.

KorSTS is a dataset for semantic textural similarity (STS) in Korean. The dataset is constructed by automatically the STS-B dataset. To ensure translation quality, two professional translators with at least seven years of experience who specialize in academic papers/books as well as business contracts post-edited a half of the dataset each and cross-checked each other’s translation afterward. The KorSTS dataset comprises 5,749 training examples translated automatically and 2,879 evaluation examples translated manually.

A range of LSTM, GP and STS models (provided as Jupyter notebooks) and yearly data (provided as excel files) used for developing explainable approaches for building electricity demand forecasting. A index of the models is also provided.

Cricket DRS

## Overview

Cricket DRS is a dataset for object detection tasks - it contains Ball Bat Stumps Pad annotations for 718 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 [Public Domain license](https://creativecommons.org/licenses/Public Domain).

Accuracy of main Egyptian models tested based on Spearman rank correlation between the cosine similarity of sentence representations and the reference labels of the testing dataset in [8] after translation to Egyptian Arabic.

SyntheticEmbeddingDataset-UA: small-v1

Small (100k+) sythetic dataset for fine-tuning text embedding models for Ukraininan language (STS task)

This study presents the first global transcriptional profiling and phenotypic characterization of the major human opportunistic fungal pathogen Candida albicans grown in spaceflight conditions. Microarray analysis revealed that C. albicans subjected to short-term spaceflight culture differentially regulated 454 genes compared to synchronous ground controls which represented 8.4% of the analyzed ORFs. Spaceflight-cultured C. albicans induced genes involved in cell aggregation (similar to flocculation) which was validated by microscopic and flow cytometry analysis. We also observed enhanced random budding of spaceflight-cultured cells as opposed to more normal bipolar budding patterns for ground samples in accordance with the gene expression data. Furthermore genes involved in antifungal agent and stress resistance were differentially regulated in spaceflight including induction of ABC transporters and members of the major facilitator family downregulation of ergosterol-encoding genes and upregulation of genes involved in oxidative stress resistance. Finally downregulation of genes involved in the actin cytoskeleton was observed. Interestingly the transcriptional regulator Cap1 and over 30% of the Cap1 regulon was differentially expressed in spaceflight-cultured C. albicans. A potential role for Cap1 in the spaceflight response of C. albicans is suggested as this regulator is involved in random budding cell aggregation actin cytoskeleton and oxidative stress resistance; all related to observed spaceflight-associated changes of C. albicans. While culture of C. albicans in microgravity potentiates a global change in gene expression that could induce a virulence-related phenotype no increased virulence in a murine intraperitoneal (i.p.) infection model was observed. This study represents an important basis for the assessment of the risk that commensal flora could play during spaceflight missions. Furthermore since the low fluid-shear environment of microgravity is relevant to physical forces encountered by pathogens during the infection process insights gained from this study could identify novel infectious disease mechanisms with downstream benefits for the general public. Cells were grown for 24 hours on the space shuttle or as ground-based controls preserved in RNALater and stored at -80C. Four samples of each flight- and ground-based controls were harvested for microarray analysis. GAP is Group Activation Pack and each GAP contains 8 FPAs. The numbers represent the # assigned to the particular GAP and the number assigned to the specific FPA (1-8) within the indicated GAP. The same hardware is used for the flight samples and the ground samples.

A new construction pre-supporting system, Steel Tube Slab system (STS), is proposed for large underground space excavation with shallow depth. The adjacent steel pipes in STS method are connected by a couple of flanges, bolt and concrete in order to improve the flexural capacity and lateral stiffness of the whole structure. STS method is firstly adopted to construct the ultra-shallow buried and large span subway station in China. Ground settlement and structural deformation are monitored during the construction. A numerical model is established for the subway station, the reliability of the numerical model is verified by comparing the numerical results with monitored data. The influence of large span underground excavation on surrounding soil and existing buildings in soft soils are investigated. Results prove that STS method can effectively control and reduce the ground settlement during construction. This study can provide a strong guidance for application of STS method in soft soils.

The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME) modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS) approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient response of Mig1 tend to be faster, more extended, and displays an increased cell-to-cell variability.

aS: number of segregating sites. bSin:number of singletons. cSpecific sites: sites polymorphic in one population but monomorphic in the other. dθ: Watterson estimator of sequence diversity per site, π: average number of differences per site between two sequences. eNumber of lineages with at least one singleton. fD values were calculated using Fabsim [50], P-values of D were calculated for the standard coalescent model (*: p

Analysis of ‘Candida albicans response to spaceflight (NASA STS-115) --- GSM1231690_Slide_43’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/c2c5814c-cc8b-426c-8e29-acf7fcf01004 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

https://c3.nasa.gov/genelab/accession/GLDS-20/

This study presents the first global transcriptional profiling and phenotypic characterization of the major human opportunistic fungal pathogen, Candida albicans, grown in spaceflight conditions. Microarray analysis revealed that C. albicans subjected to short-term spaceflight culture differentially regulated 454 genes compared to synchronous ground controls, which represented 8.4% of the analyzed ORFs. Spaceflight-cultured C. albicans induced genes involved in cell aggregation (similar to flocculation), which was validated by microscopic and flow cytometry analysis. We also observed enhanced random budding of spaceflight-cultured cells as opposed to more normal bipolar budding patterns for ground samples, in accordance with the gene expression data. Furthermore, genes involved in antifungal agent and stress resistance were differentially regulated in spaceflight, including induction of ABC transporters and members of the major facilitator family, downregulation of ergosterol-encoding genes, and upregulation of genes involved in oxidative stress resistance. Finally, downregulation of genes involved in the actin cytoskeleton was observed. Interestingly, the transcriptional regulator Cap1 and over 30% of the Cap1 regulon was differentially expressed in spaceflight-cultured C. albicans. A potential role for Cap1 in the spaceflight response of C. albicans is suggested, as this regulator is involved in random budding, cell aggregation, actin cytoskeleton, and oxidative stress resistance; all related to observed spaceflight-associated changes of C. albicans. While culture of C. albicans in microgravity potentiates a global change in gene expression that could induce a virulence-related phenotype, no increased virulence in a murine intraperitoneal (i.p.) infection model was observed. This study represents an important basis for the assessment of the risk that commensal flora could play during spaceflight missions. Furthermore, since the low fluid-shear environment of microgravity is relevant to physical forces encountered by pathogens during the infection process, insights gained from this study could identify novel infectious disease mechanisms, with downstream benefits for the general public. Cells were grown for 24 hours on the space shuttle or as ground-based controls, preserved in RNALater, and stored at -80C. Four samples of each flight- and ground-based controls were harvested for microarray analysis. GAP is Group Activation Pack and each GAP contains 8 FPAs. The numbers represent the # assigned to the particular GAP and the number assigned to the specific FPA (1-8) within the indicated GAP. The same hardware is used for the flight samples and the ground samples.

--- Original source retains full ownership of the source dataset ---

Radiotherapy is recommended for G2-G3 large Soft Tissue Sarcoma (STS) in association with radical wide excision in order to improve the local control of disease, but side-effects may develop early after radiation invalidating wound healing. The aim of this study was to evaluate retrospectively short- and long-term clinically relevant outcomes after surgery of limb STS with or without radiotherapy. A total of 243 patients with limb STS treated at the Veneto Institute Oncology (Padua, Italy) in 2015-2022 were included. Outcome measures were short- and long-term wound complications, length of hospital stay and outpatient care time. Multivariable analyses were performed using linear regression models and logistic regression models. 87 patients received neoadjuvant radiotherapy, 64 received adjuvant radiotherapy, and 92 underwent surgery alone. At short-term, multivariable analysis identified neoadjuvant radiotherapy as a risk factor for prolonged length of hospital stay (MD 6.4 days, 95%CI 3.9 to 9.0 days) and short-term wound complications (OR 3.45, 95%CI 1.82 to 6.62). At long-term, neoadjuvant radiotherapy was a risk factor for long-term wound complications (OR 4.87, 95%CI 2.48 to 9.84), and longer outpatient care time (MD 83 days, 95%CI 41 to 126 days); similarly, adjuvant radiotherapy was also a risk factor for long-term complications (OR 5.20, 95%CI 2.57 to 10.95) and longer outpatient care time (MD 62 days, 95%CI 19 to 106 days). Radiotherapy in limb STS was associated with impaired short- and long-term clinically relevant outcomes, potentially affecting quality of life and healthcare costs. Balancing with its well-known oncological benefits, new clinical strategies are needed to contain cutaneous radiogenic side effects.

https://c3.nasa.gov/genelab/accession/GLDS-20/ This study presents the first global transcriptional profiling and phenotypic characterization of the major human opportunistic fungal pathogen, Candida albicans, grown in spaceflight conditions. Microarray analysis revealed that C. albicans subjected to short-term spaceflight culture differentially regulated 454 genes compared to synchronous ground controls, which represented 8.4% of the analyzed ORFs. Spaceflight-cultured C. albicans induced genes involved in cell aggregation (similar to flocculation), which was validated by microscopic and flow cytometry analysis. We also observed enhanced random budding of spaceflight-cultured cells as opposed to more normal bipolar budding patterns for ground samples, in accordance with the gene expression data. Furthermore, genes involved in antifungal agent and stress resistance were differentially regulated in spaceflight, including induction of ABC transporters and members of the major facilitator family, downregulation of ergosterol-encoding genes, and upregulation of genes involved in oxidative stress resistance. Finally, downregulation of genes involved in the actin cytoskeleton was observed. Interestingly, the transcriptional regulator Cap1 and over 30% of the Cap1 regulon was differentially expressed in spaceflight-cultured C. albicans. A potential role for Cap1 in the spaceflight response of C. albicans is suggested, as this regulator is involved in random budding, cell aggregation, actin cytoskeleton, and oxidative stress resistance; all related to observed spaceflight-associated changes of C. albicans. While culture of C. albicans in microgravity potentiates a global change in gene expression that could induce a virulence-related phenotype, no increased virulence in a murine intraperitoneal (i.p.) infection model was observed. This study represents an important basis for the assessment of the risk that commensal flora could play during spaceflight missions. Furthermore, since the low fluid-shear environment of microgravity is relevant to physical forces encountered by pathogens during the infection process, insights gained from this study could identify novel infectious disease mechanisms, with downstream benefits for the general public. Cells were grown for 24 hours on the space shuttle or as ground-based controls, preserved in RNALater, and stored at -80C. Four samples of each flight- and ground-based controls were harvested for microarray analysis. GAP is Group Activation Pack and each GAP contains 8 FPAs. The numbers represent the # assigned to the particular GAP and the number assigned to the specific FPA (1-8) within the indicated GAP. The same hardware is used for the flight samples and the ground samples.

RO-STS-Corpus

  Overview

RoSTSC is a Romanian Semantic Textual Similarity (STS) dataset designed for evaluating and training sentence embedding models. It contains pairs of Romanian sentences along with similarity scores that indicate the degree of semantic equivalence between them.

  Dataset Structure

sentence1: The first sentence in the pair. sentence2: The second sentence in the pair. score: A numerical value representing the semantic similarity between the two… See the full description on the dataset page: https://huggingface.co/datasets/BlackKakapo/RoSTSC.