cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19793358.v1
title: Additional file 4 of Contribution of a novel gene to lysergic acid amide synthesis in Metarhizium brunneum

description: Additional file 4. Spreadsheet containing data analyzed in Figs. 2 and 3 and Additional file 2: Table S1.
DOI: 10.5281/zenodo.6560847
title: RuCoLA benchmark

description: <strong>Russian Corpus of Linguistic Acceptability</strong> The Russian Corpus of Linguistic Acceptability (RuCoLA) is a dataset consisting of Russian language sentences with their binary acceptability judgements. It includes expert-written sentences from linguistic publications and machine-generated examples. The corpus covers a variety of language phenomena, ranging from syntax and semantics to generative model hallucinations. We release RuCoLA to facilitate the development of methods for identifying errors in natural language and create a public leaderboard to track the progress made on this problem. <strong>About</strong> In recent years, natural language processing systems have rapidly improved in quality for a number of tasks, many of which involve concepts as difficult as common sense or even general world knowledge. This trend was enabled by the emergence of large-scale self-supervised pretraining methods that formed the backbone of mainstream language models like BERT or GPT-3. Such models have surpassed human performance on canonical NLU benchmarks and proved capable of generating texts hardly distinguishable from those written by humans. Despite these impressive results, modern language models are still far from perfect, particularly for the Russian language. Although passages from generative models may seem human-like at first glance, they tend to be rife with hallucinated facts or contradictory information. Furthermore, a growing number of studies have reported that even the largest language models do not properly capture various linguistic phenomena and have limited ability to make fine-grained judgments about the correct use of language. With that in mind, we designed RuCoLA as a benchmark for evaluating the linguistic competence of Russian language models. RuCoLA follows the general concept of linguistic acceptability: unlike grammatical correctness, which relates to the structure of language, acceptability denotes whether the utterance would be considered natural by a native speaker. Thus, a grammatical sentence can be unacceptable (e.g., “Colorless green ideas sleep furiously”), but an acceptable sentence has to be grammatical. Similarly to GLUE-style and probing benchmarks (e.g., GLUE, Russian SuperGLUE and RuSentEval), it can be used to compare the general language understanding capabilities of neural networks or to analyze and improve the fluency and consistency of text generation models.
DOI: 10.6084/m9.figshare.19793361
title: Additional file 1 of Impact of crustal deformation detection by the DSI (difference of split-band interferograms) method with PALSAR-2 data: a case study on the 2016 Kumamoto Earthquake

description: Additional file 1: Table S1. PALSAR-2 data analyzed in this study.
DOI: 10.6084/m9.figshare.19793361.v1
title: Additional file 1 of Impact of crustal deformation detection by the DSI (difference of split-band interferograms) method with PALSAR-2 data: a case study on the 2016 Kumamoto Earthquake

description: Additional file 1: Table S1. PALSAR-2 data analyzed in this study.
DOI: 10.6084/m9.figshare.19793364
title: Additional file 2 of Impact of crustal deformation detection by the DSI (difference of split-band interferograms) method with PALSAR-2 data: a case study on the 2016 Kumamoto Earthquake

description: Additional file 2: Table S2. Comparison of the slant-range changes from GNSS, DSI, InSAR, and offset-tracking for Path 28.
DOI: 10.6084/m9.figshare.19793364.v1
title: Additional file 2 of Impact of crustal deformation detection by the DSI (difference of split-band interferograms) method with PALSAR-2 data: a case study on the 2016 Kumamoto Earthquake

description: Additional file 2: Table S2. Comparison of the slant-range changes from GNSS, DSI, InSAR, and offset-tracking for Path 28.
DOI: 10.6084/m9.figshare.19793367.v1
title: Additional file 3 of Impact of crustal deformation detection by the DSI (difference of split-band interferograms) method with PALSAR-2 data: a case study on the 2016 Kumamoto Earthquake

description: Additional file 3: Table S3. Comparison of the slant-range changes from GNSS, DSI, InSAR, and offset-tracking for Path 126.
DOI: 10.6084/m9.figshare.19793367
title: Additional file 3 of Impact of crustal deformation detection by the DSI (difference of split-band interferograms) method with PALSAR-2 data: a case study on the 2016 Kumamoto Earthquake

description: Additional file 3: Table S3. Comparison of the slant-range changes from GNSS, DSI, InSAR, and offset-tracking for Path 126.
DOI: 10.5281/zenodo.6560846
title: RuCoLA benchmark

description: <strong>Russian Corpus of Linguistic Acceptability</strong> The Russian Corpus of Linguistic Acceptability (RuCoLA) is a dataset consisting of Russian language sentences with their binary acceptability judgements. It includes expert-written sentences from linguistic publications and machine-generated examples. The corpus covers a variety of language phenomena, ranging from syntax and semantics to generative model hallucinations. We release RuCoLA to facilitate the development of methods for identifying errors in natural language and create a public leaderboard to track the progress made on this problem. <strong>About</strong> In recent years, natural language processing systems have rapidly improved in quality for a number of tasks, many of which involve concepts as difficult as common sense or even general world knowledge. This trend was enabled by the emergence of large-scale self-supervised pretraining methods that formed the backbone of mainstream language models like BERT or GPT-3. Such models have surpassed human performance on canonical NLU benchmarks and proved capable of generating texts hardly distinguishable from those written by humans. Despite these impressive results, modern language models are still far from perfect, particularly for the Russian language. Although passages from generative models may seem human-like at first glance, they tend to be rife with hallucinated facts or contradictory information. Furthermore, a growing number of studies have reported that even the largest language models do not properly capture various linguistic phenomena and have limited ability to make fine-grained judgments about the correct use of language. With that in mind, we designed RuCoLA as a benchmark for evaluating the linguistic competence of Russian language models. RuCoLA follows the general concept of linguistic acceptability: unlike grammatical correctness, which relates to the structure of language, acceptability denotes whether the utterance would be considered natural by a native speaker. Thus, a grammatical sentence can be unacceptable (e.g., “Colorless green ideas sleep furiously”), but an acceptable sentence has to be grammatical. Similarly to GLUE-style and probing benchmarks (e.g., GLUE, Russian SuperGLUE and RuSentEval), it can be used to compare the general language understanding capabilities of neural networks or to analyze and improve the fluency and consistency of text generation models.
DOI: 10.6084/m9.figshare.19128758
title: Additional file 1 of The use of osmoregulators and antioxidants to mitigate the adverse impacts of salinity stress in diploid and tetraploid potato genotypes (Solanum spp.)

description: Additional file 1: Data S1. Plant morphological and physiological characteristics, enzymes activity and callus induction of 13 genotypes of potato divided into 7 tetraploid cultivars of Solanum tuberosum (tbr), and 6 diploid clones of S. chacoense (chc) grown in vitro under stress conditions. Explants were grown on media supplemented with four different concentrations of NaCl (0.0, 100, 200 or 300 mmol L−1).
DOI: 10.6084/m9.figshare.19128758.v1
title: Additional file 1 of The use of osmoregulators and antioxidants to mitigate the adverse impacts of salinity stress in diploid and tetraploid potato genotypes (Solanum spp.)

description: Additional file 1: Data S1. Plant morphological and physiological characteristics, enzymes activity and callus induction of 13 genotypes of potato divided into 7 tetraploid cultivars of Solanum tuberosum (tbr), and 6 diploid clones of S. chacoense (chc) grown in vitro under stress conditions. Explants were grown on media supplemented with four different concentrations of NaCl (0.0, 100, 200 or 300 mmol L−1).
DOI: 10.6084/m9.figshare.19793423.v1
title: Additional file 5 of Genome-wide identification of sugar transporter gene family in Brassicaceae crops and an expression analysis in the radish

description: Additional file 5: Table S1. The identified STP genes in six Brassicaceae species. Table S2. The physical and chemical properties of STP proteins.
DOI: 10.6084/m9.figshare.19793426
title: Additional file 6 of Genome-wide identification of sugar transporter gene family in Brassicaceae crops and an expression analysis in the radish

description: Additional file 6: Table S3. Primers used for RT-qPCR in the present study.
DOI: 10.6084/m9.figshare.19793423
title: Additional file 5 of Genome-wide identification of sugar transporter gene family in Brassicaceae crops and an expression analysis in the radish

description: Additional file 5: Table S1. The identified STP genes in six Brassicaceae species. Table S2. The physical and chemical properties of STP proteins.
DOI: 10.6084/m9.figshare.19793426.v1
title: Additional file 6 of Genome-wide identification of sugar transporter gene family in Brassicaceae crops and an expression analysis in the radish

description: Additional file 6: Table S3. Primers used for RT-qPCR in the present study.
DOI: 10.5281/zenodo.6561449
title: Predicted 13C NMR Chemical Shifts of Natural Products

description: The Natural Product structures are those from the COCONUTv5 database . Predictions were obtained by means of the "Check Chemical Shifts" method from ACD/Labs C+H NMR Predictors and DB software, version 2020.1.0. The acd_coconut.zip archive contains a single file, acd_coconut.sdf, a collection of 2D structures from COCONUT supplemented by <sup>13</sup>C NMR chemical shifts values from ACD/Labs CNMR Predictor in verification mode. The file mol1.sdf describes the first compound in acd_coconut.sdf and indicates how chemical shift values are encoded. SDF tags related to NMR: &lt;CNMR_SHIFTS&gt; for ACD/Labs DB software &lt;Predicted 13C shifts&gt;, &lt;Quaternaries&gt;, &lt;Tertiaries&gt;, &lt;Secondaries&gt;, &lt;Primaries&gt; for MixONat &lt;NMREDATA_ASSIGNMENT&gt;, &lt;NMREDATA_ORIGIN&gt; in the style of NMReDATA The calculation workflow is based on tools developped here. No attempt was made to change unlikely tautomers (like aliphatic iminols standing for aliphatic amides). Unlikely structures are likely associated to unlikely predicted chemical shift value sets.
description: A new version in which unlikely structures are replaced by more likely ones will be necessary.
DOI: 10.5281/zenodo.6561448
title: Predicted 13C NMR Chemical Shifts of Natural Products

description: The Natural Product structures are those from the COCONUTv5 database . Predictions were obtained by means of the "Check Chemical Shifts" method from ACD/Labs C+H NMR Predictors and DB software, version 2020.1.0. The acd_coconut.zip archive contains a single file, acd_coconut.sdf, a collection of 2D structures from COCONUT supplemented by <sup>13</sup>C NMR chemical shifts values from ACD/Labs CNMR Predictor in verification mode. The file mol1.sdf describes the first compound in acd_coconut.sdf and indicates how chemical shift values are encoded. SDF tags related to NMR: &lt;CNMR_SHIFTS&gt; for ACD/Labs DB software &lt;Predicted 13C shifts&gt;, &lt;Quaternaries&gt;, &lt;Tertiaries&gt;, &lt;Secondaries&gt;, &lt;Primaries&gt; for MixONat &lt;NMREDATA_ASSIGNMENT&gt;, &lt;NMREDATA_ORIGIN&gt; in the style of NMReDATA The calculation workflow is based on tools developped here. No attempt was made to change unlikely tautomers (like aliphatic iminols standing for aliphatic amides). Unlikely structures are likely associated to unlikely predicted chemical shift value sets.
description: A new version in which unlikely structures are replaced by more likely ones will be necessary.
DOI: 10.6084/m9.figshare.17126074
title: Additional file 1 of Unification of Treatments and Interventions for Tinnitus Patients (UNITI): a study protocol for a multi-center randomized clinical trial

description: Additional file 1. Ethical approvals from Germany, Spain, Greece and Belgium. Informed consent form – RCT. Information sheet – RCT. Informed consent form – blood sampling. Information sheet – blood sampling. UNITI data management plan. WHO trial registration dataset.
DOI: 10.6084/m9.figshare.19793429
title: Additional file 1 of MAIT cell counts are associated with the risk of hospitalization in COPD

description: Additional file 1. Staining panels.
DOI: 10.6084/m9.figshare.19793429.v1
title: Additional file 1 of MAIT cell counts are associated with the risk of hospitalization in COPD

description: Additional file 1. Staining panels.
DOI: 10.6084/m9.figshare.17126074.v1
title: Additional file 1 of Unification of Treatments and Interventions for Tinnitus Patients (UNITI): a study protocol for a multi-center randomized clinical trial

description: Additional file 1. Ethical approvals from Germany, Spain, Greece and Belgium. Informed consent form – RCT. Information sheet – RCT. Informed consent form – blood sampling. Information sheet – blood sampling. UNITI data management plan. WHO trial registration dataset.
DOI: 10.6084/m9.figshare.19793445
title: Additional file 1 of Draft genome of Gongronella butleri reveals the genes contributing to its biodegradation potential

description: Additional file 1: Supplementary material 1. Annotation for the 10,024 proteins through BLASTx against all fungal protein sequences available at Uniprot Protein Database
DOI: 10.6084/m9.figshare.19793445.v1
title: Additional file 1 of Draft genome of Gongronella butleri reveals the genes contributing to its biodegradation potential

description: Additional file 1: Supplementary material 1. Annotation for the 10,024 proteins through BLASTx against all fungal protein sequences available at Uniprot Protein Database
DOI: 10.6084/m9.figshare.19793448
title: Additional file 2 of Draft genome of Gongronella butleri reveals the genes contributing to its biodegradation potential

description: Additional file 2: Supplementary material 2. Characteristics of the microsatellites mined from Gongronella butleri genome
DOI: 10.6084/m9.figshare.19793451
title: Additional file 3 of Draft genome of Gongronella butleri reveals the genes contributing to its biodegradation potential

description: Additional file 3: Supplementary material 3. SNPs identified through variant analysis in Gongronella butleri genome against Cunninghamella genome
DOI: 10.6084/m9.figshare.19793448.v1
title: Additional file 2 of Draft genome of Gongronella butleri reveals the genes contributing to its biodegradation potential

description: Additional file 2: Supplementary material 2. Characteristics of the microsatellites mined from Gongronella butleri genome
DOI: 10.6084/m9.figshare.19793451.v1
title: Additional file 3 of Draft genome of Gongronella butleri reveals the genes contributing to its biodegradation potential

description: Additional file 3: Supplementary material 3. SNPs identified through variant analysis in Gongronella butleri genome against Cunninghamella genome
DOI: 10.6084/m9.figshare.19793468
title: Additional file 1 of Non-linear transformation of enzyme-linked immunosorbent assay (ELISA) measurements allows usage of linear models for data analysis

description: Additional file 1. R script for transformation of optical density values from an ELISA test. The script expects a column sample that contains the string bc for each buffer control, the string sample for each sample in the trial and the string serialdilution_ and the corresponding number of the sample of the serial dilution for each sample of the serial dilution. The R script is also available at https://github.com/tmlange/TransformELISA.
DOI: 10.6084/m9.figshare.19793468.v1
title: Additional file 1 of Non-linear transformation of enzyme-linked immunosorbent assay (ELISA) measurements allows usage of linear models for data analysis

description: Additional file 1. R script for transformation of optical density values from an ELISA test. The script expects a column sample that contains the string bc for each buffer control, the string sample for each sample in the trial and the string serialdilution_ and the corresponding number of the sample of the serial dilution for each sample of the serial dilution. The R script is also available at https://github.com/tmlange/TransformELISA.
DOI: 10.6084/m9.figshare.19793471
title: Additional file 2 of Non-linear transformation of enzyme-linked immunosorbent assay (ELISA) measurements allows usage of linear models for data analysis

description: Additional file 2. Data from the presented trial with six columns. One column describes the sample, one column describes the ELISA plate, and one column contains the corresponding optical density value from the ELISA test. Three more columns describe the factors to be analysed in the trial: The genotype, the environment, and the harvest time point.
DOI: 10.6084/m9.figshare.19793471.v1
title: Additional file 2 of Non-linear transformation of enzyme-linked immunosorbent assay (ELISA) measurements allows usage of linear models for data analysis

description: Additional file 2. Data from the presented trial with six columns. One column describes the sample, one column describes the ELISA plate, and one column contains the corresponding optical density value from the ELISA test. Three more columns describe the factors to be analysed in the trial: The genotype, the environment, and the harvest time point.
DOI: 10.6084/m9.figshare.19793474
title: Additional file 3 of Non-linear transformation of enzyme-linked immunosorbent assay (ELISA) measurements allows usage of linear models for data analysis

description: Additional file 3. Description of the 28 groups via sample size (n), p value from the D’Agostino K2 test (pA) for each response variable, and p value from the Shapiro-Wilk test (pS) for each response variable. For all analyses, OD values (OD) and transformed data (C) were used as response variables. For the group with genotype KWS D grown in environment 2 and harvested at time point 2, only 3 data points were available. Thus, for this group neither Shapiro-Wilk test nor D’Agostino K2 test were performed.
DOI: 10.6084/m9.figshare.19793474.v1
title: Additional file 3 of Non-linear transformation of enzyme-linked immunosorbent assay (ELISA) measurements allows usage of linear models for data analysis

description: Additional file 3. Description of the 28 groups via sample size (n), p value from the D’Agostino K2 test (pA) for each response variable, and p value from the Shapiro-Wilk test (pS) for each response variable. For all analyses, OD values (OD) and transformed data (C) were used as response variables. For the group with genotype KWS D grown in environment 2 and harvested at time point 2, only 3 data points were available. Thus, for this group neither Shapiro-Wilk test nor D’Agostino K2 test were performed.
DOI: 10.6084/m9.figshare.19793480.v1
title: Additional file 2 of Comparative genome analysis among Variovorax species and genome guided aromatic compound degradation analysis emphasizing 4-hydroxybenzoate degradation in Variovorax sp. PAMC26660

description: Additional file 2: Supplementary Table S4. Laterally transferred genes predicted by Island Viewer 4 tool.
DOI: 10.6084/m9.figshare.19793480
title: Additional file 2 of Comparative genome analysis among Variovorax species and genome guided aromatic compound degradation analysis emphasizing 4-hydroxybenzoate degradation in Variovorax sp. PAMC26660

description: Additional file 2: Supplementary Table S4. Laterally transferred genes predicted by Island Viewer 4 tool.
DOI: 10.6084/m9.figshare.19793483
title: Additional file 3 of Comparative genome analysis among Variovorax species and genome guided aromatic compound degradation analysis emphasizing 4-hydroxybenzoate degradation in Variovorax sp. PAMC26660

description: Additional file 3: Supplementary Table S5. Analyzing the presence (√) and absence (×) of genes related to peripheral and central aromatic compound catabolism pathway as shown by KEGG pathway analysis in each genome of Variovorax species.
DOI: 10.6084/m9.figshare.19793483.v1
title: Additional file 3 of Comparative genome analysis among Variovorax species and genome guided aromatic compound degradation analysis emphasizing 4-hydroxybenzoate degradation in Variovorax sp. PAMC26660

description: Additional file 3: Supplementary Table S5. Analyzing the presence (√) and absence (×) of genes related to peripheral and central aromatic compound catabolism pathway as shown by KEGG pathway analysis in each genome of Variovorax species.
DOI: 10.6084/m9.figshare.19793486
title: Additional file 4 of Comparative genome analysis among Variovorax species and genome guided aromatic compound degradation analysis emphasizing 4-hydroxybenzoate degradation in Variovorax sp. PAMC26660

description: Additional file 4: Supplementary Table S6. Primer designed for qRT–PCR.
DOI: 10.6084/m9.figshare.19793486.v1
title: Additional file 4 of Comparative genome analysis among Variovorax species and genome guided aromatic compound degradation analysis emphasizing 4-hydroxybenzoate degradation in Variovorax sp. PAMC26660

description: Additional file 4: Supplementary Table S6. Primer designed for qRT–PCR.
DOI: 10.6084/m9.figshare.19793510
title: Additional file 2 of Systematic identification of miRNA-regulatory networks unveils their potential roles in sugarcane response to Sorghum mosaic virus infection

description: Additional file 2: Table S1. The statistic result of sRNA-seq data in 12 samples. Table S2. The statistic result of annotation and classification of the small RNAs (%). Table S3. The differentially expressed miRNAs in sugarcane varieties ROC22 and FN39 infected by SrMV. Table S4. List of 653 annotated predicted target genes corresponding to 132 identified miRNAs. Table S5. List of predicted target genes corresponding to the differentially expressed miRNAs. Table S6. The quantitative primers ofthe 12 selected miRNAs. Table S7. The quantitative primers of the 15 predicted target genes. Table S8. Primers used for cloning the candidate miRNAs and expression analysis of the Nicotiana benthamiana immune-related marker genes.
DOI: 10.6084/m9.figshare.19793510.v1
title: Additional file 2 of Systematic identification of miRNA-regulatory networks unveils their potential roles in sugarcane response to Sorghum mosaic virus infection

description: Additional file 2: Table S1. The statistic result of sRNA-seq data in 12 samples. Table S2. The statistic result of annotation and classification of the small RNAs (%). Table S3. The differentially expressed miRNAs in sugarcane varieties ROC22 and FN39 infected by SrMV. Table S4. List of 653 annotated predicted target genes corresponding to 132 identified miRNAs. Table S5. List of predicted target genes corresponding to the differentially expressed miRNAs. Table S6. The quantitative primers ofthe 12 selected miRNAs. Table S7. The quantitative primers of the 15 predicted target genes. Table S8. Primers used for cloning the candidate miRNAs and expression analysis of the Nicotiana benthamiana immune-related marker genes.