cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8417387
title: additional data

description: df.parquet.gzip is processed raw data. This has some genes but is not fully overwrapped with training/test data drug2gene.csv is a drug-target(gene) combination. Known drug-gene interaction is defined. The combination is already standardised. smiles2fingerprint.csv SMILES (chemical vector structure) is converted to one hot vectorer derived from chemical taxnomy. For instance, if the chemical structure has "CH3" the vector has one for "CH3" columns. This is generated by RDKit
DOI: 10.5281/zenodo.8417560
title: additional data

description: df.parquet.gzip is processed raw data. This has some genes but is not fully overwrapped with training/test data drug2actions.csv is a processd data which has informations about drugs' effectiveness. drug2gene_from_db.csv is a drug-target(gene) interaction from 5 databases. drug2target_from_drugbank.csv is a drug-target(gene) interaction from drugbank. merged_drug_gene_actions.csv is a whole dataset which contains drug2action, and drug2target from drugbank drug2gene.csv is a drug-target(gene) combination. Known drug-gene interaction is defined. The combination is already standardised. smiles2fingerprint.csv SMILES (chemical vector structure) is converted to one hot vectorer derived from chemical taxnomy. For instance, if the chemical structure has "CH3" the vector has one for "CH3" columns. This is generated by RDKit
DOI: 10.5281/zenodo.8419915
title: additional data

description: df.parquet.gzip is processed raw data. This has some genes but is not fully overwrapped with training/test data drug2actions.csv is processd data that has information about drugs' effectiveness. drug2gene_from_db.csv is a drug-target(gene) interaction from 5 databases. drug2target_from_drugbank.csv is a drug-target(gene) interaction from drugbank. gene2go.csv is a gene-gene ontology relation data. Gene ontology is a hierarchal network that shows gene functions such as "Biological functions (GO:000528)". This has gene name, ontology, role, and explanation. merged_drug_gene_actions.csv is a whole dataset that contains drug2action, and drug2target from drug bank. drug2gene.csv is a drug-target(gene) combination. Known drug-gene interaction is defined. The combination is already standardized. smiles2fingerprint.csv SMILES (chemical vector structure) is converted to one hot vector derived from chemical taxonomy. For instance, if the chemical structure has "CH3" the vector has one for "CH3" columns. This is generated by RDKit
DOI: 10.5281/zenodo.8419992
title: additional data

description: df.parquet.gzip is processed raw data. This has some genes but is not fully overwrapped with training/test data


drug2actions.csv is processd data that has information about drugs' effectiveness.


drug2gene_from_db.csv is a drug-target(gene) interaction from 5 databases.


drug2target_from_drugbank.csv is a drug-target(gene) interaction from drugbank.


gene2go.csv is a gene-gene ontology relation data. Gene ontology is a hierarchal network that shows gene functions such as "Biological functions (GO:000528)". This has gene name, ontology, role, and explanation.


gene2go_train.csv is filtered data that is included in training data.


gene2go_onehot.csv is a dummy table, indexes are genes and columns are gene ontology. If they have a relations return True.


merged_drug_gene_actions.csv is a whole dataset that contains drug2action, and drug2target from drug bank.


drug2gene.csv is a drug-target(gene) combination. Known drug-gene interaction is defined. The combination is already standardized.


smiles2fingerprint.csv SMILES (chemical vector structure) is converted to one hot vector derived from chemical taxonomy. For instance, if the chemical structure has "CH3" the vector has one for "CH3" columns. This is generated by RDKit
DOI: 10.5281/zenodo.8404171
title: additional data

description: df.parquet.gzip is processed raw data. This has some genes but is not fully overwrapped with training/test data


drug2actions.csv is processd data that has information about drugs' effectiveness.


drug2gene_from_db.csv is a drug-target(gene) interaction from 5 databases.


drug2target_from_drugbank.csv is a drug-target(gene) interaction from drugbank.


gene2go.csv is a gene-gene ontology relation data. Gene ontology is a hierarchal network that shows gene functions such as "Biological functions (GO:000528)". This has gene name, ontology, role, and explanation.


gene2go_train.csv is filtered data that is included in training data.


gene2go_onehot.csv is a dummy table, indexes are genes and columns are gene ontology. If they have a relations return True.


merged_drug_gene_actions.csv is a whole dataset that contains drug2action, and drug2target from drug bank.


drug2gene.csv is a drug-target(gene) combination. Known drug-gene interaction is defined. The combination is already standardized.


smiles2fingerprint.csv SMILES (chemical vector structure) is converted to one hot vector derived from chemical taxonomy. For instance, if the chemical structure has "CH3" the vector has one for "CH3" columns. This is generated by RDKit
DOI: 10.5281/zenodo.8419930
title: additional data

description: df.parquet.gzip is processed raw data. This has some genes but is not fully overwrapped with training/test data drug2actions.csv is processd data that has information about drugs' effectiveness. drug2gene_from_db.csv is a drug-target(gene) interaction from 5 databases. drug2target_from_drugbank.csv is a drug-target(gene) interaction from drugbank. gene2go.csv is a gene-gene ontology relation data. Gene ontology is a hierarchal network that shows gene functions such as "Biological functions (GO:000528)". This has gene name, ontology, role, and explanation. gene2go_train.csv is filtered data that is included in training data. gene2go_onehot.csv is a dummy table, indexes are genes and columns are gene ontology. If they have a relations return True. merged_drug_gene_actions.csv is a whole dataset that contains drug2action, and drug2target from drug bank. drug2gene.csv is a drug-target(gene) combination. Known drug-gene interaction is defined. The combination is already standardized. smiles2fingerprint.csv SMILES (chemical vector structure) is converted to one hot vector derived from chemical taxonomy. For instance, if the chemical structure has "CH3" the vector has one for "CH3" columns. This is generated by RDKit
DOI: 10.34770/m8rz-5718
title: Alfvén waves at the interface of solar wind and magnetosphere

description: This includes data for Chapter 11 Alfvén waves at the interface of solar wind and magnetosphere in Book "AGU Monograph. Alfvén Waves across Heliophysics: Progress, Challenges, and Opportunities." It includes Matlab data and files for figures 2, 3, 4, 6, 7, 11 and 12 shown in the forthcoming book chapter.
DOI: 10.15468/53tapv
title: Checklist of Pea Clams (Sphaeriidae) in Vermont, USA

description: This is a checklist of the known species of Pea Clams (Sphaeriidae) recorded in Vermont, USA. The checklist is derived from literature and verified records from the Vermont Department of Environmental Conservation and Jim Kellogg (https://doi.org/10.15468/tq5nfn). The checklist is comprised of 28 confirmed species.
DOI: 10.25919/1c8c-q727
title: Parkes observations for project P456 semester 2023OCTS_01

description: The Parkes Pulsar Timing Array (PPTA) project has three primary goals: (a) detection of gravitational waves from astronomical sources, (b) establishment of a pulsar timescale, and (c) improvement of our understanding of Solar-system dynamics. We are now in an exciting regime where a signal detected in our (and other data sets) has the form expected for a gravitational wave background. We are therefore now attempting to confirm, or deny, this exciting result. With this proposal we aim to maintain our pre-eminent position in the field. Unlike most observing proposals, this is a continuing proposal for which the observations will continue to improve bounds on ultra-low-frequency gravitational waves until they are finally detected. Continued Parkes observations will remain valuable at least until the first stage of the SKA is able to improve on our sensitivity and observing cadence. Even after the gravitational wave background is detected we will want to continue observations in support of the nascent field of gravitational wave astronomy!
DOI: 10.25919/55ef-cp56
title: Parkes observations for project P1172 semester 2023OCTS_01

description: PSR J1713+0747 is a very important millisecond pulsar for global pulsar timing array campaigns, due to its long-term observation history, very stable and narrow profile and strong S/N. In April 2021, the pulsar experienced a significant event related to a change in its magnetosphere, presented as an observable change in the pulsar profile. Since then, the pulsar has been slowly recovering and we wish to observe this recovery with high-cadence observations to allow us to create a detailed time-resolved series of variations in the MSPs profile, polarisation, and other properties. Under this proposal, we wish to probe the profile recovery on weekly timescales (once per week per month), revealing additional short timescale behaviours, indicative of changes in the magnetosphere which are not available to other telescopes in the world, thanks to the Parkes UWL. This will also allow us to determine if the magnetosphere has returned to its original configuration or is settling into a new one. Understanding the recovery of this event is key for demonstrating that such pulsars are still viable clocks for use in gravitational wave studies, and in turn, provide us with new data on how the normally stable magnetosphere of this millisecond pulsar responds to an impulsive change in state.
DOI: 10.6084/m9.figshare.24480880
title: Unveiling the hidden diversity and functional role of Chloroflexota in full-scale wastewater treatment plants through genome-centric analyses

description: The phylum Chloroflexota has been found to exhibit high abundance in wastewater treatment plants (WWTPs). However, its metabolic role has not been fully explored due to the lack of cultured isolates. To address this gap, we report the taxonomic analysis of 314 dereplicated, medium- and high-quality metagenome-assembled genomes (MAGs).<b>Only the MAGsdRep assembled in the present study are deposited in Figshare.</b>
DOI: 10.6084/m9.figshare.24480880.v2
title: Unveiling the hidden diversity and functional role of Chloroflexota in full-scale wastewater treatment plants through genome-centric analyses

description: The phylum Chloroflexota has been found to exhibit high abundance in wastewater treatment plants (WWTPs). However, its metabolic role has not been fully explored due to the lack of cultured isolates. To address this gap, we report the taxonomic analysis of 314 dereplicated, medium- and high-quality metagenome-assembled genomes (MAGs).<b>Only the MAGsdRep assembled in the present study are deposited in Figshare.</b>
DOI: 10.6084/m9.figshare.24480880.v1
title: Unveiling the hidden diversity and functional role of Chloroflexota in full-scale wastewater treatment plants through genome-centric analyses

description: The phylum Chloroflexota has been found to exhibit high abundance in wastewater treatment plants (WWTPs). However, its metabolic role has not been fully explored due to the lack of cultured isolates. To address this gap, we report the taxonomic analysis of 314 dereplicated, medium- and high-quality metagenome-assembled genomes (MAGs).<b>Only the MAGsdRep assembled in the present study are deposited in Figshare.</b>
DOI: 10.34740/kaggle/dsv/3991802
title: Sentinel1_NEXRAD
DOI: 10.6073/pasta/78e866ab22a6be991cf19e900f108b32
title: Dataset for: Freshwater biogeochemical hotspots: High primary production and ecosystem respiration in shallow waterbodies

description: This data accompanies the manuscript: "Freshwater biogeochemical hotspots: High primary production and ecosystem respiration in shallow waterbodies" Ponds, wetlands, and shallow lakes (collectively “shallow waterbodies”) are among the most biogeochemically active freshwater ecosystems. Measurements of gross primary production (GPP), respiration (R), and net ecosystem production (NEP) are rare in shallow waterbodies compared to larger and deeper lakes, which can bias our understanding of lentic ecosystem processes. In this study, we calculated GPP, R, and NEP in 26 small, shallow waterbodies across temperate North America and Europe. We observed high rates of GPP (mean 8.4 g O2 m-3 d-1) and R (mean -9.1 g O2 m-3 d-1), while NEP varied from net heterotrophic to autotrophic. Metabolism rates were affected by depth and aquatic vegetation cover, and the shallowest waterbodies had the highest GPP, R, and the most variable NEP. The shallow waterbodies from this study had considerably higher metabolism rates compared to deeper lakes, stressing the importance of these systems as highly productive biogeochemical hotspots.
DOI: 10.34740/kaggle/dsv/6932637
title: Balochi Language to English Translation Dataset
DOI: 10.6084/m9.figshare.24539002
title: GL4U-Intro-2023

description: This zip file contains the lecture slides and jupyter notebooks used in the 2023 GeneLab for Colleges and Universities (GL4U) Introduction module.
DOI: 10.6084/m9.figshare.24539002.v1
title: GL4U-Intro-2023

description: This zip file contains the lecture slides and jupyter notebooks used in the 2023 GeneLab for Colleges and Universities (GL4U) Introduction module.
DOI: 10.3886/e149262v2-142931
title: Data and Code for "Student Performance, Peer Effects, and Friend Networks: Evidence from a Randomized Peer Intervention"

description: The data are from our own experiment. Collaborating with Lonoghui Educational Bureau, two rounds of surveys and three rounds of examinations were conducted. The baseline tests on Chinese and mathematics were conducted in June 2015. The midterm and final exams were conducted in November 2015 and February 2016, respectively. The baseline survey was conducted in September 2015, which was the beginning of a new semester. A follow-up survey with similar questions was conducted in February 2016 after the final exam. The non-cognitive skills of students were measured as well. The initial sample size is 2034, and the follow-up rate is 88.6%
description: Response Rates: 100%
description: Among the students registered in the 36 classes, 2,034 students with baseline scores were collected.
description: Economics of education. Smallest Geographic Unit: county (Longhui)
description: cognitive assessment test; paper and pencil interview (PAPI);
DOI: 10.25573/serc.23960793
title: Dataset: Sediment Carbon Content from three Maine Salt Marshes 1993

description: Sediment cores were collected from three salt marshes in Wells, Maine during the summer of 1993. The purpose was to characterize soil bulk density and carbon content in a tidally restricted marsh (Drakes Island) associated with tidal restoration, compared with two reference marshes (Webhannet and Little River).
DOI: 10.25573/serc.23960793.v1
title: Dataset: Sediment Carbon Content from three Maine Salt Marshes 1993

description: Sediment cores were collected from three salt marshes in Wells, Maine during the summer of 1993. The purpose was to characterize soil bulk density and carbon content in a tidally restricted marsh (Drakes Island) associated with tidal restoration, compared with two reference marshes (Webhannet and Little River).
DOI: 10.25573/serc.23960793.v2
title: Dataset: Sediment Carbon Content from three Maine Salt Marshes 1993

description: Sediment cores were collected from three salt marshes in Wells, Maine during the summer of 1993. The purpose was to characterize soil bulk density and carbon content in a tidally restricted marsh (Drakes Island) associated with tidal restoration, compared with two reference marshes (Webhannet and Little River).
DOI: 10.5517/ccdc.csd.cc2bkt0r
title: CCDC 2162064: Experimental Crystal Structure Determination

description: Related Article: Koichi Nakaoka, Chao Guo, Yuta Saiki, Shin Furukawa, Tadashi Ema|2022|J.Org.Chem.|88|15444|doi:10.1021/acs.joc.2c01666
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cpd6p
title: CCDC 2195302: Experimental Crystal Structure Determination

description: Related Article: Chien-Wei Chiang, Kai-Wun Jhang, Jeng-Lung Chen, Liang-Ching Hsu, Wei-Hsiang Huang, Hung-Chi Chen, Ting-Jun Lin, Ci-Yang Sun, Yu-Ning Li|2023|CSD Communication|||
description: Related Article: Chien-Wei Chiang, Kai-Wun Jhang, Jeng-Lung Chen, Liang-Ching Hsu, Wei-Hsiang Huang, Hung-Chi Chen, Ting-Jun Lin, Ci-Yang Sun, Yu-Ning Li|2023|Chem.Commun.|59|9774|doi:10.1039/D3CC02784H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ddvh5
title: CCDC 2216887: Experimental Crystal Structure Determination

description: Related Article: Kyohei Nakano, Iat Wai Leong, Daisuke Hashizume, Kirill Bulgarevich, Kazuo Takimiya, Yusuke Nishiyama, Toshio Yamazaki, Keisuke Tajima|2023|Chemical Science|14|12205|doi:10.1039/D3SC04125E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ddvj6
title: CCDC 2216888: Experimental Crystal Structure Determination

description: Related Article: Kyohei Nakano, Iat Wai Leong, Daisuke Hashizume, Kirill Bulgarevich, Kazuo Takimiya, Yusuke Nishiyama, Toshio Yamazaki, Keisuke Tajima|2023|Chemical Science|14|12205|doi:10.1039/D3SC04125E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.10093057
title: ОРГАНИЧЕСКАЯ ДОБАВКА ДЛЯ НЕЙТРАЛИЗАЦИИ ХИМИЧЕСКОЙ АГРЕССИВНОСТИ ДРЕВЕСНОГО НАПОЛНИТЕЛЯ В ГЛИНОЦЕМЕНТНЫХ КОМПОЗИТАХ
title: SCIENCE AND EDUCATION:  MODERN TIME

description: В современных условиях производства строительных материалов и конструкций, значительным резервом повышения эффективности и ресурсо энергосбережения является снижение материалоемкости и использование вторичных ресурсов. В этой связи целесообразно наращивать темпы применения легких заполнителей минерального и органического генезиса из побочных продуктов промышленностей. Определенный интерес представляют отходы деревообрабатывающего производства. Однако отходы деревообработки продукты специфичные и обладают свойствами, которые могут оказывать как положительное, так и отрицательное влияние на структурообразование и физико-механические  показатели композиционного материала [1]. Сложность применения отходов деревообработки заключается в химической агрессивности препятствующая процессам схватывания, твердения и структурообразования цементной композиции. Наиболее активное воздействие на эти процессы оказывают экстрактивные вещества, так называемые «цементные яды», в частности это углеводы и простейшие водорастворимые сахара (фруктоза, глюкоза, сахароза), в меньшей степени – гемицеллюлоза, крахмал, танины и смол
DOI: 10.5281/zenodo.10093058
title: ОРГАНИЧЕСКАЯ ДОБАВКА ДЛЯ НЕЙТРАЛИЗАЦИИ ХИМИЧЕСКОЙ АГРЕССИВНОСТИ ДРЕВЕСНОГО НАПОЛНИТЕЛЯ В ГЛИНОЦЕМЕНТНЫХ КОМПОЗИТАХ
title: SCIENCE AND EDUCATION:  MODERN TIME

description: В современных условиях производства строительных материалов и конструкций, значительным резервом повышения эффективности и ресурсо энергосбережения является снижение материалоемкости и использование вторичных ресурсов. В этой связи целесообразно наращивать темпы применения легких заполнителей минерального и органического генезиса из побочных продуктов промышленностей. Определенный интерес представляют отходы деревообрабатывающего производства. Однако отходы деревообработки продукты специфичные и обладают свойствами, которые могут оказывать как положительное, так и отрицательное влияние на структурообразование и физико-механические  показатели композиционного материала [1]. Сложность применения отходов деревообработки заключается в химической агрессивности препятствующая процессам схватывания, твердения и структурообразования цементной композиции. Наиболее активное воздействие на эти процессы оказывают экстрактивные вещества, так называемые «цементные яды», в частности это углеводы и простейшие водорастворимые сахара (фруктоза, глюкоза, сахароза), в меньшей степени – гемицеллюлоза, крахмал, танины и смол
DOI: 10.6084/m9.figshare.24539050
title: <b>Dataset: High methane concentrations in tidal salt marsh soils: where does the methane go?</b>

description: Tidal salt marshes produce and emit CH<sub>4</sub>. Therefore, it is critical to understand the biogeochemical controls that regulate CH<sub>4</sub> spatial and temporal dynamics in wetlands. The prevailing paradigm assumes that acetoclastic methanogenesis is the dominant pathway for CH<sub>4</sub> production, and higher salinity concentrations inhibit CH<sub>4 </sub>production in salt marshes. Recent evidence shows that CH<sub>4</sub> is produced within salt marshes via methylotrophic methanogenesis, a process not inhibited by sulfate reduction. To further explore this conundrum, we performed measurements of soil-atmosphere CH<sub>4</sub> and<sub> </sub>CO<sub>2 </sub>fluxes coupled with depth profiles of soil CH<sub>4</sub> and CO<sub>2</sub> pore water gas concentrations, stable and radioisotopes, pore water chemistry, and microbial community composition to assess CH<sub>4</sub> production and fate within a temperate tidal salt marsh. We found unexpectedly high CH<sub>4</sub> concentrations up to 145,000 μmol mol<sup>-1</sup> positively correlated with S<sup>2-</sup> (salinity range: 6.6 to 14.5 ppt). Despite large CH<sub>4</sub> production within the soil, soil-atmosphere CH<sub>4</sub> fluxes were low but with higher emissions and extreme variability during plant senescence (84.3 ± 684.4 nmol m<sup>-2</sup> s<sup>-1</sup>). CH<sub>4</sub> and CO<sub>2</sub> within the soil pore water were produced from young carbon, with most Δ<sup>14</sup>C-CH<sub>4</sub><sup> </sup>and Δ<sup>14</sup>C-CO<sub>2</sub> values at or above modern. We found evidence that CH<sub>4</sub> within soils was produced by methylotrophic and hydrogenotrophic methanogenesis. Several pathways exist after CH<sub>4</sub> is produced, including diffusion into the atmosphere, CH<sub>4</sub> oxidation, and lateral export to adjacent tidal creeks; the latter being the most likely dominant flux. Our findings demonstrate that CH<sub>4</sub> production and fluxes are biogeochemically heterogeneous, with multiple processes and pathways that can co-occur and vary in importance over the year. This study highlights the potential for high CH<sub>4</sub> production, the need to understand the underlying biogeochemical controls, and the challenges of evaluating CH<sub>4</sub> budgets and blue carbon in salt marshes.
DOI: 10.5281/zenodo.10092433
title: A twofold perspective on the quality of research publications: The use of ICTs and research activity models

description: Results of the study
DOI: 10.5281/zenodo.10092434
title: A twofold perspective on the quality of research publications: The use of ICTs and research activity models

description: Results of the study