cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/1f40684b4a856861855c62972d47c348
title: Activity budgets and space use for two common Pacific parrotfish (Chlorurus Sp.) at Palmyra Atoll National Wildlife Refuge

description: Data was collected at Palmyra Atoll National Wildlife Refuge located in the Central Pacific in 2014, and the work focuses on two species of Parrotfish, Chlorurus microrhinos and Chlorurus spilurus (formerly Cholrurus sordidus). For C. microrhinos, the project was designed to collect fine-scale spatial behavior data, focusing on territory size, species interactions, and benthic impact (i.e. feeding behavior). Focal follow data was collected by one or two observer(s), either on snorkel or SCUBA, and recording focal activity down to the second. Simultaneously, the observer would be towing a GPS that was recording a location every 5 seconds and each location was then associated with a particular behavior. Throughout this study individual fish were identifiable and successive follows were possible on individuals. For C. spilurus the focus of the project was to collect behavioral time budget data on feeding, territorial defense, and spawning behavior. The ‘Chlorurus_Area_Palmyra_2014.csv’ data only covers C. Microrhinos and gives the 95% KUD area estimation for GPS towed tracks, as well as the 95% KUD area for locations where feeding was occurring. We also report the step length between successive points for the entire follow as well as where feeding was occurring. The ‘Chlorurus_Activity_Palmyra_2014.csv’ is for both C. Microrhinos and C. spilurus and reports the start and stop time of each focal follow as well as the start and stop time of each activity. Activity descriptions can be found in the metadata and the total length and phase for each individual in our study can be found in ‘Fish_Information_Chlorurus_Data_2014.csv.
DOI: 10.5066/p9pzux70
title: Volumetric and Mid-Section Discharge Measurement data, Summer through Fall 2020, H.J. Andrews Experimental Forest, Lookout Creek Basin, Oregon

description: Discrete volumetric and mid-section stream discharge measurements were conducted from July through October 2020 in H.J. Andrews Experimental Forest near Blue River, OR. The measured streams are part of the Lookout Creek basin, draining into Blue River and subsequently the McKenzie River on the west slope of the Cascade Range. ORWSC Streamflow measurements supplemented an eco-drought low-flow modeling project in partnership with the Forest and Rangeland Ecosystem Science Center (FRESC) and the USGS Water Mission Area (WMA). Measurements were collected at 25 selected sites with co-located HOBO data loggers and 7 miscellaneous (MISC) sites with no data loggers present. HOBO logger data were collected and processed by FRESC team members. Volumetric measurements were collected by placing a modified weir into the stream and directing the entire streamflow over the weir, easing the collection of water into a bucket. Collections of water were timed to the hundredth of a second using a stopwatch, and volumes were measured with a graduated cylinder in 20 ml increments. Mid-section measurements were conducted following USGS protocol, wading in streams using SonTek FlowTracker-2 handheld acoustic Doppler velocimeters. Sites were measured during two field runs occurring July 6th through 10th 2020 and August 10th through 14th 2020. Two of the sites were measured a third time on October 26th and 27th, 2020, to compare midsection measurements with volumetric measurements. In the streams with HOBO dataloggers, the volumetric measurements achieved satisfactory channeling of the streams with the weir method and are considered more accurate with less uncertainty than the mid-section measurements. Steep channel conditions, large boulders and cobbles through the channel cross-section, large stream velocity angles, non-standard stream velocity profiles, and the channelization of flows created unideal conditions for midsection measurements. The MISC streamflow measurements were conducted at adequate channel cross-sections detailed by USGS protocols.
DOI: 10.6073/pasta/a1a75672f652cfe35406aced8d2ae219
title: Activity budgets and space use for two common Pacific parrotfish (Chlorurus Sp.) at Palmyra Atoll National Wildlife Refuge

description: Data was collected at Palmyra Atoll National Wildlife Refuge located in the Central Pacific in 2014, and the work focuses on two species of Parrotfish, Chlorurus microrhinos and Chlorurus spilurus (formerly Cholrurus sordidus). For C. microrhinos, the project was designed to collect fine-scale spatial behavior data, focusing on territory size, species interactions, and benthic impact (i.e. feeding behavior). Focal follow data was collected by one or two observer(s), either on snorkel or SCUBA, and recording focal activity down to the second. Simultaneously, the observer would be towing a GPS that was recording a location every 5 seconds and each location was then associated with a particular behavior. Throughout this study individual fish were identifiable and successive follows were possible on individuals. For C. spilurus the focus of the project was to collect behavioral time budget data on feeding, territorial defense, and spawning behavior. The ‘Chlorurus_Area_Palmyra_2014.csv’ data only covers C. Microrhinos and gives the 95% KUD area estimation for GPS towed tracks, as well as the 95% KUD area for locations where feeding was occurring. We also report the step length between successive points for the entire follow as well as where feeding was occurring. The ‘Chlorurus_Activity_Palmyra_2014.csv’ is for both C. Microrhinos and C. spilurus and reports the start and stop time of each focal follow as well as the start and stop time of each activity. Activity descriptions can be found in the metadata and the total length and phase for each individual in our study can be found in ‘Fish_Information_Chlorurus_Data_2014.csv.
DOI: 10.6084/m9.figshare.19074188.v1
title: GeneLab Mouse reference genome kraken2 db

description: built as described here: https://github.com/asaravia-butler/GeneLab_Data_Processing/blob/mikes-branch/Metagenomics/Estimate_host_reads_in_raw_data/reference-database-info.md
DOI: 10.5281/zenodo.5908204
title: A hifi testing dataset derived from SRR13128014 (zymo D6331)

description: This is a small dataset subsampled from SRR13128014 which represents a mock community, zymoBIOMICS D6331. We extraced E.coli reads by alignment, then used `seqtk subseq read.fq.gz 0.1` to randomly pick 10% from them. This is created for testing if hifiasm-meta (https://github.com/xfengnefx/hifiasm-meta ) runs. For r57, it roughly needs 170s on 48 threads with peak memory of 18GB. Refer to the tar.gz file for expected results. Hicanu and metaflye should be able to successfully run on this dataset as well.
DOI: 10.5281/zenodo.5908203
title: A hifi testing dataset derived from SRR13128014 (zymo D6331)

description: This is a small dataset subsampled from SRR13128014 which represents a mock community, zymoBIOMICS D6331. We extraced E.coli reads by alignment, then used `seqtk subseq read.fq.gz 0.1` to randomly pick 10% from them. This is created for testing if hifiasm-meta (https://github.com/xfengnefx/hifiasm-meta ) runs. For r57, it roughly needs 170s on 48 threads with peak memory of 18GB. Refer to the tar.gz file for expected results. Hicanu and metaflye should be able to successfully run on this dataset as well.
DOI: 10.17632/sszkyrzrtv.1
title: Table 1. The measured magnesium isotope composition of South China Sea seafloor basalts and international rock standards. 

description: The measured magnesium isotope composition of South China Sea seafloor basalts and international rock standards.
DOI: 10.17632/y6dh9vggf8.1
title: PYR1

description: Gene sequence and gel map
DOI: 10.17632/p57zpdc359.1
title: Diet leaves a genetic signature in a keystone member of the gut microbiota. Dapa et al.

description: Dietary switch from a low-fat and high-fiber diet to a Western-style high-fat and high-sugar diet is a common cause of microbiota imbalances underlying a variety of pathological conditions (i.e. dysbiosis). Although the effects of such dietary changes on microbiota composition and functions are well documented, their putative impact in gut bacterial evolution remains unexplored. We reasoned that the microbiota-dependent functional consequences observed in diet-induced dysbiosis could be caused not only by changes in microbiota composition and in gene/metabolic regulation, but also by evolutionary changes, via the emergence of de novo mutations, which can lead to intra-species changes. To address this hypothesis, we determined the effects of diet on mutational changes in genes at the single species level by monitoring evolutionary adaptation to the gut of mice undergoing different dietary regimens. We focused on Bacteroides thetaiotaomicron (hereafter referred as B. theta) due to its predominance in the mammalian gut. B. theta is a strict anaerobe, and is among the fiber degrading Bacteroides that in the absence of dietary plant polysaccharides can consume host glycans. This bacterium shows phenotypic plasticity by gene and metabolic regulatory mechanisms, which enable it to prioritize usage of carbon sources, and to consume host glycans only in the absence of dietary complex polysaccharides. By following the evolutionary dynamics of B. theta over a 3-month timescale, we observe genetic signatures resulting from diet-specific evolution, fluctuating rapidly as the diet consumed by the mice alternates from high in fat and sugar and low in fiber (Western-style Diet (WD)) to standard high-fiber chow diet (Standard Diet (SD)). Periodic changes in diet led to fluctuations in the frequency of such mutations and were associated with metabolic shifts, resulting in the maintenance of higher intra-species genetic diversity compared to constant dietary regimens. We show that adaptation under WD specifically favors the emergence of mutations advantageous in consumption of mucin O-glycans. This supports the hypothesis that intra-species evolution can influence the microbiota-dependent phenotypes observed upon dietary changes. Finally, through an integrative multi-omic analysis, combining metabolomic and microbiota profiling with the B. theta mutational profile, we show that intra-species mutational diversity is a powerful biomarker of dietary differences between individuals.
DOI: 10.5519/qd.ui9ahmbb
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (62 records)
DOI: 10.5517/ccdc.csd.cc27x9zg
title: CCDC 2082796: Experimental Crystal Structure Determination

description: Related Article: Ming Yang, Xue-Cen Xu, Yue Gong, Yu-Long Zhao|2022|Org.Chem.Front.|9|407|doi:10.1039/D1QO01506K
DOI: 10.5517/ccdc.csd.cc2800y8
title: CCDC 2085399: Experimental Crystal Structure Determination

description: Related Article: Camilla Loro, Letizia Molteni, Marta Papis, Egle M. Beccalli, Donatella Nava, Leonardo Lo Presti, Stefano Brenna, Gioele Colombo, Francesca Foschi, Gianluigi Broggini|2022|J.Org.Chem.|87|1032|doi:10.1021/acs.joc.1c02329
DOI: 10.5517/ccdc.csd.cc286z8r
title: CCDC 2092074: Experimental Crystal Structure Determination

description: Related Article: Juana M. Pérez, Sara Rojas, Amalia García-García, Helena Montes-Andrés, Cristina Ruiz Martínez, Manuel S. Romero-Cano, Duane Choquesillo-Lazarte, Víctor Karim Abdelkader-Fernández, Manuel Pérez-Mendoza, Javier Cepeda, Antonio Rodríguez-Diéguez, Ignacio Fernández|2022|Inorg.Chem.|61|1377|doi:10.1021/acs.inorgchem.1c02864
DOI: 10.5517/ccdc.csd.cc28806s
title: CCDC 2093064: Experimental Crystal Structure Determination

description: Related Article: Vunnam Srinivasulu, Gourishetty Srikanth, Monther A. Khanfar, Imad A. Abu-Yousef, Amin F. Majdalawieh, Ralph Mazitschek, Subbaiah Chennam Setty, Anusha Sebastian, Taleb H. Al-Tel|2022|J.Org.Chem.|87|1377|doi:10.1021/acs.joc.1c02698
DOI: 10.5517/ccdc.csd.cc28807t
title: CCDC 2093065: Experimental Crystal Structure Determination

description: Related Article: Vunnam Srinivasulu, Gourishetty Srikanth, Monther A. Khanfar, Imad A. Abu-Yousef, Amin F. Majdalawieh, Ralph Mazitschek, Subbaiah Chennam Setty, Anusha Sebastian, Taleb H. Al-Tel|2022|J.Org.Chem.|87|1377|doi:10.1021/acs.joc.1c02698
DOI: 10.5517/ccdc.csd.cc28809w
title: CCDC 2093067: Experimental Crystal Structure Determination

description: Related Article: Vunnam Srinivasulu, Gourishetty Srikanth, Monther A. Khanfar, Imad A. Abu-Yousef, Amin F. Majdalawieh, Ralph Mazitschek, Subbaiah Chennam Setty, Anusha Sebastian, Taleb H. Al-Tel|2022|J.Org.Chem.|87|1377|doi:10.1021/acs.joc.1c02698
DOI: 10.5281/zenodo.5904352
title: Data set for "Intertwined spin, charge, and pair correlations in the two-dimensional Hubbard model in the thermodynamic limit"

description: This data set is for the paper "Intertwined spin, charge, and pair correlations in the two-dimensional Hubbard model in the thermodynamic limit". It contains the raw DCA HD5 and DQMC plain text output files, as well as the scripts and final processed data used to generate figures 1-5 of the main text and supplementary figures 1-12. Copies of the figures and latex files are also included for completeness.
DOI: 10.5281/zenodo.5904351
title: Data set for "Intertwined spin, charge, and pair correlations in the two-dimensional Hubbard model in the thermodynamic limit"

description: This data set is for the paper "Intertwined spin, charge, and pair correlations in the two-dimensional Hubbard model in the thermodynamic limit". It contains the raw DCA HD5 and DQMC plain text output files, as well as the scripts and final processed data used to generate figures 1-5 of the main text and supplementary figures 1-12. Copies of the figures and latex files are also included for completeness.
DOI: 10.5517/ccdc.csd.cc289m5d
title: CCDC 2094613: Experimental Crystal Structure Determination

description: Related Article: Chongjiu Lu, Min Ye, Lipeng Long, Yue Zheng, Jiameng Liu, Yue Zhang, Zhengwang Chen|2022|J.Org.Chem.|87|1545|doi:10.1021/acs.joc.1c02498
DOI: 10.5517/ccdc.csd.cc28g1yr
title: CCDC 2098884: Experimental Crystal Structure Determination

description: Related Article: Cody F. Dickinson, Glenn P. A. Yap, Marcus A. Tius|2022|J.Org.Chem.|87|1559|doi:10.1021/acs.joc.1c02583
DOI: 10.5517/ccdc.csd.cc28rztv
title: CCDC 2108428: Experimental Crystal Structure Determination

description: Related Article: Taimin Wang, Biwei Zhang, Lin Hu, Haiyan Sun, Yan Wang, Hongbin Zhai, Bin Cheng|2022|J.Org.Chem.|87|1348|doi:10.1021/acs.joc.1c02649
description: Related Article: Bin Cheng|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28sjrc
title: CCDC 2108953: Experimental Crystal Structure Determination

description: Related Article: Ming Yang, Xue-Cen Xu, Yue Gong, Yu-Long Zhao|2022|Org.Chem.Front.|9|407|doi:10.1039/D1QO01506K
DOI: 10.5517/ccdc.csd.cc28tb8q
title: CCDC 2109713: Experimental Crystal Structure Determination

description: Related Article: Xiao-Xue Liu, Guang-Hui Chen, Jun Tao, Jian Zhang, Lei Zhang|2022|Inorg.Chem.|61|1385|doi:10.1021/acs.inorgchem.1c02891
DOI: 10.5517/ccdc.csd.cc28tn2v
title: CCDC 2110017: Experimental Crystal Structure Determination

description: Related Article: Qiang Hu, Wan-Lei Yu, Yong-Chun Luo, Xiu-Qin Hu, Peng-Fei Xu|2022|J.Org.Chem.|87|1493|doi:10.1021/acs.joc.1c02889
DOI: 10.5517/ccdc.csd.cc28tb7p
title: CCDC 2109712: Experimental Crystal Structure Determination

description: Related Article: Xiao-Xue Liu, Guang-Hui Chen, Jun Tao, Jian Zhang, Lei Zhang|2022|Inorg.Chem.|61|1385|doi:10.1021/acs.inorgchem.1c02891
DOI: 10.5517/ccdc.csd.cc295jqr
title: CCDC 2120484: Experimental Crystal Structure Determination

description: Related Article: Zhi-Wei Wang, Yu Zheng, Yu-En Qian, Jian-Ping Guan, Wei-Dong Lu, Chu-Ping Yuan, Jun-An Xiao, Kai Chen, Hao-Yue Xiang, Hua Yang|2022|J.Org.Chem.|87|1477|doi:10.1021/acs.joc.1c02796
DOI: 10.5517/ccdc.csd.cc296nry
title: CCDC 2121570: Experimental Crystal Structure Determination

description: Related Article: Victoria Haider, Paul Zebrowski, Jessica Michalke, Uwe Monkowius, Mario Waser|2022|Org.Biomol.Chem.|20|824|doi:10.1039/D1OB02235K
DOI: 10.5517/ccdc.csd.cc297cwt
title: CCDC 2122256: Experimental Crystal Structure Determination

description: Related Article: Krishna Gnyawali, Pandula T. Kirinde Arachchige, Chae S. Yi|2021|Org.Lett.|24|218|doi:10.1021/acs.orglett.1c03870
DOI: 10.5517/ccdc.csd.cc298lkr
title: CCDC 2123424: Experimental Crystal Structure Determination

description: Related Article: William P. Thomas, Sergey V. Pronin|2021|J.Am.Chem.Soc.|144|118|doi:10.1021/jacs.1c12283
DOI: 10.5517/ccdc.csd.cc28zktn
title: CCDC 2114752: Experimental Crystal Structure Determination

description: Related Article: Peng Qi, Fang Sun, Ning Chen, Hongguang Du|2022|J.Org.Chem.|87|1133|doi:10.1021/acs.joc.1c02502
DOI: 10.5517/ccdc.csd.cc29cg05
title: CCDC 2126166: Experimental Crystal Structure Determination

description: Related Article: Mukundam Vanga, Alvaro Muñoz-Castro, H. V. Rasika Dias|2022|Dalton Trans.|51|1308|doi:10.1039/D1DT04136C
DOI: 10.5517/ccdc.csd.cc29cg16
title: CCDC 2126167: Experimental Crystal Structure Determination

description: Related Article: Mukundam Vanga, Alvaro Muñoz-Castro, H. V. Rasika Dias|2022|Dalton Trans.|51|1308|doi:10.1039/D1DT04136C
DOI: 10.5281/zenodo.5904923
title: Microswimmers in turbulent fluid flow of Taylor-scale Reynolds number Re = 36 dataset

description: <strong>The data includes the trajectories and the swimming velocities of individual microswimmers embedded in a turbulent fluid flow of Taylor-scale Reynolds number \(Re_{\lambda} = 36\) .</strong> The net swimming velocity of a microswimmer is the sum of the intrinsic swimming velocity and the fluid velocity. The intrinsic swimming velocity is dictated by the swimming parameters, that is, the swimming speed \(v_s\) and the reorientation time \(B\). Different values of swimming parameters are explored. <strong>Item</strong> <strong>\(v_s\)</strong> <strong>\(B\)</strong> S1 5.24 10 S2 0 0 S3 5.24 30 S4 5.24 50 S5 2.62 10 S6 0.53 10 S7 4.39 10 S8 4.18 10 S9 6.80 10 S10 15.47 10 S11 5.24 20 S12 13.08 10 S13 8.25 10 S14 9.49 10 Each column in the file corresponds to the position and net velocity of particles, the fluid vorticity at particle location, particle id, and time step. column number item 0 x - position 1 y - position 2 z - position 3 x - velocity 4 y - velocity 5 z - velocity 15 x - vorticity 16 y - vorticity 17 z - vorticity 19 particle id 20 time step
DOI: 10.5281/zenodo.5904922
title: Microswimmers in turbulent fluid flow of Taylor-scale Reynolds number Re = 36 dataset

description: <strong>The data includes the trajectories and the swimming velocities of individual microswimmers embedded in a turbulent fluid flow of Taylor-scale Reynolds number \(Re_{\lambda} = 36\) .</strong> The net swimming velocity of a microswimmer is the sum of the intrinsic swimming velocity and the fluid velocity. The intrinsic swimming velocity is dictated by the swimming parameters, that is, the swimming speed \(v_s\) and the reorientation time \(B\). Different values of swimming parameters are explored. <strong>Item</strong> <strong>\(v_s\)</strong> <strong>\(B\)</strong> S1 5.24 10 S2 0 0 S3 5.24 30 S4 5.24 50 S5 2.62 10 S6 0.53 10 S7 4.39 10 S8 4.18 10 S9 6.80 10 S10 15.47 10 S11 5.24 20 S12 13.08 10 S13 8.25 10 S14 9.49 10 Each column in the file corresponds to the position and net velocity of particles, the fluid vorticity at particle location, particle id, and time step. column number item 0 x - position 1 y - position 2 z - position 3 x - velocity 4 y - velocity 5 z - velocity 15 x - vorticity 16 y - vorticity 17 z - vorticity 19 particle id 20 time step
DOI: 10.6084/m9.figshare.19027748
title: Table S3 and S4.xlsx

description: The relative abundances of Kos involved in C, N, S cycle transformations of KEGG pathway for bacteria.The top 50 MetaCyc pathways for micro-eukaryotes.
DOI: 10.5517/ccdc.csd.cc29cg27
title: CCDC 2126168: Experimental Crystal Structure Determination

description: Related Article: Mukundam Vanga, Alvaro Muñoz-Castro, H. V. Rasika Dias|2022|Dalton Trans.|51|1308|doi:10.1039/D1DT04136C
DOI: 10.5517/ccdc.csd.cc29cg38
title: CCDC 2126169: Experimental Crystal Structure Determination

description: Related Article: Mukundam Vanga, Alvaro Muñoz-Castro, H. V. Rasika Dias|2022|Dalton Trans.|51|1308|doi:10.1039/D1DT04136C
DOI: 10.5517/ccdc.csd.cc29cg49
title: CCDC 2126170: Experimental Crystal Structure Determination

description: Related Article: Mukundam Vanga, Alvaro Muñoz-Castro, H. V. Rasika Dias|2022|Dalton Trans.|51|1308|doi:10.1039/D1DT04136C
DOI: 10.5517/ccdc.csd.cc28tb9r
title: CCDC 2109714: Experimental Crystal Structure Determination

description: Related Article: Xiao-Xue Liu, Guang-Hui Chen, Jun Tao, Jian Zhang, Lei Zhang|2022|Inorg.Chem.|61|1385|doi:10.1021/acs.inorgchem.1c02891
DOI: 10.6084/m9.figshare.15066189
title: Data files and related resources for word type and space

description: Data files and related resources for word type and space
DOI: 10.6084/m9.figshare.17913863.v4
title: Highly improved single contig genome assembly of thioauto-trophic symbiont of hydrothermal vent mussel Bathymodiolus thermophilus

description: Mytilid mussel <i>Bathymodiolus thermophilus</i> lives in the deep-sea hydrothermal vent regions through a symbiotic relationship with chemosynthetic Gammaproteobacteria. The mussel depends on the nutrient provided by the symbiont residing inside the specialized gill cells. The symbionts in the gill bacteriocytes oxidize the reduced sulfur amply available in the vent environments. Here we sequenced the gill symbiont genome of the mussel from the East Pacific Rise, using PacBio sequencing technology, and assembled the complete genome with a hierarchical genome-assembly process (HGAP3) pipeline. The final symbiont assembly consists of a single contig size of 2.83 Mb, 126x genome coverage, a GC content of 38.6%, 2,156 protein-coding genes, and CheckM completeness of 97.19%. Comparative analysis with other <i>B. thermophilus</i> thiotrophic gill symbiont genomes indicates 1,514 shared gene clusters comprised of core gene sets and common metabolic pathways among thiotrophic mussel symbionts. In contrast, only four unique gene clusters consists of several transposase families and cadherin repeat domain-containing proteins. This complete mussel symbiont genome will be invaluable for further comparative genomic analyses studying structural genome evolution, symbiont strain population diversity, and their physiological adaptive features.
DOI: 10.6084/m9.figshare.14742708.v5
title: Correlated expression of the opsin retrogene LWS-R and its host gene in two poeciliid fishesUntitled Item

description: qPCR data of LWS-R, LWS-R intron, and GPHN form eyeball and brain of guppy and green swordtail<br>