cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11369007
title: A primary care learning collaborative to improve office systems and clinical management of pediatric asthma

description: Pediatric asthma is a common, relapsing-remitting, chronic inflammatory airway disease that when uncontrolled often leads to substantial patient and health care system burden. Improving management of asthma in primary care can help patients stay well controlled. The Vermont Child Health Improvement Program (VCHIP) developed a quality improvement (QI) learning collaborative with a primary objective to improve clinical asthma management measures through improvement in primary care office systems to support asthma care. Seven months of medical record review data were evaluated for improvements on eight clinical asthma management measures. Pre and post office systems inventory (OSI) self-assessments detailing adherence to improvement strategies were analyzed for improvement. Logistic regressions were used to test for associations between OSI strategy post scores and the corresponding clinical asthma management measures by month seven. This study found significant improvement from baseline to month seven on seven of the eight clinical asthma management measures and between pre and post OSI for seven of the nine strategies assessed (<i>N</i> = 19 practices). Additionally, one point higher average OSI scores on the assessment and monitoring of asthma severity, asthma control, asthma action plans, and asthma education strategies were associated with significantly greater odds of improvement in their respective clinical asthma management measures. A QI learning collaborative approach in primary care can improve office systems and corresponding clinical management measures for pediatric patients with asthma. This suggests that linking specific office systems strategies to clinical measures may be a helpful tactic within the learning collaborative model.
DOI: 10.25919/7t8a-8k84
title: Parkes observations for project P1032 semester 2021APRS_02

description: This project aims to continue to perform rapid measurements of relativistic parameters of southern binary pulsar systems using data from the Parkes Ultra Wideband Low (UWL) receiver and the MeerKAT telescope thereby enabling measurement of their component masses and in some cases, test theories of gravity. We will use the UWL data to obtain significant orbital coverage and timing baseline on these pulsars and obtain important constraints on orbital and temporal DM variations that will help in identifying the nature of the companion star. We will then use MeerKAT data at crucial orbital phases to improve our chances of measuring the relativistic parameters. Increase in the number of measured NS masses has profound implications for NS internal structure and for stellar and binary evolution physics. From this semester, we are converting this proposal into a ``Large project" proposal.
DOI: 10.25919/6jsn-jr32
title: Parkes observations for project P1038 semester 2021APRS_03

description: PSR~J1759-2402 is one of a small handful of pulsars which are in orbit about high mass stars. Its orbital period is 8.3 years and the orbit is highly eccentric with periastron expected in 2021 March. Although discovered at Parkes, the Lovell telescope has been monitoring the pulsar over many years. However, it’s restricted bandwidth, maintenance schedule and poorer polarization capability make it unsuitable to follow the pulsar as it enters and leaves the eclipse by the companion. In contrast, the UWL on Parkes with its wide- band and excellent polarization characteristics means that we can, and already have determined scattering, polarization, dispersion measure and rotation measure changes as the pulsar enters its companion wind. We request a continuation of our weekly observations of the pulsar to track its progress on the far side of periastron.
DOI: 10.25919/93q0-vb73
title: Parkes observations for project P885 semester 2021APRS_03

description: We propose to continue observing the magnetars 1E 1547.0-5408 and PSR J1622-4950 weekly, to track their rotation, flux density, and polarisation. The revolutionary UWL capabilities promise new opportunities to disentangle still mysterious radio emission mechanisms in magnetars. This promise is supported by the recent follow up of XTE J1810-197, again a radio magnetar after 10 years dormant, and of the hot-off-the-press magnetar Swift J1818.0-1607, for which our exciting recent results with UWL motivate an increased monitoring cadence to once weekly.
DOI: 10.6084/m9.figshare.11338823.v1
title: Betaine Supplementation Moderately Increases Total Cholesterol Levels: A Systematic Review and Meta-Analysis

description: Betaine is used to lower elevated plasma homocysteine levels, which are a risk factor for cardiovascular diseases (CVD). However, some studies have shown that betaine may have a negative effect on blood lipids. Betaine supplementation is becoming more and more common, but the relationship between betaine supplementation and blood lipoprotein levels are unclear. The purpose of the study described here was thus to perform a meta-analysis of randomized placebo-controlled trials on the effects of betaine supplementation at a daily dose of at least 4 g on blood lipids in adults. Six randomized controlled trials published between 2002 and 2018 were identified. All six studies used adult participants supplemented with at least 4 g/d of betaine for six to twenty-four weeks. A meta-analysis was carried out using a random-effects model, and the overall effect size was calculated for changes in plasma total cholesterol (TC), HDL cholesterol, LDL cholesterol, and triglycerides (TG). The pooled estimate of the effects of betaine supplementation compared to placebo on TC was 0.34 mmol/L (95% CI: 0.02, 0.65), <i>p</i> = 0.0352. No significant effect was observed for LDL, HDL, or TG. Supplementation with at least 4 g/d of betaine for a minimum of six weeks may moderately increase plasma TC, which might be important in the context of cardiovascular health.
DOI: 10.25919/hqxy-6v06
title: Parkes observations for project PX500 semester 2021APRS_03

description: This proposal relates to time purchased by the Chinese Academy of Sciences for Parkes follow-up confirmation and timing of FAST discoveries. As the observing time has been purchased this proposal (and the related PX501) does not require TAC grading. The primary reason for submitting a proposal is to ensure an outreach statement and that the proposal is entered into OPAL for the data archive to access. The Chinese team have two time requests. The time scheduled for the first, relating to this proposal, will be allocated in blocks of 24 hours and the data will become available in the data archive with an 18 month embargo period. The second type of time will be scheduled in shorter blocks and the data archived with a 10 year embargo.
DOI: 10.5517/ccrkx28
title: CCDC 702400: Experimental Crystal Structure Determination

description: Related Article: Ji-Hua Deng, Zhi-Xing Xiong, Yan-Ping Yi, Lin Yuan, Hui-Rui Guo, Meng-Ping Guo, Lin Liu|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1159|doi:10.1107/S160053680802549X
DOI: 10.5517/ccrkx39
title: CCDC 702401: Experimental Crystal Structure Determination

description: Related Article: Zhiyong Fu, Shuqiong Bai|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1161|doi:10.1107/S1600536808025233
DOI: 10.5517/ccrl4t8
title: CCDC 702640: Experimental Crystal Structure Determination

description: Related Article: Zhan Ling Li, Ya Wen Xuan, Wen Wu, Dong Po Xie|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1162|doi:10.1107/S1600536808025579
DOI: 10.5517/ccrkx4b
title: CCDC 702402: Experimental Crystal Structure Determination

description: Related Article: Shi-Jia Long, Xiao-Lan Liu, Yong-Hong Liu|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1164|doi:10.1107/S1600536808025518
DOI: 10.5517/ccrkx5c
title: CCDC 702403: Experimental Crystal Structure Determination

description: Related Article: Fang Chen, Heng-Yun Ye|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1165|doi:10.1107/S1600536808025531
DOI: 10.5517/ccrkx6d
title: CCDC 702404: Experimental Crystal Structure Determination

description: Related Article: Wei Xiong, Huihui Xing, Yan Su, Zilu Chen|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1166|doi:10.1107/S1600536808025701
DOI: 10.5517/ccrkx7f
title: CCDC 702405: Experimental Crystal Structure Determination

description: Related Article: Wei Xiong, Huihui Xing, Yan Su, Zilu Chen|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1168|doi:10.1107/S1600536808025713
DOI: 10.5517/ccrkx8g
title: CCDC 702406: Experimental Crystal Structure Determination

description: Related Article: Li-Tao An, Jian Zhou, Jian-Feng Zhou, Min Xia|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1170|doi:10.1107/S1600536808025671
DOI: 10.5517/ccrkx9h
title: CCDC 702407: Experimental Crystal Structure Determination

description: Related Article: Hong-Xu Guo, Min Liang, Bin Lin, Qing-Hua Wang, Xi-Zhong Li|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1171|doi:10.1107/S160053680802583X
DOI: 10.5517/ccrkxbj
title: CCDC 702408: Experimental Crystal Structure Determination

description: Related Article: M.Ramos Silva, E.Motyeian, H.Aghabozorg, M.Ghadermazi|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1173|doi:10.1107/S160053680802566X
DOI: 10.5517/ccrkxck
title: CCDC 702409: Experimental Crystal Structure Determination

description: Related Article: B.B.M.D.Soume, R.Yahya, S.N.Gan, S.W.Ng|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1175|doi:10.1107/S1600536808025798
DOI: 10.5517/ccrkxdl
title: CCDC 702410: Experimental Crystal Structure Determination

description: Related Article: P.Poplaukhin, E.R.T.Tiekink|2008|Acta Crystallogr.,Sect.E:Struct.Rep.Online|64|m1176|doi:10.1107/S1600536808025889
DOI: 10.5517/ccdc.csd.cc13x82c
title: CCDC 1040052: Experimental Crystal Structure Determination

description: Related Article: Vanda Dašková, Jeffrey Buter, Anne K. Schoonen, Martin Lutz, Folkert Vries, Ben L. Feringa|2021|Angew.Chem.,Int.Ed.|60|11120|doi:10.1002/anie.202014955
DOI: 10.5517/ccdc.csd.cc21vbt2
title: CCDC 1902154: Experimental Crystal Structure Determination

description: Related Article: Hualong Chen, Yajing Liu, Xuebo Cheng, Senbiao Fang, Yuli Sun, Zequn Yang, Wei Zheng, Xunming Ji, Zehui Wu|2021|Angew.Chem.,Int.Ed.|60|10833|doi:10.1002/anie.202102174
DOI: 10.5517/ccdc.csd.cc21vbv3
title: CCDC 1902155: Experimental Crystal Structure Determination

description: Related Article: Hualong Chen, Yajing Liu, Xuebo Cheng, Senbiao Fang, Yuli Sun, Zequn Yang, Wei Zheng, Xunming Ji, Zehui Wu|2021|Angew.Chem.,Int.Ed.|60|10833|doi:10.1002/anie.202102174
DOI: 10.5517/ccdc.csd.cc21vby6
title: CCDC 1902158: Experimental Crystal Structure Determination

description: Related Article: Hualong Chen, Yajing Liu, Xuebo Cheng, Senbiao Fang, Yuli Sun, Zequn Yang, Wei Zheng, Xunming Ji, Zehui Wu|2021|Angew.Chem.,Int.Ed.|60|10833|doi:10.1002/anie.202102174
DOI: 10.5517/ccdc.csd.cc23z9hx
title: CCDC 1965539: Experimental Crystal Structure Determination

description: Related Article: S. Pangajavalli, R. Ranjith Kumar, S. Ramaswamy|2021|J.Mol.Struct.|1239|130503|doi:10.1016/j.molstruc.2021.130503
DOI: 10.5517/ccdc.csd.cc25vs50
title: CCDC 2021732: Experimental Crystal Structure Determination

description: Related Article: Chengming Li, Zhenmei Huang, Yanmei Hu, Wenbo Liang, Rongchuan Su, Mao Chen, Linsen Zhou, Di Wu, Ge Gao, Jingsong You|2021|Org.Lett.|23|3746|doi:10.1021/acs.orglett.1c01156
DOI: 10.5517/ccdc.csd.cc25vs61
title: CCDC 2021733: Experimental Crystal Structure Determination

description: Related Article: Chengming Li, Zhenmei Huang, Yanmei Hu, Wenbo Liang, Rongchuan Su, Mao Chen, Linsen Zhou, Di Wu, Ge Gao, Jingsong You|2021|Org.Lett.|23|3746|doi:10.1021/acs.orglett.1c01156
DOI: 10.5439/1532341
title: HSRL Liquid cloud base height (nsaC1)

description: Liquid layers in clouds affect their microphysical processes, as well as the surface energy budget. Studies focusing on these and other areas of research are often in need of skillful estimation of liquid-bearing cloud-layer boundaries. The bases of these layers are predominantly determined by ground-based lidar instruments. Most studies requiring liquid cloud base height (LCBH) information use either fixed lidar depolarization and/or backscatter cross-section thresholds or cloud base height data products that do not distinguish between ice and liquid, all of which might introduce inconsistencies and errors in the resolved LCBH. This data set contains LCBH data at 1-min temoporal resolution based on an explicit LCBH detection algorithm, which uses the high-spectral-resolution lidar (HSRL) data. Examination of this algorithm in multiple cases and scenarios during numerous days and first-order comparison with microwave-radiometer data show satisfactory results.
DOI: 10.34740/kaggle/dsv/2190153
title: Bitcoin Market Trade Informativeness and Liquidity
DOI: 10.5439/1764692
title: HSRL Liquid cloud base height

description: Liquid layers in clouds affect their microphysical processes, as well as the surface energy budget. Studies focusing on these and other areas of research are often in need of skillful estimation of liquid-bearing cloud-layer boundaries. The bases of these layers are predominantly determined by ground-based lidar instruments. Most studies requiring liquid cloud base height (LCBH) information use either fixed lidar depolarization and/or backscatter cross-section thresholds or cloud base height data products that do not distinguish between ice and liquid, all of which might introduce inconsistencies and errors in the resolved LCBH. This data set contains LCBH data at 1-min temoporal resolution based on an explicit LCBH detection algorithm, which uses the high-spectral-resolution lidar (HSRL) data. Examination of this algorithm in multiple cases and scenarios during numerous days and first-order comparison with microwave radiometer data show satisfactory results.
DOI: 10.5281/zenodo.4743315
title: Features values of Solid-State Lithium Battery datasets

description: Features values of Solid-State Lithium Battery datasets.
DOI: 10.5281/zenodo.4697237
title: Features values of Solid-State Lithium Battery datasets

description: Features values of Solid-State Lithium Battery datasets.
DOI: 10.6084/m9.figshare.14558842
title: Additional file 1 of Short‐term outcomes in infants with mild neonatal encephalopathy: a retrospective, observational study

description: Maternal and neonatal characteristics and short-term outcomes in infants. This file shows maternal and neonatal characteristics and short-term outcomes of all screened infants by severity.
DOI: 10.6084/m9.figshare.14558842.v1
title: Additional file 1 of Short‐term outcomes in infants with mild neonatal encephalopathy: a retrospective, observational study

description: Maternal and neonatal characteristics and short-term outcomes in infants. This file shows maternal and neonatal characteristics and short-term outcomes of all screened infants by severity.
DOI: 10.6084/m9.figshare.14558845
title: Additional file 2 of Short‐term outcomes in infants with mild neonatal encephalopathy: a retrospective, observational study

description: Comparison among infants with mild NE according to whether therapeutic hypothermia was provided or not. This file shows maternal and neonatal characteristics of infants with mild NE according to whether therapeutic hypothermia was provided or not.
DOI: 10.6084/m9.figshare.14558848
title: Additional file 3 of Short‐term outcomes in infants with mild neonatal encephalopathy: a retrospective, observational study

description: Details of infants with abnormal short-term outcomes. This file shows detailed data for infants with mild neonatal encephalopathy who had an abnormal short-term outcome.
DOI: 10.6084/m9.figshare.14558845.v1
title: Additional file 2 of Short‐term outcomes in infants with mild neonatal encephalopathy: a retrospective, observational study

description: Comparison among infants with mild NE according to whether therapeutic hypothermia was provided or not. This file shows maternal and neonatal characteristics of infants with mild NE according to whether therapeutic hypothermia was provided or not.
DOI: 10.6084/m9.figshare.14558848.v1
title: Additional file 3 of Short‐term outcomes in infants with mild neonatal encephalopathy: a retrospective, observational study

description: Details of infants with abnormal short-term outcomes. This file shows detailed data for infants with mild neonatal encephalopathy who had an abnormal short-term outcome.
DOI: 10.6084/m9.figshare.14558858.v1
title: Additional file of Specific and conserved patterns of microbiota-structuring by maize benzoxazinoids in the field

description: Additional file of Specific and conserved patterns of microbiota-structuring by maize benzoxazinoids in the field
DOI: 10.6084/m9.figshare.14558861
title: Additional file 2 of Specific and conserved patterns of microbiota-structuring by maize benzoxazinoids in the field

description: Additional file 1: Supplementary Results. Figure S1. Setup of field experiments. Figure S2. Analysis steps. Figure S3. Sequencing effort by sample groups. Figure S4. Sampling intensity analysis. Figure S5. Taxonomy. Figure S6. Alpha diversity. Figure S7. BX-sensitive rhizosphere microbes across locations. Figure S8. Taxonomic patterns of BX-sensitive rhizosphere microbes. Figure S9. Abundance of Methylophilaceae bOTUs across compartments and locations. Table S1. Deposition of raw sequence data. Table S2. Soil characteristics in each location. Table S3. Taxonomic analysis comparing locations and compartments. Table S4. Alpha diversity analysis comparing locations and compartments. Table S5. Beta diversity analysis comparing locations and compartments. Table S6. Taxonomic analysis (phylum level) comparing BX effects in each compartment. Table S7. Taxonomic analysis (family level) comparing BX effects in each compartment and location. Table S8. Alpha diversity analysis comparing BX effects in each compartment. Table S9. Beta diversity analysis comparing BX and location effects in each compartment. Table S10. Beta diversity analysis comparing genetic background and genotype effects in each compartment (Reckenholz experiment). Table S11. zOTUs differing by genetic background or genotype (Reckenholz experiment). Table S12. Beta diversity analysis comparing mutant genotypes in each compartment (Aurora experiment). Table S13. zOTUs differing by mutant genotypes (Aurora experiment). Table S14. BX-sensitive zOTUs across all locations.
DOI: 10.6084/m9.figshare.14558861.v1
title: Additional file 2 of Specific and conserved patterns of microbiota-structuring by maize benzoxazinoids in the field

description: Additional file 1: Supplementary Results. Figure S1. Setup of field experiments. Figure S2. Analysis steps. Figure S3. Sequencing effort by sample groups. Figure S4. Sampling intensity analysis. Figure S5. Taxonomy. Figure S6. Alpha diversity. Figure S7. BX-sensitive rhizosphere microbes across locations. Figure S8. Taxonomic patterns of BX-sensitive rhizosphere microbes. Figure S9. Abundance of Methylophilaceae bOTUs across compartments and locations. Table S1. Deposition of raw sequence data. Table S2. Soil characteristics in each location. Table S3. Taxonomic analysis comparing locations and compartments. Table S4. Alpha diversity analysis comparing locations and compartments. Table S5. Beta diversity analysis comparing locations and compartments. Table S6. Taxonomic analysis (phylum level) comparing BX effects in each compartment. Table S7. Taxonomic analysis (family level) comparing BX effects in each compartment and location. Table S8. Alpha diversity analysis comparing BX effects in each compartment. Table S9. Beta diversity analysis comparing BX and location effects in each compartment. Table S10. Beta diversity analysis comparing genetic background and genotype effects in each compartment (Reckenholz experiment). Table S11. zOTUs differing by genetic background or genotype (Reckenholz experiment). Table S12. Beta diversity analysis comparing mutant genotypes in each compartment (Aurora experiment). Table S13. zOTUs differing by mutant genotypes (Aurora experiment). Table S14. BX-sensitive zOTUs across all locations.
DOI: 10.6084/m9.figshare.14558864
title: Additional file 3 of Specific and conserved patterns of microbiota-structuring by maize benzoxazinoids in the field

description: Additional file 2: Experimental design with the sample-to-barcode assignments.
DOI: 10.6084/m9.figshare.14558858
title: Additional file of Specific and conserved patterns of microbiota-structuring by maize benzoxazinoids in the field

description: Additional file of Specific and conserved patterns of microbiota-structuring by maize benzoxazinoids in the field
DOI: 10.6084/m9.figshare.14558864.v1
title: Additional file 3 of Specific and conserved patterns of microbiota-structuring by maize benzoxazinoids in the field

description: Additional file 2: Experimental design with the sample-to-barcode assignments.
DOI: 10.6084/m9.figshare.14558867
title: Additional file 4 of Specific and conserved patterns of microbiota-structuring by maize benzoxazinoids in the field

description: Additional file 3: Bioinformatic script.
DOI: 10.6084/m9.figshare.14558867.v1
title: Additional file 4 of Specific and conserved patterns of microbiota-structuring by maize benzoxazinoids in the field

description: Additional file 3: Bioinformatic script.
DOI: 10.6084/m9.figshare.14558941
title: Additional file 1 of Performance evaluation of the Q.Clear reconstruction framework versus conventional reconstruction algorithms for quantitative brain PET-MR studies

description: Additional file 1: Supplementary file 1. Fig. 1 Bland-Altman plots assessing agreement between FBP with 5mm and Q.Clear with different β values, for the contrast recovery data obtained from the NEMA phantom. FBP 5mm and Q.Clear β100 (A); FBP 5mm and Q.Clear β200 (B); FBP 5mm and Q.Clear β300 (C); FBP 5mm and Q.Clear β400 (D); FBP 5mm and Q.Clear β500 (E). Fig. 2 Bland-Altman plots assessing agreement between FBP with 5mm and Q.Clear with different β values, for the contrast recovery data obtained from the NEMA phantom. FBP 5mm and Q.Clear β600 (F); FBP 5mm and Q.Clear β700 (G); FBP 5mm and Q.Clear β800 (H); FBP 5mm and Q.Clear β900 (I); FBP 5mm and Q.Clear β1000 (J).
DOI: 10.6084/m9.figshare.14558941.v1
title: Additional file 1 of Performance evaluation of the Q.Clear reconstruction framework versus conventional reconstruction algorithms for quantitative brain PET-MR studies

description: Additional file 1: Supplementary file 1. Fig. 1 Bland-Altman plots assessing agreement between FBP with 5mm and Q.Clear with different β values, for the contrast recovery data obtained from the NEMA phantom. FBP 5mm and Q.Clear β100 (A); FBP 5mm and Q.Clear β200 (B); FBP 5mm and Q.Clear β300 (C); FBP 5mm and Q.Clear β400 (D); FBP 5mm and Q.Clear β500 (E). Fig. 2 Bland-Altman plots assessing agreement between FBP with 5mm and Q.Clear with different β values, for the contrast recovery data obtained from the NEMA phantom. FBP 5mm and Q.Clear β600 (F); FBP 5mm and Q.Clear β700 (G); FBP 5mm and Q.Clear β800 (H); FBP 5mm and Q.Clear β900 (I); FBP 5mm and Q.Clear β1000 (J).