cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21160825.v1
title: Supplementary Material for: Long-Term Trends in Risk Factor Management in Respondents with Chronic Kidney Disease in the USA

description: <b><i>Introduction:</i></b> Unhealthy lifestyle factors are known to increase the risk of chronic kidney disease (CKD) and its complications. The long-term trends in these factors are unclear. <b><i>Methods:</i></b> The aim of the study was to assess temporal trends in the prevalence of risk factors in adults with CKD in the USA and identify sociodemographic subgroups at most risk. Subanalysis of data was carried out from a stratified, complex, multistage probability-based cross-sectional and nationally representative survey. We examined participants from National Health and Nutritional Examination Survey (NHANES) respondents aged ≥20 years with CKD from 1999 to 2018. CKD was defined as estimated glomerular filtration rate of 15–59 mL/min/1.73 m<sup>2</sup>. Evaluated risk factors included uncontrolled blood pressure, blood glucose, blood lipids, excessive sodium intake, excessive protein intake, poor diet, obesity, smoking, depression, physical inactivity, and sedentary behavior. Sociodemographic variables included age, sex, race/ethnicity, marital status, education level, family income, and employment status. <b><i>Results:</i></b> Blood pressure control among respondents with CKD (<i>n</i> = 4,342) was poor but significantly improved from the 1999–2000 (82% uncontrolled) to 2017–2018 surveys (66%; <i>p</i> for linear trend = 0.02). Prevalence of uncontrolled blood glucose (15–22%; <i>p</i> &lt; 0.01), excessive sodium intake (72–78%; <i>p</i> = 0.04), and obesity (32–51%; <i>p</i> &lt; 0.01) significantly increased over this time. The proportion of respondents with uncontrolled blood lipids, depression, smoking, excessive protein intake, poor diet, physical inactivity, or sedentary behavior showed no significant change over the 10-year period. Older people were more likely to have high blood pressure, high blood glucose, and high blood lipids but healthier lifestyle habits than younger people. And respondents of males, non-Hispanic blacks, Hispanics, low income, low education, widowed/divorced/separated, and employed had worse risk factor control compared to reference groups. <b><i>Discussion/Conclusion:</i></b> Although the control of several risk factors in US NHANES respondents with CKD improved from 1999 to 2018, further reductions remain of value.
DOI: 10.6084/m9.figshare.20472129
title: Supplementary Material for: Mosaic GLUD1 mutations associated with hyperinsulinism hyperammonemia syndrome

description: Introduction: The hyperinsulinemia-hyperammonemia syndrome (HIHA) is the second most common cause of congenital hyperinsulinism and is caused by activating heterozygous missense mutations in GLUD1. In the majority of HIHA cases, the GLUD1 mutation is found to be de novo. We have identified three patients in whom clinical evaluation was suggestive of HIHA but with negative mutation analysis in peripheral blood DNA for GLUD1 as well as other known HI genes. Methods: We performed next-generation sequencing (NGS) on peripheral blood DNA from two children with clinical features of HIHA in order to look for mosaic mutations in GLUD1. Pancreas tissue was also available in one of these cases for NGS. In addition, NGS was performed on peripheral blood DNA from a woman with a history of HI in infancy whose child had HIHA due to a presumed de novo GLUD1 mutation. Results: Mosaic GLUD1 mutations were identified in these three cases at percent mosaicism ranging from 2.7% to 10.4% in peripheral blood. In one case with pancreas tissue available, the mosaic GLUD1 mutation was present at 17.9% and 28.9% in different sections of pancreas. Two unique GLUD1 mutations were identified in these cases, both of which have been previously reported (c.1493c&gt;t/p.Ser445Leu and c.820c&gt;t/p.Arg221Cys). Conclusion: The results suggest that low-level mosaic mutations in known HI genes may be the underlying molecular mechanism in some children with HI who have negative genetic testing in peripheral blood DNA.
DOI: 10.34820/fk2/l1kmer
title: ANALISIS BIAYA LOGISTIK DENGAN MENGGUNAKAN KONSEP SUPPLY CHAINMANAGEMENT (SCM)

description: Prinsip dalam penerapan aspek manajemen, industri yang membantu pengguna
DOI: 10.34730/d493601ff5bc4dbaa45ac85da028e2cd
title: DeepRain project presentations

description: In this entry a collection of internal publications, presentations, slides and reports from DeepRain. DeepRain is funded by the Bundesministerium für Bildung und Forschung (BMBF) under grant agreement 01 IS18047A-E.
DOI: 10.5281/zenodo.7095388
title: Database Litani

description: This database was used to calibrate the mathematical programming models used to simulate climate change and policy scenarios in the Litani River Basin
DOI: 10.5281/zenodo.7095387
title: Database Litani

description: This database was used to calibrate the mathematical programming models used to simulate climate change and policy scenarios in the Litani River Basin
DOI: 10.21227/3yea-xm39
title: Residential Smart Meter Energy Time Series: One month of active power measurements with 1s reporting rate

description: The dataset includes active power measurements for a residential dwelling (apartment) located in Bucharest, Romania, collected at 1s second reporting rate over one month.We hope that the dataset is useful to energy systems and computational intelligence researchers for time series forecasting, classification and energy disaggregation tasks.For collecting the energy measurement data SLAMs (Smart Low-Cost Advance Meter) is used. SLAM is the new generation of smart meters which takes advantages of new technologies in ICT and it is based on the smart meter Unbundled concept, differentiating the two modules (SMM and SMX). The SLAM meter is an advanced multi-function digital single-phase smart meter Class B in active energy and Class 2 in reactive energy, which complies with European legislation related to energy meters (MID) EN 50470-1 and EN 50470-3. It includes the SMX module that allows development of business related applications while allowing a multi user, multi- protocol communications with the grid actors. The communication of the smart meter with the exterior environment is done while preserving on the user side a strong control of data content and considering privacy and security aspects for data exchange to support data protection regulation rules.The USM concept is described in detail in:M. Sanduleac, L. Pons, G. Fiorentino, R. Pop and M. Albu, "The unbundled smart meter concept in a synchro-SCADA framework," 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings, 2016, pp. 1-5, doi: 10.1109/I2MTC.2016.7520459.A data analytics approach using this data set for time series data mining using the Matrix Profile technique for feature extraction is presented in:G. Stamatescu, R. Plamanescu, A. -M. Dumitrescu, I. Ciomei and M. Albu, "Multiscale Data Analytics for Residential Active Power Measurements through Time Series Data Mining," 2022 IEEE 7th International Energy Conference (ENERGYCON), 2022, pp. 1-5, doi: 10.1109/ENERGYCON53164.2022.9830170.
DOI: 10.6084/m9.figshare.21161809
title: Supplementary Material for: Salivary Proteins as Dental Caries Biomarkers: A Systematic Review

description: Salivary proteins play an important role in repairing mechanisms of damaged tissues and the maintenance of oral health. However, there is a dearth of information in the literature regarding the concentrations of salivary proteins in caries-free (CF) and caries-active (CA) subjects. Hence, this systematic review was conducted to update our previous systematic review published in 2013 that aimed to assess the association between caries and salivary proteins by comparing CF and CA individuals. Thereby, evaluating the possibility of whether salivary proteins can be regarded as biomarkers for caries. An extensive search of studies was conducted using PubMed, EMBASE, Clarivate Analytics’ Web of Science, and Elsevier’s Scopus between July 2012 and January 2022, without any language restriction. Manual searching in Google Scholar and evaluation of bibliographies of the included studies were also undertaken. The Newcastle-Ottawa Scale was used to assess the risk of bias (RoB) within the included studies. Of 22 included studies, 1551 human subjects (range: 30 – 213 participants) were recruited, of which 848 (54.7%) were CA and 703 (45.3%) individuals were CF. Regarding the utilization of DMFT as the caries index, high variability was observed across different articles. A statistically significant increase in the salivary levels of alpha-amylase, acidic proline-rich protein-1, histatin-5, lactoperoxidase, and mucin-1 was found in CA patients, while the salivary levels of carbonic anhydrase 6, proteinase-3, and statherin were observed to be significantly increased in CF subjects. Conflicting results were found regarding the salivary levels of immunoglobulin-A and total proteins among CA and CF subjects. The included studies were categorized as low RoB (n=15), medium RoB (n=4), and high RoB (n=3). Due to significant heterogeneity among the included studies, no meta-analysis could be performed. In conclusion, salivary levels of protein(s) might be useful biomarker for caries diagnosis, especially alpha-amylase, acidic proline-rich protein-1, histatin-5, lactoperoxidase, mucin-1, carbonic anhydrase 6, proteinase-3, and statherin. However, their diagnostic value must be verified by large-scale prospective studies.
DOI: 10.6084/m9.figshare.21161809.v1
title: Supplementary Material for: Salivary Proteins as Dental Caries Biomarkers: A Systematic Review

description: Salivary proteins play an important role in repairing mechanisms of damaged tissues and the maintenance of oral health. However, there is a dearth of information in the literature regarding the concentrations of salivary proteins in caries-free (CF) and caries-active (CA) subjects. Hence, this systematic review was conducted to update our previous systematic review published in 2013 that aimed to assess the association between caries and salivary proteins by comparing CF and CA individuals. Thereby, evaluating the possibility of whether salivary proteins can be regarded as biomarkers for caries. An extensive search of studies was conducted using PubMed, EMBASE, Clarivate Analytics’ Web of Science, and Elsevier’s Scopus between July 2012 and January 2022, without any language restriction. Manual searching in Google Scholar and evaluation of bibliographies of the included studies were also undertaken. The Newcastle-Ottawa Scale was used to assess the risk of bias (RoB) within the included studies. Of 22 included studies, 1551 human subjects (range: 30 – 213 participants) were recruited, of which 848 (54.7%) were CA and 703 (45.3%) individuals were CF. Regarding the utilization of DMFT as the caries index, high variability was observed across different articles. A statistically significant increase in the salivary levels of alpha-amylase, acidic proline-rich protein-1, histatin-5, lactoperoxidase, and mucin-1 was found in CA patients, while the salivary levels of carbonic anhydrase 6, proteinase-3, and statherin were observed to be significantly increased in CF subjects. Conflicting results were found regarding the salivary levels of immunoglobulin-A and total proteins among CA and CF subjects. The included studies were categorized as low RoB (n=15), medium RoB (n=4), and high RoB (n=3). Due to significant heterogeneity among the included studies, no meta-analysis could be performed. In conclusion, salivary levels of protein(s) might be useful biomarker for caries diagnosis, especially alpha-amylase, acidic proline-rich protein-1, histatin-5, lactoperoxidase, mucin-1, carbonic anhydrase 6, proteinase-3, and statherin. However, their diagnostic value must be verified by large-scale prospective studies.
DOI: 10.6084/m9.figshare.21154846
title: Common_bean_pangenome

description: Resequencing data from 683 common bean landraces and breeding lines provided a pan-genome construction data resource.
DOI: 10.6084/m9.figshare.21161839
title: distance-matrix.csv

description: This data is a matrix version of Table-2 in the paper
DOI: 10.6084/m9.figshare.21161842
title: Untitled Item

description: In the Yangjiang profile, a total of 29 (27 groundwater samples and 2 surface water samples: seawater and aquaculture wastewater) and 32 (29 groundwater samples and 2 surface water samples: seawater and aquaculture wastewater) samples were collected on August 12, 2020 (wet season) and November 8, 2020 (dry season), respectively. The measurement procedures for the trace metals (As, Ba, Cd, Cr, Fe, Mn, Pb, and Zn) in groundwater samples were described elsewhere (Luo et al., 2021). In brief, the samples with high salinity (&gt;1) were first diluted and then analyzed using inductively coupled plasma mass spectrometry (ICP–MS) (Agilent 7900 Series, USA). The detection limits (μg/L) of trace metals were 0.12, 0.20, 0.05, 0.11, 0.82, 0.12, 0.09, and 0.67 for As, Ba, Cd, Cr, Fe, Mn, Pb, and Zn, respectively. A mixed standard solution and two standard reference materials were used to construct the calibration curve and control the analytical quality, respectively. The recoveries of the standard reference materials were 105.4%, 101.7%, 102.6%, 104.0%, and 103.4% for As, Cd, Cr, Pb, and Zn, respectively, indicating that the measured results were within the range of the certified values (Luo et al., 2021). Reagent blanks were determined for each sample analysis and trace metals were undetectable therein.
DOI: 10.6084/m9.figshare.21161842.v1
title: Untitled Item

description: In the Yangjiang profile, a total of 29 (27 groundwater samples and 2 surface water samples: seawater and aquaculture wastewater) and 32 (29 groundwater samples and 2 surface water samples: seawater and aquaculture wastewater) samples were collected on August 12, 2020 (wet season) and November 8, 2020 (dry season), respectively. The measurement procedures for the trace metals (As, Ba, Cd, Cr, Fe, Mn, Pb, and Zn) in groundwater samples were described elsewhere (Luo et al., 2021). In brief, the samples with high salinity (&gt;1) were first diluted and then analyzed using inductively coupled plasma mass spectrometry (ICP–MS) (Agilent 7900 Series, USA). The detection limits (μg/L) of trace metals were 0.12, 0.20, 0.05, 0.11, 0.82, 0.12, 0.09, and 0.67 for As, Ba, Cd, Cr, Fe, Mn, Pb, and Zn, respectively. A mixed standard solution and two standard reference materials were used to construct the calibration curve and control the analytical quality, respectively. The recoveries of the standard reference materials were 105.4%, 101.7%, 102.6%, 104.0%, and 103.4% for As, Cd, Cr, Pb, and Zn, respectively, indicating that the measured results were within the range of the certified values (Luo et al., 2021). Reagent blanks were determined for each sample analysis and trace metals were undetectable therein.
DOI: 10.24400/802406/n1p5-p61z
title: WIND 3DP Solar Wind Electron Distribution Functions

description: This data set contains the three-dimensionnal distribution functions, provided by WIND 3-DP EESA-Low (electrons in the 3 eV - 300 eV energy range) The data provided in this data set are not corrected for calibration factors and are given in raw counts. Thus they correspond to a Level 1 data processing on ground, and they can be transformed into physical units by multiplying them by a calibration factor and using the appropriate geometric factor.
DOI: 10.24400/802406/x3t6-5jxc
title: WIND 3DP Solar Wind Proton Distribution Functions

description: This data set contains the three-dimensionnal distribution functions, provided by WIND 3-DP PESA-Low (protons in the 80 eV - 6 keV energy range) . The data provided in this data set are not corrected for calibration factors and are given in raw counts. Thus they correspond to a Level 1 data processing on ground, and they can be transformed into physical units by multiplying them by a calibration factor and using the appropriate geometric factor.
DOI: 10.24400/802406/9wxv-t80q
title: WIND 3DP Solar Wind Proton and Helium Moments

description: This data set contains the four first moments of the distribution function, provided by WIND 3-DP, as computed on-board, for both proton and alpha particles.
DOI: 10.24400/802406/w6vt-hsmz
title: WIND 3DP Solar Wind Electron Moments

description: This data set contains the five first moments of the distribution function, provided by WIND 3-DP, as computed on-board, for electrons.
DOI: 10.24400/802406/gkyr-p7zd
title: WIND 3DP Suprathermal Proton Distribution Functions

description: This data set contains the three-dimensionnal distribution functions, provided by WIND 3-DP PESA-High (protons in the 300 eV - 30 keV energy range). The data provided in this data set are not corrected for calibration factors and are given in raw counts. Thus they correspond to a Level 1 data processing on ground, and they can be transformed into physical units by multiplying them by a calibration factor and using the appropriate geometric factor.
DOI: 10.24400/802406/tp1d-a7t2
title: WIND 3DP Suprathermal Electron Distribution Functions

description: This data set contains the three-dimensionnal distribution functions, provided by WIND 3-DP EESA-High (electrons in the 100 eV - 30 keV energy range). The data provided in this data set are not corrected for calibration factors and are given in raw counts. Thus they correspond to a Level 1 data processing on ground, and they can be transformed into physical units by multiplying them by a calibration factor and using the appropriate geometric factor.
DOI: 10.24400/802406/f97x-6yzq
title: WIND 3DP SST-SF Electrons (25 keV - 600 keV)

description: This data set contains three-dimensionnal distribution functions of electrons (25keV - 600 keV), provided by WIND 3-DP Solid State Telescope Foil, not corrected for calibration factors and given in raw counts. Thus they correspond to a Level 1 data processing on ground, and they can be transformed into physical units by multiplying them by a calibration factor and using the appropriate geometric factor.
DOI: 10.24400/802406/pg3v-dsp2
title: WIND 3DP SST-SFT Electrons (300 keV - 2 MeV)

description: This data set contains three-dimensionnal distribution functions of electrons (300 keV - 2 MeV), provided by WIND 3-DP Solid State Telescope Foil Thick, not corrected for calibration factors and given in raw counts. Thus they correspond to a Level 1 data processing on ground, and they can be transformed into physical units by multiplying them by a calibration factor and using the appropriate geometric factor.
DOI: 10.24400/802406/b6vg-5dg9
title: WIND 3DP SST-SO Protons (50 keV - 5 MeV) Alpha particles (6.7 MeV)

description: This data set contains three-dimensionnal distribution functions of protons (50 keV - 5 MeV) and alpha particles (6.7 MeV), provided by WIND 3-DP Solid State Telescope Open, not corrected for calibration factors and are given in raw counts. Thus they correspond to a Level 1 data processing on ground, and they can be transformed into physical units by multiplying them by a calibration factor and using the appropriate geometric factor.
DOI: 10.24400/802406/ke76-vx9j
title: WIND 3DP SST-SOT Protons (6MeV - 10 MeV) Alpha particles (11.6 MeV)

description: This data set contains three-dimensionnal distribution functions of protons (6MeV - 10 MeV) and alpha particles (11.6 MeV), provided by WIND 3-DP Solid State Telescope Open Thick, not corrected for calibration factors and given in raw counts. Thus they correspond to a Level 1 data processing on ground, and they can be transformed into physical units by multiplying them by a calibration factor and using the appropriate geometric factor.
DOI: 10.24400/802406/y6ev-x63s
title: Wind Waves TNR L1 Data

description: This data set contains Wind WAVES Thermal Noise Receiver decommutated telemetry data. Spectra are uncompressed and given in dB with respect to the acquisition mode. Automatic Gain Control values are given without further processing in a raw telemetry format.
DOI: 10.24400/802406/hqac-xz9t
title: Wind Waves TNR L2 Data

description: This data set contains Wind WAVES Thermal Noise Receiver calibrated data. Spectra are given in µV^2 / Hz. The spectra dynamic range is 120 dB [10^-6 , 10^+6 ] and an undefined value is represented by 10-10 µV^2 / Hz. The AGC factors are given in dB with respect to a reference voltage V0 specified in laboratory. These voltages are given for each frequency band as follows: Band : V0 (dB) A : -40.34 B : -43.45 C : -46.60 D : -49.61 E : -51.62
DOI: 10.24400/802406/r9fz-n1g9
title: Wind Waves TNR L2 Temporal Series Data

description: Wind Waves Thermal Noise Receiver Temporal Series These are calibrated data presented as a temporal series. Each record consists on a unique spectrum (given in µV^2 / Hz) made with 96 frequencies. In modes 0, 1 and 4 the number of channels per band is increased to 32 by interpolation. The interpolated frequencies are located by the odd indexes. In mode 4, spectra issued from the TNR B are ignored. In mode 2 and 3, data are not altered. If the cycle is in state fixed tune (event_state = 1) , then only 32 values are defined. With respect to the band sweeped, the following values are defined: Band: Index of defined values A : 0 to 31 B : 16 to 47 C : 32 to 63 D : 48 to 79 E : 64 to 95 If the cycle is in state ABCDE (event_state=2), then band B and D are ignored, while in state ACE (event_state=3) all data are available.
DOI: 10.24400/802406/9rxv-hyyr
title: Wind Waves RAD1_L2 : High Resolution Data (Range 20 - 1040 kHz)

description: This data set contains Wind Waves RADIO RAD1 high resolution calibrated spectra. The spectral power density is given in µV^2/Hz measured at the Preamplifiers (PA) for the three receiver channels S, SP and Z. No background level is removed from the data, and the intensity modulation due to the spacecraft rotation is not corrected.
DOI: 10.24400/802406/swc8-9nbz
title: Wind Waves RAD2_L2 : High Resolution Data (Range 1.075 - 13.825 MHz)

description: This data set contains Wind Waves RADIO RAD2 high resolution calibrated spectra. The spectral power density is given in µV^2/Hz measured at the Preamplifiers (PA) for the three receiver channels S, SP and Z. No background level is removed from the data, and the intensity modulation due to the spacecraft rotation is not corrected.
DOI: 10.24400/802406/vtey-bcw8
title: Wind Waves TNR_L2_60S : 60-second Averaged Data (Range 4 - 256 kHz)

description: This data set contains Wind WavesThermal Noise Receiver 60-second Averaged Data (Range 4 - 256 kHz, number of channels 96). Experimental data have been processed and averaged over 60-second intervalls from the corresponding high resolution datasets at L2 level. They are presented as temporal series. Each record consists on an averaged spectrum (given in µV^2/Hz @ PA), as well as the minimum and maximum spectrum values. Interpolations are performed in the case of missing/bad values, while the min. and max. values are left equal to -1.0e31. The intensity modulation due to the spacecraft rotation, as well as the background level are not removed from the data.
DOI: 10.24400/802406/f7jb-1j4f
title: Wind Waves RAD1_L2_60S : 60-second Averaged Data (Range 20 - 1040 kHz)

description: This data set contains Wind Waves RADIO RAD1 60-second Averaged Data (Range 1.075 - 13.825 MHz, number of channels 16, 32, 64 or 256) Experimental data have been processed and averaged over 60-second intervalls from the corresponding high resolution datasets at L2 level. They are presented as temporal series. Each record consists on an averaged spectrum (given in µV^2/Hz @ PA), as well as the minimum and maximum spectrum values. Interpolations are performed in the case of missing/bad values, while the min. and max. values are left equal to -1.0e31. The intensity modulation due to the spacecraft rotation, as well as the background level are not removed from the data.