cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25646/10219
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.25646/10000
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.5281/zenodo.6513788
title: Agilent v7 exomes of NA12878

description: FastQ files used in the NGS-CN benchmarking initiative
DOI: 10.25646/10064
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.5281/zenodo.7022549
title: Simulation Reveals the Chameleonic Behavior of Macrocycles

description: Supporting Information for article titled "Simulation Reveals the Chameleonic Behavior of Macrocycles"
DOI: 10.5281/zenodo.7022548
title: Simulation Reveals the Chameleonic Behavior of Macrocycles

description: Supporting Information for article titled "Simulation Reveals the Chameleonic Behavior of Macrocycles"
DOI: 10.25646/10055
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.6084/m9.figshare.20709724
title: Organizational Study

description: Multi mediation data set that was collected from employees working in India.
DOI: 10.6084/m9.figshare.20709724.v1
title: Organizational Study

description: Multi mediation data set that was collected from employees working in India.
DOI: 10.5281/zenodo.7013300
title: HSICityV2: Urban Scene Understanding via Hyperspectral Images

description: Light in all spectrum travel in the physical world. The trichromatism (RGB) human vision captures and understands it. Machine vision makes an analogy which use RGB camera for semantic segmentation and scene understanding. We argue that such machine vision suffers from metamerism, that different objects may appear in same RGB color while actually distinctive in spectrum. While learning based solutions, especially deep learning, have been heavily explored, they do not solve the fundamental physical limitation. In this paper, we propose to use Hyperspectral images (HSIs), which capture hundreds of consecutive narrow bands from the real visible world and therefore metamerism no longer exists. In short, we aim to 'see beyond human vision'. In practice, we introduce a novel large scale high quality HSI dataset for semantic segmentation in cityscapes. Namely, Hyperspectral City dataset. The dataset contains 1330 HSIs which are captured in typical urban driving scenes. Each HSI has 1889×1422 spatial resolution and 128 spectral channels ranged from 450nm to 950nm. The dataset provides semantic annotation at pixel level which is done manually by professional annotators. We believe this dataset enables a new direction for scene understanding.
DOI: 10.5281/zenodo.7013301
title: HSICityV2: Urban Scene Understanding via Hyperspectral Images

description: Light in all spectrum travel in the physical world. The trichromatism (RGB) human vision captures and understands it. Machine vision makes an analogy which use RGB camera for semantic segmentation and scene understanding. We argue that such machine vision suffers from metamerism, that different objects may appear in same RGB color while actually distinctive in spectrum. While learning based solutions, especially deep learning, have been heavily explored, they do not solve the fundamental physical limitation. In this paper, we propose to use Hyperspectral images (HSIs), which capture hundreds of consecutive narrow bands from the real visible world and therefore metamerism no longer exists. In short, we aim to 'see beyond human vision'. In practice, we introduce a novel large scale high quality HSI dataset for semantic segmentation in cityscapes. Namely, Hyperspectral City dataset. The dataset contains 1330 HSIs which are captured in typical urban driving scenes. Each HSI has 1889×1422 spatial resolution and 128 spectral channels ranged from 450nm to 950nm. The dataset provides semantic annotation at pixel level which is done manually by professional annotators. We believe this dataset enables a new direction for scene understanding.
DOI: 10.5281/zenodo.7030857
title: HSICityV2: Urban Scene Understanding via Hyperspectral Images

description: Light in all spectrum travel in the physical world. The trichromatism (RGB) human vision captures and understands it. Machine vision makes an analogy which use RGB camera for semantic segmentation and scene understanding. We argue that such machine vision suffers from metamerism, that different objects may appear in same RGB color while actually distinctive in spectrum. While learning based solutions, especially deep learning, have been heavily explored, they do not solve the fundamental physical limitation. In this paper, we propose to use Hyperspectral images (HSIs), which capture hundreds of consecutive narrow bands from the real visible world and therefore metamerism no longer exists. In short, we aim to 'see beyond human vision'. In practice, we introduce a novel large scale high quality HSI dataset for semantic segmentation in cityscapes. Namely, Hyperspectral City dataset. The dataset contains 1330 HSIs which are captured in typical urban driving scenes. Each HSI has 1889×1422 spatial resolution and 128 spectral channels ranged from 450nm to 950nm. The dataset provides semantic annotation at pixel level which is done manually by professional annotators. We believe this dataset enables a new direction for scene understanding.
DOI: 10.5281/zenodo.6337832
title: Data sets for assessing potential CC impacts on the activity of the Vögelsberg landslide

description: Bias-corrected air temperature and precipitation time series (RCM sample from EURO CORDEX) for Kleinvolderberg station near the Vögelsberg landslide (OAL-AT) under RCP8.5, monthly water balance components derived from an empirical model for six elevation steps under current and potential land cover conditions for 1950-2100, median monthly displacement and current hydrological forcing of the Vögelsberg landslide
DOI: 10.5281/zenodo.6337833
title: Data sets for assessing potential CC impacts on the activity of the Vögelsberg landslide

description: Bias-corrected air temperature and precipitation time series (RCM sample from EURO CORDEX) for Kleinvolderberg station near the Vögelsberg landslide (OAL-AT) under RCP8.5, monthly water balance components derived from an empirical model for six elevation steps under current and potential land cover conditions for 1950-2100, median monthly displacement and current hydrological forcing of the Vögelsberg landslide
DOI: 10.25646/10098
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.5281/zenodo.7030874
title: ISTAR Demo Wing Abaqus Model

description: An ABAQUS Version of the ISTAR Demonstrator Wing is provided. The discretization resembles to the original Nastran Version with the following modifications: The ribs have been deleted. The unswept region of the wing connected to the fuselage has been removed. The virtual sensors from which the strain data are extracted are listed in the set nemed "Set-StrainGaugesElem"
DOI: 10.5281/zenodo.7030873
title: ISTAR Demo Wing Abaqus Model

description: An ABAQUS Version of the ISTAR Demonstrator Wing is provided. The discretization resembles to the original Nastran Version with the following modifications: The ribs have been deleted. The unswept region of the wing connected to the fuselage has been removed. The virtual sensors from which the strain data are extracted are listed in the set nemed "Set-StrainGaugesElem"
DOI: 10.25646/10215
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.25646/10189
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.6084/m9.figshare.20709451
title: Mars atmosphere reanalyses during the MY34 Global Dust Storm produced by assimilation of ExoMars TGO-ACS-TIRVIM observations into the Mars PCM using the LETKF

description: This dataset contains files supporting the results in the paper "Assimilation of temperatures and column dust opacities measured by ExoMars TGO-ACS-TIRVIM during the MY34 Global Dust Storm" by R. M. B. Young et al. Each file is a sequence of 577 complete atmospheric states for Mars' atmosphere during Mars Year 34 between L<sub>s</sub> = 182.3 - 211.4°, with 12 states per sol. These were created by assimilating observations from ExoMars TGO-ACS-TIRVIM into the Mars PCM (formerly the LMD Mars GCM) using the LETKF, as described in the paper. Each atmospheric state is the mean of an ensemble of 36 model states. The dataset includes analysis means for the TuTD, TuT-CuD, and TuTD-CuD cases presented in the paper, and the GCM ensemble mean used for comparison. The files are in netCDF-4/HDF5 format. The file structure and variable names are (in most respects) based on the diagfi.nc output file produced by the Mars PCM. The user is referred to Section 6.3.2 of the Mars PCM User Manual for full details of this file. A few of the variable names are changed, and a large number of diagnostic variables related to aerosols have been added in post-processing. Where appropriate, CF-compliant (https://cfconventions.org/) variable names have been added using the attribute <em>standard_name</em>. Units are in CF-compliant form using the attribute <em>units</em>. The file DATASET_DESCRIPTION.pdf contains full details.
DOI: 10.34740/kaggle/dsv/4134220
title: AutoXGB
DOI: 10.5281/zenodo.7030888
title: AmelHap Metadata

description: Curated sample information for drones processed for AmelHap. Details include: ENA_Run (European Nucleotide Archive accession number) ENA_Project (European Nucleotide Archive accession number) ENA_Sample (European Nucleotide Archive accession number) Sample_ID (Sample name given by ENA accession) Sample_Locale (Sampling location given by either ENA accession or published study) Sample_Country (Sample country of origin given by either ENA accession or published study) Sample_Continent (Sample continent of origin given by either ENA accession or published study) Reported_Sibling (Drones sampled from the same colony are labelled with the same ENA_Run accession for one of their siblings) Reported_Type (Reported type or subspecies based on details from ENA or published study) Reported_Lineage (Reported lineage based on details from ENA or published study) Notes (Miscellaneous details from published study that may be of interest)
DOI: 10.5281/zenodo.7030887
title: AmelHap Metadata

description: Curated sample information for drones processed for AmelHap. Details include: ENA_Run (European Nucleotide Archive accession number) ENA_Project (European Nucleotide Archive accession number) ENA_Sample (European Nucleotide Archive accession number) Sample_ID (Sample name given by ENA accession) Sample_Locale (Sampling location given by either ENA accession or published study) Sample_Country (Sample country of origin given by either ENA accession or published study) Sample_Continent (Sample continent of origin given by either ENA accession or published study) Reported_Sibling (Drones sampled from the same colony are labelled with the same ENA_Run accession for one of their siblings) Reported_Type (Reported type or subspecies based on details from ENA or published study) Reported_Lineage (Reported lineage based on details from ENA or published study) Notes (Miscellaneous details from published study that may be of interest)
DOI: 10.6084/m9.figshare.20710084
title: 34_papers.doc

description: papers
DOI: 10.6084/m9.figshare.20710084.v1
title: 34_papers.doc

description: papers
DOI: 10.5281/zenodo.6983103
title: AmelHap

description: <strong>AmelHap 1.1.0.f4</strong> 1,328 samples 17,414,346 variants Sequencing reads were aligned to the Amel_HAv3.1 reference genome using BWA-MEM v0.7.17. Reads were sorted with SAMtools v1.9 and duplicates marked (MarkDuplicates) with GATK v4.0.11.0. Variants for each sample were called using GATK’s HaplotypeCaller with the following non-default parameters --ERC GVCF, --sample-ploidy 1 and -A AlleleFraction. Joint variant calling was performed across all samples collated for AmelHap using GATK’s GenomicDBImport and GenotypeGVCFs with --sample-ploidy 1 and a window size of 10 Mb. The AmelHap dataset comprises samples and variants that have passed a series of filters. The first filter excluded variants with quality by depth (QD) less than 20 or greater than 40, or with mapping quality (MQ) less than 50, or with a strand odds ratio (SOR) greater than 3. The second filter set genotypes with depth (DP) greater than 704 or quality (GQ) less than 40 as missing. The third filter removed monomorphic variants. The fourth and final filter retained samples and variants with a minimum call rate of 90%. Unfiltered data for all samples processed is also available in the community repository in the form of individual gVCF files and joint-called raw variants grouped by ENA project accession. Sample metadata is available here: https://doi.org/10.5281/zenodo.7030888
DOI: 10.6084/m9.figshare.20710120
title: 34_papers.pdf

description: papers
DOI: 10.6084/m9.figshare.20710120.v1
title: 34_papers.pdf

description: papers
DOI: 10.6084/m9.figshare.20120897
title: Supplementary Material for: Screening for low-tract genital infections in women with threatened preterm labour. Which role?

description: Objectives: to evaluate the possible relationship between cultural specimens and preterm birth in women admitted for threatened preterm labour. Preterm birth is the leading cause of neonatal mortality and antenatal hospitalization: several risk factors including intrauterine infections have been identified but its real causes remain poorly understood. Design: retrospective, multicentre, cohort study including 250 women admitted for threatened preterm labour. Methods, Participants/Materials, Setting: all women admitted for threatened Preterm Labour, i.e. presenting with cervical changes and uterine activity before 37 weeks at the Obstetrics Unit of the hospitals of Modena, Monza, Carate and Vimercate were included in the study. We excluded twin pregnancies and cases with preterm premature rupture of membranes at admission. Data about maternal history, pregnancy complications, cervical length, vaginal swabs and urine culture at admission and gestational age at delivery were collected from clinical records in order to compare the incidence of preterm birth according to some known risk factors, cervical length and microbiological test at admission. Results: 250 women were included in the study; preterm birth at less than 37 weeks occurred in 44.4% women admitted for threatened preterm labour. The incidence of preterm birth was not different between those with a positive or a negative vaginal swab (45.7% vs. 39%, p=0.38), or positive vs. negative urine culture (31.8% vs. 42.1%, p=0.23) at admission. A shorter cervical length at admission was found in women with subsequent preterm birth (17± vs 19.5± mm, p=0.03). Cervical length &lt;15 mm (OR 1.82, CI95% 1.03-3.23, p=0.039) predicted the risk of PTB. Further, only the history of a previous preterm birth (p=0.02) and a previous uterine curettage (p=0.045) were associated with preterm birth. Limitations: the observational and retrospective nature of the study and its small sample size are important limitations of the study. Moreover, women were not systematically or randomly assigned to the screening for vaginal or urinary infections. Conclusions: there is no evidence that the search for vaginal or urinary infections in women admitted for threatened preterm labour is helpful to identify those at increased risk of preterm birth. Although several studies have explored the role of screening for bacterial vaginosis in asymptomatic women and some studies evaluated vaginal or urinary infections in women with PTB, none of them focused on the possible role of microbiological specimens as a predictive tool in women admitted for threatened PTL. No association was found in our study but prospective randomized controlled trials are required to confirm the results of this observation.
DOI: 10.6084/m9.figshare.20290620.v1
title: Supplementary Material for: The relationship between HPV prevalence and DNA damage in cervical cancer population in Gansu province, China.

description: Objectives: To assess the possible reason of high incidence and mortality of cervical cancer in Longnan, China. Materials and Methods: 147 and 124 invasive squamous cell carcinoma (SCC) samples from Longnan and different cities and districts of Gansu province were collected in the present study. All the samples were obtained from patients who underwent biopsies with colposcopy or advanced operations and were evaluated by experienced pathologists. HPV genotypes were examined with a validated HPV subtypes kit. The prevalence of HPV infection in SCC patients of China was analyzed by evidence-based medicine in published literature. The markers of DNA damage response (DDR) - ATMpSer1981, H2AXp Ser139 (γH2AX), Chk2pThr68 and P53 - were analyzed by immunohistochemistry. Results: HPV positivity, high risk and multiple HPV positivity and HPV 58 infection were significantly higher in Longnan. Our results the prevalence of HPV infection in SCC patients of Longnan are consistent with the HPV prevalence in China. ATM, γH2AX and P53 expression in total and HPV+ samples were also higher in Longnan. Conclusions: HPV related DDR activation may be one reason for high incidence and mortality of Longnan cervical cancer.