cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19242899.v1
title: Setting Multivariate and Correlated Acceptance Limits for Assessing the Conformity of Items

description: Many industrial products, foodstuffs and environmental samples are checked for values of different chemical parameters against tolerance limits or intervals defined in a specification or legislation. In some cases, the measured values of the different parameters are correlated due to how materials are obtained, chemical constraints and/or due to the simple fact that determinations are performed by multi-analyte procedures that share analytical operations and effects. In these cases, instead of defining an acceptance criterion for each measured value on the tested item separately based on the respective measurement uncertainty, the multivariate problem should be addressed by defining multivariate criteria. These multivariate criteria are set for a maximum total risk of wrong conformity decisions that is a complex function of all particular risks of the item being rejected or accepted by comparing each measured value with its respective limit. Computational tools have been developed to estimate the total specific risk of an item being wrongly considered to conform or not to conform with tolerance limits for various components when the measured values are independent or correlated. However, these tools must be applied for each test to check if the total specific risk is acceptable. This work presents a tool for setting multivariate acceptance limits applicable to correlated measurements and referenced to a defined total specific risk. The acceptance limits allow the decision about conformity of an item based on the simple comparison of the measured values with the acceptance limits. The acceptance limits are estimated by a user-friendly and iterative tool implemented in a MS-Excel spreadsheet and available in the Supplementary Material. This tool is successfully applied to various conformity problems. Acceptance limits based on informative and non-informative prior information are compared for a critical review of the merits and problems associated with Bayesian or frequentist conformity assessments.
DOI: 10.57810/lattedata/tqad9d
title: Influências precoces sobre a composição corporal, capital humano e precursores de doenças crônicas c

description: Vide projeto anexo
DOI: 10.57810/lattedata/l3jk6o
title: Avaliação de possibilidades de dispersão passiva do carrapato Rhipicephalus sanguineus sensu lato na

description: Vide projeto anexo
DOI: 10.21227/g4nj-q303
title: Analysis method of Dissolved gas in transformer oil based on EW Pentagon

description: Analysis method of Dissolved gas in transformer oil based on EW Pentagon
DOI: 10.5281/zenodo.6759635
title: Convenios

description: Relación de Convenios desarrollados por los Servicios municipales. El servicio de visualización ofrece los datos a través de un buscador, en el que se puede filtrar por línea estratégica, servicio gestor y/o año. Acceso a la ficha descriptiva del dataset
DOI: 10.5281/zenodo.6759634
title: Convenios

description: Relación de Convenios desarrollados por los Servicios municipales. El servicio de visualización ofrece los datos a través de un buscador, en el que se puede filtrar por línea estratégica, servicio gestor y/o año. Acceso a la ficha descriptiva del dataset
DOI: 10.5281/zenodo.6084556
title: Crust and uppermost mantle magma plumbing system beneath Changbaishan intraplate volcano, China/North Korea, revealed by ambient noise adjoint tomography

description: This dataset contains the original ambient noise cross-correlation data and the final inverted 3D Vs model for our research paper "Crust and uppermost mantle magma plumbing system beneath Changbaishan intraplate volcano, China/North Korea, revealed by ambient noise adjoint tomography", which has been published in <strong><em>Geophysical Research Letters</em></strong> (https://doi.org/10.1029/2022GL098308).
DOI: 10.5281/zenodo.6084555
title: Crust and uppermost mantle magma plumbing system beneath Changbaishan intraplate volcano, China/North Korea, revealed by ambient noise adjoint tomography

description: This dataset contains the original ambient noise cross-correlation data and the final inverted 3D Vs model for our research paper "Crust and uppermost mantle magma plumbing system beneath Changbaishan intraplate volcano, China/North Korea, revealed by ambient noise adjoint tomography", which has been published in <strong><em>Geophysical Research Letters</em></strong> (https://doi.org/10.1029/2022GL098308).
DOI: 10.5281/zenodo.6675783
title: Therapeutic targeting of ATR in alveolar rhabdomyosarcoma

description: Data related to the manuscript "Therapeutic targeting of ATR in alveolar rhabdomyosarcoma" It can be divided in three parts <strong>Raw data from the phosphoproteomics screen (Raw data phosphoprot.7z)</strong> Inside contains the following files:<br> Phosphopeptides in three replicates: Waldorf_20170621_KI_HS_314_phospho_1_L-ctrl_H-inh_NH4OH.raw Waldorf_20170621_KI_HS_314_phospho_1_L-ctrl_H-inh_pipe.raw Waldorf_20170621_KI_HS_314_phospho_2_L-ctrl_H-inh_NH4OH.raw Waldorf_20170621_KI_HS_314_phospho_2_L-ctrl_H-inh_pipe.raw Waldorf_20170621_KI_HS_314_phospho_3_L-inh_H-ctrl_NH4OH.raw Waldorf_20170621_KI_HS_314_phospho_3_L-inh_H-ctrl_pipe.raw Total proteome (three replicates): Waldorf_20170621_KI_HS_314_whole_1.raw Waldorf_20170621_KI_HS_314_whole_2.raw Waldorf_20170621_KI_HS_314_whole_3.raw <strong>Raw data from the CRISPRa screen (CRISPR.7z)</strong> Inside contains the following files: (control sample) flexbarOut_barcode_DMSO.fastq (treated sample) flexbarOut_barcode_AZD6738.fastq <strong>Raw data from the RNAseq experiment (RNAseq.7z)</strong> Inside contains the following files (NOTE: paired-end sequencing): (control sample) AH_HDG_1_S1_R1_001.fastq (control sample) AH_HDG_1_S1_R2_001.fastq (treated sample) AH_HDG_2_S2_R1_001.fastq (treated sample) AH_HDG_2_S2_R2_001.fastq (control sample) AH_HDG_3_S3_R1_001.fastq (control sample) AH_HDG_3_S3_R2_001.fastq (treated sample) AH_HDG_4_S4_R1_001.fastq (treated sample) AH_HDG_4_S4_R2_001.fastq (control sample) AH_YB_027_S7_R1_001.fastq (control sample) AH_YB_027_S7_R2_001.fastq AH_YB_028_S8_R1_001.fastq AH_YB_028_S8_R2_001.fastq
DOI: 10.5281/zenodo.6675782
title: Therapeutic targeting of ATR in alveolar rhabdomyosarcoma

description: Data related to the manuscript "Therapeutic targeting of ATR in alveolar rhabdomyosarcoma" It can be divided in three parts <strong>Raw data from the phosphoproteomics screen (Raw data phosphoprot.7z)</strong> Inside contains the following files:<br> Phosphopeptides in three replicates: Waldorf_20170621_KI_HS_314_phospho_1_L-ctrl_H-inh_NH4OH.raw Waldorf_20170621_KI_HS_314_phospho_1_L-ctrl_H-inh_pipe.raw Waldorf_20170621_KI_HS_314_phospho_2_L-ctrl_H-inh_NH4OH.raw Waldorf_20170621_KI_HS_314_phospho_2_L-ctrl_H-inh_pipe.raw Waldorf_20170621_KI_HS_314_phospho_3_L-inh_H-ctrl_NH4OH.raw Waldorf_20170621_KI_HS_314_phospho_3_L-inh_H-ctrl_pipe.raw Total proteome (three replicates): Waldorf_20170621_KI_HS_314_whole_1.raw Waldorf_20170621_KI_HS_314_whole_2.raw Waldorf_20170621_KI_HS_314_whole_3.raw <strong>Raw data from the CRISPRa screen (CRISPR.7z)</strong> Inside contains the following files: (control sample) flexbarOut_barcode_DMSO.fastq (treated sample) flexbarOut_barcode_AZD6738.fastq <strong>Raw data from the RNAseq experiment (RNAseq.7z)</strong> Inside contains the following files (NOTE: paired-end sequencing): (control sample) AH_HDG_1_S1_R1_001.fastq (control sample) AH_HDG_1_S1_R2_001.fastq (treated sample) AH_HDG_2_S2_R1_001.fastq (treated sample) AH_HDG_2_S2_R2_001.fastq (control sample) AH_HDG_3_S3_R1_001.fastq (control sample) AH_HDG_3_S3_R2_001.fastq (treated sample) AH_HDG_4_S4_R1_001.fastq (treated sample) AH_HDG_4_S4_R2_001.fastq (control sample) AH_YB_027_S7_R1_001.fastq (control sample) AH_YB_027_S7_R2_001.fastq AH_YB_028_S8_R1_001.fastq AH_YB_028_S8_R2_001.fastq
DOI: 10.5281/zenodo.6759657
title: Piscinas de verano

description: Este conjunto de datos incluye un directorio con los datos de las <strong>Piscinas de Verano</strong> de Zaragoza. A través del Servicio de Visualización, el Ayuntamiento de Zaragoza pone a disposición una visualización en la que se muestran datos sobre Piscinas de verano. El conjunto de datos contiene información de localización (dirección, código postal, latitud y longitud), contacto (email y teléfono), horario y url a la web de cada centro. Contiene información sobre superficie y uso. El buscador le permite hacer búsquedas filtrando por territorio. También cabe la posibilidad de ver los resultados en forma de mapa. <strong>Fuente de información: </strong>Instalaciones Deportivas Buscador Facetado SOLR: El buscador le permite hacer búsquedas por los siguientes filtros: Temas Subtemas Sector de Población al que va dirigido Juntas Titularidad Acceso a la ficha descriptiva del dataset
DOI: 10.5281/zenodo.6759656
title: Piscinas de verano

description: Este conjunto de datos incluye un directorio con los datos de las <strong>Piscinas de Verano</strong> de Zaragoza. A través del Servicio de Visualización, el Ayuntamiento de Zaragoza pone a disposición una visualización en la que se muestran datos sobre Piscinas de verano. El conjunto de datos contiene información de localización (dirección, código postal, latitud y longitud), contacto (email y teléfono), horario y url a la web de cada centro. Contiene información sobre superficie y uso. El buscador le permite hacer búsquedas filtrando por territorio. También cabe la posibilidad de ver los resultados en forma de mapa. <strong>Fuente de información: </strong>Instalaciones Deportivas Buscador Facetado SOLR: El buscador le permite hacer búsquedas por los siguientes filtros: Temas Subtemas Sector de Población al que va dirigido Juntas Titularidad Acceso a la ficha descriptiva del dataset
DOI: 10.5281/zenodo.6759706
title: Farmacias

description: Este conjunto de datos incluye un directorio con los datos de las <strong>Farmacias</strong> de Zaragoza. A través del Servicio de Visualización, el Ayuntamiento de Zaragoza pone a disposición una visualización en la que se muestran datos sobre Farmacias. El conjunto de datos contiene información de localización (dirección, código postal, latitud y longitud), contacto (email y teléfono), horario y url a la web de cada centro. <strong>Fuente de información:</strong> Colegio Oficial de Farmacéuticos de Zaragoza Acceso a la ficha descriptiva del dataset
DOI: 10.5281/zenodo.6759705
title: Farmacias

description: Este conjunto de datos incluye un directorio con los datos de las <strong>Farmacias</strong> de Zaragoza. A través del Servicio de Visualización, el Ayuntamiento de Zaragoza pone a disposición una visualización en la que se muestran datos sobre Farmacias. El conjunto de datos contiene información de localización (dirección, código postal, latitud y longitud), contacto (email y teléfono), horario y url a la web de cada centro. <strong>Fuente de información:</strong> Colegio Oficial de Farmacéuticos de Zaragoza Acceso a la ficha descriptiva del dataset
DOI: 10.5517/ccdc.csd.cc2bccfj
title: CCDC 2155877: Experimental Crystal Structure Determination

description: Related Article: Benita Barton, Mino R. Caira, Ulrich Senekal, Eric C. Hosten|2022|CrystEngComm|24|4573|doi:10.1039/D2CE00327A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bh332
title: CCDC 2159463: Experimental Crystal Structure Determination

description: Related Article: Chang-Qing Miao, Ni Wang, Yan-Ni Ling, Xia-Qing Ma, Yu-Xin Chen, Rui-Feng Wang, Li-Hua Hou, Yu-Peng Hua, Min-Yan Kang, Ming Fang|2022|Inorg.Chim.Acta|540|121050|doi:10.1016/j.ica.2022.121050
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bh387
title: CCDC 2159468: Experimental Crystal Structure Determination

description: Related Article: Chang-Qing Miao, Ni Wang, Yan-Ni Ling, Xia-Qing Ma, Yu-Xin Chen, Rui-Feng Wang, Li-Hua Hou, Yu-Peng Hua, Min-Yan Kang, Ming Fang|2022|Inorg.Chim.Acta|540|121050|doi:10.1016/j.ica.2022.121050
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bh398
title: CCDC 2159469: Experimental Crystal Structure Determination

description: Related Article: Chang-Qing Miao, Ni Wang, Yan-Ni Ling, Xia-Qing Ma, Yu-Xin Chen, Rui-Feng Wang, Li-Hua Hou, Yu-Peng Hua, Min-Yan Kang, Ming Fang|2022|Inorg.Chim.Acta|540|121050|doi:10.1016/j.ica.2022.121050
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.20160377.v1
title: Supplementary Material for: S3 Guideline “Smoking and Tobacco Dependence: Screening, Diagnosis, and Treatment” – Short Version

description: <b><i>Introduction:</i></b> In addition to the prevention of tobacco consumption, the establishment and assurance of high-quality treatment for harmful use and dependence on tobacco products remains an important health-related task in Germany. Regular updating of the Association of the Scientific Medical Societies (AWMF) S3 guideline “Smoking and Tobacco Dependence: Screening, Diagnosis, and Treatment” (Tobacco Guideline) offers a sustainable and reputable source of knowledge on smoking cessation. <b><i>Methods:</i></b> Under the auspices of the German Society for Psychiatry, Psychotherapy, Psychosomatics, and Neurology (DGPPN) and the German Society for Addiction Research and Addiction Therapy (DG-Sucht), the Tobacco Guideline was revised in 2019–2020 by 63 experts, who were involved in the development process of the text, in 11 working groups. Undue influence of conflicts of interest on the guideline could be minimized through careful conflict of interest management. Delegates from 50 professional societies discussed the 80 guideline recommendations and voted online. <b><i>Results:</i></b> In addition to recommendations for screening and diagnostics, the Tobacco Guideline takes a positive stance towards the use of low-threshold counseling and support services. If, due to the severity of the tobacco-related disorder, brief counseling, telephone counseling, or internet- or smartphone-based methods are not sufficiently effective, individual or group behavioral therapy, possibly in combination with medication, is indicated. If nicotine replacement therapy is not effective, varenicline or bupropion should be offered. Alternative strategies with a lower level of recommendation are hypnotherapy, mindfulness-based treatments, or medication with cytisine. In adolescents and pregnant women, the use of medication should be limited to well-specified exceptions and nicotine replacement. The mean agreement with the recommendations reached a value of 98%. A general overview of the treatment recommendations of the Tobacco Guideline is provided by three clinical algorithms.
DOI: 10.6084/m9.figshare.20012816.v1
title: Supplementary Material for: First trimester screening for gestational diabetes mellitus with maternal factors and biomarkers

description: Introduction: This study aimed to identify risk factors among maternal characteristics, obstetric history and first trimester preeclampsia-specific biomarkers that were associated with subsequent development of gestational diabetes mellitus (GDM) and evaluate the performance of the prediction models. Methods: Secondary analysis of a prospective cohort study. The performance of the prediction models was assessed by area under receiver operating characteristic curve (AUROC). Results: A total of 837 (8.9%) cases of GDM and 8535 (91.1%) unaffected cases were included. The AUROC of the prediction model combining maternal characteristics and obstetric history (0.735) was better than that of the model utilizing maternal characteristics (AUROC 0.708) and preeclampsia-specific biomarkers (AUROC 0.566). Amongst the preeclampsia-specific biomarkers, the mean arterial pressure (MAP) contributed to the increasing risk of GDM, however, its addition did not improve the AUROC of the model combining maternal characteristics and obstetric history (0.738). Conclusion: The first trimester prediction model for GDM with maternal characteristics and obstetric history achieves moderate predictability. The inclusion of MAP in the model combining maternal characteristics and obstetric history does not improve the screening performance for GDM. Future studies are needed to explore the effect of blood pressure control from early pregnancy on preventing GDM.
DOI: 10.6084/m9.figshare.20012816
title: Supplementary Material for: First trimester screening for gestational diabetes mellitus with maternal factors and biomarkers

description: Introduction: This study aimed to identify risk factors among maternal characteristics, obstetric history and first trimester preeclampsia-specific biomarkers that were associated with subsequent development of gestational diabetes mellitus (GDM) and evaluate the performance of the prediction models. Methods: Secondary analysis of a prospective cohort study. The performance of the prediction models was assessed by area under receiver operating characteristic curve (AUROC). Results: A total of 837 (8.9%) cases of GDM and 8535 (91.1%) unaffected cases were included. The AUROC of the prediction model combining maternal characteristics and obstetric history (0.735) was better than that of the model utilizing maternal characteristics (AUROC 0.708) and preeclampsia-specific biomarkers (AUROC 0.566). Amongst the preeclampsia-specific biomarkers, the mean arterial pressure (MAP) contributed to the increasing risk of GDM, however, its addition did not improve the AUROC of the model combining maternal characteristics and obstetric history (0.738). Conclusion: The first trimester prediction model for GDM with maternal characteristics and obstetric history achieves moderate predictability. The inclusion of MAP in the model combining maternal characteristics and obstetric history does not improve the screening performance for GDM. Future studies are needed to explore the effect of blood pressure control from early pregnancy on preventing GDM.
DOI: 10.6084/m9.figshare.19929182.v1
title: SUPPLEMENTS.docx

description: These supplements contain the search strategy, the score from agency for healthcare research and quality (AHRQ) checklist (cross-sectional) for studies, and the score of the risk of bias of included studies
DOI: 10.6084/m9.figshare.19929182.v3
title: Supplements.Docx

description: These supplements contain the search strategy, the score from agency for healthcare research and quality (AHRQ) checklist (cross-sectional) for studies, and the score of the risk of bias of included studies
DOI: 10.6084/m9.figshare.19929182.v2
title: Supplementary Material.docx

description: These supplements contain the search strategy, the score from agency for healthcare research and quality (AHRQ) checklist (cross-sectional) for studies, and the score of the risk of bias of included studies
DOI: 10.35110/2774795b-e223-47c7-82d4-03f2b2ceecef
title: Port Ganny (Giant's Causeway - Northern Ireland)

description: Nuage de points 3D par photogrammétrie terrestre RTK
DOI: 10.6084/m9.figshare.20160407
title: PKR_chiroptera_tree.txt

description: Phylogenetic tree of PKR from Chiroptera (Fig 1A Jacquet et al 2022)
DOI: 10.6084/m9.figshare.20160407.v1
title: PKR_chiroptera_tree.txt

description: Phylogenetic tree of PKR from Chiroptera (Fig 1A Jacquet et al 2022)
DOI: 10.6084/m9.figshare.20160446.v1
title: PKR_carnivora_tree.txt

description: Phylogenetic tree of PKR from Carnivora (Fig 1A Jacquet et al 2022)
DOI: 10.5281/zenodo.6759729
title: Supplementary Files

description: The content of the package contains 3 Supplementary tables entitled as follows: <strong>-Supplementary File 1:</strong>Primer picking results for (BSP) bisulfite sequencing PCR<strong>;</strong> <strong>-Supplementary File 2: </strong>Down-regulated microRNAs curated from literature analysis; <strong>-Supplementary File 3:</strong> Up-regulated microRNAs curated from literature analysis.
DOI: 10.5281/zenodo.6759728
title: Supplementary Files

description: The content of the package contains 3 Supplementary tables entitled as follows: <strong>-Supplementary File 1:</strong>Primer picking results for (BSP) bisulfite sequencing PCR<strong>;</strong> <strong>-Supplementary File 2: </strong>Down-regulated microRNAs curated from literature analysis; <strong>-Supplementary File 3:</strong> Up-regulated microRNAs curated from literature analysis.
DOI: 10.6084/m9.figshare.20160446
title: PKR_carnivora_tree.txt

description: Phylogenetic tree of PKR from Carnivora (Fig 1A Jacquet et al 2022)
DOI: 10.6084/m9.figshare.20160446.v3
title: PKR_carnivora_tree.txt

description: Phylogenetic tree of PKR from Carnivora (Fig 1A Jacquet et al 2022)
DOI: 10.6084/m9.figshare.20160446.v2
title: PKR_carnivora_tree.txt

description: Phylogenetic tree of PKR from Carnivora (Fig 1A Jacquet et al 2022)
DOI: 10.6084/m9.figshare.20160419
title: PKR_artiodactyla_tree.txt

description: Phylogenetic tree of PKR from Artiodactyla (Fig 1A Jacquet et al 2022)
DOI: 10.6084/m9.figshare.20160419.v1
title: PKR_artiodactyla_tree.txt

description: Phylogenetic tree of PKR from Artiodactyla (Fig 1A Jacquet et al 2022)
DOI: 10.18728/igb-fred-728.2
title: Mongolian Aquatic Insect Survey (MAIS)

description: Study site: Mongolia. Authors: Alain Maasri. Contact details: Alain Maasri. E-mail: alainmaasri@gmail.com. ORCID: https://orcid.org/0000-0003-1236-8374. Affiliation: Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany AND The Academy of Natural Sciences of Drexel University, Philadelphia, Pennsylvania, USA. We thank the PIs Jon Gelhaus, Barbara Hayford, Riley Nielson and John Morse, and Boloroo Erdenee, Suvdtsetseg Chuluunbat and Oyunchuluun Yadamsuren from Mongolia, who were instrumental in getting the MAIS data sampled and identified.
DOI: 10.5519/qd.v6g1ui4f
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5163570 records)
DOI: 10.6084/m9.figshare.20160416
title: PKR_rodentia_tree.txt

description: Phylogenetic tree of PKR from Rodentia (Fig 1A Jacquet et al 2022)
DOI: 10.6084/m9.figshare.20160416.v1
title: PKR_rodentia_tree.txt

description: Phylogenetic tree of PKR from Rodentia (Fig 1A Jacquet et al 2022)
DOI: 10.5281/zenodo.6759760
title: Harvesting the Value of Data: A Data Architectural Smart Solutions Approach for Enabling Digital Water - Dataset

description: This database includes the test data used to produce the results for the following article: Harvesting the Value of Data: A Data Architectural Smart Solutions Approach for Enabling Digital Water by S. Seshan, D. Vries, M. Zandvoort, A. W. C. van der Helm, J. Poinapen, Smart Water - WaterAge Magazine, February 16-23