cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6024778
title: lyDATA/2021 USZ Oropharynx

description: Dataset: We provide a dataset on lymphatic metastatic progression in head & neck squamous cell carcinoma (HNSCC). 287 patients with newly diagnosed oropharyngeal SCC treated at a single institution between 2013 and 2019 were retrospectively analyzed. For each patient, lymph node level (LNL) involvement for levels I to VII was recorded together with clinicopathological factors including TNM-stage, primary tumor subsite, tumor lateralization, HPV status, sex, age, smoking status, and primary treatment. Ipsilateral and contralateral LNL involvement was assessed individually based on available diagnostic modalities (PET, MRI, CT, FNA) by reviewing pathology and radiology reports together with the images. The data is shared as a large CSV-table with rows of patients and columns of patient/tumor-specific information and the involvement of individual LNL based on the respective diagnostic modalities.


Reuse potential: While prevalence of LNL involvement has been reported previously, patterns of lymphatic progression have never been reported on a patient-individual basis in as much detail as provided in this dataset. The data can be used to build quantitative models for lymphatic tumor progression to estimate the probability of occult metastases in LNL, which may allow for further personalized elective clinical target volume definition in radiotherapy. The data can be pooled with other data to build large multi-institutional datasets on lymphatic metastatic progression in the future.
description: This work was supported by the clinical research priority program (CRPP) "Artificial intelligence in oncological imaging" at the University of Zurich.
DOI: 10.5281/zenodo.6630713
title: lyDATA: 2021 USZ Oropharynx

description: Dataset:


We provide a dataset on lymph node level (LNL) involvement in 287 patients with newly diagnosed oropharyngeal squamous cell carcinoma (OPSCC). For each patient, ipsilateral and contralateral LNL involvement for levels I to VII is reported together with clinicopathological factors including TNM-stage, primary tumor subsite, tumor lateralization, HPV status, sex, age, smoking status, and primary treatment. LNL involvement was assessed individually based on available diagnostic modalities (PET, MRI, CT, fine needle aspiration) by reviewing pathology and radiology reports together with the radiological images. The data is shared as a CSV-table with rows of patients and columns of patient/tumor-specific information and the involvement of individual LNL based on the respective diagnostic modalities.


Reuse potential:


Patterns of lymphatic progression have never been reported on a patient-individual basis in as much detail as provided in this dataset. The data can be used to build quantitative models for lymphatic tumor progression to estimate the probability of occult metastases in LNLs. This may in turn allow for further personalization of the elective clinical target volume definition in radiotherapy and the extent of neck dissection for surgically treated patients. The data can be pooled with other data to build large multi-institutional datasets on lymphatic metastatic progression in the future.
description: This work was supported by the clinical research priority program (CRPP) "Artificial intelligence in oncological imaging" at the University of Zurich.
DOI: 10.5281/zenodo.5840172
title: lyDATA/2021 Oropharynx Dataset

description: Dataset: We provide a dataset on lymphatic metastatic progression in head & neck squamous cell carcinoma (HNSCC). 287 patients with newly diagnosed oropharyngeal SCC treated at a single institution between 2013 and 2019 were retrospectively analyzed. For each patient, lymph node level (LNL) involvement for levels I to VII was recorded together with clinicopathological factors including TNM-stage, primary tumor subsite, tumor lateralization, HPV status, sex, age, smoking status, and primary treatment. Ipsilateral and contralateral LNL involvement was assessed individually based on available diagnostic modalities (PET, MRI, CT, FNA) by reviewing pathology and radiology reports together with the images. The data is shared as a large CSV-table with rows of patients and columns of patient/tumor-specific information and the involvement of individual LNL based on the respective diagnostic modalities. Reuse potential: While prevalence of LNL involvement has been reported previously, patterns of lymphatic progression have never been reported on a patient-individual basis in as much detail as provided in this dataset. The data can be used to build quantitative models for lymphatic tumor progression to estimate the probability of occult metastases in LNL, which may allow for further personalized elective clinical target volume definition in radiotherapy. The data can be pooled with other data to build large multi-institutional datasets on lymphatic metastatic progression in the future.
description: This work was supported by the clinical research priority program (CRPP) "Artificial intelligence in oncological imaging" at the University of Zurich.
DOI: 10.5281/zenodo.8355469
title: Targeted color design of silver-gold alloy nanoparticles

description: This is the raw data for the manuscript:
Targeted color design of silver-gold alloy nanoparticlesAbstract:This research article focuses on the targeted color design of silver-gold alloy nanoparticles (NPs), employing a multivariate optimization approach. NP synthesis involves interconnected process parameters, making independent variation challenging. Data-based property-process relationships are established to optimize optical properties effectively. We define a color target, employ a green chemical co-reduction method at room temperature and optimize process parameters accordingly. The CIEL*a*b* color space and Euclidean distances facilitate accurate color matching to establish the property-process relationship. Concurrently, theoretical Mie calculations explore the structure-property relationship across particle sizes, concentrations, and molar gold contents. The theoretically optimal structure agrees very well with experimental particle structures at the property-process relationship's optimum. The data-driven property-process relationship provides valuable insights into the formation mechanism of a complex particle system, sheds light on the role of relevant process parameters and allows to evaluate the practically available property space. Model validation beyond the original grid demonstrates its robustness, yielding colors close to the target. Additionally, Design of Experiments (DoE) methods reduce experimental work by threefold with slight accuracy trade-offs. Our novel methodology for targeted color design demonstrates how data-based methods can be utilized alongside structure-property relationships to unravel property-process relationships in the design of complex nanoparticle systems and paves the way for future developments in targeted property design.
All data are sorted according to their appearance in the figures of the main manuscript.
DOI: 10.5281/zenodo.8355470
title: Targeted color design of silver-gold alloy nanoparticles

description: This is the raw data for the manuscript:
Targeted color design of silver-gold alloy nanoparticlesAbstract:This research article focuses on the targeted color design of silver-gold alloy nanoparticles (NPs), employing a multivariate optimization approach. NP synthesis involves interconnected process parameters, making independent variation challenging. Data-based property-process relationships are established to optimize optical properties effectively. We define a color target, employ a green chemical co-reduction method at room temperature and optimize process parameters accordingly. The CIEL*a*b* color space and Euclidean distances facilitate accurate color matching to establish the property-process relationship. Concurrently, theoretical Mie calculations explore the structure-property relationship across particle sizes, concentrations, and molar gold contents. The theoretically optimal structure agrees very well with experimental particle structures at the property-process relationship's optimum. The data-driven property-process relationship provides valuable insights into the formation mechanism of a complex particle system, sheds light on the role of relevant process parameters and allows to evaluate the practically available property space. Model validation beyond the original grid demonstrates its robustness, yielding colors close to the target. Additionally, Design of Experiments (DoE) methods reduce experimental work by threefold with slight accuracy trade-offs. Our novel methodology for targeted color design demonstrates how data-based methods can be utilized alongside structure-property relationships to unravel property-process relationships in the design of complex nanoparticle systems and paves the way for future developments in targeted property design.
All data are sorted according to their appearance in the figures of the main manuscript.
DOI: 10.5281/zenodo.10199711
title: Data From: A Trunk Diameter Estimation Mobile App for the Masses

description: Overview
This dataset contains RGB and depth images (raw images and text files) of tree trunks collected using Google ARCore. It has 154 samples from four countries, with DBH ranging from 4.8-155.3cm. We annotated aspects like trunk shapes, leaning, lighting conditions when captured, etc. The data was originally intended for evaluating our designed tree diameter measurement app (https://github.com/MingyueX/GreenLens).
Data introduction

treedata.zip contains three folders - rgb, depthimg and depthtxt - representing raw RGB images, depth images and depth text files respectively.
data_label.xlsx includes the labels and corresponding descriptions.
Usage Notes
The rgb and depthimg folders contain jpg images with 480*360 resolution, where the depthimg images are obtained by reading the raw text files in depthtxt folder and resizing to 480*360.
The files with no extension in the depthtxt folder are stored in the format as x-coordinate of pixel, y-coordinate of pixel, depth measurement of pixel and confidence value.
DOI: 10.6084/m9.figshare.23309477
title: Supplementary tables for PAS and NAS statements in Communication skills attitude scale

description: This data pertains to the study where medical students and interns attitude towards learning communication skills was assessed using communication skills and attitude scale(CSAS). The medical students were taught communication skills required for healthcare professionals using modules on Foundations of Communication in AETCOM course over all professional years. The feedback was collected from interns regarding the effectiveness of these modules in equipping them to interact with patients and family during the internship. The mean of the responses to the communication skills and attitude scale(CSAS) for the positive attitude statements(PAS) is presented in supplementary table 1 and negative attitude statements(NAS) in supplementary table 2.<b>Supplementary table 1:</b><b> </b><b>Mean scores of PAS in CSAS</b><b>Supplementary table 2:</b><b> </b><b>Mean scores of </b><b>NAS in </b><b>CSAS</b>
DOI: 10.21942/uva.24624342
title: Raw EEG data

description: This folder contains all the raw EEG data. Filenames have the following structure: {subjectID}_{session}_attend.raw.fif. For example for the first, subject and session the filename is: 01_0_attend.raw.fif <br> <br>
DOI: 10.21942/uva.24624342.v1
title: Raw EEG data

description: This folder contains all the raw EEG data. Filenames have the following structure: {subjectID}_{session}_attend.raw.fif. For example for the first, subject and session the filename is: 01_0_attend.raw.fif <br> <br>
DOI: 10.21942/uva.24624321
title: Pupil data

description: This dataset contains the pupil data that was used to establish effects of atomoxetine and donepezil on pupil size prior to the onset of the first behavioral experiment (when levels of both atomoxetine and donepezil were assumed to peak in blood levels). Note that task order was counter-balanced between participants. The first task of each participant is named in the .edf file containing the pupil data. <br> From the start of the recording participants saw an instruction text for 5s, followed by three periods (15s each) in which the monitor background was first dark (RGB=(0,0,0)), then bright (RGB=(0,0,0)), and then dark again (RGB=(0,0,0)). One can use these timings to extract raw pupil data during these time-windows to extract minimal and maximal pupil size during each drug condition.
DOI: 10.21942/uva.24624321.v1
title: Pupil data

description: This dataset contains the pupil data that was used to establish effects of atomoxetine and donepezil on pupil size prior to the onset of the first behavioral experiment (when levels of both atomoxetine and donepezil were assumed to peak in blood levels). Note that task order was counter-balanced between participants. The first task of each participant is named in the .edf file containing the pupil data. <br> From the start of the recording participants saw an instruction text for 5s, followed by three periods (15s each) in which the monitor background was first dark (RGB=(0,0,0)), then bright (RGB=(0,0,0)), and then dark again (RGB=(0,0,0)). One can use these timings to extract raw pupil data during these time-windows to extract minimal and maximal pupil size during each drug condition.
DOI: 10.5281/zenodo.10204017
title: SEM Images of Arrays of III-V Nanowires with Labelled Data

description: The Dataset is a .zip folder.
The Dataset contains 240 .tiff images in black and white, each paired by file name to a .json file containing labeling information. 
Each image consists of an array of 66 nanowire structures. Some images contain parasitic crystals and defective wires. Wires growing from seed surfaces parallel to and misaligned with the array walls are present.
The .json label files were created and can be processed with LabelMe (https://github.com/wkentaro/labelme). The explanation for the labels can be found in the associated open-access paper currently submitted for publication.
The Licensor, IBM Corp.
DOI: 10.5281/zenodo.10204018
title: SEM Images of Arrays of III-V Nanowires with Labelled Data

description: The Dataset is a .zip folder.
The Dataset contains 240 .tiff images in black and white, each paired by file name to a .json file containing labeling information. 
Each image consists of an array of 66 nanowire structures. Some images contain parasitic crystals and defective wires. Wires growing from seed surfaces parallel to and misaligned with the array walls are present.
The .json label files were created and can be processed with LabelMe (https://github.com/wkentaro/labelme). The explanation for the labels can be found in the associated open-access paper currently submitted for publication.
The Licensor, IBM Corp.
DOI: 10.25625/ueeluh/kj67fi
title: Suppl-Fig-3-Itzum(Maul-Loh-Riegel)_ergaenzt-1.jpg

description: Suppl. Fig. 3. Columar section of the lower and middle Posidonienschiefer Formation at Hildesheim-Itzum according to Maul (1984), Loh et al. (1986), and Riegel et al. (1986).
DOI: 10.25625/ueeluh/c8lpni
title: ms-Arp-et-al_Tab-1-Geochemistry(Hainberg)_R1.xls

description: Tab. 1. Carbon, sulphur, and nitrogen contents of sedimentary rocks of the Hainberg section.
DOI: 10.25625/ueeluh/a5m7vq
title: Fig-1-Hainberg-location-map_R1.jpg

description: Fig. 1. Geographic and geological overview with the location of the Hainberg section and further locations of Toarcian sections in Northern Germany. Outcrop and subsurface deposits of Lower Jurassic after Arnold et al. (1973), Duphorn et al. (1974), Motzka et al. (1979), Waldeck (1986), Kriebel et al. (1998), Motzka-Nöring (1998), Seidel et al. (1998), Radzinski et al. (1999), Knoth et al. (2000), Martiklos (2002), and Reinhold et al. (2008). Supposed former coastlines of the Toarcian after Brockamp (1944; outdated) and Ziegler (1990). Areas outlined in red are Variscan basement rocks, uplifted during the Cretaceous.
DOI: 10.25625/ueeluh/ogxfgs
title: Suppl-Fig-2-Listringen(Vinken)-1.jpg

description: Suppl. Fig. 2. Columnar section from the middle part of the Posidonienschiefer Formation at Listringen according to Vinken (1971).
DOI: 10.25625/ueeluh/egnwpf
title: Fig-2-Hainberg-section_geochemistry_R1.jpg

description: Fig. 2. Overview on lithology and lithostratigraphy of the Hainberg section (top Amaltheenton Fm. to lower Opalinuston Fm.) with CaCO3, organic carbon, and sulphur contents. For legend see Fig. 6.
DOI: 10.25625/ueeluh/rzmnh7
title: ms-Arp-et-al_Suppl-Tab-1-Belemnite-orientation(Hainberg)-1.xls

description: Suppl. Tab. 1. Measurements of belemnite alignments in the Posidonienschiefer and Jurensismergel Formations, Toarcian, Hainberg section.
DOI: 10.25625/ueeluh/kh6eyh
title: Suppl-Fig-1-Hainberg-biofacies-1.jpg

description: Suppl. Fig. 1. Selected biofacies of the Toarcian to lowermost Aalenian succession, Hainberg section. (1) Parainoceramya biofacies, bed 11 "Boreale Concretions", middle Posidonienschiefer Formation. GZG.INV.891. (2) Bositra buchi biofacies, bed 21, middle Posidonienschiefer Formation. GZG.INV.892. (3) Cephalopod-free dwarf Bositra buchi biofacies, 9 m above basis of bed 24, upper Posidonienschiefer Formation. GZG.INV.893. (4) Chlamys textoria biofacies, bed 27 "oolite marl", Jurensismergel Formation. GZG.INV.894. (5) Nubeculariid foraminifera on bioclasts of the Chlamys textoria biofacies. Bed 29, Jurensismergel Formation. GZG.INV.895. (6) Bositra suessi biofacies, 80 cm above basis of bed 40, Opalinuston Formation. GZG.INV.896.
DOI: 10.25625/ueeluh/iam3k7
title: Fig-3-10-Hainberg_cephalopods-1_R2.jpg

description: Figures 3–10. Ammonites and Belemnites of the Toarcian Hainberg section 3. Dactylioceras cf. crosbeyi (Simpson), bed 9, Posidonienschiefer Formation, Tenuicostatum Zone. GZG.INV.866: d = (21) mm, n = (7), wh = (8) mm, rb/2 = (20); 4. Hildaites murleyi (Moxon), bed 11 “Boreale Concretions”, Posidonienschiefer Formation, Exaratum Subzone. GZG.INV.867: d = 75 mm, di = 53 mm, u = 30 mm, wh = 23 mm, wb = (17) mm, rb/2 = (20); 5. Lytoceras sp. und Parainoceramya dubia (Sowerby), bed 12, Posidonienschiefer Formation, Exaratum/Elegans Subzone. GZG.INV.868: d = (33) mm, u = (10) mm, wh = 14 mm; 6. Eleganticeras elegans (Sowerby), bed 15, Posidonienschiefer Formation, Elegans Subzone. GZG.INV.869: d = 66 mm, di = (42) mm, u = (13) mm, wh = (36) mm; 7. Dactylioceras (Dactylioceras) cf. commune (Sowerby), 5 cm above basis of bed 24, Posidonienschiefer Formation, Commune Subzone. GZG.INV.870: d = 53 mm, di = (42) mm, u = (27) mm, wh = (12) mm; 8. Acrocoelites sp., left: lateral view, right: ventral view, bed 23, Posidonienschiefer Formation, Commune Subzone. GZG.INV.871: Length = 63.5 mm (incomplete: without alveolar region); 9. Dactyloteuthis irregularis (Schlotheim) [syn.: Dactyloteuthis digitalis (Blainville)], left: lateral view, right: ventral view, bed 23, Posidonienschiefer Formation, Commune Subzone. GZG.INV.872: Length = 40.5 mm; 10. Osperleioceras cf. beauliziense (Monestier), bed 27, Jurensismergel Formation, ?Thouarsense Zone. GZG.INV.873: d = 40 mm, di = (27) mm, u = 11 mm, wh = 18 mm, wb = 9.5 mm, rb/2 = 20.
DOI: 10.25625/ueeluh/2bhb4o
title: Fig-11-26-Hainberg_cephalopods-2_R2.jpg

description: Figures 11–26. Ammonites and Belemnites of the Upper Toarcian of the Hainberg section 11. Phlyseogrammoceras dispansiforme (Wunstorf), bed 28 “zeta conglomerate”, Jurensismergel Formation, Dispansum Subzone. GZG.INV.874: d = 55.5 mm, di = (38) mm, u = 17 mm, wh = 24 mm, wb = 14 mm, rb/2 = (30); 12. Phlyseogrammoceras dispansiforme (Wunstorf), bed 28 “zeta conglomerate”, Jurensismergel Formation, Dispansum Subzone. GZG.INV.875: d = 49.5 mm, di = 34.5 mm, u = 13 mm, wh = 23.5 mm, wb = 13 mm, rb/2 = 31; 13. Phlyseogrammoceras transiens (Ernst), bed 28 „zeta conglomerate“, Jurensismergel Formation, Dispansum Subzone. GZG.INV.876: d = 34 mm, di = (23) mm, u = 9.5 mm, wh = 15.5 mm, wb = 10 mm, rb/2 = 24; 14. ?Alocolytoceras sp., bed 28, Jurensismergel Formation, Dispansum Subzone. GZG.INV.877: d = (59) mm, wh = 28 mm, wb = 24 mm; 15. Cotteswoldia aalensis (Zieten), bed 32, Opalinuston Formation, Aalensis Subzone. GZG.INV.878: d = (34) mm, wh = 17 mm, wb = 9 mm; 16. Pleydellia subcompta (Branco), bed 32, Opalinuston Formation, Aalensis Subzone. GZG.INV.879: d = 40 mm, di = (28) mm, u = 15 mm, wh = 14.5 mm, wb = 18 mm, rb/2 = (45); 17. Fragment of Pleurolytoceras cf. hircinum (Schlotheim), dorsal view showing v-shaped constriction; bed 32, Opalinuston Formation, Aalensis Subzone. GZG.INV.880; 18. Pleydellia cf. pseudoarcuata Maubeuge, bed 39, Opalinuston Formation, Pseudolotharingicum Subzone. GZG.INV.881: wh = 11.5 mm, wb = 7 mm; 19. ?Cotteswoldia sp., bed 39, Opalinuston Formation, Pseudolotharingicum Subzone. GZG.INV.882: wh= 20 mm, wb = 10 mm; 20. Leioceras cf. goetzendorfensis (Dorn), Opalinuston Formation, Opalinum Subzone. GZG.INV.883: d = (70) mm, di = (48) mm, u = 19 mm, wh = 31 mm, wb = 14 mm; 21. Dactyloteuthis irregularis (Schlotheim) [syn.: Dactyloteuthis digitalis (Blainville)], left: lateral view, right: dorsal view; bed 27, Jurensismergel Formation, ?Thouarsense Zone. GZG.INV.884: Length = 61 mm; 22. Dactyloteuthis similis (Seebach), left: lateral view; right: dorsal view; bed 28, Jurensismergel Formation, Dispansum Subzone. GZG.INV.885: Length = 59 mm; 23. Acrocoelites rostriformis (Theodori in Bronn) [syn.: Acrocoelites (Odontobelus) curtus (d’Orbigny)], left: lateral view, right: dorsal view; bed 32, Opalinuston Formation, Aalensis Subzone. GZG.INV.886: Length = 28 mm; 24. Hastites subclavatus (Voltz), left: lateral view, right: dorsal or ventral view; bed 32, Opalinuston Formation, Aalensis Subzone. GZG.INV.887: Length = 52 mm; 25. Hastites subclavatus (Voltz), left: lateral view, right: dorsal or ventral view; bed 32, Opalinuston Formation, Aalensis Subzone. GZG.INV.888: Length = 42.5 mm; 26. Acrocoelites rostriformis (Theodori in Bronn) [syn.: Acrocoelites (Odontobelus) curtus (d’Orbigny)], left: lateral view, right: dorsal view; bed 39, Opalinuston Formation, Pseudolotharingicum Subzone. GZG.INV.889: Length = 24.5 mm.
DOI: 10.25625/ueeluh/e2gws0
title: Fig-28-Hainberg-section-Posidoniensfr-stratigraphy_R1.jpg

description: Figure 28. Lithostratigraphy, biostratigraphy and biofacies of the Posidonienschiefer Formation, Lower Toarcian, exposed at the Hainberg section.
DOI: 10.25625/ueeluh/qllr4c
title: Fig-32-Hainberg-adjacent-sections-sequenzstratigraphy_R1.jpg

description: Figure 32. Sequence stratigraphic interpretation of the Toarcian succession in Northern Germany (including the Hainberg section) and Thuringia in comparison with 3rd order South-German and the 2nd order Boreal standard cycles. Sedimentary succession and ammonite biostratigraphic evidence according to Denckmann (1892), Ernst (1923–1924), Kumm (1941), Ernst (1970), Maul (1984), Brachmann (1991), Krause and Katzung (1999), and specimens from the BGR collection [https://gewis.bgr.de/, leg. K. Hoffmann, R. Jordan, K. Wiedenroth]. T-R cycles: 1 third order sequences Northern Germany (Zimmermann et al. 2015), 2 third order sequences Southern Germany (Röhl and Schmid-Röhl 2005; Arp et al. 2021); 3 second order sequences Boreal standard (de Graciansky et al. 1998; Jacquin et al. 1998).
DOI: 10.25625/ueeluh/p1wmkg
title: Fig-29-Hainberg-section-Jurensismergel-stratigraphy_R1.jpg

description: Figure 29. Lithostratigraphy, biostratigraphy and biofacies of the Jurensismergel Formation, Upper Toarcian, exposed at the Hainberg section. For legend see Fig. 28.
DOI: 10.25625/ueeluh/5bqnu6
title: Fig-27-Hainberg_Lepidotes_R1.JPG

description: Figure 27. Limestone concretion (“Elegantulum Concretion”) of bed 10 with Lepidotes elvensis (de Blainville) and Eleganticeras elegantulum (Young & Bird). GZG.INV.890ab: d = 28.7 mm, u = 8 mm, wh = 12 mm, wb = 7.8 mm.
DOI: 10.25625/ueeluh/s3s8b2
title: Fig-31-Hainberg-adjacent-sections-correlation_R1.jpg

description: Figure 31. Correlation of the investigated section Hainberg with sections from Northern Germany and Thuringia, with suggested T-R cycles for the sections Hainberg and Dörnten.