cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18150/ec3qmi
title: Data for the article entitled: Multiphoton microscopy at a microwatt level via gain-managed nonlinear amplification and pulse picking

description: The following files include data presented in the manuscript “Multiphoton microscopy at a microwatt level via gain-managed nonlinear amplification and pulse picking,” written by Katarzyna Kunio, Grzegorz Soboń, and Jakub Bogusławski.Fig. 2a – Characterization of the pulse: optical spectrum at the output of the oscillator and at the output of the bandpass filterFig. 2b – Characterization of the pulse: autocorrelation with the Gaussian fit at the output of the oscillatorFig. 2c – Characterization of the pulse: autocorrelation with the Gaussian fit at the output of the bandpass filterFig. 3a – Characterization of the pulse after amplification and compression at different values of the pump power: optical spectraFig. 3b – Characterization of the pulse after amplification and compression at different values of the pump power: FROG-retrieved temporal intensity with temporal phaseFig. 4a – Characterization of the pulse at the pump power of 2.26 W: optical spectrumFig. 4b – Characterization of the pulse at the pump power of 2.26 W: FROG-retrieved temporal intensity with temporal phaseFig. 4b (inset) – FROG spectrograms: measured and retrievedFig. 5a – Analysis of the influence of lowering both the repetition frequency and average power at the sample on TPE microscopy: (a) TPE fluorescence images of convallaria majalis obtained by gradually decreasing the repetition frequency while simultaneously decreasing the average power at the sample. Scale bars: 80 µm.Fig. 5b – Change in the SNR depending on the repetition frequency as a function of number of averaged framesFig. 6 – SHG microscopy images of urea microcrystals obtained by gradually decreasing the repetition frequency while simultaneously decreasing the average power at the sample. Scale bars: 80 µm. Fig. 7a – Comparison of pixel intensities in the images obtained at the same values of the mean signal and different values of the repetition frequency measured in row 250 of images depicting convallaria majalis. Scale bars: 80 µmFig. 7b – Comparison of pixel intensities in the images obtained at the same values of the mean signal and different values of the repetition frequency measured in row 110 of images depicting urea microcrystals. Scale bars: 80 µmFig. 7c – Oscilloscope traces of the detector response measured while imaging urea microcrystals at different repetition frequenciesFig. 8a – Spectral phasor-based 3PEF imaging of epidermal cells without staining: transmission spectra of sine and cosine filtersFig. 8b – Spectral phasor-based 3PEF imaging of epidermal cells without staining: epidermal cell images obtained without an additional filter in front of the PMT (INT), with cosine (COS), and with sine (SIN) filters. Scale bars: 200 µm.Fig. 8c – Spectral phasor-based 3PEF imaging of epidermal cells without staining: spectral phasor plotFig. 8d – Spectral phasor-based 3PEF imaging of epidermal cells without staining: spectral phasor-based color-coded image of epidermal cells. Scale bars: 200 µm.
DOI: 10.18154/rwth-2025-00177
title: Experimental Dataset on Thermoset Injection Molding of a Phenolic Resin Compound

description: The data set shown here contains recorded experimental data for the injection molding of a phenolic resin (Bakelite PF6680) using a flat-plate geometry. The data set includes 15 experiments with different injection velocities and holding pressure levels. Each measurement record includes the pressures in the screw antechamber and inside the cavity, as well as the screw velocity and the volume of the screw antechamber over time. The experiments were conducted on an Arburg Allrounder 370 A 600-170/170 injection molding machine at the Institute for Plastics Processing at RWTH Aachen University.
DOI: 10.26050/wdcc/nextgems_cyc3
title: nextGEMS: output of the model development cycle 3 simulations for ICON and IFS

description: Project: Next Generation Earth Modelling Systems - nextGEMS is a collaborative European project. Funded by the EU’s Horizon 2020 programme, it will tap expertise from fourteen European Nations to develop two next generation (storm-resolving) Earth-system Models. Through breakthroughs in simulation realism, these models will allow us to understand and reliably quantify how the climate will change on a global and regional scale, and how the weather, including its extreme events, will look like in the future. See further details at https://nextgems-h2020.eu/ and https://cordis.europa.eu/project/id/101003470. Summary: In the first phase of the nextGEMS project, the two Earth-system models ICON (Version ee0ee6) and IFS (Cycle 48r1 nextGEMS) are developed in three iterative cycles aiming at simulating the climate 30 years into the future at storm-resolving scale. In each development cycle new features are implemented into the models improving the physical representation of the coupled Earth system as well as the technical feasibility to run at high resolution for increasing simulation time periods. A development cycle concludes with a simulation for at least one year at 5 km horizontal resolution or lower. A subset of the Cycle 3 data is published here, namely monthly averages of selected 2d variables from the 5km ICON simulation and 4km IFS simulation.
DOI: 10.34626/2024/zcdk-7706
title: Stealthing in Brazil: Non-consensual condom removal and health consequences
DOI: 10.3886/e192181v1
title: Data and Code For: The Productivity Consequences of Pollution-Induced Migration in China

description: <b>Summary</b>: This is replication code and data for the paper "The Productivity Consequences of Pollution-Induced Migration in China."<br><br><b>Abstract</b>: We quantify how pollution affects aggregate productivity and welfare in spatial equilibrium. We document a robust pattern in which skilled workers in China emigrate away from polluted cities, more than the unskilled. These patterns are evident under various empirical specifications, such as when instrumenting for pollution using distant upwind power-plants, or thermal inversions that trap pollutants. Pollution changes the spatial distribution of skilled and unskilled workers, which increases returns-toskill in cities that the educated emigrate from. We quantify the loss in aggregate productivity due to this re-sorting by estimating a spatial equilibrium model. Counterfactual simulations show that reducing pollution increases productivity through spatial re-sorting by approximately as much as the direct health benefits of clean air. We identify a new channel through which pollution lowers aggregate productivity significantly. Hukou mobility restrictions exacerbate welfare losses. Skilled workers’aversion to pollution explains a substantial portion of the wage-gap between cities.
DOI: 10.3886/e203821v1
title: Code for: Family Spillover Effects of Marginal Diagnoses: The Case of ADHD

description: Code accompanying article with the following abstract: The health care system uses patient family medical history in many settings, and this practice is widely believed to improve the efficiency of health care allocation. This paper provides a counterpoint by documenting that reliance on hereditary information can amplify the misallocation of low-value care. We study Attention Deficit Hyperactivity Disorder, and show that reliance on family medical history generates a “snowball effect”—the propagation of an original marginal diagnosis to a patient’s relatives. This snowball effect raises the private and social costs of low-value care.
DOI: 10.48364/isimip.600567
title: ISIMIP3b N-deposition input data

description: This dataset contains the nitrogen deposition input data for ISIMIP3a (Frieler et al. 2023, in prep., https://www.isimip.org). It is derived from gridded NHx and NOy deposition data simulated by NCAR Chemistry-Climate Model Initiative (CCMI) in support of CMIP6 and in accordance with the Global N2O Model Intercomparison Project (NMIP) protocol (Tian et al. 2018). <br>The historical period is covered from 1850 to 2014, while the future scenarios ssp126, ssp370, and ssp585 extend from 2015 to 2100. The original CCMI data was downscaled to the ISMIP half degree grid using the nearest neighbor remapping.
DOI: 10.5067/erbs/sageii/solar_binary_l2-v7.0
title: SAGE II/ERBS Level 2 Solar Event Species Profiles Native Binary file - Version 7.0
DOI: 10.5281/zenodo.10514181
title: Raw data to "A Computational Chemistry Study on the Evolution of Oxygen Functional Groups During Char Burnout"

description: This data is a supplement to the publication entitled "A Computational Chemistry Study on the Evolution of Oxygen Functional Groups During Charg Burnout".
DOI: 10.5281/zenodo.13207434
title: A Compiled Archaeobiological Dataset for Central Asia's Chalcolithic through Bronze Age: macrobotanical and zooarchaeological data transcribed, standardized, and summarized from original publications

description: This dataset contains archaeobotnaical and zooarchaeological data that have been compiled, transcribed, standardized, and summarized from original published data sources. Original data publications are given herein as a List of References (Microsoft Word file). These publications appeared between 1960-2022, presenting data in various formats, in various languages, and in scientific works that included journals, books, and conference proceedings - .

Data have been compiled and are given in two Microsoft Excel files, one corresponding to archaeobotanical data and one to zooarchaeological data. On the first tab (worksheet) of each of these files, original publication sources are given in a summarized reference (Author, Year, Table/Figure Number) that corresponds to the full bibliographic reference in the accompanying List of References file. This first tab (worksheet) also summarizes additional information on the archaeological context of each dataset, collection and analysis methods (when reported), and the availabilty of other relevant and/or corresponding datasets. The remaining tabs (worksheets) in each file, organized alphabetically by author last name, tabularize the original data in a standardized format; these data are compiled and transcribed as necessary from the various formatting of original data sources, though they keep the original reported species names, table ordering, and numerical data. In the cases where totals were obviously erroneous or superceded by later or additional analyses, transcription notes have been offered directly in the worksheet.

A fair number of these data sources are now out of print, have no digital distribution, and are otherwise difficult to access physically and/or linguistically. Accordingly, the sole aim in compiling these data here is to facilitate their widespread availablity, proper citation, and increased use within the international community of archaeological scientists working in Central Asia in the present day. Other scholars are encouraged to utilize these compiled datasets for foundational regional data and extended analyses, and to add to and expand these datasets going forward.
DOI: 10.5281/zenodo.13259599
title: Human head models and populational framework for simulating brain stimulations: part 5

description: We share an organized computational model data collection for noninvasive brain stimulation (NIBS) modeling. This dataset includes a subset of the collection's 100 preprocessed, quality-assured, realistic head models based on imaging data from the Human Connectome Project (HCP) s1200 release (Van Essen et al., 2012). We provide verified finite-element meshes, underlying anatomical images, tissue segmentations, standard space co-registrations, quality metrics, and lead-field matrices. We suggest individual tissue conductivity values for each head model from a range of biologically plausible values (McCann et al., 2019). Additionally, we provide straightforward computer code for several use cases of the current dataset. 

 





McCann, H., Pisano, G., & Beltrachini, L. (2019). Variation in Reported Human Head Tissue Electrical Conductivity Values. Brain Topography, 32(5), 825–858. https://doi.org/10.1007/s10548-019-00710-2




Van Essen, D. C., Ugurbil, K., Auerbach, E., Barch, D., Behrens, T. E. J., Bucholz, R., Chang, A., Chen, L., Corbetta, M., Curtiss, S. W., Della Penna, S., Feinberg, D., Glasser, M. F., Harel, N., Heath, A. C., Larson-Prior, L., Marcus, D., Michalareas, G., Moeller, S., … WU-Minn HCP Consortium. (2012). The Human Connectome Project: A data acquisition perspective. NeuroImage, 62(4), 2222–2231. https://doi.org/10.1016/j.neuroimage.2012.02.018



 

This dataset is split into 6 parts, you are currently on part 5. All parts are linked below:

Dataset_1: https://zenodo.org/records/13259679

Dataset_2: https://zenodo.org/records/13259747

Dataset_3: https://zenodo.org/records/13259943

Dataset_4: https://zenodo.org/records/13260068

Dataset_5: https://zenodo.org/records/13259599

Dataset_6: https://zenodo.org/records/13260208
DOI: 10.5281/zenodo.13259747
title: Human head models and populational framework for simulating brain stimulations: part 2

description: We share an organized computational model data collection for noninvasive brain stimulation (NIBS) modeling. This dataset includes a subset of the collection's 100 preprocessed, quality-assured, realistic head models based on imaging data from the Human Connectome Project (HCP) s1200 release (Van Essen et al., 2012). We provide verified finite-element meshes, underlying anatomical images, tissue segmentations, standard space co-registrations, quality metrics, and lead-field matrices. We suggest individual tissue conductivity values for each head model from a range of biologically plausible values (McCann et al., 2019). Additionally, we provide straightforward computer code for several use cases of the current dataset. 

 





McCann, H., Pisano, G., & Beltrachini, L. (2019). Variation in Reported Human Head Tissue Electrical Conductivity Values. Brain Topography, 32(5), 825–858. https://doi.org/10.1007/s10548-019-00710-2




Van Essen, D. C., Ugurbil, K., Auerbach, E., Barch, D., Behrens, T. E. J., Bucholz, R., Chang, A., Chen, L., Corbetta, M., Curtiss, S. W., Della Penna, S., Feinberg, D., Glasser, M. F., Harel, N., Heath, A. C., Larson-Prior, L., Marcus, D., Michalareas, G., Moeller, S., … WU-Minn HCP Consortium. (2012). The Human Connectome Project: A data acquisition perspective. NeuroImage, 62(4), 2222–2231. https://doi.org/10.1016/j.neuroimage.2012.02.018



 

This dataset is split into 6 parts, you are currently on part 2. All parts are linked below:

Dataset_1: https://zenodo.org/records/13259679

Dataset_2: https://zenodo.org/records/13259747

Dataset_3: https://zenodo.org/records/13259943

Dataset_4: https://zenodo.org/records/13260068

Dataset_5: https://zenodo.org/records/13259599

Dataset_6: https://zenodo.org/records/13260208
DOI: 10.5281/zenodo.13260068
title: Human head models and populational framework for simulating brain stimulations: part 4

description: We share an organized computational model data collection for noninvasive brain stimulation (NIBS) modeling. This dataset includes a subset of the collection's 100 preprocessed, quality-assured, realistic head models based on imaging data from the Human Connectome Project (HCP) s1200 release (Van Essen et al., 2012). We provide verified finite-element meshes, underlying anatomical images, tissue segmentations, standard space co-registrations, quality metrics, and lead-field matrices. We suggest individual tissue conductivity values for each head model from a range of biologically plausible values (McCann et al., 2019). Additionally, we provide straightforward computer code for several use cases of the current dataset. 

 





McCann, H., Pisano, G., & Beltrachini, L. (2019). Variation in Reported Human Head Tissue Electrical Conductivity Values. Brain Topography, 32(5), 825–858. https://doi.org/10.1007/s10548-019-00710-2




Van Essen, D. C., Ugurbil, K., Auerbach, E., Barch, D., Behrens, T. E. J., Bucholz, R., Chang, A., Chen, L., Corbetta, M., Curtiss, S. W., Della Penna, S., Feinberg, D., Glasser, M. F., Harel, N., Heath, A. C., Larson-Prior, L., Marcus, D., Michalareas, G., Moeller, S., … WU-Minn HCP Consortium. (2012). The Human Connectome Project: A data acquisition perspective. NeuroImage, 62(4), 2222–2231. https://doi.org/10.1016/j.neuroimage.2012.02.018



 

This dataset is split into 6 parts, you are currently on part 4. All parts are linked below:

Dataset_1: https://zenodo.org/records/13259679

Dataset_2: https://zenodo.org/records/13259747

Dataset_3: https://zenodo.org/records/13259943

Dataset_4: https://zenodo.org/records/13260068

Dataset_5: https://zenodo.org/records/13259599

Dataset_6: https://zenodo.org/records/13260208
DOI: 10.5281/zenodo.13831998
title: Loss Cone Offset Method for Evaluating the Effect of Magnetic Field Line Curvature Scattering [Dataset]
DOI: 10.5281/zenodo.13958618
title: Code and Data for: Hessami et al., 2024

description: Code to reproduce all figures is within the R markdown file. The associated data (e.g., shapefiles and csv's) is within the Data zip folder.
DOI: 10.5281/zenodo.14524055
title: Data availability for Combining detection dogs and camera traps improves minimally-invasive population monitoring for the cheetah, an elusive and rare large carnivore
DOI: 10.5281/zenodo.14824700
title: Rhizophora mangle prop roots epibionts surveys

description: Surveys for year 2013 and 2014 on Rhizophora mangle prop root communites from Key West to Melbourne, Florida.
DOI: 10.5281/zenodo.14830658
title: Variable upper mantle geochemical processes constrained from independent component analysis of the Fizh massif, northern Oman ophiolite

description: ・Description

We present a petrological, geochemical, and statistical dataset comprising 142 peridotite samples from the Fizh Massif in the northern Oman Ophiolite. This dataset has been compiled from Takazawa et al. (2003), Kanke & Takazawa (2014), Takazawa et al. (2024), and Miki et al. (2025). The contents of the dataset are detailed below.

・Mineral mode

The modal abundances of primary minerals (olivine, orthopyroxene, clinopyroxene, and spinel) were calculated using the least-squares method, based on mass balance between whole-rock and average primary mineral compositions, considering SiO2, Al2O3, Cr2O3, FeO, MgO, and CaO (Miki et al., 2025). The modal compositions of serpentine were independently determined using the point-counting method for selected samples, with 2,000 points measured within a 2.5 × 1.5 cm area (Miki et al., 2025).

・Mineral chemistry

We present the major element compositions of primary minerals in the northern Oman (Fizh massif) peridotites, including olivine, orthopyroxene, clinopyroxene, and spinel, based on data reported by Takazawa et al. (2003), Kanke & Takazawa (2014), and Takazawa et al. (2024).

・Whole-rock geochemistry

We present whole-rock major element (wt.%) and trace element (ppm) compositions based on data from Takazawa et al. (2003), Kanke & Takazawa (2014), and Takazawa et al. (2024). Additionally, we provide whole-rock chemical composition compositions transformed using the Additive Log Ratio (ALR) method, a type of compositional data analysis. The elemental contents are normalized to SiO₂, and natural logarithm transformation of their data was taken. For a detailed discussion and calculation of the compositional data analysis, please refer to Miki et al. (2025).

・Independent component scores

We analyzed 19 trace elements (Ba, Cs, Rb, La, Sr, Ce, Nd, Hf, Sm, Eu, Ga, Gd, Tb, Y, Dy, Ho, Er, Lu, and Yb) using Independent Component Analysis (ICA), assuming four independent mantle processes. Based on this analysis, we also provide IC1–IC4 values for each sample (i.e., IC scores). For a detailed discussion and calculation of ICA, please refer to Miki et al. (2025).
DOI: 10.5281/zenodo.14992864
title: Research data of the paper
DOI: 10.6084/m9.figshare.27043408
title: <b>Evaluation of the effect of two conventional and one herbal mouthwash on the Modulus of Elasticity of three orthodontic wires: An in vitro study</b>

description: It was an in vitro study that tested MoE of stainless steel (SS), nickel-titanium (NiTi), and β-titanium (β-Ti) archwires after immersing them in chlorhexidine (CHX), sodium fluoride (NaF), and HiORA mouthwashes along with distilled water (control) for one minute daily over three months. The wires were then subjected to a three-point bending test to measure their flexural modulus of elasticity (MoE) while applying loading and unloading forces at 0.5, 1, 1.5, 2, and 2.5 mm deflections. Statistical analysis included two-way ANOVA and Tukey’s Post Hoc test at significant
DOI: 10.6084/m9.figshare.28674788
title: Supplementary Material for: Mycobacterium chelonae keratitis following Keratorefractive Lenticule Extraction (KLEX): Highlighting diagnostic and treatment complexities

description: A 35-year-old female presented to the emergency eye clinic with 4 days of eye pain and decreased vision following Keratorefractive Lenticule Extraction (KLEX) surgery. She was using topical tobramycin drops four times per day, which was changed to ciprofloxacin drops. Following initial improvement, the eye deteriorated with further stromal infiltrates. A corneal culture identified Mycobacterium chelonae. The keratitis required extensive topical and systemic medications, repeat scrapes and an amniotic membrane over several weeks to reach quiescence. Vision deteriorated to hand movements but an emergency keratoplasty was avoided. This is the third reported case serving to highlight the diagnostic and treatment challenges associated with postoperative keratitis involving non-tuberculous mycobacteria (NTM).
DOI: 10.6084/m9.figshare.28675787
title: Supplementary Material for: Zollinger-Ellison Syndrome Unmasked during Hiatal Hernia Evaluation: A Case Report

description: <b><i>Introduction:</i></b> Zollinger-Ellison syndrome (ZES) is a rare entity consisting of tumors called gastrinomas in the stomach, pancreas, and duodenum. It usually presents with symptoms of acid hyper secretion including abdominal pain, diarrhea, nausea, and vomiting and can be misdiagnosed as peptic ulcer disease, hiatal hernia, and gastroesophageal reflux disease. <b><i>Case Presentation:</i></b> We report a case of ZES presenting duodenal perforation and later mimicking a hiatal hernia. This case highlights a complex presentation and underscores the importance of thorough evaluation, multidisciplinary management, and including rare diagnosis in the differential. Our patient presented to the hospital with nausea, back pain, and abdominal pain, and imaging demonstrated a perforated duodenum which was managed with surgical repair. Following surgery, the patient continued to have worsening nausea and acid reflux which was deemed to be due to a hiatal hernia noted on prior imaging until an esophagogastroduodenoscopy (EGD) was performed which confirmed the diagnosis of ZES. <b><i>Conclusion:</i></b> Our case emphasizes the importance and necessity of doing an EGD in a timely fashion to ensure that a diagnosis of rare ZES is not missed.
DOI: 10.1594/pangaea.738489
title: Physical oceanography during POLARSTERN cruise ANT-XIII/4 on section S04A

description: For definition of quality flags see hdl:10013/epic.31518.d001
DOI: 10.1594/pangaea.742626
title: Physical oceanography during POLARSTERN cruise ANT-XV/4 (DOVETAIL) on section SR04

description: For definition of quality flags see hdl:10013/epic.31518.d001