Find research datasets worth reusing

Continuous Heart Rate Variability Monitoring in Doctors; Understanding Patterns of Stress and Recovery and Their Relationship With Self-reported Resilience, Burnout and Wellbeing.

ClinicalTrials.gov study NCT06721312. IPD Sharing: NO. Countries: 1. Publications: 1.

Epidemiological Observation From a Smartphone Self-monitoring Application for Suspected COVID-19 Patients' Triage

ClinicalTrials.gov study NCT04331171. IPD Sharing: NO. Countries: 1. Publications: 3.

Application for Self-Monitoring of Cardiovascular Risk

ClinicalTrials.gov study NCT01883050. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.

Self-monitoring of Blood Glucose in Insulin-treated Patients With Type 2 Diabetes

ClinicalTrials.gov study NCT01460459. IPD Sharing: Not stated. Countries: 1. Publications: 1.

opencc-by-4.0Feb 2022View details →

zenodo28/100

A precise and general FRET-based method for monitoring structural transitions in protein self-organization

Data underlying the figures in the manuscript

zenodo28/100

Monitoring Solid-Phase Reactions in Self-Assembled Monolayers by Surface-Enhanced Raman Spectroscopy

Data underlying the figures in the publication “Monitoring Solid-Phase Reactions in Self-Assembled Monolayers by Surface-Enhanced Raman Spectroscopy”, published in Angew. Chem. Int. Ed., 2021, 60, 2–10. <a href="https://onlinelibrary.wiley.com/doi/full/10.1002/anie.202102319">https://onlinelibrary.wiley.com/doi/full/10.1002/anie.202102319</a> Table of contents: 1. Figure 1C; Zip file containing the numerical data for Figure 1C. The data were obtained from optical numerical simulations using the software Lumerical. The parameters used for the simulations are described in the SI of the publication. The file “OCH04-015_0nm.txt” has been exported from the simulated solution. It includes the distribution of the electric field intensity (|E|^2) in x and y directions at the Au-air interface. The data were then plotted as the electromagnetic enhancement factor in log scale (log|E|^4) using the origin lab software (“OCH04-015.opju”. 2. Figure 1D, 1E, 1F; Zip file containing the numerical data for Figures 1D, 1E and 1F. Figure 1D: 100 data files with the general file name: “OCH04-021_3_633nm_300lpermm_10perc_2x30s_300hole_100x_Yyy_Xxx.txt” The yy and xx are different numeric values for each file indicating the position in the 10 x 10 map. And: «OCH02-072_2_blankAu_2x30s_10perc_633nm_100x_01.txt” is the dataset of the orange dotted spectrum which was recorded on the planar Au surface. In all text files, there are two columns: The first one is the Raman shift in cm–1 and the second one the intensity in photon counts. The Raman spectroscopy data in the files starting with “OCH04-021…” were generated using the Horiba LabRAM Software and the baseline has already been subtracted using this software. The 100 spectra were plotted without further data smoothing (grey spectra) and the average spectrum (black) was generated by using the dedicated function in the Origin Lab software. The orange spectrum originates from «OCH02-072_2_blankAu_2x30s_10perc_633nm_100x_01.txt”. It was smoothed with 10 points using a Savitzky-Golay Filter in Origin Lab and the Baseline was subtracted. Figure 1E: The Box Plot was generated using the 100 grey spectra from 1D and applying a Gaussian fit to the three peaks indicated in the figure and extracting the peak positions. Using these peak position data, the box plot was generated using the Origin Lab software. Figure 1F: The contour plot was generated using the 100 grey spectra from 1D and applying a gaussian fit to the peak indicated in the figure description and extracting the peak heights. Using these peak height data, the contour plot was generated using the Origin Lab software. 3. Figure 2; Zip file containing the numerical data for Figure 2. In all text files, there are two columns: The first one is the Raman shift in cm–1 and the second one the intensity in photon counts. The spectra were smoothed with 10 points using a Savitzky-Golay Filter in Origin Lab and the Baseline was subtracted. The y intensity was normalized so that the Si peak at approx. 950 cm–1 had the same height. The Raman shift in x direction was shifted so that the Si peak at 300 cm–1 was at the same position in each spectrum. 4. Figure 3A, 3C; Zip file containing the numerical data for Figures 3A and 3C. In all text files, there are two columns: The first one is the Raman shift in cm–1 and the second one the intensity in photon counts. The spectra were smoothed with 8 points using a Savitzky-Golay Filter in Origin Lab and the Baseline was subtracted. The average of three spectra was calculated for the spectra with the same y description for the plotted spectra in 3A. Figure 3C was generated by applying a gaussian fit to the three peaks indicated in the figure in the original 12 data sets and extracting the peak heights. The average and standard deviation of the peak height data from the spectra with the same y description was then calculated to generate Figure 3C. 5. Figure 4A, 4B; Zip file containing the numerical data for Figures 4A and 4B. 4A: In all text files, there are two columns: The first one is the Raman shift in cm–1 and the second one the intensity in photon counts. The spectra were smoothed with 10 points using a Savitzky-Golay Filter in Origin Lab and the Baseline was subtracted. The y intensity was normalised so that the Si peak at approx. 950 cm–1 had the same height. The Raman shift in x direction was shifted so that the Si peak at 300 cm–1 was at the same position in each spectrum. 4B: The peak positions from Figures 2 and 4A were used to generate Figure 4B.

opencc-by-4.0Jul 2021View details →

Speeko for Elderspeak: A Self-Monitoring App to Improve Nursing Home Communication

ClinicalTrials.gov study NCT04064164. IPD Sharing: YES. Countries: 1. Publications: 0.

Microrandomized Trial to Optimize Use of Burden-reducing Self-monitoring Approaches in Behavioral Obesity Treatment

ClinicalTrials.gov study NCT07228130. IPD Sharing: YES. Countries: 1. Publications: 0.

Care Partner-Assisted Diabetes Self-Management Through Linking Continuous Glucose Monitoring With Mobile Health: Improving Outcomes for Older Adults With Mild Cognitive Impairment

ClinicalTrials.gov study NCT05601583. IPD Sharing: YES. Countries: 1. Publications: 0.

Self-monitoring of Spirometry & Symptoms Via patientMpower App in Idiopathic Pulmonary Fibrosis

ClinicalTrials.gov study NCT03744598. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Optimizing Self-Monitoring Feedback Delivery for the Treatment of Overweight and Obesity

ClinicalTrials.gov study NCT07227051. IPD Sharing: YES. Countries: 1. Publications: 0.

Enhancing the Risk Assessment and Management Program by Promotion of Self-blood Pressure Monitoring

ClinicalTrials.gov study NCT02551393. IPD Sharing: Not stated. Countries: 0. Publications: 2.

Examining Valence-based Effects in Self-Monitoring Feedback Messages

ClinicalTrials.gov study NCT07292389. IPD Sharing: YES. Countries: 0. Publications: 0.

Improve Hypertension Monitoring and Self-management by Using mHealth

ClinicalTrials.gov study NCT02632838. IPD Sharing: NO. Countries: 1. Publications: 0.

Self-Monitoring of Carbon Monoxide to Enhance Reproductive Outcomes in Women

ClinicalTrials.gov study NCT02246114. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Method Comparison/User Evaluation of the i-SENS Self-Monitoring Blood Glucose / β-Ketone System

ClinicalTrials.gov study NCT05833100. IPD Sharing: NO. Countries: 1. Publications: 0.

Optimizing Self-Monitoring Feedback for the Treatment of Obesity

ClinicalTrials.gov study NCT06508580. IPD Sharing: YES. Countries: 1. Publications: 0.

Mobile-Based Contingency Management to Promote Daily Self-monitoring in Primary Care Patients

ClinicalTrials.gov study NCT03962491. IPD Sharing: NO. Countries: 1. Publications: 0.