Dataset Information

50 Ω driver circuits for digital signals: Revised test board and new measurement data.

ABSTRACT: In "Evaluation of 50 Ω driver circuits for digital signals based on oscilloscope measurements" (Heliyon, Volume 7, Issue 7, July 2021) different 50 Ω driver circuits for digital signals were compared and evaluated. Notably, the BJT-based discrete push-pull driver circuit showed a rather modest performance. It is also questionable whether the fast-switching signals of the individual driver circuits were reproduced completely and correctly with the PicoScope 3206A oscilloscope used in that study, as its sampling rate is quite low. For these reasons, the experiments were continued, several improvements were made to the test board. A new driver circuit was implemented on the test board, too. New measurement data were recorded both with a Tektronix MDO3024 oscilloscope and for comparison with the previously used PicoScope 3206A. The following dataset is made available: The revised test board (PCB layout and schematic design files), oscilloscope measurement data in CSV format, Python scripts for graphical representation of the CSV data.

SUBMITTER: Kupper T

PROVIDER: S-EPMC10792677 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

50 Ω driver circuits for digital signals: Revised test board and new measurement data.

Küpper Tilman T

Data in brief 20231226

In "Evaluation of 50 Ω driver circuits for digital signals based on oscilloscope measurements" (Heliyon, Volume 7, Issue 7, July 2021) different 50 Ω driver circuits for digital signals were compared and evaluated. Notably, the BJT-based discrete push-pull driver circuit showed a rather modest performance. It is also questionable whether the fast-switching signals of the individual driver circuits were reproduced completely and correctly with the PicoScope 3206A oscilloscope used in that study, ...[more]

PMID: 38235172

Similar Datasets

Project description:BackgroundThe World Wide Web has become an essential source of health information. Nevertheless, the amount and quality of information provided may lead to information overload. Therefore, people need certain skills to search for, identify, and evaluate information from the internet. In the context of health information, these competencies are summarized as the construct of eHealth literacy. Previous research has highlighted the relevance of eHealth literacy in terms of health-related outcomes. However, the existing instrument assessing eHealth literacy in the German language reveals methodological limitations regarding test development and validation. The development and validation of a revised scale for this important construct is highly relevant.ObjectiveThe objective of this study was the development and validation of a revised German eHealth literacy scale. In particular, this study aimed to focus on high methodological and psychometric standards to provide a valid and reliable instrument for measuring eHealth literacy in the German language.MethodsTwo internationally validated instruments were merged to cover a wide scope of the construct of eHealth literacy and create a revised eHealth literacy scale. Translation into the German language followed scientific guidelines and recommendations to ensure content validity. Data from German-speaking people (n=470) were collected in a convenience sample from October to November 2020. Validation was performed by factor analyses. Further, correlations were performed to examine convergent, discriminant, and criterion validity. Additionally, analyses of measurement invariance of gender, age, and educational level were conducted.ResultsAnalyses revealed a 2-factorial model of eHealth literacy. By item-reduction, the 2 factors information seeking and information appraisal were measured with 8 items reaching acceptable-to-good model fits (comparative fit index [CFI]: 0.942, Tucker Lewis index [TLI]: 0.915, root mean square error of approximation [RMSEA]: 0.127, and standardized root mean square residual [SRMR]: 0.055). Convergent validity was comprehensively confirmed by significant correlations of information seeking and information appraisal with health literacy, internet confidence, and internet anxiety. Discriminant and criterion validity were examined by correlation analyses with various scales and could partly be confirmed. Scalar level of measurement invariance for gender (CFI: 0.932, TLI: 0.923, RMSEA: 0.122, and SRMR: 0.068) and educational level (CFI: 0.937, TLI: 0.934, RMSEA: 0.112, and SRMR: 0.063) were confirmed. Measurement invariance of age was rejected.ConclusionsFollowing scientific guidelines for translation and test validation, we developed a revised German eHealth Literacy Scale (GR-eHEALS). Our factor analyses confirmed an acceptable-to-good model fit. Construct validation in terms of convergent, discriminant, and criterion validity could mainly be confirmed. Our findings provide evidence for measurement invariance of the instrument regarding gender and educational level. The newly revised GR-eHEALS questionnaire represents a valid instrument to measure the important health-related construct eHealth literacy.

Dataset Information

50 Ω driver circuits for digital signals: Revised test board and new measurement data.

Publications

50 Ω driver circuits for digital signals: Revised test board and new measurement data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets