System Environmental Metrics Collector for EM facilities
Alink, L. M.; Eng, E. T.; Gheorghita, R.; Rice, W.; Cheng, A.; Carragher, B.; Potter, C. S.
Show abstract
Recent developments in cryo-electron microscopy (cryoEM) have led to the routine determination of structures at near atomic resolution and greatly increased the number of biomedical researchers wanting access to high-end cryoEM instrumentation. The high costs and long wait times for gaining access encourages facilities to maximize instrument uptime for data collection. To support these goals, we developed a System Environmental Metrics Collector for facilities (SEMCf) that serves as a laboratory performance and management tool. SEMCf consists of an architecture of automated and robust sensors that track, organize and report key facility metrics. The individual sensors are connected to Raspberry Pi (RPi) single board computers installed in close proximity to the input metrics being measured. The system is controlled by a central server that may be installed on a RPi or existing microscope support PC. Tracking the system and the environment provides feedback of imminent issues, suggestions for interventions that are needed to optimize data production, and indications as to when preventative maintenance should be scheduled. The sensor components are relatively inexpensive and widely commercially available, and the open-source design and software enables straightforward implementation, customization, and optimization by any facility that would benefit from real time environmental monitoring and reporting.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Advances on sparse Dynamic Scanning in Spectromicroscopy through Compressive Sensing 94%
- A framework to enhance the Signal-to-Noise Ratio for quantitative fluorescence microscopy 92%
- Implementing QR Codes in Academia to Improve Sample Tracking, Data Accessibility, and Traceability in Multicampus Interdisciplinary Collaborations 92%
Similar papers in this journal
- Mix-and-extrude: high-viscosity sample injection towards time-resolved protein crystallography 90%
- BioXTAS RAW 2: new developments for a free open-source program for small angle scattering data reduction and analysis 89%
- Combination of an inject-and-transfer system for serial femtosecond crystallography 89%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.