Synchronization of high speed framing camera and intense electron-beam accelerator
Bibliographic record
Abstract
A new trigger program is proposed to realize the synchronization of high speed framing camera (HSFC) and intense electron-beam accelerator (IEBA). The trigger program which include light signal acquisition radiated from main switch of IEBA and signal processing circuit could provide a trigger signal with rise time of 17 ns and amplitude of about 5 V. First, the light signal was collected by an avalanche photodiode (APD) module, and the delay time between the output voltage of APD and load voltage of IEBA was tested, it was about 35 ns. Subsequently, the output voltage of APD was processed further by the signal processing circuit to obtain the trigger signal. At last, by combining the trigger program with an IEBA, the trigger program operated stably, and a delay time of 30 ns between the trigger signal of HSFC and output voltage of IEBA was obtained. Meanwhile, when surface flashover occurred at the high density polyethylene sample, the delay time between the trigger signal of HSFC and flashover current was up to 150 ns, which satisfied the need of synchronization of HSFC and IEBA. So the experiment results proved that the trigger program could compensate the time (called compensated time) of the trigger signal processing time and the inherent delay time of the HSFC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".