Design and Evaluation of a Receiver for Wired Nano-Communication Networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, we propose a bio-inspired receiver, which detects the electrons transmitted through a nanowire, then, it converts the detected information to blue light using bioluminescence. We simulate the construction of the nanowire, present its electrical characteristics and calculate its maximum capacity for a better design of the receiver. The designed receiver contains two parts; a part that detects the transmitted electrons, which we model by using an equivalent circuit, and a part that converts the detected electrons to blue light. We derive the analytical expressions of the components of the equivalent circuit and give an approximation of their values. We calculate the probability of photons emission for each electrical pulse detected. We also determine the optimal threshold for Integrate Sample and Dump (ISD) receiver. We calculate the error probability of bits detection and present analytical and simulation results to evaluate the performance of the designed receiver. The results of this study show that the designed receiver can accurately detect the electrons sent through a conductive nanowire. Thus providing, to the best of our knowledge, the first technical solution that leads towards integrated wired electrical and optical nanonetworks.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it