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Channel
@scientific_programming
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
152subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001396429401 |
|---|---|
| Type | Channel |
| Username | @scientific_programming |
| Description | Tutorials and applications from scientific programming https://github.com/Ziaeemehr |
| Created | Between 1 August 2018 and 31 May 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 8 August 2026 |
| Last confirmed live | 8 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/scientific_programming |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Aug 2026, 19:31 | 152 | no change |
| 7 Aug 2026, 11:28 | 152 | first reading |
20 posts held, back to 4 May 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 2 of 3 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 7 August 2026 |
|---|---|
| Posts held | 20 (4 May 2025 – 7 August 2026) |
| Views total | 158 |
| Reactions total | 3 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Aug 2026, 19:31 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
Lifetime counters from Telegram’s own channel header, read 8 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
15 reactions across 7 posts, in 4 distinct kinds. The most used accounts for 46.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 7 | 46.7% | |
| ❤ | 6 | 40.0% | |
| 🎉 | 1 | 6.67% | |
| 🔥 | 1 | 6.67% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 7 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 15reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 4 May 2025 to 7 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
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Github: https://github.com/Ziaeemehr/lyapax Docs: https://lyapax.readthedocs.io/en/latest
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Github: https://github.com/Ziaeemehr/JaxCont Docs: https://jaxcont.readthedocs.io/en/latest
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To see how many clients is connected and other details: docker logs conduit --tail 1
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Scientific Programming pinned «Conduit is a lightweight relay server used by Psiphon that helps users in censored networks access the open internet by securely forwarding their traffic through volunteer-run nodes outside the censorship zone. (for LINUX) docker run -d --name conduit \ …»
### Docker command flags explained (brief) - `docker run -d` Run the container in detached (background) mode. - `--name conduit` Assign a fixed name to the container. - `--cpus="2.0"` Limit the container to using at most 2 CPU cores. - `--memory="2g"` Limit the container’s RAM usage to 2 GB. - `--ulimit nofile=65536:65536` Increase the maximum number of open file descriptors (important for many connect…
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Conduit is a lightweight relay server used by Psiphon that helps users in censored networks access the open internet by securely forwarding their traffic through volunteer-run nodes outside the censorship zone. (for LINUX) docker run -d --name conduit \ --cpus="2.0" \ --memory="2g" \ --ulimit nofile=65536:65536 \ -v conduit-data:/home/conduit/data \ --restart unless-stopped \ --log-driver local --log-opt …
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Dear colleagues, Applications for non-EU students are now open for the Master 2 in Computational Neuroscineces (CNS) at the University of Lyon (France). See our website for more details: https://masterneuro.univ-lyon1.fr/m2-cns/ The Lyon neurograduate school also offers fully funded scholarships to enrol in the CNS program or in other neurosciences training paths. Deadline : 23/01/2026, more information here : ht…
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PhD Position in Computational & Systems Neuroscience (Marseille, France): Neuromodulatory control of predictive processing in visual cortical circuits ⏰️ Deadline: January 28, 2026
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🧠📦 vbjax_dynamics *A JAX-based library for numerical integration of dynamical systems.* 🚀 GitHub: github.com/Ziaeemehr/vbjax_dynamics ⚙️ Features • ODE Integration — Ordinary Differential Equations – Efficient loop-based integrators with JIT compilation – Full support for jax.vmap (parallel trajectories) • SDE Integration — Stochastic Differential Equations – make_sde(): Integration with pre-generated noise – ma…
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ساخت خودکار فلشکارتهای هوشمند با کمک مدل زبانی و پایتون مدتی پیش در مورد ساخت فلشکارت با چت جی پی تی نوشتم. اینجا حالا یه قدم جلوتر رفتم و یه پکیج پایتون ساختم که کل فرایند- استخراج متن تا اصلاح و اضافه کردن صدا-رو خودش انجام میده. 🔊 تفاوت مهم نسخه جدید اینه که صداها با مکثهای طبیعی بین جملهها تولید میشن و نتیجه خیلی روانتر و گوشنوازتر شده. 🧠 بخش اصلی تولید کارتها همچنان توسط مدل زبانی (GPT) انجام میشه، و …
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Showing the 12 most recent of 20 posts we hold for @scientific_programming. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Citation-graph rank — 791,621 of 1,183,361entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 8 August 2026 — this entry's latest reading, not the date you are reading this.
“Scientific Programming” (@scientific_programming), 152 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/scientific_programming.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.