This channel’s posts match, word for word or near enough, posts on 2 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
3 measurements spanning 3 days, net +9. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 3,189–3,200 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
10 Aug 2026, 00:28
3,199
+8
6 Aug 2026, 20:42
3,191
+1
6 Aug 2026, 17:18
3,190
first reading
Engagement
17 posts held, back to 14 June 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 3 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
21.9%
avg views ÷ 3,199 subscribers
Avg views / post
701
7 posts measured
Reaction rate
0.325%
reactions ÷ views · ER floor
Posts in window
7
of 17 held
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 5 of 7 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 4 August 2026
Posts held
17 (14 June 2026 – 4 August 2026)
Views total
4,907
Reactions total
12
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 23:43 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.
What this channel posts
Video runtime
2m 56s
Average length
59s
Measured directly from 3 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
39 reactions across 12 posts, in 3 distinct kinds. The most used accounts for 94.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
37
94.9%
👍
1
2.56%
🙏
1
2.56%
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 14 of the 17 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 39reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 17 most recent posts we hold, published 14 June 2026 to 4 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.
🧠 نورولوژی، یکی از اون مهارتهایی است که نمیشه با حدس و گمان از کنارش بگذریم
وقتی یک سگ یا گربه با تشنج، فلجی، عدم تعادل، کج شدن سر، درد گردن یا کمردرد وارد کلینیک میشود، معمولا اولین سؤال این نیست که "چه بیماریای دارد؟"
بلکه اینه که:
محل ضایعه دقیقا کجاست؟
اگر نتونیم با یک معاینه عصبی اصولی محل آسیب رو لوکالیزه کنیم، حتی بهترین MRI و CT هم ممکنه ما رو به پاسخ درست نرسونن.
🐾 به همین دلیل، معاینه عصبی و نورولوک…
🙈 چند بار شده رادیوگراف قفسه سینه یک سگ یا گربه رو ببینن اما مطمئن نباشین دقیقا چی غیرطبیعیه؟
تفسیر رادیوگرافی قفسه سینه یکی از مهارتهاییه که مستقیما روی تصمیمهای بالینی شما اثر میذاره؛ از تشخیص بیماریهای تنفسی گرفته تا تصمیمگیری برای ادامه مسیر درمان.
💻 در این وبینار قرار نیست ساعتها درباره تئوریهای کمکاربرد اشعه ایکس صحبت کنیم!
به جاش مستقیم میریم سراغ چیزی که در کلینیک بهش نیاز دارین:
🔎 دیدن، تحلیل کرد…
🇸🇪 اگر رویای کار و زندگی در کشورهای نوردیک رو دارید، قبل از پرداخت هزاران یورو به مؤسسات مهاجرتی، این وبینار رو ببینین.
فنلاند، سوئد، نروژ، دانمارک و ایسلند از بهترین کشورهای دنیا برای زندگی و کار هستند؛ اما مسیر تطبیق مدرک دامپزشکی در هر کدوم کاملا متفاوته و کوچکترین اشتباهی میتونه ماهها یا حتی سالها شما رو از هدفتون عقب بیندازد.
💻 در این وبینار بیش از ۴ ساعت، تمام مراحل تطبیق مدرک دامپزشکان در کشورهای نوردیک …
🐶🐱 برای اینکه کیسهای مغز و اعصاب سگ و گربه رو بهتر و دقیقتر به نتیجه برسونیم، نیاز به آموزش اختصاصی در این زمینه داریم.
💁🏻♀ چند تا وبینار به سبک پرزنتیشن محور و کاربردی داشتیم که بهتون کمک میکنه:
۱. معاینات عصبی و تعیین محل آسیب سیستم عصبی با دکتر آریازند متخصص جراحی حیوانات کوچک از آمریکا
۲. نوروآناتومی همراه با مرور تصاویر ام آر آی با دکتر زهتاب ور، استاد آناتومی دانشگاه تهران
۳. نکات تشخیصی و شیوه مدیریت تش…
🩹 مدیریت زخم؛ جاییه که تشخیص درست، از خودِ درمان مهمتر میشه.
هر زخمی را نمیتونیم با یک نسخه ثابت درمان کرد.
گاهی باید زخم را باز گذاشت، گاهی بخیه کرد.
گاهی دبرایدمنت نجاتبخشه، گاهی میتونه به بافت آسیب بیشتری وارد کند.
گاهی پانسمان و درمان دارویی کافیه و گاهی تأخیر در جراحی، شانس موفقیت درمان رو بهشدت کاهش میده.
اینکه چه زمانی، چه کاری و چرا باید انجام شود، بخش مهمی از مدیریت اصولی زخم در حیوانات کوچک است.
…
🦜 یک کیس واقعی...
یک لاوبرد با بیحالی، کاهش اشتها و کمی اسهال به کلینیک مراجعه میکنه.
🤔 در نگاه اول شاید به عفونت، مشکلات گوارشی یا حتی سوءتغذیه فکر کنیم.
چند روز درمان میشه...
اما متاسفانه حال پرنده تغییری نمیکنه.
🤔 اینجاست که یک سؤال مهم مطرح میشه:
اگر منشأ اصلی بیماری کبد یا پانکراس باشد، آیا از همون اول متوجه میشیم؟
واقعیت اینه که بسیاری از بیماریهای کبد و پانکراس در پرندگان با علائم غیراختصاصی ظاهر م…
❓ شما پرسيديد؟
🤩 میخوام بدونم چهطورى با آزمون كانادا براى آمريكا هم ميشه لايسنس گرفت؟ آيا ايالتهاى آمريكا هركدوم جدا نيستند از لحاظ تطبيق مدرک؟
🔁 و آيا ميشه بين برنامه كانادا و آمريكا وسط تطبيق مدرک هم ترنسفر كنيم؟
🔗 برای دریافت وقت مشاوره، سوالات و ابهاماتتون رو برامون ارسال کنید:
🍀 @ArazEdu
🌈 @ArazEvents آراز
💊 دامپزشکی پر از داروهایی است که همه میشناسیم
اما چیزی که کمتر دربارهاش صحبت میشه، داروهایی هستند که نباید کنار هم تجویز بشن.
🐱 همون دارویی که هر روز با خیال راحت استفاده میکنیم، ممکنه در یک گونه خاص، در کنار یک داروی دیگه یا حتی در یک شرایط بالینی مشخص، به یک انتخاب اشتباه تبدیل بشه.
💻این وبینار دقیقا دربارهی همین تصمیمهای حساس است؛
تصمیمهایی که در کتابها معمولا در حد یک خط نوشته شدهاند، اما در کلینیک می…
🚨 اگر هنوز نمیدونی آینده حرفهایت قراره به کدوم سمت بره، این وبینار رو از دست نده.
بیشتر دانشجویان و دامپزشکان فقط چند تخصص محدود رو میشناسند؛ در حالی که در دنیا بیش از ۴۰ تخصص بالینی با مسیرها، فرصتها و آیندههای کاملا متفاوت وجود داره.
❓اگر حتی یک بار این سؤالها از ذهنت گذشته:
• تخصص بگیرم یا نه؟
• کدام رشته برای من مناسبتر است؟
• رزیدنسی خارج از کشور چطور انجام میشود؟
• اینترنشیپ، اکسترنشیپ، VIRMP و بورد …
❓ شما پرسیدید؟
به عنوان VET TECH بریم کانادا یا باید تطبیق مدرک بدیم؟
📎 برای دریافت وقت مشاوره، سوالات و ابهاماتتون رو برامون ارسال کنید:
🌱 @ArazEdu
🌈 @ArazEvents آراز
🍂 اگر قصد مهاجرت و کار بهعنوان دامپزشک در کانادا رو دارید، این وبینار میتونه ماهها آزمون و خطا و هزاران دلار هزینه رو براتون کاهش بده.
🤩 کانادا در سالهای اخیر با کمبود جدی دامپزشک روبهرو بوده و فرصتهای شغلی مناسبی برای دامپزشکان، بهویژه افرادی که مسیر تطبیق مدرک را بهدرستی طی کنند، فراهم شده.
🔴 در این وبینار ۵.۵ ساعته، مسیر تطبیق مدرک کانادا رو از صفر تا صد و بهصورت کاملا عملی بررسی کردیم؛ از شرایط و آزمون…
❓شما پرسیدید؟
💼بعد از دادن ازمونهای تطبیق، امکان کاربالینی رو داریم؟
📎 برای دریافت وقت مشاوره، سوالات و ابهاماتتون رو برامون ارسال کنید:
🌸 @ArazEdu
🌈 @ArazEvents آراز
❤2
Showing the 12 most recent of 17 posts we hold for @ArazEvents. 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
Citation-graph rank — 84,252 of 1,151,006entries 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.
Forward network
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.
Mentions
Named by 8 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
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 10 August 2026 — this
entry's latest reading, not the date you are reading this.
“🌈 آراز Araz - رویدادهای دامپزشکی” (@ArazEvents), 3,199 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/ArazEvents.
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.