🎓کانال انجمن علمی دانشجویی کتابداری و اطلاعرسانی پزشکی دانشگاه علومپزشکی بوشهر Telegram | Bale 🌻به جمع ما بپیوندید. #نسخه_مطالعه #کتاب_ویترین #دانشگاه_علوم_پزشکی_بوشهر
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Channel
@mlisbpums
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
100subscribers
+4 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003791454980 |
|---|---|
| Type | Channel |
| Username | @mlisbpums |
| Created | Between 1 February 2026 and 30 June 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 9 August 2026 |
| Last confirmed live | 12 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 12 August 2026 |
| On Telegram | t.me/mlisbpums |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 19:14 | 100 | +3 |
| 9 Aug 2026, 11:47 | 97 | no change |
| 6 Aug 2026, 19:36 | 97 | +1 |
| 6 Aug 2026, 08:15 | 96 | first reading |
20 posts held, back to 2 August 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 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 17 of 20 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 9 August 2026 |
|---|---|
| Posts held | 20 (2 August 2026 – 9 August 2026) |
| Views total | 1,592 |
| Reactions total | 49 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 9 Aug 2026, 11:47 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.
Measured directly from 1 video 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.
49 reactions across 17 posts, in 11 distinct kinds. The most used accounts for 28.6% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 14 | 28.6% | |
| 🔥 | 13 | 26.5% | |
| ⚡ | 7 | 14.3% | |
| 💔 | 3 | 6.12% | |
| 🍓 | 2 | 4.08% | |
| 👌 | 2 | 4.08% | |
| 👏 | 2 | 4.08% | |
| 🕊 | 2 | 4.08% | |
| 🥰 | 2 | 4.08% | |
| 😁 | 1 | 2.04% | |
| 🤩 | 1 | 2.04% |
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 17 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 49reactions 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 2 August 2026 to 9 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.
🎓کانال انجمن علمی دانشجویی کتابداری و اطلاعرسانی پزشکی دانشگاه علومپزشکی بوشهر Telegram | Bale 🌻به جمع ما بپیوندید. #نسخه_مطالعه #کتاب_ویترین #دانشگاه_علوم_پزشکی_بوشهر
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🩺 نسخه مطالعه | رستگاری یک قدیسه اگر فکر میکنید رمانهای جنایی فقط برای پیدا کردن قاتل هستند، رستگاری یک قدیسه نظرتان را تغییر خواهد داد. این اثر از کیگو هیگاشینو، نویسنده برجسته ژاپنی، تنها یک پرونده قتل را روایت نمیکند؛ بلکه با نگاهی دقیق به عشق، اعتماد، ازدواج و انگیزههای پنهان انسان، شما را وارد بازی پیچیدهای از منطق و احساس میکند. در این مسیر، «کارآگاه گالیله» با ذهن علمی و استدلالهای دقیق خود، مرز میان …
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🩺 بیشترِ دانشجوهای علوم پزشکی فقط PubMed رو میشناسن... اما دنیای پژوهش پزشکی خیلی بزرگتر از یک پایگاه هست! 📖 اگه تا حالا برای پیدا کردن مقاله، مرور منابع یا انجام پژوهش فقط به گوگل یا PubMed تکیه کردی، وقتشه با ابزارهایی آشنا بشی که پژوهشگرهای حرفهای ازشون استفاده میکنن. در این کانال با هم یاد میگیریم: 📚 پایگاههای اطلاعاتی معتبر پزشکی و سلامت 🤖 ابزارهای هوش مصنوعی مخصوص پژوهش 🔍 ترفندهای جستجوی حرفهای مقاله …
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🩺اصطلاحات پزشکی | شماره بیستم✨ 🚹 سیستم تنفسی (Respiratory System) ◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇ 📌 عبارت: papillary 🔊 تلفظ لاتین: /ˈpæp.ɪ.ler.i/ 🗣️ تلفظ فارسی: پاپیلاری 💡 معنی: دارای ساختار انگشتیشکل 📖 توضیح کوتاه: اصطلاحی در پاتولوژی که به رشد یا تومورهایی اشاره دارد که ساختاری شبیه به برآمدگیهای کوچک، باریک و انگشتمانند (پاپیلا) دارند. •••••••••••••••••••••••••••••••••••••••••••••••••••••• 📌 عبارت: acid-fast bacil…
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یک پادکست ساده و دلی با صدای وزش باد، جیغ بچهها و تا حدی رد شدن کامیون و بدون هیچ آهنگ بکگراند و کات کردنِ صدایی😁 چون احساس کردم یک پادکست که در اون صدای من با صدای جزئیات ِ زندگی ترکیب شده بیشتر میتونه من رو به حس بیاره. حس اینکه من نمی خوام یک سخنران باشم. فقط میخوام حرف بزنم برای کسی که گوش میده🤍 کانی عزیززاده🌱💚 🎙"اپیزود پنجم پیشکشِ همه ی شما عزیزانی که قلبتون مشتاقِ زندگی کردنه."💫 •••••••••••••••••••••••••…
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📚 پاورپوینت آموزشی | جلسه دوم تابستان پژوهش ۱۴۰۵ امیدواریم این مجموعه، نقطه شروعی برای یادگیری مهارتهای پژوهشی و استفاده آگاهانه از منابع علمی باشد. ••••••••••••••••••••••••••••••••••••••••••••••••••••• 🎓کانال انجمن علمی دانشجویی کتابداری و اطلاعرسانی پزشکی دانشگاه علومپزشکی بوشهر Telegram | Bale 🌻به جمع ما بپیوندید. #تابستان_پژوهش_۱۴۰۵ #دانشگاه_علوم_پزشکی_بوشهر
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🔍 تابستان پژوهش ۱۴۰۵ | جلسه دوم 🔑 کلیدواژهنویسی "یک کلیدواژه درست، صدها نتیجه بهتر!" در دومین قسمت از مجموعه «تابستان پژوهش» با: 🔶 بخش اول: آشنایی با مفاهیم 🔹 مفهوم و تعریف Keyword 🔹 جستجوی کلیدواژهای، ویژگیها، مزایا و محدودیتها 🔹 معرفی Subject Heading و واژگان کنترلشده 🔹 معرفی MeSH و ساختار درختی آن 🔹 مقایسه Keyword و Subject Heading 🔶 بخش دوم: مهارت عملی 🔹 مراحل انتخاب کلیدواژه مناسب 🔹 ارزیابی و اصلاح نتای…
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✅خبر خوب برای کاربران ChatGPT که از نسخه رایگان استفاده میکنند 🔹شرکت OpenAI اعلام کرده که از هفته آینده، محدودیت تعداد پیامهای متنی برای کاربران نسخههای Free و Go حذف میشود 🔹حالا امکان چت متنی نامحدود دارید و قابلیت Think هم برای کاربران رایگان فعال میشود تا پاسخهای دقیقتری برای سؤالهای پیچیده دریافت کنند 🔹البته محدودیت ارسال عکس، فایل و برخی قابلیتهای دیگر همچنان باقی میماند 🔹بهنظر میرسد OpenAI قصد …
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🩺اصطلاحات پزشکی | شماره نوزدهم✨ 🚹 سیستم تنفسی (Respiratory System) ◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇◇ 📌 عبارت: postural drainage 🔊 تلفظ لاتین: /ˈpɒs.tʃər.əl ˈdreɪ.nɪdʒ/ 🗣️ تلفظ فارسی: پوستورال درینج 💡 معنی: روش تخلیه ترشحات ریوی با استفاده از گرانش 📖 توضیح کوتاه: در این روش درمانی، بیمار در وضعیتهای فیزیکی خاصی قرار میگیرد تا ترشحات و مخاط موجود در مجاری تنفسی با کمک نیروی جاذبه به سمت راههای هوایی بزرگتر حرکت کرده و تخ…
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Sticker, posted without a caption
📁 یک انفجار، هزاران پرونده پزشکی ۶ آگوست ۱۹۴۵؛ روزی که هیروشیما شاهد یکی از تلخترین رویدادهای تاریخ بشر بود؛ اما در کنار ویرانیها، هزاران داده پزشکی و انسانی شکل گرفت که مسیر علم سلامت را برای همیشه تغییر داد. پروندههای پزشکی بازماندگان، تنها مجموعهای از اعداد و اطلاعات نبودند؛ بلکه روایت زندگی انسانهایی بودند که به شناخت بهتر اثرات تشعشعات، پیشرفت پژوهشهای پزشکی و حفاظت از سلامت نسلهای آینده کمک کردند. 📚 د…
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✅ مدل های ویدیو ساز هر کدوم فارسی رو چطور میفهمن ؟ مدل Omni: فارسی رو عالی میفهمه و با همون کیفیت و جزئیات پرامپت انگلیسی، ویدیو رو میسازه. مدل Kling: هر دو زبان فارسی و انگلیسی رو یکسان متوجه میشه. مدل Seedance: با پرامپت فارسی کلاً گیج شد و به جای شیر، یه خرس قطبی تحویل داد. مدل Grok: فارسی رو بینقص متوجه میشه و خروجی عالی و بدون تفاوتی میده. مدل Wan: پرامپت فارسی رو به جای یه شیر باابهت، تبدیل به یه پیشی کوچو…
Showing the 12 most recent of 20 posts we hold for @mlisbpums. 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 — 198,623 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
Named by 6 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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
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 12 August 2026 — this entry's latest reading, not the date you are reading this.
“انجمن علمی دانشجویی کتابداری و اطلاع رسانی پزشکی بوشهر” (@mlisbpums), 100 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/mlisbpums.
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.