https://github.com/zs1083339604/FaceWinUnlock-Tauri 发现了一个不错的 Windows 面容解锁方案,先用着试试。虽然有指纹解锁器,但需要连接一根很长的线。而 Windows Hello 还要求有红外摄像头。先用这个方案度过一段时间,等自己以后有了台式重新 DIY 面部和指纹解锁方案。 #Windows #解锁

Channel
新·留三
@xinliusan
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
118subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
Register entry
| Telegram ID | -1001776977769 |
|---|---|
| Type | Channel |
| Username | @xinliusan |
| Created | Between 1 December 2021 and 30 April 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 9 August 2026 |
| Last confirmed live | 9 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/xinliusan |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 9 Aug 2026, 04:45 | 118 | no change |
| 7 Aug 2026, 15:28 | 118 | first reading |
Engagement
18 posts held, back to 31 January 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 18 posts for this entry, the most recent from 30 June 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
- Photos
- 82
- Videos
- 14
- Links
- 59
Lifetime counters from Telegram’s own channel header, read 9 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.
- Video runtime
- 5m 26s
- Average length
- 1m 22s
Measured directly from 4 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
29 reactions across 7 posts, in 7 distinct kinds. The most used accounts for 34.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| custom 6228643855642661981 | 10 | 34.5% | |
| custom 5467824548441245872 | 8 | 27.6% | |
| custom 5114340437808645487 | 3 | 10.3% | |
| ❤ | 3 | 10.3% | |
| 🐳 | 2 | 6.90% | |
| 👏 | 2 | 6.90% | |
| custom 6091313736641942215 | 1 | 3.45% |
Custom emoji. 4 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them areTelegram’s.
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 18 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 29reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 31 January 2026 to 30 June 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.
Recent posts
之前无聊跑过一堆特殊规则的,想换就换吧。纯数字的 gmail 有一千万个,之前无聊用脚本跑了一些特殊规则的。我自己用不了那么多就空开了。可能有些显示被占用了,毕竟有段时间没看了。 0434555 4447657 9543444 9543111 3338234 0634555 8444654 3338769 0766678 4876111 3214442 4448760 8111543 3452228 4443243 4443765 4446234 4666876 6210008 6876444 7210006 7444234 7444345 7444543 7657444 7778764 #Gmail
这两天应该是全量开放了,不看IP/账号归属地之类(我有几个HK的Google也可以改)终于可以改掉以前的嘉豪邮箱名了。 新前缀将会和老前缀共存,不会影响到你曾经注册过的服务。 https://myaccount.google.com/ 赶快去抢吧! 分享来自 秋风のとおり道 🍁 #邮箱 #实时消息
现在广告脚本都能过人机验证了,我还设计的分步算数验证,这都有两条广告,我真的生气了😡 在考虑了很久是用引导到一个网站 cloudflare 点击验证,或手性碳,或特定暗号,还是 OTOP 滚动。 发现这个问题之前就被讨论过了,之前就有大量的广告号通过给私聊机器人发广告,这样比直接发给用户更不容易被举报。算数验证实在对他们太简单,据说 CAPTCHA 方案都不行了。如果弄太简单还会有广告,使用难的增加的门槛又太高。 于是还是回归频道私信,至少目前来看频道私信没到广告泛滥,而且举报也会更有效。至于写的代码就完全浪费了。归档,以后 广告有效减少再放出来,或是想到什么有效的方式了再开。
Google I/O 2026 🔥
Codex 实在是太强了,晚上抽空在额度烧干之前把私聊机器人重构了……放眼望去全都是自己发给自己的“测试”,估计几十倍于其他来私聊我的人的消息数量吧。 这段时间还做了网站,估摸着等几个月还能把谷歌的健康数据放进去,TG 的小程序也试了试,还是土气,也卡。大陆地区能卡个半分钟加载出来,可能导航页面的东西太多……等一个星期之后用 Codex 修,之前用 AI Studio 实在太累了。 Q:为什么不写代码了? A:因为免费额度用光了🤷♀️ Q:会有项目跑路风险吗? A:免费的全转为付费就立马跑路😏 #Codex
更简单的电脑无限备份的方式来了。今天频道主这个笨蛋还在试图把雷电模拟器下回来,结果用起来不理想,root 用的还是老一套,模块装不上,勇哥相册还卡的很。想着又转到 WSA,一看密密麻麻的教程和注意事项,想到这玩意儿会再一次给我带来各种问题养着这个吃性能和内存的怪兽,畏惧了一问 AI,居然还真给我了有用的帮助,是来自 reddit 的帖子。 项目地址:https://github.com/xob0t/gotohp 用起来挺不错的,比我那个挂浏览器的好太多。没想到为了电脑上方便的备份,研究那么久…… #GooglePhotos
custom 54678245484412458723
更新下头像
custom 54678245484412458724❤1
Channel photo updated
计划是从这里里选择,如果有好的建议也欢迎来提。
👏2
因为这部分来自专题表情包,计划后续进行替换 如果还需要使用这部分,可以添加 https://t.me/addstickers/myadestes_1_nacho #贴纸
如果能把调用云服务器的 api 写到代码里,什么读取数据和日志的,编辑代码,弄上最基础的一套功能确保运行,然后再弄上 AI 的 api,每天一刷新 token 就自己检测自己目前状态,自己维护和检查代码并优化,感觉那还挺酷的。不知怎得,我觉得这个现在就能实现。甚至 AI 应该去自己申请更多的 api ,然后自己去规划,甚至能拉来好几个 AI 一起撺掇。 当然,我现在没有那么多时间去弄。而且还是有很多风险,毕竟那么多 api 完全交给他们去做。不过我还是蛮期待的,就像是在《我的世界》里玩《我的世界》,他们一边去优化自己的代码,创建新的世界,尝试更加仿真,这比看 《生命游戏》的黑白点点有意思太多了。 #AI狂想
❤1custom 51143404378086454871
Showing the 12 most recent of 18 posts we hold for @xinliusan. 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.
Forward network
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.
Mentions
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.
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 9 August 2026 — this entry's latest reading, not the date you are reading this.
“新·留三” (@xinliusan), 118 subscribers as measured 9 August 2026. Telegram Register, tgregister.com/channel/xinliusan.
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.