If your laptop’s CPU is running very hot and you’ve tried to undervolt it, you’ve probably discovered there’s no easy way to do so—especially on laptops whose BIOS doesn’t expose those controls. I ran into the same issue with my Ryzen 7 5800H, despite numerous attempts, I couldn’t undervolt because the firmware simply wouldn’t allow it. While it may seem drastic, disabling Turbo Boost is one workaround—and you might be surprised how little real-world performance you lose by turning it off.

I have looked around online and noticed a lot of users that moved to Niri come from KDE, or were using Dolphin on their previous WM/DE and want to use it on Niri. The problem is that unlike Nautilus, the Dolphin experience on Niri is not out of the box, it has a lot of issues. 90% of the time you open Dolphin the first time it doesn't work properly and it looks horrible. So I try to write this to stealgather all the fixes that I have found and turn it into a guide for newcomers to make Dolphin functions as close as it was on KDE.

This guide focuses on Vanilla Niri. I personally don't use any plugin or theming shell so I don't know exactly how they work.

At the time I'm writing this I'm thinking of upload it into a gist or something at some point, to make it easier to update things and to access/download. Edit: gist

Welcome to the comprehensive, community-driven resource repository for GATE Computer Science & Information Technology (CS & IT) 2027 aspirants. Securing a top rank in the Graduate Aptitude Test in Engineering (GATE) unlocks direct admissions to premier postgraduate programs (M.Tech/Ph.D.) at IITs, NITs, and IISc, alongside prestigious technical roles within leading PSUs.

This repository serves as a centralized documentation hub compiled from authoritative open-source archives, topper strategies, and verified learning pathways for your GATE CSE study material search.

1. Core Syllabus Structure & Weightage Analysis

I created a crude comparison of the syntax of the various common Markdown extensions to have a better view on what are the most common extensions and what is the most widely accepted syntax for them. The list of Markdown flavors that I looked at was based on the list found on CommonMark's GitHub Wiki.

Authors: Yanbao Yu, Madeline Smith & Rembert Pieper

The stop-and-go-extraction tips (StageTips) have been widely used in shotgun proteomics to clean/desalt peptide samples prior to LC-MS/MS analysis. Here, an extremely simple and high throughput StageTip protocol is described. In this protocol, an adaptor is introduced to the StageTip, and makes it readily available for bench-top centrifugation. Each spin step (with 200 μL buffer loaded) takes around 2 min at 4,000 rpm. Compared with previous syringe-based manual pressure device, the spinnable StageTip is completely labor-free, automatable, and can be easily scaled up. Considered with the recently developed 96FASP method, the spinnable StageTips provide another component to the high throughput workflow for clinical proteomics and biomarker discoveries.

Shotgun (or bottom-up)-based proteomic technologies in clinical researches have enabled the identification of many potential biomarkers for various diseases (1-3). A typic

This is a sample web app implemetation in Google Apps Script that receives a JSON payload and inserts it directly into a Google spreadsheet. It is a demo implementation for Automate app flow Google Spreadsheets Integration.

Using just one HTTP Request block in an Automate flow you can send data from your Automate flows directly into Google Spreadsheets! Pretty neat, isn't it?

https://docs.google.com/spreadsheets/d/1VZEp-ru9BH9AQSNHzRxnJZx1Nabviz6UiN9PIelOjA8

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

A list of GitHub emoji markup, adapted from rxavier's Complete list of github markdown emoji markup, generated with a Grunt script for maintainability (see repository).

Additional original source material: http://unicode.org/emoji/charts/full-emoji-list.html

This table is available as a gist at https://gist.github.com/GerHobbelt/b9b87a2257ddd5251a45628d61385717 and as part of the build repo at https://github.com/GerHobbelt/emoji-list/blob/master/dist/emoji-list.md

• Smileys and People

Guide to install a LAMP system on on your archlinux system and serve php-based database applications.
LAMP stands for a Linux system with Apache (webserver), MariaDB (database) and PHP (programming language). In this guide we will also install PhpMyAdmin (database admin GUI) to easily manage the SQL tables.

The Apache HTTP Server is an open-source and free product of the Apache Software Foundation and one of the most widely used web servers on the Internet. In addition to factors such as performance, expandability, security, freedom from license costs and support from a very large community, its long-term availability for a wide variety of operating systems is one of the reasons for its widespread use; it is most frequently used as a LAMP system.