Jagtesh Chadha jagtesh

If you're using a high-end bluetooth headset on your Macbook Pro it's likely your mac is using an audio codec which favors battery efficiency over high quality. This results in a drastic degradation of sound, the SBC codec is the likely culprit, read more about it here.

Find out what codec you're using

Play a song on your headphones
Option (⌥) click the Bluetooth button at the top of your screen
If you're using AAC or aptX, you can stop here—those are the highest quality codecs.

Change your codec to AAC or aptX

More info can be found at, https://docs.microsoft.com/en-us/dotnet/api/system.environment.specialfolder?view=netframework-4.7.2

Code example

// C:\ProgramData\
var path1 = System.Environment.GetFolderPath(System.Environment.SpecialFolder.CommonApplicationData);

// C:\Users\USERNAME\AppData\Roaming
var path2 = System.Environment.GetFolderPath(System.Environment.SpecialFolder.ApplicationData);

	function sleep(ms) {
	return new Promise(resolve => setTimeout(resolve, ms));
	}

	function getPage(page) {
	// returns the uid of a specific page in your graph.
	// _page_: the title of the page.
	let results = window.roamAlphaAPI.q(`
	[:find ?uid
	:in $ ?title

	"""Automatic distraction detection. Work in progress.

	Usage:
	python detect.py main
	"""
	import fire
	import subprocess

	import plyvel
	import re

	Copy this to roam/js page, including the "{{[[roam/js]]}}" node:

	- {{[[roam/js]]}}
	- ```javascript
	/*
	* Roam template PoC by @ViktorTabori
	* 0.1alpha
	*
	* How to install it:
	* - go to `roam/js` page`

	import numpy as np
	import pandas as pd
	from math import e

	class Node:

	'''
	A node object that is recursivly called within itslef to construct a regression tree. Based on Tianqi Chen's XGBoost
	the internal gain used to find the optimal split value uses both the gradient and hessian. Also a weighted quantlie sketch
	and optimal leaf values all follow Chen's description in "XGBoost: A Scalable Tree Boosting System" the only thing not

	#!/usr/bin/env python

	import os
	import sys
	import argparse
	import logging
	from datetime import datetime, timedelta

	from typing import List, Optional
	from collections import defaultdict

	# Load relevant libraries
	import numpy as np
	import numba as nb
	import matplotlib.pyplot as plt

	# Goal is to implement a numba compatible polyfit (note does not include error handling)

	# Define Functions Using Numba
	# Idea here is to solve ax = b, using least squares, where a represents our coefficients e.g. x**2, x, constants
	@nb.njit

	use std::collections::HashMap;
	use std::fmt;
	use std::io;
	use std::num::ParseFloatError;
	use std::rc::Rc;

	/*
	Types
	*/

	########################################
	# 1. Build nodejs frontend
	########################################
	FROM node:10.9-alpine as build-node

	# prepare build dir
	RUN mkdir -p /app/assets
	WORKDIR /app

	# set build ENV