This study investigates whether habitual use of short-form video platforms—specifically Instagram Reels—may inhibit trauma processing in individuals exposed to adverse experiences. By combining qualitative interviews with psychometric data and usage analytics, the study aims to explore the hypothesis that compulsive engagement with Reels serves as a dissociative coping mechanism, potentially delaying or impeding emotional integration and trauma recovery.
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using Shouldly; | |
namespace ADG.Server.AppHost.Tests.Utilities; | |
public static class DateTimeTestingExtensions | |
{ | |
public static void ShouldBeAfter(this DateTime actual, DateTime expected) | |
{ | |
if (actual <= expected) | |
throw new ShouldAssertException($"Expected {actual} to be after {expected}"); |
La fermentation algorithmique est un processus d’adaptation progressive d’un algorithme de recommandation, déclenché par une réduction volontaire, mais non totale, de l'interaction avec une plateforme (ex. TikTok, YouTube, Instagram Reels).
Plutôt que de couper l’usage complètement, l’utilisateur adopte une posture d’interactions lentes, espacées et réfléchies :
- 📉 Moins de sessions, moins de scroll impulsif
- 🧠 Interactions uniquement avec du contenu réellement intéressant
- 🕰️ Attente prolongée pour permettre à l’algorithme de recalculer ses priorités
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using Sirenix.OdinInspector; | |
using UnityEngine; | |
public class RotationFollowSmooth : MonoBehaviour | |
{ | |
[SerializeField, BoxGroup("References"), Required] | |
private Transform _target; | |
[BoxGroup("Settings")] | |
[SerializeField, BoxGroup("Settings/Rotation"), Required] |
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#Requires AutoHotkey v2.0 | |
CoordMode "Mouse", "Screen" | |
; Settings | |
moveSpeed := 5 ; Time in ms between movements | |
stepSize := 2 ; Pixels per step | |
; Global state | |
moving := true |
Black and white .NET Aspire console? Worry no more. Use this :
applyThemeToRedirectedOutput: true
Full code example, taken from ADG's Logging helper method :
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using Microsoft.Extensions.DependencyInjection; | |
using Microsoft.Extensions.Hosting; | |
using Microsoft.Extensions.AI; | |
using OpenCvSharp; | |
using AForge.Video.DirectShow; | |
namespace ADG.Playground.Vision | |
{ | |
internal class VisionResponse | |
{ |
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using System.Text; | |
namespace ADG.ConsoleSpin; | |
public static class ConsoleSpinner | |
{ | |
private static int counter; | |
private static readonly string[] SpinnerChars = ["⠋", "⠙", "⠹", "⠸", "⠼", "⠴", "⠦", "⠧", "⠇", "⠏"]; // Braille characters that work reliably |
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import matplotlib.pyplot as plt | |
import numpy as np | |
def time_to_hours(time_str, start_hour=None): | |
""" | |
Convert a time string "HH:MM" to a float representing hours. | |
If the time is "00:00" and start_hour is provided and greater than 0, | |
assume that it represents midnight at the end of the day (i.e., 24:00). | |
""" | |
h, m = map(int, time_str.split(":")) |
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using System.Diagnostics; | |
using System.Text; | |
using System.Text.Json; | |
using System.Xml.Linq; | |
using AGX.Common.Logging.Serilog; | |
using Serilog; | |
namespace AGX.Common.Publishing | |
{ | |
internal class Program |
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