The study of historical languages presents unique challenges due to their complex orthographic systems, fragmentary textual evidence, and the absence of standardized digital representations of text in those languages. Tackling these challenges needs special NLP digital tools to handle phonetic transcriptions and analyze ancient texts. This work introduces ParsiPy, an NLP toolkit designed to facilitate the analysis of historical Persian languages by offering modules for tokenization, lemmatization, part-of-speech tagging, phoneme-to-transliteration conversion, and word embedding. We demonstrate the utility of our toolkit through the processing of Parsig (Middle Persian) texts, highlighting its potential for expanding computational methods in the study of historical languages. Through this work, we contribute to computational philology, offering tools that can be adapted for the broader study of ancient texts and their digital preservation.

Long sessions of computer use introduce physical and mental health risks, particularly for programmers and intensive computer users. Breathing exercises can improve focus, reduce stress, and overall well-being. However, existing tools for such practices are often app-based, requiring users to leave their workspace. In this technical report, we introduce Nafas, a command-line interface (CLI) application designed specifically for computer users, enabling them to perform breathing exercises directly within the terminal. Nafas offers structured breathing programs with various levels tailored to the needs of busy developers and other intensive computer users.

Generative art merges creativity with computation, using algorithms to produce aesthetic works. This paper introduces Samila, a Python-based generative art library that employs mathematical functions and randomness to create visually compelling compositions. The system allows users to control the generation process through random seeds, function selections, and projection modes, enabling the exploration of randomness and artistic expression. By adjusting these parameters, artists can create diverse compositions that reflect intentionality and unpredictability. We demonstrate that Samila's outputs are uniquely determined by two random generation seeds, making regeneration nearly impossible without both. Additionally, altering the point generation functions while preserving the seed produces artworks with distinct graphical characteristics, forming a visual family. Samila serves as both a creative tool for artists and an educational resource for teaching mathematical and programming concepts. It also provides a platform for research in generative design and computational aesthetics. Future developments could include AI-driven generation and aesthetic evaluation metrics to enhance creative control and accessibility.