Abstract
An optical fiber sensor for hydrogen detection is presented. It is based on processed fiber Bragg gratings coated with palladium thin films where its expansion due to the hydrogen adsorption is monitored as strain measurements. © Optica Publishing Group 2023, © 2023 The Author(s)

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Cryptographic ransomware attacks are constantly evolving by obfuscating their distinctive features (e.g., I/O patterns) to bypass detection mechanisms and to run unnoticed at infected servers. Thus, efficiently exploring the I/O behavior of ransomware families is crucial so that security analysts and engineers can better understand these and, with such knowledge, enhance existing detection methods. In this paper, we propose CRIBA, an open-source framework that simplifies the exploration, analysis, and comparison of I/O patterns for Linux cryptographic ransomware. Our solution combines the collection of comprehensive information about system calls issued by ransomware samples, with a customizable and automated analysis and visualization pipeline, including tailored correlation algorithms and visualizations. Our study, including 5 Linux ransomware families, shows that CRIBA provides comprehensive insights about the I/O patterns of these attacks while aiding in exploring common and differentiating traits across families.

Abstract
Paint bases are the essence of the color palette, allowing for the creation of a wide range of tones by combining them in different proportions. In this paper, an Artificial Neural Network is developed incorporating a pre-trained Decoder to predict the proportion of each paint base in an ink mixture in order to achieve the desired color. Color coordinates in the CIELAB space and the final finish are considered as input parameters. The proposed model is compared with commonly used models such as Linear Regression, Random Forest and Artificial Neural Network. It is important to note that the Artificial Neural Network was implemented with the same architecture as the proposed model but without incorporating the pre-trained Decoder. Experimental results demonstrate that the Artificial Neural Network with a pre-trained Decoder consistently outperforms the other models in predicting the proportions of paint bases for color tuning. This model exhibits lower Mean Absolute Error and Root Mean Square Error values across multiple objectives, indicating its superior accuracy in capturing the complexities of color relationships. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Abstract
A linear fiber laser system for measurements of paracetamol concentration is experimentally demonstrated. The cavity is based on a fiber loop mirror and an FBG centered at 1567.8 nm. The sensing head corresponds to a refractometric sensor, whose which principle of operation is based on Fresnel reflection in the fiber tip (FBG side). The system works at detected variations of paracetamol concentrations with a sensitivity of [(8.74 +/- 0.34) x10(-5)] mu W/(g/kg) and a resolution of 2.77 g/kg. The results prove that the fiber laser system could be an asset for processing industries, specifically for non-invasive and real-time measurements of concentration.