Abstract
Over the last decades, considerable research efforts have been devoted to the determination of total ammonia nitrogen (TAN) due to its critical importance across several fields. This review aims to highlight the potential of electrochemical methods for ammonia nitrogen sensing, with emphasis on potentiometric, amperometric, and conductometric approaches. It begins by addressing the chemical and biological relevance of ammonia in diverse contexts, ranging from vital physiological functions in the human body (urea cycle, disease biomarker), quality parameter in drinking water to its key involvement in environmental processes (the nitrogen cycle), and food safety and industrial applications (e.g., livestock, agriculture). Then, a general overview of the main methods for ammonia nitrogen quantification is provided. After that, most impacting achievements on electrochemical methods for ammonia nitrogen sensing are discussed from several perspectives, including selectivity in complex environments, sensitivity and detection levels achieved, improvements in set-up design and functionality (such as simplicity, cost-effectiveness, miniaturization for on-site, real-time, and continuous monitoring), and multiplex detection capabilities. In addition, current limitations of ammonia electroanalytical approaches, future perspectives, and emerging research trends in TAN sensing technologies are addressed in a dedicated chapter. Finally, the last section focuses on current achievements of state-of-the-art electrochemical solutions for ammonia nitrogen detection and highlights their substantial advances over conventional analytical methods.

Abstract
We present the first formally verified implementation of a hash-based signature scheme that is linked to a machine-checked proof of security. Specifically, we provide reference implementations of XMSS and XMSSMT written in Jasmin, targeting the amd64 architecture. Beyond the implementations, we provide formal EasyCrypt specifications of XMSS and XMSSMT, transcribed from RFC 8391, and prove that our implementations adhere to these specifications. Furthermore, for XMSS, we give a machine-checked proof that our specification of RFC 8391 refines the abstract specification proven secure in EasyCrypt by Barbosa, Dupressoir, Grégoire, Hülsing, Meijers and Strub [CRYPTO’23]. In particular, we prove the security of our specification via a reduction, demonstrating that breaking our specification contradicts the [CRYPTO’23] result for our instantiation. Consequently, our implementation is not only functionally correct, but also adheres to a specification that is proven secure. The core technical challenge in our work resides in bridging low-level implementations of TreeHash algorithms with high-level functional specifications used in the preexisting formalization. © 2026, Ruhr-University of Bochum. All rights reserved.

Abstract
The growing availability of online data creates new opportunities to improve the timeliness and detail of official statistics, particularly in domains such as price monitoring and inflation measurement. However, leveraging web-scraped data for official use requires alignment with standardized classification frameworks such as the European Classification of Individual Consumption According to Purpose (ECOICOP). We train two natural-language models, a lightweight convolutional neural network (CNN) and a fine-tuned BERTimbau transformer, to classify Portuguese food and beverage items into ECOICOP categories. Using 100,000 product titles scraped from six national supermarket sites and labeled via a human-in-the-loop workflow, the CNN reaches a macro-F1 of 92.19 % with minimal computing cost, while the transformer attains 94.00 %, the first such result for Portuguese. Both models are published on Hugging Face, enabling reproducible inference at scale while the source data remain confidential. The study delivers the first open-source Portuguese ECOICOP classifiers for food and beverage products, a replicable low-resource labeling workflow, and a benchmark of accuracy-speed trade-offs to guide researchers in similar tasks.

Abstract
This study aimed to develop a strategic marketing plan for the Polytechnic University of Viana do Castelo. The methodology applied was a questionnaire survey applied in person to the students of the Polytechnic University of Viana do Castelo, during the class period. A total of 1762 valid responses were obtained. Although some answers indicate the necessary improvements to be made, most respondents are satisfied with the UPVC, pointing it out as young, welcoming and accessible higher education institution.

Abstract

Abstract
This proposal is the fourth edition of a workshop previously held at EICS 2023, 2024 and 2025. This edition aims to bring together researchers and practitioners interested in the engineering of interactive systems that embed AI technologies (e.g. AI-based recommender systems) or that use AI during the engineering lifecycle of interactive systems. The overall objective is to identify (based on experience reported by participants) methods, techniques, and tools to support the use and inclusion of AI technologies throughout the engineering lifecycle for interactive systems. A specific focus is on guaranteeing that user-relevant properties such as usability and user experience are accounted for. Contributions are also expected to address system-related properties, such as resilience, dependability, reliability, safety, security or performance. Another focus is on the identification and definition of software architectures supporting this integration in a generic way, ensuring properties such as maintainability and reusability. © 2026 Copyright held by the owner/author(s).