Abstract
The purpose of this study is to ascertain the hierarchical importance of a patent's characteristics to licensing. This research has a causal-exploratory purpose, in that it sought to establish relationships between variables. This research aims to identify which characteristics are influential in the licensing of Brazilian academic patents in the biotechnology and pharmaceutical technology fields, based on the mining of data contained in licensed and unlicensed patent documents. Which characteristics of Brazilian academic patents are most influential in their licensing potential? An analysis through Random Forest was performed. To the best of our knowledge, there are no studies in Brazil using machine learning to identify which characteristics are influential in licensing a particular academic patent, especially given the difficulty of gathering this information. We found that regardless of the measure used, the three most critical licensing characteristics for the Biotechnology and Pharmaceutical patents analysed are Patent Scope, Life Cycle, and Claims. At the same time, the least important is the Patent Cooperation Treaty. The relevance of this research is based on the fact that after identifying which intrinsic characteristics influence the final value and licensing probabilities of a given patent, it will be possible to develop mathematical models that provide accurate information for establishing technology transfer agreements. In practical terms, the results suggest that greater patent versatility, combined with lifecycle management and a technical effort to build strong claims, increases the licensing potential of academic biopharmaceutical patents.

Abstract
Code comprehension is often supported by source code analysis tools that provide more abstract views over software systems, such as those detecting design patterns. These tools encompass analysis of source code and ensuing extraction of relevant information. However, the analysis of the source code is often specific to the target programming language. We propose DP-LARA, a multilanguage pattern detection tool that uses the multilanguage capability of the LARA framework to support finding pattern instances in a code base. LARA provides a virtual AST, which is common to multiple OOP programming languages, and DP-LARA then performs code analysis of detecting pattern instances on this abstract representation. We evaluate the detection performance and consistency of DP-LARA with a few software projects. Results show that a multilanguage approach does not compromise detection performance, and DP-LARA is consistent across the languages we tested it for (i.e., Java and C/C++). Moreover, by providing a virtual AST as the abstract representation, we believe to have decreased the effort of extending the tool to new programming languages and maintaining existing ones.

Abstract
Mutation testing maybe used to guide test case generation and as a technique to assess the quality of test suites. Despite being used frequently, mutation testing is not so commonly applied in the mobile world. One critical challenge in mutation testing is dealing with its computational cost. Generating mutants, running test cases over each mutant, and analyzing the results may require significant time and resources. This research aims to contribute to reducing Android mutation testing costs. It implements mutation testing operators (traditional and Android-specific) according to mutant schemata (implementing multiple mutants into a single code file). It also describes an Android mutation testing framework developed to execute test cases and determine mutation scores. Additional mutation operators can be implemented in JavaScript and easily integrated into the framework. The overall approach is validated through case studies showing that mutant schemata have advantages over the traditional mutation strategy (one file per mutant). The results show mutant schemata overcome traditional mutation in all evaluated aspects with no additional cost: it takes 8.50% less time for mutant generation, requires 99.78% less disk space, and runs, on average, 6.45% faster than traditional mutation. Moreover, considering sustainability metrics, mutant schemata have 8,18% less carbon footprint than traditional strategy.

Abstract
This chapter aims to understand how Esports organizations can improve digital marketing strategies, considering the unique characteristics of this sector and the importance of maintaining solid relationships with the target audience. The research was carried out using a mixed methodology, which included the application of quantitative research to evaluate the behaviors of Esports fans and a qualitative literature review to explore the trends and challenges of digital marketing in this context. The results show that the esports audience consists predominantly of young males, with a strong interest in video games, technology and pop culture. The personalization of digital strategies, focusing on platforms such as YouTube and Twitch, as well as the use of promotions and sweepstakes, proved essential for audience engagement. Although the use of influencers has a neutral perception, campaigns that offer direct benefits, such as promotions, are more attractive.

Abstract
Non-adherence to medication is a pervasive issue worldwide, affecting 50% of prescription users, resulting in suboptimal therapy outcomes and premature death. One of the key factors contributing to non-adherence is the complexity associated with managing medication regimens. To address this challenge, an automated pill dispenser “SelfMed, your medication partner” has been proposed. This study focuses on studying determinants of medication non-adherence, its ramifications and alternatives available in the market in order to increase medication adherence among adults aged 60 and over. The overarching goal of this research is to evaluate whether digital solutions like SelfMed are required for addressing non-compliance issues in Portugal while assessing their effectiveness over time for our target audience within the marketplace. The research was conducted using primary data collected through a questionnaire distributed to users and care institutions/companies in Portugal (Northern area). According to the analysis, 40% of users and 40% of care companies are interested in obtaining SelfMed to simplify the complex medication management and prescription regimen for the end user. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

Abstract
The aim of this study was to conduct a qualitative analysis research that will support the internal and external analysis, as well as the strategic options to be developed for a Marketing Plan for the Polytechnic Institute of Viana do Castelo. The methodology used was through exploratory interviews using a script based on nine key dimensions for creating a marketing plan. The script was applied through face-to-face interviews with the president of the Polytechnic Institute of Viana do Castelo. We obtained six interviews that could be analyzed in the nine dimensions. It was possible to understand that the elements suggest some changes in the different dimensions of the script. One of the points with the most observations for improvement was communication, mostly internal. However, all the improvements and growth that the institute has achieved over the years were acknowledged. It was also possible to realize that the six people interviewed have the same perspective and make similar observations on the different questions asked. With the interviews, it will be possible to outline the best structure and path for the strategic marketing plan. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.