Abstract
The growing demand for sustainable and environment-friendly energy sources resulted in extensive research in the field of renewable energy. Biomass, derived from organic materials such as agricultural waste, forestry products, and wastewater treatment plant (WWTP) sludge, holds great potential as a renewable energy resource that can reduce greenhouse gas emissions and offer sustainable solutions for energy production. This study focused on diverse biomass materials, including sludge from WWTPs, forest biomass, swine waste, cork powder, and biochar. Chemical and physicochemical characterizations were performed to understand their energy potential, highlighting their elemental composition, proximate analysis, and calorific values. Results showed that different biomasses have varying energy content, with biochar and cork powder emerging as high-energy materials with net heating values of 32.56 MJ/kg and 25.73 MJ/kg, respectively. WWTP sludge also demonstrated considerable potential with net heating values of around 14.87 MJ/kg to 17.44 MJ/kg. The relationships between biomass compositions and their heating values were explored, indicating the significance of low nitrogen and sulphur content and favourable carbon, hydrogen, and moisture balances for energy production. Additionally, this study looked into the possibility of mixing different biomasses to optimize their use and overcome limitations like high ash and moisture contents. Mixtures, such as 75% Santo Emiliao WWTP Sludge + 25% Biochar, showed impressive net heating values of approximately 21.032 MJ/kg and demonstrated reduced emissions during combustion. The study's findings contribute to renewable energy research, offering insights into efficient and sustainable energy production processes and emphasizing the environmental benefits of biomass energy sources with low nitrogen and sulphur content.

Abstract
The dowry payment system is used in the cultural context and tradition of certain financial transactions related to marriages and engagement. However, disputes, fraud, and financial gaps in exploitation occur in these systems, which affect user confidence. This study uses an exploratory approach to identify the main weaknesses of current traditional dowry payment systems and analyses the benefits that blockchain technology and smart contracts can provide. The proposed data security framework combines blockchain security features such as decentralisation, cryptography, and automatic verification through smart contracts to ensure the integrity and reliability of dowry payment transactions. In this study, we adopt the Design Science Research (DSR) methodology to propose producing and developing artefacts that support solving problems in the existing dowry payment system more efficiently. We will disseminate new ideas or concepts developed to indigenous communities in Timor-Leste using the Diffusion of Innovation (DOI) and Technology Acceptance Model (TAM) frameworks to ensure that the technological framework developed can be used safely and efficiently.

Abstract
Education is vital in fostering economic growth and societal development, particularly in developing countries like Timor-Leste. As technology has revolutionised education in the digital transformation era, the concept of a smart university, driven by advanced technologies and data analytics, has gained prominence globally. Timor-Leste, amid its progress in institutional structures and public infrastructure, is also exploring integrating smart technologies in higher education. This underscores a commitment of The East Timor National Education Strategic Plan (NESP) 2011-2030 to meet national and international standards, positioning the country at the forefront of educational innovation. This study aims to assess the feasibility of implementing a Smart University in Timor-Leste to evaluate the readiness of the country to embrace digital technologies and integrate them into higher education practices. The research employs a Design Science Research methodology where qualitative and quantitative data are gathered through interviews, surveys, and document analysis. Design artefacts, including system architecture and an evaluation framework, are developed to comprehensively understand the technological and informatics aspects of implementing a Smart University in Timor-Leste. The findings will contribute to decision-making and inform the implementation plan, offering valuable insights into stakeholders' perspectives and perceptions, and will support the advancement of the educational landscape in Timor Leste by integrating smart technologies and innovative practices in higher education.

Abstract
In the context of Industry 4.0, this paper explores the vital role of advanced technologies, including Cyber–Physical Systems (CPS), Big Data, Internet of Things (IoT), digital twins, and Artificial Intelligence (AI), in enhancing data valorization and management within industries. These technologies are integral to addressing the challenges of producing highly customized products in mass, necessitating the complete digitization and integration of information technology (IT) and operational technology (OT) for flexible and automated manufacturing processes. The paper emphasizes the importance of interoperability through Service-Oriented Architectures (SOA), Manufacturing-as-a-Service (MaaS), and Resource-as-a-Service (RaaS) to achieve seamless integration across systems, which is critical for the Industry 4.0 vision of a fully interconnected, autonomous industry. Furthermore, it discusses the evolution towards Supply Chain 4.0, highlighting the need for Transportation Management Systems (TMS) enhanced by GPS and real-time data for efficient logistics. A guideline for implementing CPS within Industry 4.0 environments is provided, focusing on a case study of real-time data acquisition from logistics vehicles using CPS devices. The study proposes a CPS architecture and a generic platform for asset tracking to address integration challenges efficiently and facilitate the easy incorporation of new components and applications. Preliminary tests indicate the platform’s real-time performance is satisfactory, with negligible delay under test conditions, showcasing its potential for logistics applications and beyond.

Abstract
The growing use of technology and social media has resulted in the emergence of digital influencers, a new profession capable of changing the mentalities and behaviours of those who follow them. This study arises to better understand the potential impact digital influencers might have on the Portuguese population’s purchase behaviour and patterns, and for this purpose, seven hypotheses were formulated. An online questionnaire was conducted to respond to these theoretical assumptions and collected data from 175 respondents. A total of 129 valid answers were considered. It was possible to conclude that purchase intention does not necessarily translate into a purchase action. It was also concluded that the relationship between social network use and the purchase of products/services recommended by influencers is only significant for Instagram. Furthermore, individuals’ Generation is not significantly linked with purchasing a product/service recommended by influencers. Furthermore, a small percentage of respondents have also identified themselves as impulsive shoppers and perceived Instagram as their favourite social network. With the results of this study, it is also possible to state that the influencer’s opinion was classified as the last factor considered in the purchase decision process. Additionally, there is a weak negative association between purchasing a product/service recommended by influencers with sponsorship disclosure and remunerated partnership, which decreases credibility and discourages purchasing.

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.