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- The dual effects of digitalization on SMEsPublication . Gomes, Emanuel; Lehman, David W.; Vendrell-Herrero, Ferran; NOVA School of Business and Economics (NOVA SBE); Palgrave MacmillanLongstanding debates persist about the impact of new technologies on firms, particularly as it relates to internationalization. Some scholars suggest that digitalization will enhance the benefits of export activity by facilitating connections with partners and customers. Others, however, suggest that digitalization will simply fail to live up to the hype—or perhaps even worse. This debate is especially relevant for SMEs given that export activity is the primary route to global markets for such firms. We propose that digitalization will exert dual effects on SMEs: on the “bright” side, larger investments in digital technologies will lead to greater export activity (i.e., higher export sales); on the “dark” side, however, digitalization-induced export activity will generate fewer learning opportunities from export partners (i.e., smaller productivity gains). The proposed hypotheses were tested and supported using detailed firm-level panel data from 20,133 Portuguese firms from 2010 to 2019. Additional analyses and case studies corroborate the proposed mechanisms and point to hybrid approaches as one possible way to balance these dual effects of digitalization. Taken together, the findings shed new light on the debate about the role of digitalization in internationalization efforts.
- Towards a sustainable futurePublication . Rodrigues, José Noronha; Bhattacharya, Sumanta; Shinde, Tushaba; Cabete, Dora Cristina Ribeiro; Centro de Investigação e Desenvolvimento sobre Direito e Sociedade (CEDIS); Centro Universitario Curitiba - UNICURITIBAObjective: The objective of this article is to examine the legal and regulatory framework governing Indian Railways in order to assess its capacity to support modernization, financial sustainability, safety, digital transformation, and environmental protection. Through a comparative analysis of international railway governance models from countries such as Japan, Germany, China, the United Kingdom, France, the United States, and Switzerland, the study aims to identify global best practices that can inform regulatory reform in India and contribute to transforming Indian Railways into a competitive, efficient, and sustainable transport system aligned with constitutional principles and international environmental commitments. Methodology: This study employs a qualitative and doctrinal research methodology, combining legal analysis, policy evaluation, and comparative law. Primary sources include Indian legislation, regulatory instruments, policy documents, and landmark judicial decisions, particularly those related to environmental protection and public accountability, while secondary sources comprise academic literature, government reports, and international institutional publications. A comparative framework is used to analyse global railway models, focusing on governance structures, privatization strategies, regulatory autonomy, safety mechanisms, digitalization, and sustainability policies, in order to identify regulatory gaps and propose context-specific reforms for Indian Railways. Results: The findings indicate that Indian Railways operates within an outdated and fragmented regulatory framework that limits operational autonomy, discourages private investment, and weakens safety and environmental enforcement. The absence of an independent regulator, politically influenced tariff-setting, financial imbalances caused by cross-subsidization, and slow adoption of advanced technologies undermine efficiency and service quality. Comparative analysis reveals that successful international railway systems rely on regulatory independence, transparent pricing, structured public–private partnerships, strong safety oversight, and legally binding sustainability mandates—elements that remain insufficiently developed or inconsistently implemented within the Indian railway system. Conclusions: The study concludes that meaningful transformation of Indian Railways requires comprehensive legal and regulatory reform grounded in global best practices and constitutional obligations. Establishing an independent railway regulator, strengthening public–private partnership frameworks, modernizing safety and digital governance, and embedding environmental sustainability within binding legal mandates are essential steps toward creating a future-ready railway system. By aligning regulatory modernization with international standards and India’s climate and development commitments, Indian Railways can evolve into a resilient, efficient, and sustainable transport network capable of supporting long-term economic growth and social connectivity.
- Regulatory framework and innovations for advanced nuclear technologies balancing safety, efficiency, and decarbonizationPublication . Rodrigues, José Noronha; Bhattacharya, Sumanta; Cabete, Dora Cristina Ribeiro; Centro de Investigação e Desenvolvimento sobre Direito e Sociedade (CEDIS); Centro Universitario Curitiba - UNICURITIBAThe familiarity with the risk governance of existing nuclear reactors, observation of the path taken by other critical sectors and the evolving role of regulation is useful to define for regulatory governance and policy framework for future nuclear technologies that can be safe, efficient and consistent with decarbonization objectives. It explores emerging scientific innovations like small modular reactors (SMRs), next-gen fission, and nuclear fusion, for peace, energy security, sustainable development, etc. This paper conducts a detailed analysis of the key regulatory challenges (e.g., waste management, non-proliferation, public acceptance) and maps them against policy-strategies that promote innovation. Combining strong safety regulations with technological innovations, the study outlines pathways for nuclear energy to play a role in a low-carbon future that is both economically viable and environmentally responsible.
- Applicability Assessment of a Microbial Proteolytic Fermentation Broth to Leather Processing and Protein Stain RemovalPublication . Lageiro, Manuela; Moura, Maria João; Simões, Fernanda; Alvarenga, Nuno; Reis, Alberto; GeoBioTec - Geobiociências, Geoengenharias e Geotecnologias; MDPI - Multidisciplinary Digital Publishing InstituteMicrobial proteases are fundamental towards the eco-sustainability of proteolysis at the industrial scale. A proteolytic broth was obtained from a bioreactor fermentation of a proteolytic Bacillus strain isolated from an industrial alkaline bath. Broth proteolytic activity was applied to leather tanning and to the removal of protein stains. The hide tanned with the microbial proteolytic fermentation broth showed better physical properties than the one tanned with commercial pancreatic proteases of the same activity (780 LVU). Proteinaceous stains on cotton fabric were removed more efficiently using the Bacillus proteolytic broth than water or a commercial detergent. Blood and egg yolk disappeared in less than 30 min. The removal of soya and English sauce stains was even faster. Broth proteolytic activity was characterised by caseinolytic (5200 LVU), collagenolytic (10.0 U mg−1), elastolytic (3.7 U mg−1), and keratinolytic (0.7 U mg−1) activities, which were compared with those of a commonly used commercial protease. Alkaline protease activity in the broth was demonstrated by a 20% increase in caseinolytic activity from pH 5 to 8. Besides the demonstrated applications in the leather and detergent industries, the produced alkaline microbial proteases can also be used in the treatment of proteinaceous wastes and effluents, offering potential environmental benefits reinforcing and impacting the bioeconomy.
- Os desafios da diversidade linguística no ensino de português como língua estrangeiraPublication . Castro, Catarina; Centro de Estudos Ingleses de Tradução e Anglo-portugueses (CETAPS)
- Oxidation and Mechanical Behavior of Nb-Ti-(Cr)-(Al) Refractory Multi-principal Element Alloys at 1000 °CPublication . Borges, Spyridion Haritos; Pasini, Willian Martins; Dainezi, Isabela; Rząd, Ewa; Kateusz, Filip; de Souza, Thalles Henrique Faria; Dudziak, Tomasz; Polkowski, Wojciech; Chaia, Nabil; Mariano, Neide Aparecida; DEMI - Departamento de Engenharia Mecânica e Industrial; ASM International | SpringerThe oxidation and mechanical behavior at 1000 °C of five single-phase body-centered cubic (BCC) Nb-Ti-(Cr)-(Al) Refractory Multi-Principal Element Alloys (RMPEAs), with low density of ~ 6.5 g cm−3 and intrinsic room-temperature ductility, was systematically investigated. Isothermal oxidation tests conducted in air for up to 100 h revealed a strongly composition-dependent response. The binary NbTi alloy exhibited near-linear oxidation kinetics and an extensive internal reaction zone (IRZ). Conversely, Cr- and Al-containing alloys demonstrated reduced mass gain, narrowed IRZ and altered kinetic regimes, attributed to the formation of chemically complex oxide scales. Although Cr and Al additions reduced both mass gain and IRZ, oxide-scale spallation persisted across all compositions. Compression tests at 1000 °C confirmed that all alloys retained ductile behavior, with Cr-containing compositions exhibiting superior yield strength. Among the evaluated alloys, Nb3Ti3Cr1Al1 achieved the most favorable balance between oxidation resistance (mass gain of 14.4 mg cm−2 after 100 h of exposure) and mechanical stability (yield strength 229.0 MPa at 1000 °C). The combined addition of Cr and Al to the equimolar NbTi alloy improves oxidation resistance and mechanical performance, advancing the development of lightweight RMPEAs for high-temperature structural applications.
- História pública em PortugalPublication . Cruzeiro, Cristina Pratas; Pereira, Joana Dias; Almeida, Joana Miguel; Prista, Marta; Roque Martins, Patrícia; Vespeira de Almeida, Sónia; Instituto de História da Arte (IHA); Departamento de Antropologia (DA); Centro em Rede de Investigação em Antropologia (CRIA - NOVA FCSH); Instituto de História Contemporânea (IHC)
- Improving the Quality of Patient Post-Discharge Care using a Machine Learning–Based Decision Support SystemPublication . Santos, Matilde M.; Peyroteo, Mariana; Lapão, Luís Velez; UNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e IndustrialHospital readmissions represent a persistent challenge for healthcare systems, often stemming from inadequate postdischarge monitoring. This study presents a Machine Learning-based Clinical Decision Support System (CDSS) designed to enhance nursing risk assessment in post-discharge care. Developed using a Design Science Research Methodology, the artefact integrates a digital questionnaire, a Machine Learning (ML)-based risk stratification model and a real-time dashboard to optimise follow-up processes. The system was developed at a medical-surgical inpatient unit of a private hospital in Lisbon. A retrospective dataset of 10,134 structured telephone follow-up records, classified by nurses into three risk levels—stable (A), requiring reassessment (B) and clinically concerning (C)—was used to train and evaluate the ML model. Among the evaluated classifiers, Logistic Regression was selected for deployment based on its high specificity (0.9993), precision (0.9879) and absence of critical false negatives. The CDSS enables real-time risk classification based on patient-reported outcomes, supporting timely identification and prioritisation of patients requiring clinical attention. Simulation results indicate a potential reduction of up to 79% in nurse follow-up workload, while preserving care quality by focusing resources on moderate- and high-risk patients. This study demonstrates the feasibility and utility of ML-based dynamic risk analysis for post-discharge monitoring, offering a scalable and interpretable solution that enhances clinical decision-making and resource allocation in healthcare opening the way to digital transformation.
- Elaboração, implementação e validação de recursos didáticos de Português como Língua GlobalPublication . Caels, Fausto; Castro, Catarina; Mangas, Catarina Frade; Centro de Estudos Ingleses de Tradução e Anglo-portugueses (CETAPS); Centro Interdisciplinar de Ciências Sociais (CICS.NOVA - pólo IPLeiria)
- Mapping Hybrid and Ensemble Models for Financial Volatility ForecastingPublication . Alvarez, Rodrigo Baggi Prieto; Bravo, Jorge Miguel; NOVA Information Management School (NOVA IMS); Information Management Research Center (MagIC) - NOVA Information Management SchoolFinancial volatility forecasting has undergone a rapid methodological transition from parametric econometric models towards machine and deep learning, hybrid architectures, and ensemble techniques. Despite this expansion, the literature lacks a synthesis combining bibliometric mapping with a granular methodological taxonomy of hybrid and ensemble models for volatility forecasting. This paper addresses that gap by retrieving 690 publications from Scopus and Web of Science, mapping the bibliometric landscape with bibliometrix, and constructing a 121-paper core corpus through multi-stage filtering on citation impact, recency, and Bradford Zone 1 sources. The corpus is classified using a tendimensional taxonomy covering model category, hybrid subtype, base models, combination strategy, forecast target, input features, data frequency, market and asset class, evaluation framework, and methodological novelty. To assess scalable annotation, we implement a three-model LLM-assisted pipeline using Claude 4.6, Gemini 3, and GPT-5, validated against a domain-expert human audit on a stratified subsample. Bibliometric results show a marked acceleration after 2020 and convergence between financial econometrics and computational predictive modelling. Hybrid and ensemble architectures outperform single-model benchmarks, with sequential GARCH–DL cascades, stacking and shrinkage ensembles, and decomposition-based hybrids emerging as prominent designs; CEEMDAN and VMD provide the most transferable gains. LLM agreement is strongly dimensionspecific: lexically observable dimensions (data frequency, model category, forecast target) achieve moderate agreement, whereas inferential dimensions (evaluation framework, methodological novelty) remain unreliable under abstract-only classification. These findings position LLMs as useful but bounded research assistants for systematic reviews in quantitative finance, capable of scaling first-pass classification when embedded in transparent, multi-model, and human-validated workflows.