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This chapter explores the internationalization path of ALPHA, a family-owned, medium-sized Portuguese company. The analysis reveals a two-stage process. Initially, ALPHA's gradual market entry aligns with the Uppsala model, prioritizing geographically close markets and leveraging accumulated experience. However, later stages demonstrate network-based theory influences. While lacking formal networks, ALPHA prioritizes strong B2B relationships with large international clients, mirroring network bridges for market access. The case highlights the importance of trust-based B2B relationships for success. ALPHA leverages these partnerships to gain market knowledge and access new opportunities. Exporting plays a vital role, keeping ALPHA updated on technological trends and fostering innovation through diverse client projects. The company prioritizes a pragmatic approach focused on strong client relationships and win-win partnerships, emphasizing trust as a key resource. While the RBV perspective highlights investment in internal resources, reliance on intermediaries introduces limitations.

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Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class variability, time and errors produced in manual labeling, and in some cases privacy concerns, among others. This paper presents an overview of the 2(nd) edition of the Face Recognition Challenge in the Era of Synthetic Data (FRCSyn) organized at CVPR 2024. FRCSyn aims to investigate the use of synthetic data in face recognition to address current technological limitations, including data privacy concerns, demographic biases, generalization to novel scenarios, and performance constraints in challenging situations such as aging, pose variations, and occlusions. Unlike the 1(st) edition, in which synthetic data from DCFace and GANDiffFace methods was only allowed to train face recognition systems, in this 2(nd) edition we propose new subtasks that allow participants to explore novel face generative methods. The outcomes of the 2(nd) FRCSyn Challenge, along with the proposed experimental protocol and benchmarking contribute significantly to the application of synthetic data to face recognition.

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Aim: Aloysia citrodora has a long history of traditional use in treating various ailments. This study evaluated the in vivo chemopreventive efficacy and systemic toxicity of an extract of A. citrodora in a transgenic mouse model of HPV16 (human papillomavirus type 16)-induced cancer. Methods: The experiment involved six groups (n = 5): group 1 (G1, wild-type (WT), water), group 2 (G2, HPV, water), group 3 (G3, WT, 0.013 g/mL), group 4 (G4, HPV, 0.006 g/mL), group 5 (G5, HPV, 0.008 g/mL), and group 6 (G6, HPV, 0.013 g/mL). Throughout the assay, humane endpoints, body weight, food, and water consumption were recorded weekly. The internal organs and skin of the mice were collected for analysis after they were sacrificed. Toxicological parameters that were studied included hematological and biochemical blood markers, splenic and hepatic histology, and hepatic oxidative stress. Results: A. citrodora extract seems to reduce the incidence of dysplastic and in situ carcinoma skin lesions induced by HPV16 in this model, suggesting that dietary supplementation with concentrations of 0.008 g/mL and 0.013 g/mL may have beneficial chemopreventive effects. Conclusions: The extract did not induce any concentration-dependent toxicological effects on any of the parameters included in the study, indicating a favorable toxicological profile under these experimental conditions. © 2024 Open Exploration Publishing Inc. All rights reserved.

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Urban retrofitting has emerged as a key strategy in the transition towards sustainable cities, with Positive Energy Districts (PEDs) serving as a model for achieving energy-positive urban environments. This paper explores the potential for urban retrofitting to achieve a positive energy balance through a case study of four existing districts in European Municipalities: Settimo Torinese (Italy), Großschönau (Austria), Amsterdam (Netherlands), and Resita (Romania). The analysis leverages energy balance simulations, considering various retrofitting scenarios, including building insulation, photovoltaic (PV) installations, and the adoption of flexible grid usage. The findings indicate that while achieving a PED is challenging, it is attainable through a combination of aggressive retrofitting measures, renewable energy integration, and smart energy management. The study highlights the importance of context-specific strategies, as climatic and urban characteristics significantly influence the outcomes. It aims to add to the ongoing discourse on sustainable urban development by providing empirical insights into the pathways and challenges of achieving PEDs through urban retrofitting. © 2024 IEEE.

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