Abstract
Background: E-commerce has emerged as a good response to the pandemic of COVID-19. However, the costs of providing a service, which includes a driver and a vehicle, in a regular vehicle that can transport goods that need positive cold (0 & DEG; to 5 & DEG;C) are very high. Objectives: This paper aims to investigate how a big Portuguese retailer company can reduce its dependence on refrigerated vehicles, simplifying operations and reducing the costs of transporting positive and negative cold food. Methods/Approach: This research was carried out in a food retailer Portuguese company, more precisely in a Dark Store dedicated to the online channel. The study was developed based on the AS-IS/TO-BE process analysis methodology, starting with the analysis of the current situation, giving rise to the so-called AS-IS model. Results: It was possible to reduce costs associated with transporting positive cold goods. As a result, there are 30% fewer costs associated with order transportation. With an additional 10% in space optimization with the gain of space within the galley of each vehicle. Conclusions: The costs of transporting positive and negative cold foods were decreased, and substituting vehicles with room temperature transport reduced the need for refrigerated vehicles.

Abstract
Background: Regional Development (RD) allows countries to balance regional differences by providing economic and social benefits to communities. This research highlights the importance of logistics activities to regional social development, and a framework to assess these connections is proposed. Objectives: How to boost regional socioeconomic development through logistics. Methods/Approach: The contributions of logistics to socioeconomic development are analysed based on the previous research, and the case of the Alto Minho (AM) region in Portugal was used to illustrate the connection between logistics and regional development. Results showed that logistics had created jobs, increased company turnover and exports, and increased GDP growth in several regions. For the AM region, results indicate that many companies are operating in this area, contributing to supporting municipalities to reduce regional disparities. Conclusions: A framework for assessing regional logistics performance is proposed together with several logistics performance indicators. This approach is essential for future developments integrating logistics into socioeconomic development.

Abstract
Companies focus on achieving high service levels and need to combine short service times with the dynamics between cost and quality. Their transportation systems are therefore a fundamental part; they must be reliable and efficient. This study was implemented in a company of the marine industry, and its final product has special characteristics that require special transportation, i.e., they need a truck with a special structure to be able to transport the boats. This situation causes the vehicle to return empty to the company, a route that the company must support economically. The company has already approached several options with logistic service providers (3PL) without obtaining positive solutions. It is in this sense that the present project arises, which aims to develop a tool for the creation of round-trip circuits, given that in the current context the company intends to acquire a vehicle with reduced environmental impact. In a first phase we analyze the company’s needs based on the unique characteristics of the final product, then we study the existing options on the market. Culminating in the proposal of a vehicle that allows performing a circuit in round trip (distribute the final product and return with raw material and not empty) powered by renewable energy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Nowadays, social media are inevitably part of people's daily lives. Thus, political communication should also go through digital communication channels, particularly on social media. In such channels, it is important to define a digital marketing and communication strategy to attract new voters and consecutively more votes. As in offline communication channels and also in digital communication, one of the indispensable points in political communication is the candidate’s image. This image must show its own style and differentiate the candidate from his opponents. The main objective of this study is to understand the influence of social media on Portuguese voters’ decision-making process. Throughout the study, different research questions were also analyzed to access which social media are the most used to follow the online political campaign and which criteria influence the voting decision-making process. To achieve this purpose, exploratory research was carried out through questionnaire surveys. Three surveys were conducted based on the Portuguese presidential elections of January 24, 2021. The surveys were distributed before, during, and after the end of the electoral campaign, and 106 people were questioned and answered all 3 surveys. With the results of this study, it was possible to conclude that only 11% of respondents changed their voting intention due to the political communication made by political parties on social media during this electoral campaign. The social media most used by respondents was Facebook, which is also the one they consider the safest and most trustworthy to follow political communication in online media.

Abstract
Ferramentas de e-learning no contexto ensino-aprendizagem

Abstract
Recently, deep learning has proven to be a successful technique especially in medical image analysis. This paper aims to highlight the importance of deep learning architectures in lung disease diagnosis using CXR images. Related articles were identified through searches of electronic resources, including IEEE, Springer, Elsevier, PubMed, Nature and, Hindawi digital library. The inclusion of articles was based on high-performance artificial intelligence models, developed for the classification of possible findings in CXR images published from 2018 to 2023.After the quality assessment of papers, 129 articles were included according to PRISMA guidelines. Papers were studied by types of lung disease, data source, algorithm type, and outcome metrics. Three main categories of computer-aided lung disease detection were covered: traditional machine learning, deep learning-based methods, and combination of aforementioned methods for all lung diseases.The results showed that various pre-trained networks including ResNet, VGG, and DenseNet, are the most frequently used CNN architectures and would result in a notable increase in sensitivity and accuracy. Recent research suggests that utilizing a combination of deep networks with a robust machine learning classifier can outperform deep learning approaches that rely solely on fully connected neural networks as their classifier. Finally, the limitations of the existing literature and potential future research opportunities in possible findings in CXR images using deep learning architectures are discussed in this systematic review.