Abstract
Introduction/Objective: the objective of this article is to analyze the current academic literature on smart cities in Brazil with evidence of the application of Digital Twin or Digital Shadow technology. Method: Integrative Literature Review was used as the research instrument, analyzing in the articles: a) objective; b) research method; c) study subject (location); d) application of Digital Twin or Digital Shadow; e) Results and conclusions. Results: portfolio with 25 articles on the topic and qualitative analysis regarding objective, method, study location, Digital Twin technology, Digital Shadow, and results. Studies with elements of Digital Shadow are perceived timidly in two cases of smart cities in Brazil. Conclusions: smart city technologies should be centered on the interests of users to not lose their humanity. It is worth adding that people's needs change and, therefore, smart technologies should have a forward-looking vision to anticipate the needs of future generations. Digital Twin technology is a model that can contribute in this sense, monitoring and providing readings of future scenarios for smart cities.

Abstract

Abstract
This research examined factors that help microfinance achieve sustained poverty reduction based on a systematic literature review (SLR). A search was conducted on the SCOPUS database up to December 2023. After analyzing hundreds of documents, a subset of 30 articles was subject to in-depth analysis, exploring factors and corresponding measurement indicators for sustainable poverty reduction in microfinance contexts. This article emphasizes that sustained poverty reduction is a gradual process requiring ongoing efforts from both Microfinance Institutions (MFIs) and governments. Two key success factors are empowering borrowers and ensuring the microfinance programs themselves are profitable. When implemented in an integrated and coordinated manner, these factors can empower individuals to escape poverty by fostering self-employment and income generation, ultimately reducing dependence on external support. Additionally, the study highlights the role of personality traits in influencing long-term entrepreneurial success. The findings provide valuable tools for MFIs and policymakers. MFIs gain a practical framework to guide their interventions towards sustained poverty reduction. Policymakers can leverage the identified factors and indicators when designing and implementing microfinance policies with a long-term focus on poverty alleviation. This study breaks new ground by presenting an operational framework that categorizes and integrates two critical factor groups: empowerment and beneficiary profitability. Furthermore, it links these factors to corresponding measurement indicators within a unified framework, enabling a more holistic assessment of poverty reduction efforts. © 2024 by the authors.

Abstract
Deep-learning techniques can improve the efficiency of medical diagnosis while challenging human experts’ accuracy. However, the rationale behind these classifier’s decisions is largely opaque, which is dangerous in sensitive applications such as healthcare. Case-based explanations explain the decision process behind these mechanisms by exemplifying similar cases using previous studies from other patients. Yet, these may contain personally identifiable information, which makes them impossible to share without violating patients’ privacy rights. Previous works have used GANs to generate anonymous case-based explanations, which had limited visual quality. We solve this issue by employing a latent diffusion model in a three-step procedure: generating a catalogue of synthetic images, removing the images that closely resemble existing patients, and using this anonymous catalogue during an explanation retrieval process. We evaluate the proposed method on the MIMIC-CXR-JPG dataset and achieve explanations that simultaneously have high visual quality, are anonymous, and retain their explanatory value.

Abstract
Reactive graphs are transition structures whereas edges become active and inactive during its evolution, that were introduced by Dov Gabbay from a mathematical's perspective. This paper presents Marge (https://fm- dcc.github.io/MARGe), a web-based tool to visualise and analyse reactive graphs enriched with labels. Marge animates the operational semantics of reactive graphs and offers different graphical views to provide insights over concrete systems. We motivate the applicability of reactive graphs for adaptive systems and for featured transition systems, using Marge to tighten the gap between the existing theoretical models and their usage to analyse concrete systems.

Abstract
The use of model checking tools allows for the formal verification of properties over models of systems, improving their robustness. However, these tools are challenging to use, and their results require much work of interpretation to communicate to stakeholders. To address this issue, the IVY Workbench offers a plethora of options to make the process of creating and understanding the models, properties and results of the verification process more accessible, with a particular focus on interactive computing systems. Despite this, there is still a significant requirement of expertise to use the tool. To solve this, an approach to provide structured natural language explanations for the results of model checking-based tools is being developed, to be later incorporated into the IVY Workbench. This paper presents the current state of the approach's development, stating its objective and what results can already be achieved.