Electric vehicles (EVs) are crucial for mitigating greenhouse gas emissions in urban transportation. However, their integration requires efficient charging infrastructure and allocation strategies. In this paper, five heuristic algorithms were developed to allocate EVs to urban charging stations. This allocation process incorporates critical constraints, such as user preferences and charger type compatibility, while respecting station capacities governed by power output rules. The proposed methods include four initial allocation heuristics, ranging from capacity-centric and nearest-neighbor approaches to random assignments, complemented by a local search algorithm for solution refinement. To evaluate these heuristics, an optimization model minimizing station establishment and vehicle travel costs was adapted from the literature. Computational experiments were performed on both synthetic instances and real-world case studies. The results indicate that the developed heuristics, especially when enhanced by local search, deliver high-quality, near-optimal solutions within highly competitive computational times. Consequently, this study offers a scalable decision-support tool for urban planners, demonstrating how the joint optimization of infrastructure costs and user preferences can foster sustainable urban mobility and accelerate EV adoption. Ultimately, these findings offer actionable insights for scaling heterogeneous EV infrastructure, fostering urban sustainability and mitigating transport-related carbon emissions.
PurposeGrounded in information processing theory, this study aims to investigate the impact of digital technologies and memory on humanitarian supply chains' readiness to respond to natural disasters. It also examines whether the use of digital technologies influences memory development within these supply chains.Design/methodology/approachWe collected data from 255 key professionals involved in humanitarian operations and analyzed the proposed model using partial least squares structural equation modeling.FindingsThe results show that emerging digital technologies (e.g. artificial intelligence, machine learning, the Internet of Things, blockchain, 3D printing, virtual reality and drones) act as essential information-processing mechanisms that do not directly affect readiness. Instead, they facilitate the systematic generation, storage and retrieval of complex disaster data, transforming it into a humanitarian supply chain memory. This memory serves as a full mediator, ensuring that processed information becomes a durable repository of actionable knowledge that significantly enhances predisaster readiness.Originality/valueThis study contributes to both the literature and practice by empirically demonstrating that humanitarian supply chain memory is a necessary mechanism through which digital technologies improve readiness, and by highlighting the importance of prior knowledge, beyond experience alone, for enhancing humanitarian supply chains' ability to respond to natural disasters. For policymakers and public governance, the results emphasize the strategic importance of integrating digital technologies and memory into disaster management policies. Policies that preserve and mobilize disaster memory, supported by digital technologies, can enhance readiness, foster collective learning and build more adaptive and connected responses to natural disasters.
Os traumatismos dentários constituem uma condição que demanda identificação e orientação inicial adequadas, especialmente em situações nas quais o atendimento odontológico imediato pode não estar disponível. Este estudo desenvolveu um sistema inteligente baseado em visão computacional para apoio à identificação inicial de traumatismos dentários, integrando o modelo YOLO11n a uma arquitetura automatizada de comunicação e orientação ao usuário. Na etapa de visão computacional, foram utilizadas 1.142 imagens, distribuídas em quatro classes: avulsão, fratura pulpar, fratura de esmalte e fratura dentinária. O conjunto de dados foi dividido em 70% para treinamento, 20% para validação e 10% para teste do modelo YOLO11n. O desempenho obtido apresentou Precision de 66,58%, Recall de 70,52%, mAP@0.50 de 69,20%, mAP@0.50:0.95 de 36,35% e F1-Score de 0,67. Os resultados demonstram desempenho experimental moderado do modelo na identificação das classes de traumatismos dentários avaliadas. A arquitetura desenvolvida possibilitou a integração da visão computacional com o fluxo automatizado de comunicação e orientação ao usuário. A avaliação foi realizada em ambiente experimental, não envolvendo validação clínica prospectiva, comparação direta com cirurgiões-dentistas ou aplicação em ambiente assistencial real. Dessa forma, o sistema deve ser compreendido como uma ferramenta de apoio à identificação inicial e à orientação, não substituindo a avaliação realizada por um cirurgião-dentista.
No cenário global, edificações respondem por parcela significativa do consumo de energia e das consequentes emissões de gases de efeito estufa, o que motivou a criação de modelos de certificação para avaliar e incentivar a melhoria de seu desempenho energético. Este estudo compara quatro certificações governamentais: EPC (União Europeia), PBE Edifica (Brasil), Energy Star (Estados Unidos da América) e ESGB (China). A partir de pesquisa documental e bibliográfica, foram analisados aspectos como origem institucional, escopo, metodologias, critérios, escalas, processos, obrigatoriedade, custos e impactos. Conclui-se que a efetividade desses instrumentos depende do rigor técnico, de políticas públicas consistentes e de incentivos fiscais, configurando-os como estratégicos para a transição energética e a sustentabilidade urbana.
When presenting the image of the Line in Book VI of the Republic, Socrates explains that the soul progresses through four stages of investigation: supposition (εἰκασία), belief (πίστις), discursive thinking (διάνοια), and intelligence (νόησις). In the third stage, although the investigation already addresses the hypothesis of the Forms, the type of intellectual operation found at this level does not allow advancement to the next stage, which corresponds to the Form of the Good. This is because, through discursive thinking, which involves logical processes, it is impossible to reach the "principle of everything." It is therefore necessary to abandon hypothesis-based investigation and rely exclusively on another type of intellectual operation, no longer instrumental but intuitive. For this reason, only through the path of noesis, or direct vision, can one attain knowledge of the Good. This article analyzes the distinction between these two types of reasoning operations present in the Divided Line. Keywords: Hypothesis. Divided Line. Good. Plato.
