Abstract
This work exploits the nexus of agricultural activities, water, and electrical and thermal energies to propose a framework to develop efficient circular renewable energy communities for the agricultural sector, by analyzing and optimizing the resources and the energy flows among them, profiting from the energy sources available. In this framework, local industries and agricultural facilities can invest in solar PV plants, livestock residues digestors to produce biogas, and cogeneration plants to supply the thermal and electrical energy needs. A simplified case study is presented, based on using biomass residues from livestock processed in an anaerobic digestor to produce biogas for a cogeneration plant. Their optimal capacities are computed considering the optimal supply of thermal and electrical energy needs and the supply from the public electricity and gas grids.

Abstract

Abstract
A terceira edição dos Cadernos de Investigação do Mestrado em Negócio Eletrónico (MNE) testemunha o contínuo amadurecimento deste ciclo de estudos como polo de reflexão académica e científica. Este volume reúne 21 artigos de jovens investigadores que, sob orientação de docentes-investigadores, exploram os fenómenos mais relevantes que moldam o atual panorama do negócio eletrónico.

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Abstract
This paper presents machine digitalization solutions with particular application in forest machines, such as harvesters and wood processing machines. In line with all the requirements of Industry 4.0, this type of machines also needs digitization to align with the concept defined as Forestry 4.0, where we think of a smarter forest in which all stakeholders, humans, forest producers, machines and factories communicate. For machine manufacturers is a step that must be taken to modernize machines, enabling remote access services for maintenance, productivity monitoring, and management of forest operations. It consists of developing cyber-physical systems around the machines with digital twins that allow the simulation and identification of faults that may occur. A solution is presented to enable CAN Bus communication between the controller, operator joysticks, and sensors/actuators, as well as a Digital Twin solution to emulate machine operations. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Timeline summarization (TLS) is a challenging research task that requires researchers to distill extensive and intricate temporal data into a concise and easily comprehensible representation. This paper proposes a novel approach to timeline summarization using Abstract Meaning Representations (AMRs), a graphical representation of the text where the nodes are semantic concepts and the edges denote relationships between concepts. With AMR, sentences with different wordings, but similar semantics, have similar representations. To make use of this feature for timeline summarization, a two-step sentence selection method that leverages features extracted from both AMRs and the text is proposed. First, AMRs are generated for each sentence. Sentences are then filtered out by removing those with no named-entities and keeping the ones with the highest number of named-entities. In the next step, sentences to appear in the timeline are selected based on two scores: Inverse Document Frequency (IDF) of AMR nodes combined with the score obtained by applying a keyword extraction method to the text. Our experimental results on the TLS-Covid19 test collection demonstrate the potential of the proposed approach.