Abstract
Training motor imagery (MI) and motor observation (MO) tasks is being intensively exploited to promote brain plasticity in the context of post-stroke rehabilitation strategies. This may benefit from the use of closed-loop neurofeedback, embedded in brain-computer interfaces (BCI's) to provide an alternative non-muscular channel, which may be further augmented through embodied feedback delivered through virtual reality (VR). Here, we used functional magnetic resonance imaging (fMRI) in a group of healthy adults to map brain activation elicited by an ecologically-valid task based on a VR-BCI paradigm called NeuRow, whereby participants perform MI of rowing with the left or right arm (i.e., MI), while observing the corresponding movement of the virtual arm of an avatar (i.e., MO), on the same side, in a first-person perspective. We found that this MI-MO task elicited stronger brain activation when compared with a conventional MI-only task based on the Graz BCI paradigm, as well as to an overt motor execution task. It recruited large portions of the parietal and occipital cortices in addition to the somatomotor and premotor cortices, including the mirror neuron system (MNS), associated with action observation, as well as visual areas related with visual attention and motion processing. Overall, our findings suggest that the virtual representation of the arms in an ecologically-valid MI-MO task engage the brain beyond conventional MI tasks, which we propose could be explored for more effective neurorehabilitation protocols. Copyright: © 2023 Nunes et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Abstract
Efficient use of resources is a critical factor in almond crops. Technological solutions can significantly contribute to this purpose. The VeraTech project aims to explore the integration of sensors and cloud-based technologies in almond crops for efficient use of resources and reduction of environmental impact. It also makes available a set of relevant and impactful performance indicators in agricultural activity, which promote productivity gains supported by efficient use of resources. The proposed solution includes a sensor network in the almond crops, the transmission of data and its integration in the cloud, making this data available to be consumed, processed, and presented in the monitoring and alerts dashboard. In the current state of the development, several data are collected by sensors, transmitted over LoRaWAN, integrated using AWS IoT Core, and monitored and analysed through a cloud business analytics service. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract

Abstract
The role of digital transformation (DT) in economic development is a vital and recurring point of research. It is particularly relevant if we consider the high percentage of digital transformation initiatives that fail to deliver the expected results, particularly in Small and Medium Enterprises (SMEs). This paper analyzes what is needed to make this transformation successful from an implementation perspective and, simultaneously, from the standpoint of obtaining the company’s expected results. This phenomenon is even more critical to decipher and understand when we look at the small and medium enterprises that face more significant challenges due to the scarcity of resources and needed skills. This work reviews a large variety of models through an extensive systematic literature review (SLR) that assess the readiness and maturity of the digital transformation of enterprises, with a focus on SMEs, with its primary objectives being (1) to review the existing studies and models that assess an organization’s maturity and readiness in the context of digital transformation, focusing on SMEs; (2) to identify if there are gaps considering the importance of the SMEs; and (3) to propose a standardized set of dimensions that should always be considered in a digital transformation assessment. The outcome of this research provides an essential contribution by identifying apparent gaps in the assessment of digital transformation in SMEs and proposing a scalable and standardized set of categories and subcategories that can be used across any future assessment model. These contributions are even more relevant when referencing minimal deep research in the context of SMEs and Digital Transformation.

Abstract
Traditional identity management (IdM) systems rely on third-party identity providers (IdPs) and are centralised, which can make them vulnerable to data breaches and other security risks. Self-sovereign identity (SSI) is a newer IdM model that allows users to control their own identities by using decentralised technologies like blockchain to store and verify them. However, SSI systems have their own security concerns, such as digital wallet vulnerabilities, blockchain threats and conflicts with general data protection regulation (GDPR). Additionally, the lack of incentives for issuers, verifiers and data owners could limit its acceptance. This paper proposes SPIDVerify, which is a decentralised identity verification framework that utilises an SSI-based architecture to address these issues. The framework uses a mixed method for acquiring a W3C standard verified credentials and to ensure that only a thoroughly verified entity acquires verified credential, and employs secure key cryptographic protocols; Diffie-Hellman (DH) and Extended Triple Diffie-Hellman (X3DH) for forward secrecy secure communication, single-use challenge-response for authentication, and Swarm network for decentralised storage of data. These methods enhance the security of the proposed framework with better resilience against impersonation and credential stealing. To evaluate the proposal, we have outlined the limitations in related works and demonstrated two scenarios to showcase the strength and effectiveness of SPIDVerify in dealing with the threats identified. We have also tested the methods used in SPIDVerify by measuring the time taken to execute certain processes.