Abstract
Embodied Communication Agents are being used to support older adults but there is still a lack of knowledge about their impact. Therefore, this paper presents a scoping review of the literature on user centred evaluation of the impact of Embodied Communication Agents when embedded in digital solutions to support older adults. The ten studies that were included in this scoping review reported on the implementation of digital solutions to promote physical activity, minimize loneliness, provide spiritual comfort, facilitate problem solving and knowledge acquisition, and support the diagnosis of neurodegenerative diseases. In terms of impact assessment, different outcomes were considered, and the included studies reported significant impact in terms of steps walked and acknowledge acquisition, a trend in the reduction of loneliness, and good sensitivity and specificity to diagnose neurodegenerative diseases.

Abstract
The aim of this study is to analyze the typical process of the practical part of software development courses at universities and to evaluate whether the current process meets the expectations of students or whether the needs of students would be better met by the benefits of automated code feedback. A semiautomated survey was conducted in German, involving bachelor students from different universities who had attended an introductory programming class within the last 6 semesters. The results clearly show that the students would like to have individual assignments instead of the due to time constraints, usual group exercises as they see more advantages for their learning progress. The use of automated code feedback could not only solve this time problem but would also bring other benefits.

Abstract

Abstract
The scoping review reported by this article aimed to analyse how security and privacy mechanism are being integrated with Fast Health Interoperability Resources (FHIR). An electronic search was conducted, and 37 studies were included in the review. The results show that 19 studies (i.e., more than half of the included studies) reported on the use of blockchain technology to (i) assure secure data sharing, (ii) provide secure Personal Health Records, (iii) support authentication and auditing mechanisms, (iv) support smart legal contracts, and (v) monitor the access to clinical data. The remainder 18 articles reported on the implementation of security and privacy mechanisms related to (i) data security at transmission, (ii) data security at storage, (iii) access control; (iv) data anonymization, and (v) management of informed consents. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The scoping review reported by this article aimed to analyze and synthesize state-of-the-art studies focused on the integration of cyber resilience in the implementation of smart cities. An electronic search was conducted, and 11 studies were included in this review after the selection process. According to the findings, cyber resilience represents a gap of the current research related to smart cities and, therefore, additional efforts are required to guarantee that smart cities are resilient to challenging events such as cyber-attacks or natural disasters. © 2023 ITMA.

Abstract
This scoping review systematizes the current research related to the use of both blockchain and machine learning techniques in medical imaging applications. A systematic electronic search was performed, and twenty-five studies were included in the review. These studies aimed to use blockchain and machine learning techniques to provide (i) efficient security mechanisms to support the communication of medical imaging data, (ii) aggregation of distributed medical imaging data to train machine learning algorithms, and (iii) machine learning algorithms based on federated learning strategies. Among the ten machine learning techniques identified in the included studies, Convolutional Neural Network was the most representative (i.e., 44% of the studies). Moreover, Artificial Neural Network, Capsule Network, Deep Neural Network, Gated Recurrent Units, and Neural Network were machine learning techniques used by more than one study. Although the included studies developed algorithms with potential impact in clinical practice, it must be noted that they did not discuss the generalizability of their algorithms in real-world clinical conditions.