Abstract
Multiple factors can affect presence in virtual environments, such as the number of human senses engaged in a given experience or the extent to which the virtual experience is credible. The purpose of the present work is to study how the inclusion of credible multisensory stimuli affects the sense of presence, namely, through the use of wind, passive haptics, vibration, and scent. Our sample consisted of 37 participants (27 men and 10 women) whose ages ranged from 17 to 44 years old and were mostly students. The participants were divided randomly into 3 groups: Control Scenario (visual and auditory - N = 12), Passive Haptic Scenario (visual, auditory, and passive haptic - N = 13) and Multisensory Scenario (visual, auditory, wind, passive haptic, vibration, and scent - N = 12). The results indicated a significant increase in the involvement subscale when all multisensory stimuli were delivered. We found a trend where the use of passive haptics by itself has a positive impact on presence, which should be the subject of further work.

Abstract
Cloud Computing services for data analytics are increasingly being sought by companies to extract value from large quantities of information. However, processing data from individuals and companies in third-party infrastructures raises several privacy concerns. To this end, different secure analytics techniques and systems have recently emerged. These initial proposals leverage specific cryptographic primitives lacking generality and thus having their application restricted to particular application scenarios. In this work, we contribute to this thriving body of knowledge by combining two complementary approaches to process sensitive data. We present SafeSpark, a secure data analytics framework that enables the combination of different cryptographic processing techniques with hardware-based protected environments for privacy-preserving data storage and processing. SafeSpark is modular and extensible therefore adapting to data analytics applications with different performance, security and functionality requirements. We have implemented a SafeSpark’s prototype based on Spark SQL and Intel SGX hardware. It has been evaluated with the TPC-DS Benchmark under three scenarios using different cryptographic primitives and secure hardware configurations. These scenarios provide a particular set of security guarantees and yield distinct performance impact, with overheads ranging from as low as 10% to an acceptable 300% when compared to an insecure vanilla deployment of Apache Spark. © IFIP International Federation for Information Processing 2020.

Abstract
Pedestrian behavior is an essential subject of study when developing or enhancing urban infrastructure. However, most behavior elicitation techniques are inherently bound to be biased by either the observer, the subject, or the environment. The SIMUSAFE project aims at collecting road users’ behavioral data in naturalistic and realistic scenarios to produce more accurate decision-making models. Using video captured from a monocular camera worn by a pedestrian, we employ machine learning and computer vision techniques to identify areas of interest surrounding a pedestrian. Namely, we use object detection and depth estimation to generate a map of obstacles that may influence the pedestrian’s actions. Our methods have shown to be successful in detecting free and occupied areas from monocular video. © 2020, Springer Nature Switzerland AG.

Abstract
Family businesses (FBs) are central to economies: in Portugal the impact of these structures reaches 2/3 of the GDP, 1/2 of the labour force, and 4/5 of the firms in operation, most of them being SMEs. These organisations play a central role in terms of job creation, local development, knowledge transfer, and territorial cohesion. Innovative activities are key factors for competitive economies; yet innovation increases risk exposure and FBs are conservative and risk adverse, resisting change, relying on internal factors rather than opening to the external environment, consequently postponing innovation and thus pledging their future. Their embedded culture reduces innovative propensity; still, the existence loyalty trust and informal networks enhance individual or collective innovation processes. Using a dataset of 110 FBs innovation and internationalization along with other structural characteristics are connected to their economic performance, shedding light on the determinants FB economic efficiency. Given their importance, made-to-measure policy schemes should be designed.

Abstract
Many domestic enterprises in emerging economies are concerned with the question of how to better utilize the portfolio of technology sourcing channels to achieve rapid economic growth by technological innovation. This paper looks at this issue by exploring the impacts of knowledge acquisition diversity (KAD) on innovation performance of domestic enterprises in China and the technological contexts (in terms of technology gap and technology development speed) under which KAD is most likely to contribute. Using panel data of the manufacturing industry in China over the 2001-2009 period, the results show that KAD has an inverse U-shaped relationship with innovation performance in terms of both product-related innovation performance (NPS) and knowledge-related innovation performance (PAT). Specifically, it reveals that the capability to generate technological innovation over time is dependent on how domestic enterprises manage their portfolio of knowledge sourcing channels to learn from foreign enterprises. Moreover, it is shown that the technology gap significantly moderates the inverted U-shaped relationship between KAD and both NPS and PAT. Technology development speed has a moderating effect on the inverted U-shaped relationship between KAD and innovation only in terms of NPS. The results of this study can help us to understand the relationships among technological contexts, KAD and innovation performance of domestic enterprises in emerging countries.

Abstract
Purpose This short communication aims to explore and synthesize the main effects of COVID-19 on the labor market in Portugal regarding the dimensions related to job security and unemployment. Design/methodology/approach Field research is used to identify and understand the challenges posed by the COVID-19 pandemic to the labor market in Portugal. Data from the National Institute of Statistics of Portugal are analyzed and compared with artifacts published in the field, which allow us to explore the impact of this phenomenon from multiple perspectives. Findings The findings indicate that the impact on the labor market is very asymmetric regarding geographical regions, sectors of activity, age groups and the nature of labor ties. The most touristic regions and those with a strong dependence on the exterior are the most affected. Young people and women with unstable employment relationships and in temporary work situations are also particularly vulnerable. Originality/value This study focuses on an emerging area with a strong impact of the COVID-19 pandemic on the labor market. This study seeks both to identify challenges in the Portuguese labor market and to discuss measures that should be taken to mitigate their effects, such as reforming the social security model, the role of teleworking or the more balanced development of the territory.