Abstract
The majority of virtual reality (VR) applications rely on audiovisual stimuli and do not exploit the addition of other sensory cues that could increase the potential of VR. This systematic review surveys the existing literature on multisensory VR and the impact of haptic, olfactory, and taste cues over audiovisual VR. The goal is to identify the extent to which multisensory stimuli affect the VR experience, which stimuli are used in multisensory VR, the type of VR setups used, and the application fields covered. An analysis of the 105 studies that met the eligibility criteria revealed that 84.8 percent of the studies show a positive impact of multisensory VR experiences. Haptics is the most commonly used stimulus in multisensory VR systems (86.6 percent). Non-immersive and immersive VR setups are preferred over semi-immersive setups. Regarding the application fields, a considerable part was adopted by health professionals and science and engineering professionals. We further conclude that smell and taste are still underexplored, and they can bring significant value to VR applications. More research is recommended on how to synthesize and deliver these stimuli, which still require complex and costly apparatus be integrated into the VR experience in a controlled and straightforward manner.

Abstract

Abstract
The evacuation of buildings in case of fire is a sensitive issue for civil society that also motivates the academic community to develop and study solutions to improve the efficiency of evacuating these spaces. The study of human behavior in fire emergencies has been one of the areas that have deserved the attention of researchers. However, this modeling of human behavior is difficult and complex because it depends on factors that are difficult to know and that vary from country to country. In this paper, a paradigm shift is proposed which, instead of focusing on modeling the behavior of occupants, focuses on conditioning this behavior by providing real-time information on the most efficient evacuation routes. Making this information available to occupants is possible with a solution that takes advantage of the growing use of the IoT (Internet of Things) in buildings to help occupants adapt to the environment. Supported by the IoT, multi-agent recommender systems can help users to adapt to the environment and provide the occupants with the most efficient evacuation routes. This paradigm shift is achieved through a context-based multi-agent recommender system based on contextual data obtained from IoT devices, which recommends the most efficient evacuation routes at any given time. The obtained results suggest that the proposed solution can improve the efficiency of evacuating buildings in the event of a fire; for a scenario with two hundred people following the system recommendations, the time they take to reach a safe place decreases by 17.7%.

Abstract
Both logic programming in general and Prolog in particular have a long and fascinating history, intermingled with that of many disciplines they inherited from or catalyzed. A large body of research has been gathered over the last 50 years, supported by many Prolog implementations. Many implementations are still actively developed, while new ones keep appearing. Often, the features added by different systems were motivated by the interdisciplinary needs of programmers and implementors, yielding systems that, while sharing the classic core language, in particular, the main aspects of the ISO-Prolog standard, also depart from each other in other aspects. This obviously poses challenges for code portability. The field has also inspired many related, but quite different languages that have created their own communities. This article aims at integrating and applying the main lessons learned in the process of evolution of Prolog. It is structured into three major parts. First, we overview the evolution of Prolog systems and the community approximately up to the ISO standard, considering both the main historic developments and the motivations behind several Prolog implementations, as well as other logic programming languages influenced by Prolog. Then, we discuss the Prolog implementations that are most active after the appearance of the standard: their visions, goals, commonalities, and incompatibilities. Finally, we perform a SWOT analysis in order to better identify the potential of Prolog and propose future directions along with which Prolog might continue to add useful features, interfaces, libraries, and tools, while at the same time improving compatibility between implementations.

Abstract
We propose an approach to summarize large semantics graphs using namespaces. Semantic graphs based on the Resource Description Framework (RDF) use namespaces on their serializations. Although these namespaces are not part of RDF semantics, they have intrinsic meaning. Based on this insight, we use namespaces to create summary graphs of reduced size, more amenable to be visualized. In the summarization, object literals are also reduced to their data type and the blank nodes to a group of their own. The visualization created for the summary graph aims to give insight of the original large graph. This paper describes the proposed approach and reports on the results obtained with representative large semantic graphs. © Ana Rita Santos Lopes da Costa, André Santos, and José Paulo Leal.

Abstract
Memristor crossbar arrays can compose the efficient hardware for artificial intelligent applications. However, the requirements for a linear and symmetric synaptic weight update and low cycle-to-cycle (C2C) and device-to-device variability as well as the sneak-path current issue have been delaying its further development. This study reports on a thin-film amorphous oxide-based 4x4 1-transistor 1-memristor (1T1M) crossbar. The a-IGZO crossbar is built on a flexible polyimide substrate, enabling IoT and wearable applications. In the novel framework, the thin-film transistor and memristor are fabricated at the same level, with the same processing steps and sharing the same materials for all layers. The 1T1M cells show linear and symmetrical plasticity characteristic with low C2C variability. The memristor performs like an analog dot product engine and vector-matrix multiplications in the 4x4 crossbars is demonstrated experimentally, in which the sneak-path current issue is successfully suppressed, resulting in a proof-of-concept for a cost-effective, flexible artificial neural networks hardware.