Large-scale magnetic fields from inflation due to a CPTCPT-even Chern-Simons-like term with Kalb-Ramond and scalar fields

We investigate the generation of large-scale magnetic fields due to the breaking of the conformal invariance in the electromagnetic field through the $CPT$-even dimension-six Chern-Simons-like effective interaction with a fermion current by taking account of the dynamical Kalb-Ramond and scalar fields in inflationary cosmology. It is explicitly demonstrated that the magnetic fields on 1Mpc scale with the field strength of $\sim 10^{-9}$G at the present time can be induced.Comment: 18 pages, 6 figures, version accepted for publication in Eur. Phys. J.

Augmented Spatiality

Designers have long been concerned with new and visionary types of public space.With the advent of ubiquitous computing, architects and designers have become increasingly aware of the opportunities and challenges in designing spaces and everyday objects to support socially- oriented human interactions whether through spatial or technological means.This paper presents a novel transdiscplinary method for designing new interactive architectural prototypes that promote connectivity and social interactions in the public space in order to address specific agendas of urban interventions.The proposed method was evaluated in a pilot studio, in which students across various design and technical disciplines were invited to propose utopian socio- technological visions for a particular site and to develop their ideas into working architectural prototypes that could be installed at the chosen site and tested by the public.The open brief generated various responses and outcomes in eight projects, of which two are discussed in this paper

Spatiotemporal data mining: a survey on challenges and open problems

Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay between space and time. Several available surveys capture STDM advances and report a wealth of important progress in this field. However, STDM challenges and problems are not thoroughly discussed and presented in articles of their own. We attempt to fill this gap by providing a comprehensive literature survey on state-of-the-art advances in STDM. We describe the challenging issues and their causes and open gaps of multiple STDM directions and aspects. Specifically, we investigate the challenging issues in regards to spatiotemporal relationships, interdisciplinarity, discretisation, and data characteristics. Moreover, we discuss the limitations in the literature and open research problems related to spatiotemporal data representations, modelling and visualisation, and comprehensiveness of approaches. We explain issues related to STDM tasks of classification, clustering, hotspot detection, association and pattern mining, outlier detection, visualisation, visual analytics, and computer vision tasks. We also highlight STDM issues related to multiple applications including crime and public safety, traffic and transportation, earth and environment monitoring, epidemiology, social media, and Internet of Things. 2021, The Author(s), under exclusive licence to Springer Nature B.V.Qatar Foundation;Qatar National Research Fund;RMIT UniversityScopu