Optimal Monetary Policy and the Asset Market: A Non-cooperative Game

In this paper we construct a model of a policy game in order to analyse the optimal reaction function of the Central Bank to a shock in the asset market. In doing so, we consider three different noncooperative games: Nash equilibrium, Stackelberg equilibrium with “FED” as leader and “ECB” Stacklberg as leader. Three major conclusions can be drawn from our work in the presence of asset market shocks. First, in the Nash equilibrium the ECB will adopt a less restrictive monetary policy compared to the FED’s behaviour. Second, comparing the Nash and Stackelberg non-cooperative equilibria, the Stackelberg solution is certainly superior when the FED is the leader, but the Nash solution is superior for the follower. Finally, irrespective of where the shocks originate, if the FED would choose the Stackelberg leader equilibrium the ECB would minimize its social loss along with a lower level of interest rates

Pattern-driven security, privacy, dependability and interoperability management of iot environments

Achieving Security, Privacy, Dependability and Interoperability (SPDI) is of paramount importance for the ubiquitous deployment and impact maximization of Internet of Things (IoT) applications. Nevertheless, said requirements are not only difficult to achieve at system initialization, but also hard to prove and maintain at run-time. This paper highlights an approach to tackling the above challenges, through the definition of pattern language and a framework that can guarantee SPDI in IoT orchestrations. By integrating pattern reasoning engines at the various layers of the IoT infrastructure, and a machine-processable representation of said pattern through Drools rules, the proposed framework can provide ways to fulfill SPDI requirements at design time, and also provide the means to guarantee those SPDI properties and manage the orchestrations accordingly. Moreover, an application example of the framework is presented in an Industrial IoT monitoring environment

WARDOG: Awareness detection watchbog for Botnet infection on the host device

Botnets constitute nowadays one of the most dangerous security threats worldwide. High volumes of infected machines are controlled by a malicious entity and perform coordinated cyber-attacks. The problem will become even worse in the era of the Internet of Things (IoT) as the number of insecure devices is going to be exponentially increased. This paper presents WARDOG – an awareness and digital forensic system that informs the end-user of the botnet’s infection, exposes the botnet infrastructure, and captures verifiable data that can be utilized in a court of law. The responsible authority gathers all information and automatically generates a unitary documentation for the case. The document contains undisputed forensic information, tracking all involved parties and their role in the attack. The deployed security mechanisms and the overall administration setting ensures non-repudiation of performed actions and enforces accountability. The provided properties are verified through theoretic analysis. In simulated environment, the effectiveness of the proposed solution, in mitigating the botnet operations, is also tested against real attack strategies that have been captured by the FORTHcert honeypots, overcoming state-of-the-art solutions. Moreover, a preliminary version is implemented in real computers and IoT devices, highlighting the low computational/communicational overheads of WARDOG in the field

An automatic method to generate domain-specific investigator networks using PubMed abstracts

<p>Abstract</p> <p>Background</p> <p>Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts.</p> <p>Results</p> <p>We developed a novel strategy to obtain detailed investigator information by automatically parsing the affiliation string in PubMed records. We illustrated the results by using a published literature database in human genome epidemiology (HuGE Pub Lit) as a test case. Our parsing strategy extracted country information from 92.1% of the affiliation strings in a random sample of PubMed records and in 97.0% of HuGE records, with accuracies of 94.0% and 91.0%, respectively. Institution information was parsed from 91.3% of the general PubMed records (accuracy 86.8%) and from 94.2% of HuGE PubMed records (accuracy 87.0). We demonstrated the application of our approach to dynamic creation of investigator networks by creating a prototype information system containing a large database of PubMed abstracts relevant to human genome epidemiology (HuGE Pub Lit), indexed using PubMed medical subject headings converted to Unified Medical Language System concepts. Our method was able to identify 70–90% of the investigators/collaborators in three different human genetics fields; it also successfully identified 9 of 10 genetics investigators within the PREBIC network, an existing preterm birth research network.</p> <p>Conclusion</p> <p>We successfully created a web-based prototype capable of creating domain-specific investigator networks based on an application that accurately generates detailed investigator profiles from PubMed abstracts combined with robust standard vocabularies. This approach could be used for other biomedical fields to efficiently establish domain-specific investigator networks.</p

Manifesto for a European research network into Problematic Usage of the Internet

Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.The Internet is now all-pervasive across much of the globe. While it has positive uses (e.g. prompt access to information, rapid news dissemination), many individuals develop Problematic Use of the Internet (PUI), an umbrella term incorporating a range of repetitive impairing behaviours. The Internet can act as a conduit for, and may contribute to, functionally impairing behaviours including excessive and compulsive video gaming, compulsive sexual behaviour, buying, gambling, streaming or social networks use. There is growing public and National health authority concern about the health and societal costs of PUI across the lifespan. Gaming Disorder is being considered for inclusion as a mental disorder in diagnostic classification systems, and was listed in the ICD-11 version released for consideration by Member States (http://www.who.int/classifications/icd/revision/timeline/en/). More research is needed into disorder definitions, validation of clinical tools, prevalence, clinical parameters, brain-based biology, socio-health-economic impact, and empirically validated intervention and policy approaches. Potential cultural differences in the magnitudes and natures of types and patterns of PUI need to be better understood, to inform optimal health policy and service development. To this end, the EU under Horizon 2020 has launched a new four-year European Cooperation in Science and Technology (COST) Action Programme (CA 16207), bringing together scientists and clinicians from across the fields of impulsive, compulsive, and addictive disorders, to advance networked interdisciplinary research into PUI across Europe and beyond, ultimately seeking to inform regulatory policies and clinical practice. This paper describes nine critical and achievable research priorities identified by the Network, needed in order to advance understanding of PUI, with a view towards identifying vulnerable individuals for early intervention. The network shall enable collaborative research networks, shared multinational databases, multicentre studies and joint publications.Peer reviewe

MobileTrust: Secure Knowledge Integration in VANETs

Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust – a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies in order to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform in order to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy

Exercise addiction, body dysmorphic disorder, and use of enhancement drugs during the COVID-19 pandemic confinement period: a transcultural study

info:eu-repo/semantics/publishedVersio

A systematic survey for eruptive young stellar objects using mid-infrared photometry

Accretion in young stellar objects (YSOs) is at least partially episodic, i.e. periods with high accretion rates ('bursts') are interspersed by quiescent phases. These bursts manifest themselves as eruptive variability. Here we presenta systematic survey for eruptive YSOs aiming to constrain the frequency of accretion bursts. We compare mid-infrared photometry from Spitzer and WISE separated by ~5 yr for two samples of YSOs, in nearby star-forming regions and in the Galactic plane, each comprising about 4000 young sources. All objects for which the brightness at 3.6 and 4.5 μm is increased by at least 1 mag between the two epochs may be eruptive variables and burst candidates. For these objects, we carry out follow-up observations in the near-infrared. We discover two new eruptive variables in the Galactic plane which could be FU Ori-type objects, with K-band amplitudes of more than 1.5 mag. One object known to undergo an accretion burst, V2492 Cyg, is recovered by our search as well. In addition, the young star ISO-Oph-50, previously suspected to be an eruptive object, is found to be better explained by a disc with varying circumstellar obscuration. In total, the number of burst events in a sample of 4000 YSOs is 1-4. Assuming that all YSOs undergo episodic accretion, this constraint can be used to show that phases of strong accretion (&gt;10-6Mâ?? yr-1) occur in intervals of about 104 yr, most likely between 5000 and 50 000 yr. This is consistent with the dynamical time-scales for outflows, but not with the separations of emission knots in outflows, indicating that episodic accretion could either trigger or stop collimated large-scale outflows. © 2013 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society

Ontology-Based Integration of Streaming and Static Relational Data with Optique

An important application of semantic technologies in industry has been the formalisation of information models usingOWL 2 ontologies and the use of RDF for storing and exchanging application data. Moreover, legacy data can be virtualised asRDF using ontologies following the ontology-based data access (OBDA) approach. In all these applications, it is important toprovide domain experts with query formulation tools for expressing their information needs in terms of queries over ontologies. Inthis work, we present such a tool, OptiqueVQS, which is designed based on our experience with OBDA applications in Statoil andSiemens and on best HCI practices for interdisciplinary engineering environments. OptiqueVQS implements a number of uniquetechniques distinguishing it from analogous query formulation systems. In particular, it exploits ontology projection techniquesto enable graph-based navigation over an ontology during query construction. Secondly, while OptiqueVQS is primarily ontologydriven, it exploits sampled data to enhance selection of data values for some data attributes. Finally, OptiqueVQS is built onwell-grounded requirements, design rationale, and quality attributes. We evaluated OptiqueVQS with both domain experts andcasual users and qualitatively compared our system against prominent visual systems for ontology-driven query formulation andexploration of semantic data. OptiqueVQS is available online and can be downloaded together with an example OBDA scenario

WhoLoDancE: Towards a methodology for selecting Motion Capture Data across different Dance Learning Practice

<p>In this paper we present the objectives and preliminary work of WhoLoDancE a Research and Innovation Action funded under the European Union‘s Horizon 2020 programme, aiming at using new technologies for capturing and analyzing dance movement to facilitate whole-body interaction learning experiences for a variety of dance genres. Dance is a diverse and heterogeneous practice and WhoLoDancE will develop a protocol for the creation and/or selection of dance sequences drawn from different dance styles for different teaching and learning modalities. As dance learning practice lacks standardization beyond dance genres and specific schools and techniques, one of the first project challenges is to bring together a variety of dance genres and teaching practices and work towards a methodology for selecting the appropriate shots for motion capturing, to acquire kinetic material which will provide a satisfying proof of concept for Learning scenarios of particular genres. The four use cases we are investigating are 1) classical ballet, 2) contemporary dance, 3) flamenco and 4) Greek folk dance.</p