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

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 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 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

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

An accessory middle scalene muscle causing thoracic outlet syndrome

The aim of our study is to present a very rare accessory middle scalene muscle, leading to thoracic outlet syndrome. In particular, a muscular bundle was discovered on a male cadaver connecting the middle portion of the middle scalene muscle with the anterior scalene muscle insertion to Lisfranc`s tubercle. This triangular accessory muscle and, especially, its sharp medial border compressed the middle and lower trunk of the brachial plexus and the subclavian artery. This anomaly is of great importance because it emphasises the fact that it is not primarily the anterior scalene muscle that produces symptoms of thoracic outlet syndrome but the anterior displacement of the middle scalene muscle or its accessory muscular bands. We also present the relative international literature and the clinical significance of our finding

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

YSO jets in the Galactic Plane from UWISH2: II - Outflow Luminosity and Length distributions in Serpens and Aquila

Jets and outflows accompany the mass accretion process in protostars and young stellar objects. Using a large and unbiased sample, they can be used to study statistically the local feedback they provide and the typical mass accretion history. Here we analyse such a sample of Molecular Hydrogen emission line Objects in the Serpens and Aquila part of the Galactic Plane. Distances are measured by foreground star counts with an accuracy of 25%. The resulting spacial distribution and outflow luminosities indicate that our objects sample the formation of intermediate mass objects. The outflows are unable to provide a sizeable fraction of energy and momentum to support, even locally, the turbulence levels in their surrounding molecular clouds. The fraction of parsec scale flows is one quarter and the typical dynamical jet age of the order of 1E4yrs. Groups of emission knots are ejected every 1E3yrs. This might indicate that low level accretion rate fluctuations and not FU-Ori type events are responsible for the episodic ejection of material. Better observational estimates of the FU-Ori duty cycle are needed.Comment: 16pages, 3tables, 10figures, accepted for publication by MNRAS, a version with higher resolution figures can be found at http://astro.kent.ac.uk/~df

Predicting complicated appendicitis based on clinical findings: the role of Alvarado and appendicitis inflammatory response scores

PURPOSE: The pre-interventional differentiation between complicated and uncomplicated appendicitis is decisive for treatment. In the context of conservative therapy, the definitive diagnosis of uncomplicated appendicitis is mandatory. This study investigates the ability of clinical scoring systems and imaging to differentiate between the two entities. METHODS: This is a retrospective analysis of two cohorts from two tertiary referral centers in Switzerland and Germany. All consecutive patients underwent appendectomy between January 2008 and April 2013 (in the first cohort) or between January 2017 and June 2019 (the second cohort). Exclusion criteria did not apply as all patients found by the database search and received an appendectomy were included. Diagnostic testing and calculation of a receiver operating curve were performed to identify a cutoff for clinical scores that resulted in a minimum sensitivity of 90% to detect complicated appendicitis. The cutoff was combined with additional diagnostic imaging criteria to see if diagnostic properties could be improved. RESULTS: Nine hundred fifty-six patients were included in the analysis. Two hundred twenty patients (23%) had complicated appendicitis, and 736 patients (77%) had uncomplicated appendicitis or no inflammation. The complicated appendicitis cohort had a mean Alvarado score of 7.03 and a mean AIR of 5.21. This compared to a mean Alvarado of 6.53 and a mean AIR of 4.07 for the uncomplicated appendicitis cohort. The highest Alvarado score with a sensitivity of > 90% to detect complicated appendicitis was >== 5 (sensitivity = 95%, specificity 8.99%). The highest AIR score with a sensitivity of > 90% to detect complicated appendicitis was >== 3 (sensitivity 91.82%, specificity 18.53). The analysis showed that additional CT information did not improve the sensitivity of the proposed cut-offs. CONCLUSION: AIR and Alvarado scores showed limited capability to distinguish between complicated and uncomplicated appendicitis even with additional imaging in this retrospective cohort. As conservative management of appendicitis needs to exclude patients with complicated disease reliably, appendectomy seems until now to remain the safest option to prevent undertreatment of this mostly benign disease

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