5GNOW: Challenging the LTE Design Paradigms of Orthogonality and Synchronicity

LTE and LTE-Advanced have been optimized to deliver high bandwidth pipes to wireless users. The transport mechanisms have been tailored to maximize single cell performance by enforcing strict synchronism and orthogonality within a single cell and within a single contiguous frequency band. Various emerging trends reveal major shortcomings of those design criteria: 1) The fraction of machine-type-communications (MTC) is growing fast. Transmissions of this kind are suffering from the bulky procedures necessary to ensure strict synchronism. 2) Collaborative schemes have been introduced to boost capacity and coverage (CoMP), and wireless networks are becoming more and more heterogeneous following the non-uniform distribution of users. Tremendous efforts must be spent to collect the gains and to manage such systems under the premise of strict synchronism and orthogonality. 3) The advent of the Digital Agenda and the introduction of carrier aggregation are forcing the transmission systems to deal with fragmented spectrum. 5GNOW is an European research project supported by the European Commission within FP7 ICT Call 8. It will question the design targets of LTE and LTE-Advanced having these shortcomings in mind and the obedience to strict synchronism and orthogonality will be challenged. It will develop new PHY and MAC layer concepts being better suited to meet the upcoming needs with respect to service variety and heterogeneous transmission setups. Wireless transmission networks following the outcomes of 5GNOW will be better suited to meet the manifoldness of services, device classes and transmission setups present in envisioned future scenarios like smart cities. The integration of systems relying heavily on MTC into the communication network will be eased. The per-user experience will be more uniform and satisfying. To ensure this 5GNOW will contribute to upcoming 5G standardization.Comment: Submitted to Workshop on Mobile and Wireless Communication Systems for 2020 and beyond (at IEEE VTC 2013, Spring

The relationship between mental health, sleep quality and the immunogenicity of COVID-19 vaccinations.

Sleep modulates the immune response, and sleep loss can reduce vaccine immunogenicity; vice versa, immune responses impact sleep. We aimed to investigate the influence of mental health and sleep quality on the immunogenicity of COVID-19 vaccinations and, conversely, of COVID-19 vaccinations on sleep quality. The prospective CoVacSer study monitored mental health, sleep quality and Anti-SARS-CoV-2-Spike IgG titres in a cohort of 1082 healthcare workers from 29 September 2021 to 19 December 2022. Questionnaires and blood samples were collected before, 14 days, and 3 months after the third COVID-19 vaccination, as well as in 154 participants before and 14 days after the fourth COVID-19 vaccination. Healthcare workers with psychiatric disorders had slightly lower Anti-SARS-CoV-2-Spike IgG levels before the third COVID-19 vaccination. However, this effect was mediated by higher median age and body mass index in this subgroup. Antibody titres following the third and fourth COVID-19 vaccinations ("booster vaccinations") were not significantly different between subgroups with and without psychiatric disorders. Sleep quality did not affect the humoral immunogenicity of the COVID-19 vaccinations. Moreover, the COVID-19 vaccinations did not impact self-reported sleep quality. Our data suggest that in a working population neither mental health nor sleep quality relevantly impact the immunogenicity of COVID-19 vaccinations, and that COVID-19 vaccinations do not cause a sustained deterioration of sleep, suggesting that they are not a precipitating factor for insomnia. The findings from this large-scale real-life cohort study will inform clinical practice regarding the recommendation of COVID-19 booster vaccinations for individuals with mental health and sleep problems

2D, 2.5D, or 3D? An Exploratory Study on Multilayer Network Visualisations in Virtual Reality

Relational information between different types of entities is often modelled by a multilayer network (MLN) -- a network with subnetworks represented by layers. The layers of an MLN can be arranged in different ways in a visual representation, however, the impact of the arrangement on the readability of the network is an open question. Therefore, we studied this impact for several commonly occurring tasks related to MLN analysis. Additionally, layer arrangements with a dimensionality beyond 2D, which are common in this scenario, motivate the use of stereoscopic displays. We ran a human subject study utilising a Virtual Reality headset to evaluate 2D, 2.5D, and 3D layer arrangements. The study employs six analysis tasks that cover the spectrum of an MLN task taxonomy, from path finding and pattern identification to comparisons between and across layers. We found no clear overall winner. However, we explore the task-to-arrangement space and derive empirical-based recommendations on the effective use of 2D, 2.5D, and 3D layer arrangements for MLNs.Comment: IEEE Transactions on Visualization and Computer Graphics, In press, To appear. Accepted to IEEE VIS 202

Immunogenicity and safety of coadministration of COVID-19 and influenza vaccination.

Seasonal influenza vaccination is established as important infection prevention measure, especially among highly exposed healthcare workers (HCWs) [1]. Coadministration with the third dose of COVID-19 vaccine could be an efficient strategy protecting HCWs from two major viral respiratory infections [2–4]. To date, the humoral immunogenicity and side effects of a coadministered third COVID-19 and a seasonal quadrivalent influenza vaccine are still unclear, the available data is limited in transferability to the general public [5–7]. This preference-based non-randomised controlled study examines the antibody-mediated immunogenicity and vaccine-related side effects of mRNA-based COVID-19 and seasonal influenza vaccine coadministration in HCWs

2D, 2.5D, or 3D? An Exploratory Study on Multilayer Network Visualisations in Virtual Reality

Relational information between different types of entities is often modelled by a multilayer network (MLN) – a network with subnetworks represented by layers. The layers of an MLN can be arranged in different ways in a visual representation, however, the impact of the arrangement on the readability of the network is an open question. Therefore, we studied this impact for several commonly occurring tasks related to MLN analysis. Additionally, layer arrangements with a dimensionality beyond 2D, which are common in this scenario, motivate the use of stereoscopic displays. We ran a human subject study utilising a Virtual Reality headset to evaluate 2D, 2.5D, and 3D layer arrangements. The study employs six analysis tasks that cover the spectrum of an MLN task taxonomy, from path finding and pattern identification to comparisons between and across layers. We found no clear overall winner. However, we explore the task-to-arrangement space and derive empirical-based recommendations on the effective use of 2D, 2.5D, and 3D layer arrangements for MLNs

5GNOW: Challenging the LTE Design Paradigms of Orthogonality and Synchronicity

Abstract-LTE and LTE-Advanced have been optimized to deliver high bandwidth pipes to wireless users. The transport mechanisms have been tailored to maximize single cell performance by enforcing strict synchronism and orthogonality within a single cell and within a single contiguous frequency band. Various emerging trends reveal major shortcomings of those design criteria: • The fraction of machine-type-communications (MTC) is growing fast. Transmissions of this kind are suffering from the bulky procedures necessary to ensure strict synchronism. • Collaborative schemes have been introduced to boost capacity and coverage (CoMP), and wireless networks are becoming more and more heterogeneous following the non-uniform distribution of users. Tremendous efforts must be spent to collect the gains and to manage such systems under the premise of strict synchronism and orthogonality. • The advent of the Digital Agenda and the introduction of carrier aggregation are forcing the transmission systems to deal with fragmented spectrum. 5GNOW will question the design targets of LTE and LTEAdvanced having these shortcomings in mind. The obedience of LTE and LTE-Advanced to strict synchronism and orthogonality will be challenged. It will develop new PHY and MAC layer concepts being better suited to meet the upcoming needs with respect to service variety and heterogeneous transmission setups. A demonstrator will be built as Proof-of-Concept relying upon continuously growing capabilities of silicon based processing. Wireless transmission networks following the outcomes of 5GNOW will be better suited to meet the manifoldness of services, device classes and transmission setups being present in envisioned future scenarios like smart cities. The integration of systems relying heavily on MTC, e.g. sensor networks, into the communication network will be eased. The per-user experience will be more uniform and satisfying. To ensure this 5GNOW will contribute to upcoming 5G standardization. First and foremost the need for un-tethered telephony and therefore wireless real-time communication has dominated the success of cordless phones, followed by first generation (1G) of cellular communications. Soon, incorporated in 2G, twoway paging implemented by SMS text messaging became the second killer application. With the success of wireless LAN technology (i.e. IEEE 802.11), http internet browsing, and the widespread market adoption of laptop computers internet data connectivity became interesting for anyone, opening up the opportunity for creating a market for the third killer application in 3G, wireless data connectivity. The logical next step has been the shrinkage of the laptop, merging it with the cellular telephone into todays' smartphones, and offering high bandwidth access to wireless users with the world's information at their fingertips everywhere and everytime. This is the scenario of the current 4G generation with the most prominent example LTE-A (Long Term EvolutionAdvanced). Hence, smartphones are, undoubtedly, in the focus of service architectures for future mobile access networks. Current market trends and future projections indicate that smartphone sales will keep growing and overtook conventional phones [TIA's 2009 to constitute now the lion's share of the global phone market: the smartphone has become a mass market device. Keywords-LTE- The next foreseen killer application is the massive wireless connectivity of machines with other machines, referred to as M2M or the Internet of Things (IoT). During the past years a multitude of wireless M2M applications has been explored, e.g. information dissemination in public transport systems or in manufacturing plants. However, fast deployment of M2M through a simple 'plug and play' connection via cellular networks is not a reality and the commercial success has been somewhat limited, yet. The availability of cellular coverage needs to be combined with simplicity of handling, in both software and hardware aspects, i.e. avoiding having to setup and connect as in a ZigBee or WLAN hot-spot but at the same time allowing longer battery life time and cheap devices. These principles can stimulate subscribers to buy M2M sensors and participate in the collection of monitoring data. M2M can be employed by communities (social network) to share monitoring information about cars, homes an

Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey

The existence of representative datasets is a prerequisite of many successful artificial intelligence and machine learning models. However, the subsequent application of these models often involves scenarios that are inadequately represented in the data used for training. The reasons for this are manifold and range from time and cost constraints to ethical considerations. As a consequence, the reliable use of these models, especially in safety-critical applications, is a huge challenge. Leveraging additional, already existing sources of knowledge is key to overcome the limitations of purely data-driven approaches, and eventually to increase the generalization capability of these models. Furthermore, predictions that conform with knowledge are crucial for making trustworthy and safe decisions even in underrepresented scenarios. This work provides an overview of existing techniques and methods in the literature that combine data-based models with existing knowledge. The identified approaches are structured according to the categories integration, extraction and conformity. Special attention is given to applications in the field of autonomous driving

Analytischer Vergleich der neuen dreidimensionalen Fähigkeiten des Flash Player 10 mit gängigen 3D-Engines für ActionScript 3.0 auf Basis des Flash Player 9

Die vorliegende Bachelorarbeit beschäftigt sich mit den neuen nativen Transformationsmöglichkeiten des Flash Players in der Version 10. Zunächst wird ein näherer Blick auf die Geschichte der Technologie Flash und im Besonderen auf dessen Scriptsprache ActionScript geworfen. Im Anschluss werden die konkreten Untersuchungsbeispiele vorgestellt und die Unter-suchungsmethoden erläutert. Auf Grundlage der erhobenen Daten erfolgt am Ende ein qualifiziertes Fazit