Automatic best wireless network selection based on key performance indicators

Introducing cognitive mechanisms at the application layer may lead to the possibility of an automatic selection of the wireless network that can guarantee best perceived experience by the final user. This chapter investigates this approach based on the concept of Quality of Experience (QoE), by introducing the use of application layer parameters, namely Key Performance Indicators (KPIs). KPIs are defined for different traffic types based on experimental data. A model for an ap- plication layer cognitive engine is presented, whose goal is to identify and select, based on KPIs, the best wireless network among available ones. An experimenta- tion for the VoIP case, that foresees the use of the One-way end-to-end delay (OED) and the Mean Opinion Score (MOS) as KPIs is presented. This first implementation of the cognitive engine selects the network that, in that specific instant, offers the best QoE based on real captured data. To our knowledge, this is the first example of a cognitive engine that achieves best QoE in a context of heterogeneous wireless networks

Neural Mechanisms Underlying Paradoxical Performance for Monetary Incentives Are Driven by Loss Aversion

Employers often make payment contingent on performance in order to motivate workers. We used fMRI with a novel incentivized skill task to examine the neural processes underlying behavioral responses to performance-based pay. We found that individuals’ performance increased with increasing incentives; however, very high incentive levels led to the paradoxical consequence of worse performance. Between initial incentive presentation and task execution, striatal activity rapidly switched between activation and deactivation in response to increasing incentives. Critically, decrements in performance and striatal deactivations were directly predicted by an independent measure of behavioral loss aversion. These results suggest that incentives associated with successful task performance are initially encoded as a potential gain; however, when actually performing a task, individuals encode the potential loss that would arise from failure

A Minimal Object Oriented Real-Time Operating System in C++

Most embedded software is currently developed using the C programming language, even though its low level of abstrac- tion requires a lot of effort to the programmer. The C++ language is a better choice because: it raises the level of abstraction; it is strongly typed, so it prevents many com- mon programming mistakes; it can be made as efficient as C through fine-grained customisation of memory mechanisms; it can be easily adapted to domain-specific needs. In ad- dition, recent compilers have grown in maturity and per- formance, and the new standard considerably improves the language by introducing new concepts and an easier syntax. In this paper we present ADOK, a minimal Real-Time Op- erating System entirely written in C++ with the exception of a few lines of assembler code. It directly offers a C++ interface to the developer, and it provides a flexible schedul- ing framework which allows the developer to customise the scheduling to its needs. In particular, we implement a two- level scheduler based on Earliest Deadline First, the Stack Resource Policy protocol for sharing resources and support for mode changes. We demonstrate through examples and a small case-study that ADOK can substantially improve productivity without sacrificing on performance

Dispersal of larval and juvenile seabream: Implications for Mediterranean marine protected areas

In the marine context, information about dispersal is essential for the design of networks of marine protected areas (MPAs). Generally, most of the dispersal of demersal fishes is thought to be driven by the transport of eggs and larvae in currents, with the potential contribution of dispersal in later life stages relatively minimal.Using otolith chemistry analyses, we estimate dispersal patterns across a spatial scale of approximately 180. km at both propagule (i.e. eggs and larvae) and juvenile (i.e. between settlement and recruitment) stages of a Mediterranean coastal fishery species, the two-banded seabream Diplodus vulgaris. We detected three major natal sources of propagules replenishing local populations in the entire study area, suggesting that propagule dispersal distance extends to at least 90. km. For the juvenile stage, we detected dispersal of up to 165. km. Our work highlights the surprising and significant role of dispersal during the juvenile life stages as an important mechanism connecting populations. Such new insights are crucial for creating effective management strategies (e.g. MPAs and MPA networks) and to gain support from policymakers and stakeholders, highlighting that MPA benefits can extend well beyond MPA borders, and not only via dispersal of eggs and larvae, but also through movement by juveniles

Fundamental Limits of Low-Density Spreading NOMA with Fading

Spectral efficiency of low-density spreading non-orthogonal multiple access channels in the presence of fading is derived for linear detection with independent decoding as well as optimum decoding. The large system limit, where both the number of users and number of signal dimensions grow with fixed ratio, called load, is considered. In the case of optimum decoding, it is found that low-density spreading underperforms dense spreading for all loads. Conversely, linear detection is characterized by different behaviors in the underloaded vs. overloaded regimes. In particular, it is shown that spectral efficiency changes smoothly as load increases. However, in the overloaded regime, the spectral efficiency of low- density spreading is higher than that of dense spreading

How immunosenescence and inflammaging may contribute to hyperinflammatory syndrome in COVID-19

Aging is characterized by the dynamic remodeling of the immune system designated “immunosenescence,” and is associated with altered hematopoiesis, thymic involution, and lifelong immune stimulation by multitudinous chronic stressors, including the cytomegalovirus (CMV). Such alterations may contribute to a lowered proportion of naïve T-cells and to reduced diversity of the T-cell repertoire. In the peripheral circulation, a shift occurs towards accumulations of T and B-cell populations with memory phenotypes, and to accumulation of putatively senescent and exhausted immune cells. The aging-related accumulations of functionally exhausted memory T lymphocytes, commonly secreting pro-inflammatory cytokines, together with mediators and factors of the innate immune system, are considered to contribute to the low-grade inflammation (inflammaging) often observed in elderly people. These senescent immune cells not only secrete inflammatory mediators, but are also able to negatively modulate their environments. In this review, we give a short summary of the ways that immunosenescence, inflammaging, and CMV infection may cause insufficient immune responses, contribute to the establishment of the hyperinflammatory syndrome and impact the severity of the coronavirus disease 2019 (COVID-19) in elderly people