Distributed parallelization of greedy Mobile Network Optimization algorithms

The Mobile Network Optimization (MNO) technologies have advanced at a tremendous pace in recent years. And the Dynamic Network Optimization (DNO) concept emerged years ago, aimed to continuously optimize the network in response to variations in network traffic and conditions. Yet, DNO development is still at its infancy, mainly hindered by a significant bottleneck of the lengthy optimization runtime. This paper identifies parallelism in greedy MNO algorithms and presents an advanced distributed parallel solution. The solution is designed, implemented and applied to real-life projects whose results yield a significant, highly scalable and nearly linear speedup up to 6.9 and 14.5 on distributed 8-core and 16-core systems respectively. Meanwhile, optimization outputs exhibit self-consistency and high precision compared to their sequential counterpart. This is a milestone in realizing the DNO. Further, the techniques may be applied to similar greedy optimization algorithm based applications.

Asynchronous distributed parallelization of mobile network optimization algorithms

It has been years since the introduction of the Dynamic Network Optimization (DNO) concept, yet the DNO development is still at its infant stage, largely due to a lack of breakthrough in minimizing the lengthy optimization runtime. Our previous work, a distributed parallel solution, has achieved a significant speed gain. To cater for the increased optimization complexity pressed by the uptake of smartphones and tablets, however, this paper examines the potential areas for further improvement and presents a novel asynchronous distributed parallel design that minimizes the inter-process communications. The new approach is implemented and applied to real-life projects whose results demonstrate an augmented acceleration of 7.5 times on a 16-core distributed system compared to 6.1 of our previous solution. Moreover, there is no degradation in the optimization outcome. This is a solid sprint towards the realization of DNO.

Shared cognition in childhood anxiety: interpretation bias in preschool children and their parents

Although interpretation bias has been associated with the development and/or maintenance of childhood anxiety, its origins remain unclear. The present study is the first to examine intergenerational transmission of this bias from parents to their preschool-aged children via the verbal information pathway. A community sample of fifty parent–child pairs was recruited. Parents completed measures of their own trait anxiety and interpretation bias, their child’s anxiety symptoms, and a written story-stem measure, to capture the way parents tell their children stories. Interpretation bias was assessed in preschool-aged children (aged between 2 years 7 months and 5 years 8 months) using an extended story-stem paradigm. Young children’s interpretation bias was not significantly associated with their own anxiety symptoms. Neither was there evidence for a significant association between parent and child interpretation bias. However, parents who reported they would tell their child one or more threatening story endings in the written story-stem task had significantly higher anxiety than those who did not include any threatening story endings. In turn, children whose parents did not include any threatening endings in their written stories had significantly lower threat interpretations on the child story-stem paradigm, compared to those with parents who included at least one threatening story ending. The results suggest that parental verbal information could play a role in the development of interpretation bias in young children.

An optimized auditory P300 BCI based on spatially distributed sound in different voices

In this paper, a new paradigm is presented, to improve the performance of audio-based P300 Brain-computer interfaces (BCIs), by using spatially distributed natural sound stimuli. The new paradigm was compared to a conventional paradigm using spatially distributed sound to demonstrate the performance of this new paradigm. The results show that the new paradigm enlarged the N200 and P300 components, and yielded significantly better BCI performance than the conventional paradigm.

Using Distributed Temperature Sensing to monitor field scale dynamics of ground surface temperature and related substrate heat flux

We present one of the first studies of the use of Distributed Temperature Sensing (DTS) along fibre-optic cables to purposely monitor spatial and temporal variations in ground surface temperature (GST) and soil temperature, and provide an estimate of the heat flux at the base of the canopy layer and in the soil. Our field site was at a groundwater-fed wet meadow in the Netherlands covered by a canopy layer (between 0-0.5 m thickness) consisting of grass and sedges. At this site, we ran a single cable across the surface in parallel 40 m sections spaced by 2 m, to create a 40×40 m monitoring field for GST. We also buried a short length (≈10 m) of cable to depth of 0.1±0.02 m to measure soil temperature. We monitored the temperature along the entire cable continuously over a two-day period and captured the diurnal course of GST, and how it was affected by rainfall and canopy structure. The diurnal GST range, as observed by the DTS system, varied between 20.94 and 35.08◦C; precipitation events acted to suppress the range of GST. The spatial distribution of GST correlated with canopy vegetation height during both day and night. Using estimates of thermal inertia, combined with a harmonic analysis of GST and soil temperature, substrate and soil-heat fluxes were determined. Our observations demonstrate how the use of DTS shows great promise in better characterising area-average substrate/soil heat flux, their spatiotemporal variability, and how this variability is affected by canopy structure. The DTS system is able to provide a much richer data set than could be obtained from point temperature sensors. Furthermore, substrate heat fluxes derived from GST measurements may be able to provide improved closure of the land surface energy balance in micrometeorological field studies. This will enhance our understanding of how hydrometeorological processes interact with near-surface heat fluxes.

Executive control in bilinguals: a concise review on fMRI studies

The investigation of bilingualism and cognition has been enriched by recent developments in functional magnetic resonance imaging (fMRI). Extending how bilingual experience shapes cognition, this review examines recent fMRI studies adopting executive control tasks with minimal or no linguistic demands. Across a range of studies with divergent ages and language pairs spoken by bilinguals, brain regions supporting executive control significantly overlap with brain regions recruited for language control (Abutalebi & Green, this issue). Furthermore, limited but emerging studies on resting-state networks are addressed, which suggest more coherent spatially distributed functional connectivity in bilinguals. Given the dynamic nature of bilingual experience, it is essential to consider both task-related functional networks (externally-driven engagement), and resting-state networks, such as default mode network (internal control). Both types of networks are important elements of bilingual language control, which relies on domain-general executive control.

Cognition and anxiety are regulated by thyroid hormone signaling

Anxiety and cognition are both linked to deficits in thyroid hormone concentrations in humans and in rodent models. Both processes have also been shown to be affected by the loss of the thyroid hormone receptors (TR) or by mutant transgenic TRs. Specifically, the unbalanced action of the unliganded TRα1 is thought to be important in the memory deficit and extreme anxiety seen in transgenic mice. The contribution of TRβ is less well defined and the molecular mechanisms that underlie these deficits are also unknown. We review the literature that demonstrates the importance of the thyroid hormone (TH) and the TR in these processes and focus on the mechanisms, in particular adult hippocampal neurogenesis in the dentate gyrus, that might be important in mediating both state anxiety and cognition by thyroid hormone.

Distributed access control and privacy for the internet of me

This article presents an experimental scalable message driven IoT and its security architecture based on Decentralized Information Flow Control. The system uses a gateway that exports SoA (REST) interfaces to the internet simplifying external applications whereas uses DIFC and asynchronous messaging within the home environment.