Abstract

Abstract
We study the impact of random pinning fields on the emergence of synchrony in the Kuramoto model on complete graphs and uncorrelated random complex networks. We consider random fields with uniformly distributed directions and homogeneous and heterogeneous (Gaussian) field magnitude distribution. In our analysis, we apply the Ott-Antonsen method and the annealed-network approximation to find the critical behavior of the order parameter. In the case of homogeneous fields, we find a tricritical point above which a second-order phase transition gives place to a first-order phase transition when the network is either fully connected or scale-free with the degree exponent gamma > 5. Interestingly, for scale-free networks with 2 < gamma <= 5, the phase transition is of second-order at any field magnitude, except for degree distributions with gamma = 3 when the transition is of infinite order at K-c = 0 independent of the random fields. Contrary to the Ising model, even strong Gaussian random fields do not suppress the second-order phase transition in both complete graphs and scale-free networks, although the fields increase the critical coupling for gamma > 3. Our simulations support these analytical results.

Abstract
In wireless power transfer systems, if the driver is not capable of dynamically adapt its own switching frequency, small environmental changes or even slight deviations in circuit parameters may prevent the complete system from working properly when the optimal resonance frequency moves towards new values. In this paper, we propose an adaptive system suitable for underwater wireless applications in sea water. The output voltage is regulated using the wireless power link, avoiding the need for additional wireless interfaces. Our complete system includes the power driver, coupling coils, rectifier, and two micro-controllers. The regulation is accomplished by digital load modulation, observable at the input by means of current sensing at the power supply. Experimental results demonstrate a class-D driver with a series-series resonant topology working in saline water, delivering power between 1.6 and 2.4 W. The regulated voltage is 7.5 V with error less than 7.2 % in the load range of 30 to 37 Omega and 6 to 10 V power supply variation. The switching frequency is adjusted within the range of 7 kHz deviation (-7%).

Abstract
Deductive verification tools typically rely on the conversion of code to a single-assignment (SA) form. In this paper we formalize program verification based on the translation of While programs annotated with loop invariants into a dynamic single-assignment language with a dedicated iterating construct, and the subsequent generation of compact, indeed linear-size, verification conditions. Soundness and completeness proofs are given for the entire workflow, including the translation of annotated programs to SA form. The formalization is based on a program logic that we show to be adaptation-complete. Although this important property has not, as far as we know, been established for any existing program verification tool, we believe that adaptation-completeness is one of the major motivations for the use of SA form as an intermediate language. Our results here show that indeed this allows for the tools to achieve the maximum degree of adaptation when handling subprograms.

Abstract
The news industry has gone through seismic shifts in the past decade with digital content and social media completely redefining how people consume news. Readers check for accurate fresh news from multiple sources throughout the day using dedicated apps or social media on their smartphones and tablets. At the same time, news publishers rely more and more on social networks and citizen journalism as a frontline to breaking news. In this new era of fast-flowing instant news delivery and consumption, publishers and aggregators have to overcome a great number of challenges. These include the verification or assessment of a source’s reliability; the integration of news with other sources of information; real-time processing of both news content and social streams in multiple languages, in different formats and in high volumes; deduplication; entity detection and disambiguation; automatic summarization; and news recommendation. Although Information Retrieval (IR) applied to news has been a popular research area for decades, fresh approaches are needed due to the changing type and volume of media content available and the way people consume this content. The goal of this workshop is to stimulate discussion around new and powerful uses of IR applied to news sources and the intersection of multiple IR tasks to solve real user problems. To promote research efforts in this area, we released a new dataset consisting of one million news articles to the research community and introduced a data challenge track as part of the workshop. © Springer International Publishing Switzerland 2016.

Abstract
This paper proposes a self-adaptive sampling scheme for WSNs, which aims at capturing accurately the behavior of the physical parameters of interest in each specific WSN context yet reducing the overhead in terms of sensing events. The sampling scheme relies on a set of low-complexity rules capable of auto-regulate the sensing frequency in accordance with each parameter behavior. As proof-of-concept, based on real environmental datasets, we provide statistical indicators illustrating the added value of the proposed sampling scheme in reducing sensing events without compromising the estimation accuracy of physical phenomena.