Dissolved organic matter molecular composition and concentrations from a large scale mesocosm study KOSMOS 2013 Kristineberg) on ocean acidification

Marine dissolved organic matter (DOM) represents one of the largest active carbon reservoirs on Earth. Changes in pool size or composition could have major impacts on the global carbon cycle. Ocean acidification is a potential driver for these changes because it influences marine primary production and heterotrophic respiration. Here we show that ocean acidification as expected for a 'business-as-usual' emission scenario in the year 2100 (900 µatm) does not affect the DOM pool with respect to its size and molecular composition. We applied ultrahigh-resolution mass spectrometry to monitor the production and turnover of 7,360 distinct molecular DOM features in an unprecedented long-term mesocosm study in a Swedish Fjord, covering a full cycle of marine production. DOM concentration and molecular composition did not differ significantly between present-day and year 2100 CO2 levels. Our findings are likely applicable to other coastal and productive marine ecosystems in general.

Wave height (regular and irregular waves) reduction in 2m water depth over a 40-m-long salt marsh test section in a large scale laboratory flume

Coastal communities around the world face increasing risk from flooding as a result of rising sea level, increasing storminess, and land subsidence. Salt marshes can act as natural buffer zones, providing protection from waves during storms. However, the effectiveness of marshes in protecting the coastline during extreme events when water levels and waves are highest is poorly understood. Here, we experimentally assess wave dissipation under storm surge conditions in a 300-m-long wave flume that contains a transplanted section of natural salt marsh. We find that the presence of marsh vegetation causes considerable wave attenuation, even when water levels and waves are high. From a comparison with experiments without vegetation, we estimate that up to 60% of observed wave reduction is attributed to vegetation. We also find that although waves progressively flatten and break vegetation stems and thereby reduce dissipation, the marsh substrate remained remarkably stable and resistant to surface erosion under all conditions.The effectiveness of storm wave dissipation and the resilience of tidal marshes even at extreme conditions suggest that salt marsh ecosystems can be a valuable component of coastal protection schemes.

Power output fluctuations in large scale PV plants: one year observations with one second resolution and a derived analytic model

The variable nature of the irradiance can produce significant fluctuations in the power generated by large grid-connected photovoltaic (PV) plants. Experimental 1 s data were collected throughout a year from six PV plants, 18 MWp in total. Then, the dependence of short (below 10 min) power fluctuation on PV plant size has been investigated. The analysis focuses on the study of fluctuation frequency as well as the maximum fluctuation value registered. An analytic model able to describe the frequency of a given fluctuation for a certain day is proposed

An Experimental Platform for large-scale research facing FI-IoT scenarios

Providing experimental facilities for the Internet of Things (IoT) world is of paramount importance to materialise the Future Internet (FI) vision. The level of maturity achieved at the networking level in Sensor and Actuator networks (SAN) justifies the increasing demand on the research community to shift IoT testbed facilities from the network to the service and information management areas. In this paper we present an Experimental Platform fulfilling these needs by: integrating heterogeneous SAN infrastructures in a homogeneous way; providing mechanisms to handle information, and facilitating the development of experimental services. It has already been used to deploy applications in three different field trials: smart metering, smart places and environmental monitoring and it will be one of the components over which the SmartSantander project, that targets a large-scale IoT experimental facility, will rely on

A big data platform for large scale event processing

To date, big data applications have focused on the store-and-process paradigm. In this paper we describe an initiative to deal with big data applications for continuous streams of events. In many emerging applications, the volume of data being streamed is so large that the traditional ‘store-then-process’ paradigm is either not suitable or too inefficient. Moreover, soft-real time requirements might severely limit the engineering solutions. Many scenarios fit this description. In network security for cloud data centres, for instance, very high volumes of IP packets and events from sensors at firewalls, network switches and routers and servers need to be analyzed and should detect attacks in minimal time, in order to limit the effect of the malicious activity over the IT infrastructure. Similarly, in the fraud department of a credit card company, payment requests should be processed online and need to be processed as quickly as possible in order to provide meaningful results in real-time. An ideal system would detect fraud during the authorization process that lasts hundreds of milliseconds and deny the payment authorization, minimizing the damage to the user and the credit card company.

Semantic evaluation at large scale (SEALS)

This paper describes the main goals and outcomes of the EU-funded Framework 7 project entitled Semantic Evaluation at Large Scale (SEALS). The growth and success of the Semantic Web is built upon a wide range of Semantic technologies from ontology engineering tools through to semantic web service discovery and semantic search. The evaluation of such technologies ? and, indeed, assessments of their mutual compatibility ? is critical for their sustained improvement and adoption. The SEALS project is creating an open and sustainable platform on which all aspects of an evaluation can be hosted and executed and has been designed to accommodate most technology types. It is envisaged that the platform will become the de facto repository of test datasets and will allow anyone to organise, execute and store the results of technology evaluations free of charge and without corporate bias. The demonstration will show how individual tools can be prepared for evaluation, uploaded to the platform, evaluated according to some criteria and the subsequent results viewed. In addition, the demonstration will show the flexibility and power of the SEALS Platform for evaluation organisers by highlighting some of the key technologies used.

Ventilation system design and large scale fire tests

The design, construction and operation of the tunnels of M-30, the major ring road in the city of Madrid (Spain), represent a very interesting project in wich a wide variety of situations -geometrical, topographical, etc.- had to be covered, in variable conditions of traffic. For that reasons, the M-30 project is a remarkable technical challenge, which, after its completion, turned into an international reference. From the "design for safety" perspective, a holistic approach has been used to deal with new technologies, integration of systems and development of the procedures to reach the maximum level. However, one of the primary goals has been to achieve reasonable homogeneity characteristics which can permit operate a netword of tunels as one only infraestructure. In the case of the ventilation system the mentioned goals have implied innovative solutions and coordination efforts of great interest. Consequently, this paper describes the principal ideas underlying the conceptual solution developed focusing on the principal peculiarities of the project.

Large-scale testing of proficiency in English: Back to multiple choice?

The paper analyses whether that a properly designed multiple choice test can discriminate with a high level of accuracy if a student in our context has reached a B2 level according to the CEFRL.

Use of Feynman diagrams in large-scale neural networks with nonlinear behaviour

A new proposal to the study of large-scale neural networks is reported. It is based on the use of similar graphs to the Feynman diagrams. A first general theory is presented and some interpretations are given. A propagator, based on the Green's function of the neuron, is the basis of the method. Application to a simple case is reported.

Analysis of large-scale digital optical neural networks by Feynman diagrams

A new method to study large scale neural networks is presented in this paper. The basis is the use of Feynman- like diagrams. These diagrams allow the analysis of collective and cooperative phenomena with a similar methodology to the employed in the Many Body Problem. The proposed method is applied to a very simple structure composed by an string of neurons with interaction among them. It is shown that a new behavior appears at the end of the row. This behavior is different to the initial dynamics of a single cell. When a feedback is present, as in the case of the hippocampus, this situation becomes more complex with a whole set of new frequencies, different from the proper frequencies of the individual neurons. Application to an optical neural network is reported.