Diatom distribution in sediments of the Peruvian coastal upwelling

Two shelf and upper-slope sites (681 and 686) near present cores of active coastal upwelling on the Peruvian margin were sampled continuously at 7.5 cm intervals down to approximately 25 meters below the seafloor (mbsf). Sedimentary structures were subdivided into homogeneous/bioturbated, laminated, and laminated-varved intervals. Diatom analysis and statistical treatment of data revealed almost persistent upwelling over the last 400,000 yr, with slightly increased upwelling during oxygen-isotope Stages 3, 5, 7, and 8 that resulted in anoxic bottom-water conditions and deposition of laminated/undisturbed primary sedimentary structures.

Zooplankton distribution and migration in low-oxygen modewater eddies

The eastern tropical North Atlantic (ETNA) features a mesopelagic oxygen minimum zone (OMZ) at approximately 300-600 m depth. Here, oxygen concentrations rarely fall below 40 µmol O2 kg-1, but are expected to decline under future projections of global warming. The recent discovery of mesoscale eddies that harbour a shallow suboxic (<5 µmol O2 kg-1) OMZ just below the mixed layer could serve to identify zooplankton groups that may be negatively or positively affected by on-going ocean deoxygenation. In spring 2014, a detailed survey of a suboxic anticyclonic modewater eddy (ACME) was carried out near the Cape Verde Ocean Observatory (CVOO), combining acoustic and optical profiling methods with stratified multinet hauls and hydrography. The multinet data revealed that the eddy was characterized by an approximately 1.5-fold increase in total area-integrated zooplankton abundance. At nighttime, when a large proportion of acoustic scatterers is ascending into the upper 150 m, a drastic reduction in mean volume backscattering (Sv, shipboard ADCP, 75kHz) within the shallow OMZ of the eddy was evident compared to the nighttime distribution outside the eddy. Acoustic scatterers were avoiding the depth range between about 85 to 120 m, where oxygen concentrations were lower than approximately 20 µmol O2 kg-1, indicating habitat compression to the oxygenated surface layer. This observation is confirmed by time-series observations of a moored ADCP (upward looking, 300kHz) during an ACME transit at the CVOO mooring in 2010. Nevertheless, part of the diurnal vertical migration (DVM) from the surface layer to the mesopelagic continued through the shallow OMZ. Based upon vertically stratified multinet hauls, Underwater Vision Profiler (UVP5) and ADCP data, four strategies have been identified to be followed by zooplankton in response to the eddy OMZ: i) shallow OMZ avoidance and compression at the surface (e.g. most calanoid copepods, euphausiids), ii) migration to the shallow OMZ core during daytime, but paying O2 debt at the surface at nighttime (e.g. siphonophores, Oncaea spp., eucalanoid copepods), iii) residing in the shallow OMZ day and night (e.g. ostracods, polychaetes), and iv) DVM through the shallow OMZ from deeper oxygenated depths to the surface and back. For strategy i), ii) and iv), compression of the habitable volume in the surface may increase prey-predator encounter rates, rendering zooplankton and micronekton more vulnerable to predation and potentially making the eddy surface a foraging hotspot for higher trophic levels. With respect to long-term effects of ocean deoxygenation, we expect avoidance of the mesopelagic OMZ to set in if oxygen levels decline below approximately 20 µmol O2 kg-1. This may result in a positive feedback on the OMZ oxygen consumption rates, since zooplankton and micronekton respiration within the OMZ as well as active flux of dissolved and particulate organic matter into the OMZ will decline.

Using ground-penetrating radar, topography and classification of vegetation to model the sediment and active layer thickness in a periglacial lake catchment, Western Greenland, link to shapefiles

The geometries of a catchment constitute the basis for distributed physically based numerical modeling of different geoscientific disciplines. In this paper results from ground-penetrating radar (GPR) measurements, in terms of a 3D model of total sediment thickness and active layer thickness in a periglacial catchment in western Greenland, is presented. Using the topography, thickness and distribution of sediments is calculated. Vegetation classification and GPR measurements are used to scale active layer thickness from local measurements to catchment scale models. Annual maximum active layer thickness varies from 0.3 m in wetlands to 2.0 m in barren areas and areas of exposed bedrock. Maximum sediment thickness is estimated to be 12.3 m in the major valleys of the catchment. A method to correlate surface vegetation with active layer thickness is also presented. By using relatively simple methods, such as probing and vegetation classification, it is possible to upscale local point measurements to catchment scale models, in areas where the upper subsurface is relatively homogenous. The resulting spatial model of active layer thickness can be used in combination with the sediment model as a geometrical input to further studies of subsurface mass-transport and hydrological flow paths in the periglacial catchment through numerical modelling.

(Fig 2, page 399), Distribution of Fe and Mn in ferromanganese nodules of the Eningi-Lampi Lake, Russia

The distribution of Mn and Fe in water, sediments, hydroxide nodules and crusts of Eningi-Lampi ore-bearing lake is regular, and concordant from the source to the areas of accumulation of these components. Mn-Fe hydroxide nodules and crusts occur at the water-sediment interface, and more rarely in the upper (0-5 cm) film of brown watery mud. The leading role in the formation of Mn-Fe nodules and crusts is played by the chemosorption and auto-catalytic oxidation in the course of interaction of component-bearing solutions with active surfaces. This is considered to be the basic process for the model of ferromanganese ore formation in recent basins. Despite the differences in the physico-geographical and geochemical characteristics of lakes, mediterranean seas and oceans, the formation of ferromanganese hydroxide nodules and crusts in these basins may be explained by this model.

Distribution System of China's Industrial Clusters: Case Study of Yiwu China Commodity City

This paper discusses the issue of upgrading industrial clusters from the perspective of external linkages. It is taken for granted that in most developing countries, due to the limited domestic market and poor traditional commercial networks, industrial clusters are able to upgrade only when they are involved in global value chains. However, the rise of China’s industrial clusters challenges this view. Historically, China has had a lot of industrial clusters with their own traditional commercial networks. This fact combined with its huge population resulted in the formation of a unique external linage to China’s industrial clusters after the socialist planning period ended. In concrete terms, since the 1980s, a traditional commercial institution . the transaction market . began to appear in most clusters. These markets within the clusters get connected to those in the cities due to interaction between traditional merchants and local governments. This has resulted in the formation of a powerful market network-based distribution system which has played a crucial role for China’s industrial clusters in responding to exploding domestic demand. This paper explains these features in detail, using Yiwu China Commodity City as a case study.

How are global value chains fragmented and extended in China's domestic production networks?

Global value chains are supported not only directly by domestic regions that export goods and services to the world market, but also indirectly by other domestic regions that provide parts, components, and intermediate services to final exporting regions. In order to better understand the nature of a country’s position and degree of participation in global value chains, we need to more fully examine the role of individual domestic regions. Understanding the domestic components of global supply chains is especially important for large developing countries like China and India, where there may be large variations in economic scale and development between domestic regions. This paper proposes a new framework for measuring domestic linkages to global value chains. This framework measures domestic linkages by endogenously embedding a country’s domestic interregional input-output (IO) table in an international IO model. Using this framework, we can more clearly describe how global production is fragmented and extended through linkages across a country’s domestic regions. This framework will also enable us to estimate how value added is created and distributed in both domestic and international segments of global value chains. For examining the validity and usefulness of this new approach, some numerical results are presented and discussed based on the 2007 Chinese interregional IO table, China customs statistics at the provincial level, and World Input-Output Tables (WIOTs).

A simplified energy consumption model for fiber-based Next Generation Access Networks

ICTs account nowadays for 2% of total carbon emissions. However, in a time when strict measures to reduce energyconsumption in all the industrial and services sectors are required, the ICT sector faces an increase in services and bandwidth demand. The deployment of NextGenerationNetworks (NGN) will be the answer to this new demand and specifically, the NextGenerationAccessNetworks (NGANs) will provide higher bandwidth access to users. Several policy and cost analysis are being carried out to understand the risks and opportunities of new deployments, though the question of which is the role of energyconsumption in NGANs seems off the table. Thus, this paper proposes amodel to analyze the energyconsumption of the main fiber-based NGAN architectures, i.e. Fiber To The House (FTTH) in both Passive Optical Network (PON) and Point-to-Point (PtP) variations, and FTTx/VDSL. The aim of this analysis is to provide deeper insight on the impact of new deployments on the energyconsumption of the ICT sector and the effects of energyconsumption on the life-cycle cost of NGANs. The paper presents also an energyconsumption comparison of the presented architectures, particularized in the specific geographic and demographic distribution of users of Spain, but easily extendable to other countries.

Li distribution characterization in Li-ion batteries positive electrodes containing LixNi0.8Co0.15Al0.05O2 secondary particles

The elemental distribution of as-received (non-charged) and charged Li-ion battery positive electrodes containing LixNi0.8Co0.15Al0.05O2 (0.75 ? x ? 1.0) microparticles as active material is characterized by combining μ-PIXE and μ-PIGE techniques. PIGE measurements evidence that the Li distribution is inhomogeneous (existence of Li-rich and Li-depleted regions) in as-received electrodes corresponding with the distribution of secondary particles but it is homogeneous within the studied individual secondary micro-particles. The dependence of the Li distribution on electrode thickness and on charging conditions is characterized by measuring the Li distribution maps in specifically fabricated cross-sectional samples. These data show that decreasing the electrode thickness down to 35 μm and charging the batteries at slow rate give rise to more homogeneous Li depth profiles.

Neural network controller for active demand side management with PV energy in the residential sector

In this paper, we describe the development of a control system for Demand-Side Management in the residential sector with Distributed Generation. The electrical system under study incorporates local PV energy generation, an electricity storage system, connection to the grid and a home automation system. The distributed control system is composed of two modules: a scheduler and a coordinator, both implemented with neural networks. The control system enhances the local energy performance, scheduling the tasks demanded by the user and maximizing the use of local generation.

QKD in standard optical telecommunications networks

To perform Quantum Key Distribution, the mastering of the extremely weak signals carried by the quantum channel is required. Transporting these signals without disturbance is customarily done by isolating the quantum channel from any noise sources using a dedicated physical channel. However, to really profit from this technology, a full integration with conventional network technologies would be highly desirable. Trying to use single photon signals with others that carry an average power many orders of magnitude bigger while sharing as much infrastructure with a conventional network as possible brings obvious problems. The purpose of the present paper is to report our efforts in researching the limits of the integration of QKD in modern optical networks scenarios. We have built a full metropolitan area network testbed comprising a backbone and an access network. The emphasis is put in using as much as possible the same industrial grade technology that is actually used in already installed networks, in order to understand the throughput, limits and cost of deploying QKD in a real network.

A Simplified Energy Consumption Model for Fibre-Based Next Generation Access Networks

Presentación realizada en el PhD Seminar del ITS 2011 en Budapest. ICTs (Information and Communication Technologies) currently account for 2% of total carbon emissions. However, although modern standards require strict measures to reduce energy consumption across all industrial and services sectors, the ICT sector also faces an increase in services and bandwidth demand. The deployment of Next Generation Networks (NGN) will be the answer to this new demand; more specifically, Next Generation Access Networks (NGANs) will provide higher bandwidth access to users. Several policy and cost analyses are being carried out to understand the risks and opportunities of new deployments, but the question of what role energy consumption plays in NGANs seems off the table. Thus, this paper proposes a model to analyse the energy consumption of the main fibre-based NGAN architectures: Fibre To The House (FTTH), in both Passive Optical Network (PON) and Point-to-Point (PtP) variations, and FTTx/VDSL. The aim of this analysis is to provide deeper insight on the impact of new deployments on the energy consumption of the ICT sector and the effects of energy consumption on the life-cycle cost of NGANs. The paper also presents an energy consumption comparison of the presented architectures, particularised to the specific geographic and demographic distribution of users of Spain but easily extendable to other countries.

Modeling the evolution of item rating networks using time-domain preferential attachment

The understanding of the structure and dynamics of the intricate network of connections among people that consumes products through Internet appears as an extremely useful asset in order to study emergent properties related to social behavior. This knowledge could be useful, for example, to improve the performance of personal recommendation algorithms. In this contribution, we analyzed five-year records of movie-rating transactions provided by Netflix, a movie rental platform where users rate movies from an online catalog. This dataset can be studied as a bipartite user-item network whose structure evolves in time. Even though several topological properties from subsets of this bipartite network have been reported with a model that combines random and preferential attachment mechanisms [Beguerisse Díaz et al., 2010], there are still many aspects worth to be explored, as they are connected to relevant phenomena underlying the evolution of the network. In this work, we test the hypothesis that bursty human behavior is essential in order to describe how a bipartite user-item network evolves in time. To that end, we propose a novel model that combines, for user nodes, a network growth prescription based on a preferential attachment mechanism acting not only in the topological domain (i.e. based on node degrees) but also in time domain. In the case of items, the model mixes degree preferential attachment and random selection. With these ingredients, the model is not only able to reproduce the asymptotic degree distribution, but also shows an excellent agreement with the Netflix data in several time-dependent topological properties.

Maximizing the number of polychronous groups in spiking networks

In this paper we investigate the effect of biasing the axonal connection delay values in the number of polychronous groups produced for a spiking neuron network model. We use an estimation of distribution algorithm (EDA) that learns tree models to search for optimal delay configurations. Our results indicate that the introduced approach can be used to considerably increase the number of such groups.

The Influence of Communication Range on Connectivity for Resilient Wireless Sensor Networks Using a Probabilistic Approach.

Wireless sensor networks (WSNs) consist of thousands of nodes that need to communicate with each other. However, it is possible that some nodes are isolated from other nodes due to limited communication range. This paper focuses on the influence of communication range on the probability that all nodes are connected under two conditions, respectively: (1) all nodes have the same communication range, and (2) communication range of each node is a random variable. In the former case, this work proves that, for 0menor queepsmenor quee^(-1) , if the probability of the network being connected is 0.36eps , by means of increasing communication range by constant C(eps) , the probability of network being connected is at least 1-eps. Explicit function C(eps) is given. It turns out that, once the network is connected, it also makes the WSNs resilient against nodes failure. In the latter case, this paper proposes that the network connection probability is modeled as Cox process. The change of network connection probability with respect to distribution parameters and resilience performance is presented. Finally, a method to decide the distribution parameters of node communication range in order to satisfy a given network connection probability is developed.

Multiple attractors, long chaotic transients, and failure in small-world networks of excitable neurons.

We study the dynamical states of a small-world network of recurrently coupled excitable neurons, through both numerical and analytical methods. The dynamics of this system depend mostly on both the number of long-range connections or ?shortcuts?, and the delay associated with neuronal interactions. We find that persistent activity emerges at low density of shortcuts, and that the system undergoes a transition to failure as their density reaches a critical value. The state of persistent activity below this transition consists of multiple stable periodic attractors, whose number increases at least as fast as the number of neurons in the network. At large shortcut density and for long enough delays the network dynamics exhibit exceedingly long chaotic transients, whose failure times follow a stretched exponential distribution. We show that this functional form arises for the ensemble-averaged activity if the failure time for each individual network realization is exponen- tially distributed