2017, Piniewski, Mikołaj, Szcześniak, Mateusz, Kardel, Ignacy

There is considerable concern that the water resources of Central and Eastern Europe region can be adversely affected by climate change. Projections of future water balance and streamflow conditions can be obtained by forcing hydrological models with the output from climate models. In this study, we employed the SWAT hydrological model driven with an ensemble of nine bias-corrected EURO-CORDEX climate simulations to generate future hydrological projections for the Vistula and Odra basins in two future horizons (2024–2050 and 2074–2100) under two Representative Concentration Pathways (RCPs). The data set consists of three parts: (1) model inputs; (2) raw model outputs; (3) aggregated model outputs. The first one allows the users to reproduce the outputs or to create the new ones. The second one contains the simulated time series of 10 variables simulated by SWAT: precipitation, snow melt, potential evapotranspiration, actual evapotranspiration, soil water content, percolation, surface runoff, baseflow, water yield and streamflow. The third one consists of the multi-model ensemble statistics of the relative changes in mean seasonal and annual variables developed in a GIS format. The data set should be of interest of climate impact scientists, water managers and water-sector policy makers. In any case, it should be noted that projections included in this data set are associated with high uncertainties explained in this data descriptor paper.

2014, Vitolo, Claudia, Elkhatib, Yehia, Reusser, Dominik, Macleod, Christopher J.A., Buytaert, Wouter

Recent evolutions in computing science and web technology provide the environmental community with continuously expanding resources for data collection and analysis that pose unprecedented challenges to the design of analysis methods, workflows, and interaction with data sets. In the light of the recent UK Research Council funded Environmental Virtual Observatory pilot project, this paper gives an overview of currently available implementations related to web-based technologies for processing large and heterogeneous datasets and discuss their relevance within the context of environmental data processing, simulation and prediction. We found that, the processing of the simple datasets used in the pilot proved to be relatively straightforward using a combination of R, RPy2, PyWPS and PostgreSQL. However, the use of NoSQL databases and more versatile frameworks such as OGC standard based implementations may provide a wider and more flexible set of features that particularly facilitate working with larger volumes and more heterogeneous data sources.

2018, Lorenz-Spreen, Philipp, Wolf, Frederik, Braun, Jonas, Ghoshal, Gourab, Djurdjevac Conrad, Nataša, Hövel, Philipp

Background: Hashtags are widely used for communication in online media. As a condensed version of information, they characterize topics and discussions. For their analysis, we apply methods from network science and propose novel tools for tracing their dynamics in time-dependent data. The observations are characterized by bursty behaviors in the increases and decreases of hashtag usage. These features can be reproduced with a novel model of dynamic rankings. Hashtag communities in time: We build temporal and weighted co-occurrence networks from hashtags. On static snapshots, we infer the community structure using customized methods. On temporal networks, we solve the bipartite matching problem of detected communities at subsequent timesteps by taking into account higher-order memory. This results in a matching protocol that is robust toward temporal fluctuations and instabilities of the static community detection. The proposed methodology is broadly applicable and its outcomes reveal the temporal behavior of online topics. Modeling topic-dynamics: We consider the size of the communities in time as a proxy for online popularity dynamics. We find that the distributions of gains and losses, as well as the interevent times are fat-tailed indicating occasional, but large and sudden changes in the usage of hashtags. Inspired by typical website designs, we propose a stochastic model that incorporates a ranking with respect to a time-dependent prestige score. This causes occasional cascades of rank shift events and reproduces the observations with good agreement. This offers an explanation for the observed dynamics, based on characteristic elements of online media.

2015, Villoria, Nelson B., Elliott, Joshua, Müller, Christoph, Shin, Jaewoo, Zhao, Lan, Song, Carol

We discuss an on-line tool that facilitates access to the large collection of climate impacts on crop yields produced by the Agricultural Model Intercomparison and Improvement Project. This collection comprises the output of seven crop models which were run on a global grid using climate data from five different general circulation models under the current set of representative pathways. The output of this modeling endeavor consists of more than 36,000 publicly available global grids at a spatial resolution of one half degree. We offer flexible ways to aggregate these data while reducing the technical barriers implied by learning new download platforms and specialized formats. The tool is accessed trough any standard web browser without any special bandwidth requirement.

2018, Wendi, Dadiyorto, Marwan, Norbert, Merz, Bruno

As an effort to reduce parameter uncertainties in constructing recurrence plots, and in particular to avoid potential artefacts, this paper presents a technique to derive artefact-safe region of parameter sets. This technique exploits both deterministic (incl. chaos) and stochastic signal characteristics of recurrence quantification (i.e. diagonal structures). It is useful when the evaluated signal is known to be deterministic. This study focuses on the recurrence plot generated from the reconstructed phase space in order to represent many real application scenarios when not all variables to describe a system are available (data scarcity). The technique involves random shuffling of the original signal to destroy its original deterministic characteristics. Its purpose is to evaluate whether the determinism values of the original and the shuffled signal remain closely together, and therefore suggesting that the recurrence plot might comprise artefacts. The use of such determinism-sensitive region shall be accompanied by standard embedding optimization approaches, e.g. using indices like false nearest neighbor and mutual information, to result in a more reliable recurrence plot parameterization.

2019, Chen, Jianjun, Denk, Yue, Su, Zhen, Wang, Songxin, Gao, Chao, Li, Xianghua

Online social networks (OSNs) are interaction platforms that can promote knowledge spreading, rumor propagation, and virus diffusion. Identifying influential users in OSNs is of great significance for accelerating the information propagation especially when information is able to travel across multiple channels. However, most previous studies are limited to a single network or select multiple influential users based on the centrality ranking result of each user, not addressing the overlapping influence (OI) among users. In practice, the collective influence of multiple users is not equal to the total sum of these users' influences. In this paper, we propose a novel OI-based method for identifying multiple influential users in multiplex social networks. We first define the effective spreading shortest path (ESSP) by utilizing the concept of spreading rate in order to denote the relative location of users. Then, the collective influence is quantified by taking the topological factor and the location distribution of users into account. The identified users based on our proposed method are central and relatively scattered with a low overlapping influence. With the Susceptible-Infected-Recovered (SIR) model, we estimate our proposed method with other benchmark algorithms. Experimental results in both synthetic and real-world networks verify that our proposed method has a better performance in terms of the spreading efficiency. © 2013 IEEE.

2019, Reinhardt, S., Butschkow, C., Geissler, S., Dirnaichner, A., Olbrich, F., Lane, C.E., Schröer, D., Hüttel, A.K.

Lab::Measurement is a framework for test and measurement automatization using Perl 5. While primarily developed with applications in mesoscopic physics in mind, it is widely adaptable. Internally, a layer model is implemented. Communication protocols such as IEEE 488 [1], USB Test & Measurement [2], or, e.g., VXI-11 [3] are addressed by the connection layer. The wide range of supported connection backends enables unique cross-platform portability. At the instrument layer, objects correspond to equipment connected to the measurement PC (e.g., voltage sources, magnet power supplies, multimeters, etc.). The high-level sweep layer automates the creation of measurement loops, with simultaneous plotting and data logging. An extensive unit testing framework is used to verify functionality even without connected equipment. Lab::Measurement is distributed as free and open source software. Program summary: Program Title: Lab::Measurement 3.660 Program Files doi: http://dx.doi.org/10.17632/d8rgrdc7tz.1 Program Homepage: https://www.labmeasurement.de Licensing provisions: GNU GPL v23 Programming language: Perl 5 Nature of problem: Flexible, lightweight, and operating system independent control of laboratory equipment connected by diverse means such as IEEE 488 [1], USB [2], or VXI-11 [3]. This includes running measurements with nested measurement loops where a data plot is continuously updated, as well as background processes for logging and control. Solution method: Object-oriented layer model based on Moose [4], abstracting the hardware access as well as the command sets of the addressed instruments. A high-level interface allows simple creation of measurement loops, live plotting via GnuPlot [5], and data logging into customizable folder structures. [1] F. M. Hess, D. Penkler, et al., LinuxGPIB. Support package for GPIB (IEEE 488) hardware, containing kernel driver modules and a C user-space library with language bindings. http://linux-gpib.sourceforge.net/ [2] USB Implementers Forum, Inc., Universal Serial Bus Test and Measurement Class Specification (USBTMC), revision 1.0 (2003). http://www.usb.org/developers/docs/devclass_docs/ [3] VXIbus Consortium, VMEbus Extensions for Instrumentation VXIbus TCP/IP Instrument Protocol Specification VXI-11 (1995). http://www.vxibus.org/files/VXI_Specs/VXI-11.zip [4] Moose—Apostmodern object system for Perl 5. http://moose.iinteractive.com [5] E. A. Merritt, et al., Gnuplot. An Interactive Plotting Program. http://www.gnuplot.info/ © 2018 The Author(s)

2019, Warren, R.F., Edwards, N.R., Babonneau, F., Bacon, P.M., Dietrich, J.P., Ford, R.W., Garthwaite, P., Gerten, D., Goswami, S., Haurie, A., Hiscock, K., Holden, P.B., Hyde, M.R., Joshi, S.R., Kanudia, A., Labriet, M., Leimbach, M., Oyebamiji, O.K., Osborn, T., Pizzileo, B., Popp, A., Price, J., Riley, G.D., Schaphoff, S., Slavin, P., Vielle, M., Wallace, C.

We use the flexible model coupling technology known as the bespoke framework generator to link established existing modules representing dynamics in the global economy (GEMINI_E3), the energy system (TIAM-WORLD), the global and regional climate system (MAGICC6, PLASIM-ENTS and ClimGEN), the agricultural system, the hydrological system and ecosystems (LPJmL), together in a single integrated assessment modelling (IAM) framework, building on the pre-existing framework of the Community Integrated Assessment System. Next, we demonstrate the application of the framework to produce policy-relevant scientific information. We use it to show that when using carbon price mechanisms to induce a transition from a high-carbon to a low-carbon economy, prices can be minimised if policy action is taken early, if burden sharing regimes are used, and if agriculture is intensified. Some of the coupled models have been made available for use at a secure and user-friendly web portal. © 2018 The Authors

2020, Ji, Peng, Zhu, Lipeng, Lu, Chao, Lin, Wei, Kurths, Jürgen

With the deregulation of modern power grids, electricity markets are playing a more and more important role in power grid operation and control. However, it is still questionable how the real-time electricity price-based operation affects power grid stability. From a complex network perspective, here we investigate the dynamical interactions between price-based frequency regulations and physical networks, which results in an interesting finding that a local minimum of network stability occurs when the response strength of generators/consumers to the varying price increases. A case study of the real world-based China Southern Power Grid demonstrates the finding and exhibits a feasible approach to network stability enhancement in smart grids. This also provides guidance for potential upgrade and expansion of the current power grids in a cleaner and safer way. © 2020 Peng Ji et al.

2020, Sun, Fenglan, Liu, Peiyong, Kurths, Jürgen, Zhu, Wei

This text studies the fixed-time tracking consensus for nonlinear multiagent systems with disturbances. To make the fixed-time tracking consensus, the distributed control protocol based on the integral sliding mode control is proposed; meanwhile, the adjacent followers can be maintained in a limited sensing range. By using the nonsmooth analysis method, sufficient conditions for the fixed-time consensus together with the upper and lower bounds of convergence time are obtained. An example is given to illustrate the potential correctness of the main results. © 2020 Fenglan Sun et al.