Seeds Buffering for Information Spreading Processes

Seeding strategies for influence maximization in social networks have been studied for more than a decade. They have mainly relied on the activation of all resources (seeds) simultaneously in the beginning; yet, it has been shown that sequential seeding strategies are commonly better. This research focuses on studying sequential seeding with buffering, which is an extension to basic sequential seeding concept. The proposed method avoids choosing nodes that will be activated through the natural diffusion process, which is leading to better use of the budget for activating seed nodes in the social influence process. This approach was compared with sequential seeding without buffering and single stage seeding. The results on both real and artificial social networks confirm that the buffer-based consecutive seeding is a good trade-off between the final coverage and the time to reach it. It performs significantly better than its rivals for a fixed budget. The gain is obtained by dynamic rankings and the ability to detect network areas with nodes that are not yet activated and have high potential of activating their neighbours.Comment: Jankowski, J., Br\'odka, P., Michalski, R., & Kazienko, P. (2017, September). Seeds Buffering for Information Spreading Processes. In International Conference on Social Informatics (pp. 628-641). Springe

Probing Limits of Information Spread with Sequential Seeding

We consider here information spread which propagates with certain probability from nodes just activated to their not yet activated neighbors. Diffusion cascades can be triggered by activation of even a small set of nodes. Such activation is commonly performed in a single stage. A novel approach based on sequential seeding is analyzed here resulting in three fundamental contributions. First, we propose a coordinated execution of randomized choices to enable precise comparison of different algorithms in general. We apply it here when the newly activated nodes at each stage of spreading attempt to activate their neighbors. Then, we present a formal proof that sequential seeding delivers at least as large coverage as the single stage seeding does. Moreover, we also show that, under modest assumptions, sequential seeding achieves coverage provably better than the single stage based approach using the same number of seeds and node ranking. Finally, we present experimental results showing how single stage and sequential approaches on directed and undirected graphs compare to the well-known greedy approach to provide the objective measure of the sequential seeding benefits. Surprisingly, applying sequential seeding to a simple degree-based selection leads to higher coverage than achieved by the computationally expensive greedy approach currently considered to be the best heuristic

Disentangling astroglial physiology with a realistic cell model in silico

Electrically non-excitable astroglia take up neurotransmitters, buffer extracellular K+ and generate Ca2+ signals that release molecular regulators of neural circuitry. The underlying machinery remains enigmatic, mainly because the sponge-like astrocyte morphology has been difficult to access experimentally or explore theoretically. Here, we systematically incorporate multi-scale, tri-dimensional astroglial architecture into a realistic multi-compartmental cell model, which we constrain by empirical tests and integrate into the NEURON computational biophysical environment. This approach is implemented as a flexible astrocyte-model builder ASTRO. As a proof-of-concept, we explore an in silico astrocyte to evaluate basic cell physiology features inaccessible experimentally. Our simulations suggest that currents generated by glutamate transporters or K+ channels have negligible distant effects on membrane voltage and that individual astrocytes can successfully handle extracellular K+ hotspots. We show how intracellular Ca2+ buffers affect Ca2+ waves and why the classical Ca2+ sparks-and-puffs mechanism is theoretically compatible with common readouts of astroglial Ca2+ imaging

Effective Influence Spreading in Temporal Networks with Sequential Seeding

The spread of influence in networks is a topic of great importance in many application areas. For instance, one would like to maximise the coverage, limiting the budget for marketing campaign initialisation and use the potential of social influence. To tackle this and similar challenges, more than a decade ago, researchers started to investigate the influence maximisation problem. The challenge is to find the best set of initially activated seed nodes in order to maximise the influence spread in networks. In typical approach we will activate all seeds in single stage, at the beginning of the process, while in this work we introduce and evaluate a new approach for seeds activation in temporal networks based on sequential seeding. Instead of activating all nodes at the same time, this method distributes the activations of seeds, leading to higher ranges of influence spread. The results of experiments performed using real and randomised networks demonstrate that the proposed method outperforms single stage seeding in 71% of cases by nearly 6% on average. Knowing that temporal networks are an adequate choice for modelling dynamic processes, the results of this work can be interpreted as encouraging to apply temporal sequential seeding for real world cases, especially knowing that more sophisticated seed selection strategies can be implemented by using the seed activation strategy introduced in this work.Comment: 11 pages, 10 figures, reproductory code availabl

Discussion documents – SUSVAR Visions Workshop, Karrebæksminde, Denmark, April 2008

Seven discussion documents were made during the SUSVAR Visions workshop ‘Sustainable cereal production beyond 2020: Visions from the SUSVAR1 network’, Karrebæksminde, Denmark, 14-16 April 2008. At the workshop, one discussion documents was written for each of the topics mentioned below. In total 55 persons from 21 European countries participated in the process. The participants came from different disciplines: genetics, plant breeding, genetic resources, agronomy, plant pathology, soil science, biometry and system analysis, all specialised in the area of cereal production. The approach taken at the workshop was to focus on envisioning the future of sustainable agriculture, especially cereal production. This was done by scientific creative thinking on the basis of possibilities in breeding, management and seed production and not on the basis of traditional problem solving. We followed a strategy commonly used in industrial management based on the premise “imagining the future is shaping the future”. The method “appreciative inquiry” was applied supported by a professional facilitator. Experience shows that this way of working sparks engagement and creativity and that progress and results can be reached within a short time. Focus was on the following topics of relevance to cereal production: - Competition between food and bioenergy, - Soil fertility management, - Economical and legal conditions for variety improvement, - Participation of stakeholders, - Plant breeding strategies, - Food and feed processing improvements, - Sustainable land use. The initial process was to visualise the most desirable future scenario for the seven essential topics in food and agriculture systems. This process was unhindered by no requirement for a market-driven goal. Each topic was discussed in relation to a broader socio-ecological system with a focus on the means to reach the desired and more sustainable outcomes. The next step at the workshop was to produce the discussion documents. The final stage of the process is to connect the topics in a completed vision of cereal production within a future sustainable socio-ecological system. This is in progress by a group of key persons within the network, e.g. the working group leaders (in preparation for publication in a scientific journal)

Anaerobic Digestion of Olive Mill Wastewater in the Presence of Biochar

Biological treatments focused on stabilizing and detoxifying olive mill wastewater facilitate agronomic reuse for irrigation and fertilization. Anaerobic digestion is particularly attractive in view of energy recovery, but is severely hampered by the microbial toxicity of olive mill wastewater. In this work, the addition of biochar to the digestion mixture was studied to improve the stability and efficiency of the anaerobic process. Kinetics and yields of biogas production were evaluated in batch digestion tests with biochar concentrations ranging from 0 to 45 g L−1. The addition of biochar reduced sensibly the lag phase for methanogenesis and increased the maximum rate of biogas generation. Final yields of hydrogen and methane were not affected. Upon addition of biochar, soluble COD removal increased from 66% up to 84%, and phenolics removal increased from 50% up to 95%. Digestate phytotoxicity, as measured by seed germination tests, was reduced compared to raw wastewater. Addition of biochar further reduced phytotoxicity and, furthermore, a stimulatory effect was observed for a twenty-fold dilution. In conclusion, biochar addition enhances the anaerobic digestion of olive mill wastewaters by effectively reducing methanogenesis inhibition and digestate phytotoxicity, thus improving energy and biomass recovery

Ecological restoration of rich fens in Europe and North America: from trial and error to an evidence-based approach

Fens represent a large array of ecosystem services, including the highest biodiversity found among wetlands, hydrological services, water purification and carbon sequestration. Land use change and strong drainage has severely damaged or annihilated these services in many parts of North America and Europe, which urges the need of restoration plans at the landscape level. We review the major constraints for the restoration of rich fens and fen water bodies in agricultural areas in Europe and disturbed landscapes in North America: 1) habitat quality problems: drought, eutrophication, acidification, and toxicity, 2) recolonization problems: species pools, ecosystem fragmentation and connectivity, genetic variability, invasive species, and provide possible solutions. We discuss both positive and negative consequences of restoration measures, and their causes. The restoration of wetland ecosystem functioning and services has, for a long time, been based on a trial and error approach. By presenting research and practice on the restoration of rich fen ecosystems within agricultural areas, we demonstrate the importance of biogeochemical and ecological knowledge at different spatial scales for the management and restoration of biodiversity, water quality, carbon sequestration and other ecosystem services, especially in a changing climate. We define target processes that enable scientists, nature managers, water managers and policy makers to choose between different measures and to predict restoration prospects for different types of deteriorated fens and their starting conditions