Phosphorus enrichment affects trait network topologies and the growth of submerged macrophytes

The pervasiveness of online social networks has reshaped the way people access information. Online social networks make it common for users to inform themselves online and share news among their peers, but also favor the spreading of both reliable and fake news alike. Because fake news may have a profound impact on the society at large, realistically simulating their spreading process helps evaluate the most effective countermeasures to adopt. It is customary to model the spreading of fake news via the same epidemic models used for common diseases; however, these models often miss concepts and dynamics that are peculiar to fake news spreading. In this paper, we fill this gap by enriching typical epidemic models for fake news spreading with network topologies and dynamics that are typical of realistic social networks. Specifically, we introduce agents with the role of influencers and bots in the model and consider the effects of dynamical network access patterns, time-varying engagement, and different degrees of trust in the sources of circulating information. These factors concur with making the simulations more realistic. Among other results, we show that influencers that share fake news help the spreading process reach nodes that would otherwise remain unaffected. Moreover, we emphasize that bots dramatically speed up the spreading process and that time-varying engagement and network access change the effectiveness of fake news spreading.

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Metal(loid) accumulation levels in submerged macrophytes and epiphytic biofilms and correlations with metal(loid) levels in the surrounding water and sediments

The Science of The Total Environment ◽

10.1016/j.scitotenv.2020.143878 ◽

2021 ◽

Vol 758 ◽

pp. 143878

Author(s):

Mengmeng Fan ◽

Pinhua Xia ◽

Wensheng Chen ◽

Tianyou Wang ◽

Xin Du ◽

...

Keyword(s):

Submerged Macrophytes ◽

Surrounding Water

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Omnivorous Carp (Carassius gibelio) Increase Eutrophication in Part by Preventing Development of Large-Bodied Zooplankton and Submerged Macrophytes

Water ◽

10.3390/w13111497 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1497

Author(s):

Vladimir Razlutskij ◽

Xueying Mei ◽

Natallia Maisak ◽

Elena Sysova ◽

Dzmitry Lukashanets ◽

...

Keyword(s):

Aquatic Ecosystems ◽

Submerged Macrophytes ◽

Benthic Algae ◽

Plankton Community ◽

Prussian Carp ◽

Omnivorous Fish ◽

Outdoor Experiment ◽

Nitrogen Concentrations ◽

Lower Biomass

Fish, being an important consumer in aquatic ecosystems, plays a significant role by affecting the key processes of aquatic ecosystems. Omnivorous fish consume a variety of food both from pelagic and benthic habitats and may directly or indirectly affect the plankton community as well as the lake trophic state. We conducted a 72-day outdoor experiment in mesocosms with and without Prussian carp (Carassius auratus) to evaluate the effect of this often-stocked omnivorous fish on the plankton community and water quality. We found that the presence of fish increased the biomass of planktonic algae, total and inorganic suspended solids, leading to decreased light intensity in the water and a lower biomass of benthic algae. Fish also prevented development of submerged macrophytes and the establishment of large-bodied zooplankton. However, the fish did not increase nitrogen concentrations and even was lowered total phosphorus levels, in part due to nutrient storage in the fish. We conclude that stocking of Prussian carp should be avoided, or removed where stocked and abundant, to obtain good ecological quality of shallow lakes, characterized by clear water and high abundance of macrophytes.

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Optimal Coordination of Over-Current Relays in Microgrids Using Unsupervised Learning Techniques

Applied Sciences ◽

10.3390/app11031241 ◽

2021 ◽

Vol 11 (3) ◽

pp. 1241

Author(s):

Sergio D. Saldarriaga-Zuluaga ◽

Jesús M. López-Lezama ◽

Nicolás Muñoz-Galeano

Keyword(s):

Unsupervised Learning ◽

Distributed Generation ◽

Network Topology ◽

International Electrotechnical Commission ◽

Number Of Clusters ◽

Learning Techniques ◽

Topology Changes ◽

Network Topologies ◽

Optimal Coordination ◽

Operational Modes

Microgrids constitute complex systems that integrate distributed generation (DG) and feature different operational modes. The optimal coordination of directional over-current relays (DOCRs) in microgrids is a challenging task, especially if topology changes are taken into account. This paper proposes an adaptive protection approach that takes advantage of multiple setting groups that are available in commercial DOCRs to account for network topology changes in microgrids. Because the number of possible topologies is greater than the available setting groups, unsupervised learning techniques are explored to classify network topologies into a number of clusters that is equal to the number of setting groups. Subsequently, optimal settings are calculated for every topology cluster. Every setting is saved in the DOCRs as a different setting group that would be activated when a corresponding topology takes place. Several tests are performed on a benchmark IEC (International Electrotechnical Commission) microgrid, evidencing the applicability of the proposed approach.

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