The dangerous transporters : a study of microplastic-associated bacteria passing through municipal wastewater treatment

Microplastics (MPs) provide a stable and protective habitat for diverse wastewater bacteria, including pathogenic and antibiotic-resistant species. Therefore, MPs may potentially transport these bacteria through wastewater treatment steps to the environment and far distances. This study investigated bacterial communities of MP-associated bacteria from different stages of municipal wastewater treatment processes to evaluate the potential negative effect of these biofilms on the environment. The results showed a high diversity of bacteria that were strongly attached to MPs. After all treatment steps, the core bacterial groups remained attached to MPs and escaped from the wastewater treatment plant with effluent water. Several pathogenic bacteria were identified in MP samples from all treatment steps, and most of them were found in effluent water. These data provide new insights into the possible impacts of wastewater-derived MPs on the environment. MP-associated biofilms were proved to be important sources of pathogens and antibiotic-resistant genes in natural waters. Highlights • Effluent microplastics carry a variety of different bacteria into the environment. • Wastewater microplastic biofilms contain bacteria from the human gut microbiome. • Primary and tertiary treatment have a minor impact on microplastic biofilm structure. • Effluent microplastic biofilms are combined of influent and activated sludge bacteria. • Wastewater microplastics are possible hotspots for the spread of harmful bacteria

Microbial ecology of full-scale wastewater treatment systems in the Polar Arctic Circle

Seven full-scale biological wastewater treatment systems located in the Polar Arctic Circle region in Finland were investigated to determine their Archaea, Bacteria and Fungi community structure, and their relationship with the operational conditions of the bioreactors by the means of quantitative PCR, massive parallel sequencing and multivariate redundancy analysis. The results showed dominance of Archaea and Bacteria members in the bioreactors. The activated sludge systems showed strong selection of Bacteria but not for Archaea and Fungi, as suggested by diversity analyses. Core OTUs in influent and bioreactors were classified as Methanobrevibacter, Methanosarcina, Terrestrial Group Thaumarchaeota and unclassified Euryarchaeota member for Archaea; Trichococcus, Leptotrichiaceae and Comamonadaceae family, and Methylorosula for Bacteria and Trichosporonaceae family for Fungi. All influents shared core OTUs in all domains, but in bioreactors this did not occur for Bacteria. Oligotype structure of core OTUs showed several ubiquitous Fungi oligotypes as dominant in sewage and bioreactors. Multivariate redundancy analyses showed that the majority of core OTUs were related to organic matter and nutrients removal. Also, there was evidence of competition among Archaea and Fungi core OTUs, while all Bacteria OTUs were positively correlated among them. The results obtained highlighted interesting features of extremely cold temperature bioreactors.Peer reviewe

Unconventional Energy from an Electric Impulse Heater Combined with a Wind Turbine

The widespread use of wind power plants can provide full or partial energy supply to the consumer, taking into account certain investments and the instability of energy production. Modern wind energy technology involves the conversion of mechanical energy of the wind flow into electrical energy with subsequent conversion, at the request of the consumer, into thermal energy. In addition, the unprocessed use of the low-potential part of the wind flow, characterized by non-uniformity and randomness of its reception for the purpose of supplying heat to the recipient, requires new approaches to solving this problem. Bench experimental studies of this heater confirmed the adequacy of the mathematical model: within an hour, the temperature increase of the heater core changed from 22 °C to 36 °C at a voltage of 66 V and the number of pulses entering the heater coil was (15–17) discharges, which corresponds to the values of the mathematical expectation of the wind speed of (4–5.2) m∙s−1 in the range of wind speed (4–8) m∙s−1. The scientific novelty of this work consists in the development of a mathematical model for the operation of an electric pulse heater, which made it possible to develop methodological provisions for determining its mode parameters and to estimate the temperature change of its elements at random wind speed

DUNE Offline Computing Conceptual Design Report

International audienceThis document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

International audienceLiquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation