Growth kinetics of environmental Legionella pneumophila isolated from industrial wastewater

Wastewater treatment plants are environmental niches for Legionella pneumophila, the most commonly identified causative agent of severe pneumonia known as Legionnaire's disease. In the present study, Legionella pneumophila's concentrations were monitored in an industrial wastewater treatment plant and environmental isolates were characterized concerning their growth kinetics with respect to temperature and their inhibition by organic acids and ammonium. The results of the monitoring study showed that Legionella pneumophila occurs in activated sludge tanks operated with very different sludge retention times, 2.5 days in a complete-mix reactor, and 10 days in a membrane bioreactor, indicating that this bacterium can grow at different rates, despite the same wastewater temperature of 35 degrees C. The morphology of Legionella cells is different in both reactors; in the membrane bioreactor, the bacteria grow in clusters, while in the complete-mix reactor, filaments predominate demonstrating a faster growth rate. Legionella pneumophila concentrations in the complete-mix reactor and in the membrane bioreactor were within the range 3 x 10(1) to 4.8 x 10(3) GU/mL and 3 x 10(2) to 4.7 x 10(3) GU/mL, respectively. Environmental Legionella pneumophila SG2-14 isolates showed distinct temperature preferences. The lowest growth rate was observed at 28 degrees C, and the highest 0.34 d(-1) was obtained at 42 degrees C. The presence of high concentrations of organic acids and ammonium found in anaerobically pre-treated wastewater caused growth inhibition. Despite the increasing research efforts, the mechanisms governing the growth of Legionella pneumophila in wastewater treatment plants are still unclear. New innovative strategies to prevent the proliferation of this bacterium in wastewater are in demand

Quantum criticality of U(1) gauge theories with fermionic and bosonic matter in two spatial dimensions

We consider relativistic U(1) gauge theories in 2+1 dimensions, with N_b species of complex bosons and N_f species of Dirac fermions at finite temperature. The quantum phase transition between the Higgs and Coulomb phases is described by a conformal field theory (CFT). At large N_b and N_f, but for arbitrary values of the ratio N_b/N_f, we present computations of various critical exponents and universal amplitudes for these CFTs. We make contact with the different spin-liquids, charge-liquids and deconfined critical points of quantum magnets that these field theories describe. We compute physical observables that may be measured in experiments or numerical simulations of insulating and doped quantum magnets.Comment: 30 pages, 8 figure

Quantum critical scaling behavior of deconfined spinons

We perform a renormalization group analysis of some important effective field theoretic models for deconfined spinons. We show that deconfined spinons are critical for an isotropic SU(N) Heisenberg antiferromagnet, if $N$ is large enough. We argue that nonperturbatively this result should persist down to N=2 and provide further evidence for the so called deconfined quantum criticality scenario. Deconfined spinons are also shown to be critical for the case describing a transition between quantum spin nematic and dimerized phases. On the other hand, the deconfined quantum criticality scenario is shown to fail for a class of easy-plane models. For the cases where deconfined quantum criticality occurs, we calculate the critical exponent $\eta$ for the decay of the two-spin correlation function to first-order in $\epsilon=4-d$. We also note the scaling relation $\eta=d+2(1-\phi/\nu)$ connecting the exponent $\eta$ for the decay to the correlation length exponent $\nu$ and the crossover exponent $\phi$.Comment: 4.1 pages, no figures, references added; Version accepted for publication in PRB (RC

Cross-Task Transfer for Geotagged Audiovisual Aerial Scene Recognition

Aerial scene recognition is a fundamental task in remote sensing and has recently received increased interest. While the visual information from overhead images with powerful models and efficient algorithms yields considerable performance on scene recognition, it still suffers from the variation of ground objects, lighting conditions etc. Inspired by the multi-channel perception theory in cognition science, in this paper, for improving the performance on the aerial scene recognition, we explore a novel audiovisual aerial scene recognition task using both images and sounds as input. Based on an observation that some specific sound events are more likely to be heard at a given geographic location, we propose to exploit the knowledge from the sound events to improve the performance on the aerial scene recognition. For this purpose, we have constructed a new dataset named AuDio Visual Aerial sceNe reCognition datasEt (ADVANCE). With the help of this dataset, we evaluate three proposed approaches for transferring the sound event knowledge to the aerial scene recognition task in a multimodal learning framework, and show the benefit of exploiting the audio information for the aerial scene recognition. The source code is publicly available for reproducibility purposes.Comment: ECCV 202

Análise econômica de sistemas de manejo de açaizais nativos no estuário amazônico.

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