Effectiveness of two wastewater disinfection strategies for the removal of fecal indicator bacteria, bacteriophage, and enteric viral pathogens concentrated using dead-end hollow fiber ultrafiltration (D-HFUF).

Primary influent and final effluent samples were collected from wastewater treatment plants using either chlorination or ultraviolet (UV) disinfection biweekly for one year. Paired measurements were determined for fecal indicator bacteria (Escherichia coli and enterococci), cultivated bacteriophages (somatic, F+, and CB-390 coliphage and GB-124 Bacteroides phage), human-associated viral markers (human polyomavirus [HPyV] and crAssphage), enteric pathogens (adenovirus, noroviruses genogroups I and II) as well as total infectious enteric virus. To increase the probability of detecting low concentration targets, both primary (10L) and final effluent wastewater samples (40-100 L) were concentrated using a dead-end hollow-fiber ultrafilter (D-HFUF).

Performance evaluation of a dead-end hollowfiber ultrafiltration method for enumeration of somatic and F+ coliphage from recreational waters.

Dead-end hollow fiber ultrafiltration combined with a single agar layer assay (D-HFUF-SAL) has potential use in the assessment of sanitary quality of recreational waters through enumeration of coliphage counts as measures of fecal contamination. However, information on applicability across a broad range of sites and water types is limited. Here, we tested the performance of D-HFUF-SAL on 49 marine and freshwater samples.

Development of a large volume concentration method for recovery of coronavirus from wastewater.

Levels of severe acute respiratory coronavirus type 2 (SARS CoV 2) RNA in wastewater could act as an effective means to monitor coronavirus disease 2019 (COVID-19) within communities. However, current methods used to detect SARS CoV 2 RNA in wastewater are limited in their ability to process sufficient volumes of source material, inhibiting our ability to assess viral load. Typically, viruses are concentrated from large liquid volumes using two stage concentration, primary and secondary.

Critical review of methods for isothermal amplification of nucleic acids for environmental analysis.

The past 30 years have seen the emergence and proliferation of isothermal amplification methods (IAMs) for rapid, sensitive detection and quantification of nucleic acids in a variety of sample types. These methods share dependence on primers and probes with quantitative PCR, but they differ in the specific enzymes and instruments employed, and are frequently conducted in a binary, rather than quantitative format. IAMs typically rely on simpler instruments than PCR analyses due to the maintenance of a single temperature throughout the amplification reaction, which could facilitate deployment of IAMs in a variety of environmental and field settings.

The DIAMOND Model: Deep Recurrent Neural Networks for Self-Organizing Robot Control.

The proposed architecture applies the principle of predictive coding and deep learning in a brain-inspired approach to robotic sensorimotor control. It is composed of many layers each of which is a recurrent network. The component networks can be spontaneously active due to the homeokinetic learning rule, a principle that has been studied previously for the purpose of self-organized generation of behavior.

Viral and Bacterial Fecal Indicators in Untreated Wastewater across the Contiguous United States Exhibit Geospatial Trends.

Cultivated fecal indicator bacteria such as and enterococci are typically used to assess the sanitary quality of recreational waters. However, these indicators suffer from several limitations, such as the length of time needed to obtain results and the fact that they are commensal inhabitants of the gastrointestinal tract of many animals and have fate and transport characteristics dissimilar to pathogenic viruses. Numerous emerging technologies that offer same-day water quality results or pollution source information or that more closely mimic persistence patterns of disease-causing pathogens that may improve water quality management are now available, but data detailing geospatial trends in wastewater across the United States are sparse.

Bringing Community Ecology to Bear on the Issue of Antimicrobial Resistance.

Antimicrobial resistance (AMR) is a global concern, pertaining not only to human health but also to the health of industry and the environment. AMR research has traditionally focused on genetic exchange mechanisms and abiotic environmental constraints, leaving important aspects of microbial ecology unresolved. The genetic and ecological aspects of AMR, however, not only contribute separately to the problem but also are interrelated.

A Constructed Wetland for Treatment of an Impacted Waterway and the Influence of Native Waterfowl on its Perceived Effectiveness.

A constructed, variable-flow treatment wetland was evaluated for its ability to reduce microbial loads from the Banklick Creek, an impacted recreational waterway in Northern Kentucky. For this study, levels of traditional ( and enterococci measured by culture and molecular techniques) and alternative fecal indicators (infectious somatic and F+ coliphage, spp. and by culture), potential pathogens (molecular signal of spp.

Genome Sequences of Escherichia Bacteriophages Isolated from Raw Wastewater.

Somatic coliphages are alternative indicators of fecal pollution and attractive surrogates for viral pathogens. Here, we report the draft genome sequences of three replicate plaques from a novel bacteriophage isolated from raw wastewater. These genomes were similar to felix01virus phage and are predicted to contain up to 148 protein-coding genes.

[How does a pesticide residue turn into a contaminant?].

Over the last few years pesticide residues have been repeatedly detected during official food controls that would not be expected from authorized pesticide uses. These residues do not always pose a health risk for consumers. However, the legal and economic consequences of such findings are often far-reaching, especially if the admissible maximum residue limits have been fixed at the LOQ level only.

Revealing the Initial Reaction Behavior in the Continuous Synthesis of Metal-Organic Frameworks Using Real-Time Synchrotron X-ray Analysis.

In recent years, continuous process technologies have attracted increasing attention, as a means of overcoming limitations in the repeatability and reproducibility of metal-organic framework (MOF) synthesis. Research in this area, however, has neglected to provide insight into the phenomenon leading to the formation of MOFs. In this work, we report the adaption of high-energy synchrotron powder X-ray diffraction analysis to a continuous ZIF-8 production process for online monitoring of the reaction behavior and crystallite formation during the first seconds of the MOF synthesis.

Local Autoencoding for Parameter Estimation in a Hidden Potts-Markov Random Field.

A local-autoencoding (LAE) method is proposed for the parameter estimation in a Hidden Potts-Markov random field model. Due to sampling cost, Markov chain Monte Carlo methods are rarely used in real-time applications. Like other heuristic methods, LAE is based on a conditional independence assumption.

Natural Vocalizations in the Mammalian Inferior Colliculus are Broadly Encoded by a Small Number of Independent Multi-Units.

How complex natural sounds are represented by the main converging center of the auditory midbrain, the central inferior colliculus, is an open question. We applied neural discrimination to determine the variation of detailed encoding of individual vocalizations across the best frequency gradient of the central inferior colliculus. The analysis was based on collective responses from several neurons.

Cell-Division Behavior in a Heterogeneous Swarm Environment.

We present a system of virtual particles that interact using simple kinetic rules. It is known that heterogeneous mixtures of particles can produce particularly interesting behaviors. Here we present a two-species three-dimensional swarm in which a behavior emerges that resembles cell division.

Inter-genomic sexual conflict drives antagonistic coevolution in harvester ants.

The reproductive interests of males and females are not always aligned, leading to sexual conflict over parental investment, rate of reproduction and mate choice. Traits that increase the genetic interests of one sex often occur at the expense of the other, selecting for counter-adaptations leading to antagonistic coevolution. Reproductive conflict is not limited to intraspecific interactions; interspecific hybridization can produce pronounced sexual conflict between males and females of different species, but it is unclear whether such conflict can drive sexually antagonistic coevolution between reproductively isolated genomes.

Sustainable development, demography and sexual and reproductive health: inseparable linkages and their policy implications.

The greatest challenge today is to meet the needs of current and future generations, of a large and growing world population, without imposing catastrophic pressures on the natural environment. Meeting this challenge depends on decisive policy changes in three areas: more inclusive economic growth, greener economic growth, and population policies. This article focuses on efforts to address and harness demographic changes for sustainable development, which are largely outside the purview of the current debate.

Long term stability of surface EMG pattern classification for prosthetic control.

Long-term functioning of a hand prosthesis is crucial for its acceptance by patients with upper limb deficit. In this study the reliability over days of the performance of pattern classification approaches based on surface electromyography (sEMG) signal for the control of upper limb prostheses was investigated. Recordings of sEMG from the forearm muscles were obtained across five consecutive days from five healthy subjects.

Compositionality in neural control: an interdisciplinary study of scribbling movements in primates.

This article discusses the compositional structure of hand movements by analyzing and modeling neural and behavioral data obtained from experiments where a monkey (Macaca fascicularis) performed scribbling movements induced by a search task. Using geometrically based approaches to movement segmentation, it is shown that the hand trajectories are composed of elementary segments that are primarily parabolic in shape. The segments could be categorized into a small number of classes on the basis of decreasing intra-class variance over the course of training.

Critical dynamics in associative memory networks.

Critical behavior in neural networks is characterized by scale-free avalanche size distributions and can be explained by self-regulatory mechanisms. Theoretical and experimental evidence indicates that information storage capacity reaches its maximum in the critical regime. We study the effect of structural connectivity formed by Hebbian learning on the criticality of network dynamics.

Inhibition in the dynamics of selective attention: an integrative model for negative priming.

We introduce a computational model of the negative priming (NP) effect that includes perception, memory, attention, decision making, and action. The model is designed to provide a coherent picture across competing theories of NP. The model is formulated in terms of abstract dynamics for the activations of features, their binding into object entities, their semantic categorization as well as related memories and appropriate reactions.

Cross-modal distortion of time perception: demerging the effects of observed and performed motion.

Temporal information is often contained in multi-sensory stimuli, but it is currently unknown how the brain combines e.g. visual and auditory cues into a coherent percept of time.

Identity negative priming: a phenomenon of perception, recognition or selection?

The present study addresses the problem whether negative priming (NP) is due to information processing in perception, recognition or selection. We argue that most NP studies confound priming and perceptual similarity of prime-probe episodes and implement a color-switch paradigm in order to resolve the issue. In a series of three identity negative priming experiments with verbal naming response, we determined when NP and positive priming (PP) occur during a trial.

The neural representation of time: an information-theoretic perspective.

A prominent finding in psychophysical experiments on time perception is Weber's law, the linear scaling of timing errors with duration. The ability to reproduce this scaling has been taken as a criterion for the validity of neurocomputational models of time perception. However, the origin of Weber's law remains unknown, and currently only a few models generically reproduce it.