Treatment of Biogas Produced in Anaerobic Reactors for Domestic Wastewater: Odor Control and Energy/Resource Recovery

Anaerobic municipal wastewater treatment in developing countries has important potential applications considering their huge lack of sanitation infrastructure and their advantageous climatic conditions. At present, among the obstacles that this technology encounters, odor control and biogas utilization or disposal should be properly addressed. In fact, in most of small and medium size anaerobic municipal treatment plants, biogas is just vented, transferring pollution from water to the atmosphere, contributing to the greenhouse gas inventory. Anaerobic municipal sewage treatment should not be considered as an energy producer, unless a significant wastewater flow is treated. In these cases, more than half of the methane produced is dissolved and lost in the effluent so yield values will be between 0.08 and 0.18 N m³ CH₄/kg COD removed. Diverse technologies for odor control and biogas cleaning are currently available. High pollutant concentrations may be treated with physical-chemical methods, while biological processes are used mainly for odor control to prevent negative impacts on the treatment facilities or nearby areas. In general terms, biogas treatment is accomplished by physico-chemical methods, scrubbing being extensively used for H₂S and CO₂ removal. However, dilution (venting) has been an extensive disposal method in some small- and medium-size anaerobic plants treating municipal wastewaters. Simple technologies, such as biofilters, should be developed in order to avoid this practice, matching with the simplicity of anaerobic wastewater treatment processes. In any case, design and specification of biogas handling system should consider safety standards. Resource recovery can be added to anaerobic sewage treatment if methane is used as electron donor for denitrification and nitrogen control purposes. This would result in a reduction of operational cost and in an additional advantage for the application of anaerobic sewage treatment. In developing countries, biogas conversion to energy may apply for the clean development mechanism (CDM) of the Kyoto Protocol. This would increase the economic feasibility of the project through the marketing of certified emission reductions (CERs).     

The presence–absence matrix reloaded: the use and interpretation of range–diversity plots

Aim A great deal of information on distribution and diversity can be extracted from presence–absence matrices (PAMs), the basic analytical tool of many biogeographic studies. This paper presents numerical procedures that allow the analysis of such information by taking advantage of mathematical relationships within PAMs. In particular, we show how range–diversity (RD) plots summarize much of the information contained in the matrices by the simultaneous depiction of data on distribution and diversity. Innovation We use matrix algebra to extract and process data from PAMs. Information on the distribution of species and on species richness of sites is computed using the traditional R (by rows) and Q (by columns) procedures, as well as the new Rq (by rows, considering the structure of columns) and Qr (by columns, considering the structure by rows) methods. Matrix notation is particularly suitable for summarizing complex calculations using PAMs, and the associated algebra allows the implementation of efficient computational programs. We show how information on distribution and species richness can be depicted simultaneously in RD plots, allowing a direct examination of the relationship between those two aspects of diversity. We explore the properties of RD plots with a simple example, and use null models to show that while parameters of central tendency are not affected by randomization, the dispersion of points in RD plots does change, showing the significance of patterns of co‐occurrence of species and of similarity among sites. Main conclusion Species richness and range size are both valid measures of diversity that can be analysed simultaneously with RD plots. A full analysis of a system requires measures of central tendency and dispersion for both distribution and species richness.     

nAChR‐induced octopamine release mediates the effect of nicotine on a startle response in Drosophila melanogaster

Biogenic amines (BAs) play a central role in the generation of complex behaviors in vertebrates and invertebrates, including the fly Drosophila melanogaster. The comparative advantages of Drosophila as a genetic model to study the contribution of BAs to behaviors stumble upon the difficulty to access the fly brain to ask relevant physiological questions. For instance, it is not known whether the activation of nicotinic acetylcholine receptors (nAChRs) induces the release of BAs in fly brain, a phenomenon associated to several behaviors in vertebrates. Here, we describe a new preparation to study the efflux of BAs in the adult fly brain by in vitro chronoamperometry. Using this preparation we show that nAChR agonists including nicotine induce a fast, transient, dose‐dependent efflux of endogenous BAs, an effect mediated by α‐bungarotoxin‐sensitive nAChRs. By using different genetic tools we demonstrate that the BA whose efflux is induced by nAChR activation is octopamine (Oct). Furthermore, we show that the impairment of a mechanically induced startle response after nicotine exposure is not observed in flies deficient in Oct transmission. Thus, our data show that the efflux of BAs in Drosophila brain is increased by nAChR activation as in vertebrates, and that then AChR‐induced Oct release could have implications in a nicotine‐induced behavioral response.     

Using Manifold Learning for Atlas Selection in Multi-Atlas Segmentation

Multi-atlas segmentation has been widely used to segment various anatomical structures. The success of this technique partly relies on the selection of atlases that are best mapped to a new target image after registration. Recently, manifold learning has been proposed as a method for atlas selection. Each manifold learning technique seeks to optimize a unique objective function. Therefore, different techniques produce different embeddings even when applied to the same data set. Previous studies used a single technique in their method and gave no reason for the choice of the manifold learning technique employed nor the theoretical grounds for the choice of the manifold parameters. In this study, we compare side-by-side the results given by 3 manifold learning techniques (Isomap, Laplacian Eigenmaps and Locally Linear Embedding) on the same data set. We assess the ability of those 3 different techniques to select the best atlases to combine in the framework of multi-atlas segmentation. First, a leave-one-out experiment is used to optimize our method on a set of 110 manually segmented atlases of hippocampi and find the manifold learning technique and associated manifold parameters that give the best segmentation accuracy. Then, the optimal parameters are used to automatically segment 30 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). For our dataset, the selection of atlases with Locally Linear Embedding gives the best results. Our findings show that selection of atlases with manifold learning leads to segmentation accuracy close to or significantly higher than the state-of-the-art method and that accuracy can be increased by fine tuning the manifold learning process.     

Population trends for humpback whales (Megaptera novaeangliae) foraging in the Francisco Coloane Coastal‐Marine Protected Area,Magellan Strait,Chile

In 2003 a feeding aggregation of southeastern Pacific humpback whales (Megaptera novaeangliae) was reported in the Magellan Strait. While Chile established its first marine national park in the Strait to protect humpback whale habitat, fatal ship strikes remain a concern because of overlap with a busy shipping lane. To better understand population risk, we estimated abundance and survival for this population using Bayesian robust‐design mark‐recapture models fit to photographic data from 2004 to 2016. Overall, the model estimated a total of 204 whales (95% CI: 199–210) during the last 12 yr, and 93 (95% CI: 86–100) in the 2016/2017 austral summer. The population grew at 2.3% (CI: 2.1%–3.1%), an annual increase of two whales. Annual survival (including calves) was estimated at 0.892 (CI: 0.871–0.910). Our results corroborate a persistent feeding population, but one that is increasing relatively slowly. Owing to its vulnerability stemming from its small size, coupled with significant overlap with a busy shipping lane, we argue this subpopulation is at significant risk from ship strikes and may be one of the few populations where anthropogenic mortalities could regulate population dynamics. We therefore encourage continued monitoring via photographic mark‐resighting surveys, and analyses explicitly investigating potential population‐level ship strike effects.     

The Administration of Cadmium for 2, 3 and 4 Months Causes a Loss of Recognition Memory,Promotes Neuronal Hypotrophy and Apoptosis in the Hippocampus of Rats

Cadmium (Cd) is a toxic metal and classified as a carcinogen whose exposure could affect the function of the central nervous system. There are studies that suggest that Cd promotes neurodegeneration in different regions of the brain, particularly in the hippocampus. It is proposed that its mechanism of toxicity maybe by an oxidative stress pathway, which modifies neuronal morphology and causes the death of neurons and consequently affecting cognitive tasks. However, this mechanism is not yet clear. The aim of the present work was to study the effect of Cd administration on recognition memory for 2, 3 and 4 months, neuronal morphology and immunoreactivity for caspase-3 and 9 in rat hippocampi. The results show that the administration of Cd decreased recognition memory. Likewise, it caused the dendritic morphology of the CA1, CA3 and dentate gyrus regions of the hippocampus to decrease with respect to the time of administration of this heavy metal. In addition, we observed a reduction in the density of dendritic spines as well as an increase in the immunoreactivity of caspase-3 and 9 in the same hippocampal regions of the animals treated with Cd. These results suggest that Cd affects the structure and function of the neurons of the hippocampus, which contribute to the deterioration of recognition memory. Our results suggest that the exposure to Cd represents a critical health problem, which if not addressed quickly, could cause much more serious problems in the quality of life of the human population, as well as in the environment in which they develop.

     

Species diversity in Gymnogeophagus (Teleostei: Cichlidae) and comparative biogeography of cichlids in the Middle Paraná basin,an emerging hotspot of fish endemism

Hydrobiologia - We address the diversity of two species groups of the cichlid genus Gymnogeophagus in the Middle Paraná basin using molecular phylogeography and traditional morphological...     

A meta-taxonomic investigation of the prokaryotic diversity of water bodies impacted by acid mine drainage from the São Domingos mine in southern Portugal

Extremophiles - The prokaryotic communities of water bodies contaminated by acid mine drainage from the São Domingos mining area in southern Portugal were analyzed using a meta-taxonomics...     

Spatial patterns of white stork (Ciconia ciconia) migratory phenology in the Iberian Peninsula

In contrast to the attention attracted by temporal trends of phenology, the spatial patterns of arrivals, departures or stays of trans-Saharan birds are still nowadays largely unknown in most of their European breeding areas. In the case of the white stork (Ciconia ciconia), some studies have attempted to describe its migratory patterns throughout some European countries but, to our knowledge, no one has related these patterns to some kind of explanatory variable which offers an ecologically-based explanation for the heterogeneous phenology observable among populations. Here, arrivals, departures and stays of this species, recorded in hundreds of Spanish localities, were related to a set of environmental, geographical, biological and spatial predictors, and modeled by multiple regression. The best model for arrival dates accounted for up to 34% of variability of data and pointed towards an earlier arrival in those populations located in south-western Iberia and with higher population densities. This last relationship is probably due to the competition for nest-site fidelity maintenance. However, no variable was able to explain properly the blurred spatial pattern recorded for departure dates. Departure decisions are strongly influenced by social behavior in this species and depend on collective decisions influenced by peculiar local environmental conditions of each year rather than macrogeographical gradients. Environmental, geographical or spatial variables also did not capture much of the observed variability in the length of the stays among populations. However, this variable was strongly related to the arrival and departure dates of populations. White storks stay longer in localities with earlier arrivals and, especially, later departures.