Adult female hamsters avoid interspecific mating after exposure to heterospecific males

When females mate with a heterospecific male, they do not usually produce viable offspring. Thus, there is a selective pressure for females to avoid interspecific mating. In many species, females innately avoid heterospecific males; females can also imprint on their parents to avoid later sexual interactions with heterospecific males. However, it was previously unknown whether adult females can learn to discriminate against heterospecific males. We tested the hypothesis that adult females previously unable to avoid interspecific mating learn to avoid such mating after being exposed to heterospecific males. Syrian hamster (Mesocricetus auratus) females not previously exposed to Turkish hamster (Mesocricetus brandti) males can discriminate between odors of conspecific and heterospecific males, but they mate with either type of male. However, when we exposed adult females to both a conspecific male and a heterospecific male through wire-mesh barriers for 8 days, and then paired them sequentially with the two males, females were more receptive to conspecific males and more aggressive to heterospecific males. When females were paired with the heterospecific male first and the conspecific male second, no female was receptive and all were aggressive to heterospecific males. When females were paired with the conspecific male first, only 43% of females were then aggressive toward the heterospecific male. That is, interactions with conspecific males may decrease a female’s ability to properly avoid heterospecific males. Our study clearly shows for the first time that females can learn during adulthood to avoid interspecific mating just by being exposed to stimuli from heterospecific males.     

A new simple methodology for evaluation of explosion risk in underground coal mines

The key objective of this paper is the presentation of a new risk assessment tool for underground coal mines based on a simplified semi-quantitative estimation and assessment method.In order to determine the risk of explosion of any work process or activity in underground coal mines it is necessary to assess the risk. The proposed method is based on a Risk Index obtained as a product of three factors: frequency of each individual scenario P_ucm, associated severity consequences C_ucm and exposure time to explosive atmospheres E_ucm. The influence of exposure time is usually not taken into account up to now. Moreover, the exposure to explosive atmospheres may affect factors of hazardous event probability as much as its consequences. There are many definitions of exposure to explosive atmospheres but in the case of underground coal mines the exposure is defined as frequency risk of firedamp and coal dust. The risk estimation and risk assessment are based on the developed of a risk matrix.The proposed methodology allows not only the estimation of the explosion risk but also gives an approach to decide if the proposal investment is well-justified or not in order to improve safety.     

Assessment of Self-Organizing Map artificial neural networks for the classification of sediment quality

The application of mathematical tools in initial steps of sediment quality assessment frameworks can be useful to provide an integrated interpretation of multiple measured variables. This study reveals that the Self-Organizing Map (SOM) artificial neural network can be an effective tool for the integration of multiple physical, chemical and ecotoxicological variables in order to classify different sites under study according to their similar sediment quality. Sediment samples from 40 sites of 3 estuaries of Cantabria (Spain) were classified with respect to 13 physical, chemical and toxicological variables using the SOM. Results obtained with the SOM, when compared to those of traditional multivariate statistical techniques commonly used in the field of sediment quality (principal component analysis (PCA) and hierarchical cluster analysis (HCA)), provided a more useful classification for further assessment steps. Especially, the powerful visualization tools of the SOM, which offer more information and in an easier way than HCA and PCA, facilitate the task of establishing an order of priority between the distinguished groups of sites depending on their need for further investigations or remediation actions in subsequent management steps.     

Optimization of the recovery of plastics for recycling by density media separation cyclones

Material recovery processes are presented as the optimum option for recycling plastic wastes as a means of recovering hydrocarbon resources. There exist a large variety of automated material recovery processes for recycling of such wastes but each with significant limitations. Of these, the separation based on differences in densities is advocated as the optimum process either for producing recycled products or preparing wastes for subsequent recovery processing.Density separation processes based on cyclone type density media separation (DMS) is presented as an important, potential method for increasing plastics recycling process capacities. It is demonstrated to have the capacity to separate a significantly larger range of particle sizes than those presently processed industrially. The mathematical relationship for the prediction of quality of typical LARCODEMS type density media separations by particle size and density as expressed by the Ecart Probable is presented.A proposed device configuration is presented for density media separation to optimize the recovery and purity of both density fractions produced. It is also suggested that to be economically viable, a large scale of operation is required for industrial plastics recycling operations recovering and producing a number of different plastics with a purity to be used as a substitute for virgin material.     

Estimating dyad association probability under imperfect and heterogeneous detection

In animal behaviour studies, association indices estimate the proportion of time two individuals (i.e. a dyad) spend in association. In terms of dyads, all association indices can be interpreted as estimators of the probability that a dyad is associated. However, traditional indices rely on the assumptions that the probability to detect a particular individual (p) is either approximately one and/or homogeneous between associated and not associated individuals. Based on marked individuals we develop a likelihood based model to estimate the probability a dyad is associated (ψ) accounting for p < 1 and possibly varying between associated and not associated individuals. The proposed likelihood based model allows for both individual and dyadic missing observations. In addition, the model can easily be extended to incorporate covariate information for modeling p and ψ. A simulation study showed that the likelihood based model approach yield reasonably unbiased estimates, even for low and heterogeneous individual detection probabilities, while, in contrast, traditional indices showed moderate to strong biases. The application of the proposed approach is illustrated using a real data set collected from a population of Commerson's dolphin (Cephalorhynchus commersonii) in Patagonia Argentina. Finally, we discuss possible extensions of the proposed model and its applicability in animal behaviour and ecological studies.     

Airborne pollen of ornamental tree species in the NW of Spain

This study analyzed airborne pollen counts for the tree taxa most widely used for ornamental purposes in the northwestern Iberian Peninsula (Platanus, Cupressaceae, Olea, Myrtaceae, Cedrus, and Casuarina) at four sites (Vigo, Ourense, Santiago, and Lugo), using aerobiological data recorded over a long period (1993?C2007). The abundance and the temporal and spatial distribution of these pollen types were analyzed, and the influence of weather-related factors on airborne pollen counts was assessed. Platanus (in Ourense) and Olea (in Vigo) were the taxa contributing most to pollen counts. In general terms, the results may be taken as indicators of potential risk for pollen-allergy sufferers and therefore used in planning future green areas.     

Masting mediated by summer drought reduces acorn predation in Mediterranean oak forests

Temporally variable production of seed crops by perennial plants (masting) has been hypothesized to be a valuable mechanism in the reduction of seed predation by satiating and starving seed consumers. To achieve these benefits, coexisting species subjected to the same predator would benefit from a similar pattern of seeding fluctuation over time that could lead to a reduction in predation at the within-species level. We tested for the existence of an environmental factor enforcing synchrony in acorn production in two sympatric Mediterranean oaks (Quercus ilex and Q. humilis) and the consequences on within-species and between-species acorn predation, by monitoring 15 mixed forests (450 trees) over seven years. Acorn production in Q. ilex and Q. humilis was highly variable among years, with high population variability (CVp) values. The two species exhibited a very different pattern across years in their initial acorn crop size (sum of aborted, depredated, and sound acorns). Nevertheless, interannual differences in summer water stress modified the likelihood of abortion during acorn ripening and enforced within- and, particularly, between-species synchrony and population variability in acorn production. The increase in CVp from initial to mature acorn crop (after summer) accounted for 33% in Q. ilex, 59% in Q. humilis, and 60% in the two species together. Mean yearly acorn pre-dispersal predation by invertebrates was considerably higher in Q. humilis than in Q. ilex. Satiation and starvation of predators was recorded for the two oaks, and this effect was increased by the year-to-year variability in the size of the acorn crop of the two species combined. Moreover, at a longer time scale (over seven years), we observed a significant reduction in the mean proportion of acorns depredated for each oak and the variability in both species' acorn production combined. Therefore, our results demonstrate that similar patterns of seeding fluctuation over time in coexisting species mediated by an environmental cue (summer drought) may contribute to the reduction of the impact of seed predation at a within-species level. Future research should be aimed at addressing whether this process could be a factor assisting in the coexistence of Q. ilex and Q. humilis.     

Dust emission calculations in open storage piles protected by means of barriers, CFD and experimental tests

The importance of open mineral storage piles in bulk solids port terminals have increased considerably in recent years in Europe and USA (in Spain, great extensions of transoceanic ports are being made) to address the increasing demand of raw material importation due to local mining operation closure. These storage piles are affected by the climatologically processes and the dust emission to the atmosphere, causing repercussions to health and environmental, which is intimately related to the air velocity, according to USEPA studies, maximum ratio of dust emission emitted from CFD and software Ansys CFX 10.0 is determined. In addition, an emission variability study based on the pile distance of different height solid barriers is developed, reducing the emission to 66%. The studies have been contrasted by published investigations and industrial measurement.     

Compositional data analysis of smoke emissions from debris piles with low-density polyethylene

ABSTRACT

Data describing the composition of smoke are inherently multivariate and always non-negative parts of a whole. The data are relative and the information is contained in the ratios between parts of the composition. A prior analysis of smoke emissions produced from the burning of manzanita wood mixed with low-density polyethylene plastic applied traditional statistical methods to the compositional data and found no effect. The current paper applies compositional data techniques to these smoke emissions to determine if the prior analysis was accurate. Analysis of variance of the isometric log-ratios showed that LDPE significantly affected the CO₂ emission ratio for 8 of the 191 trace gases; this analysis showed none of the gases identified in the previous analysis were affected by LDPE. LDPE did not affect the CO₂ emission ratios for the alkanes, alkenes, alkynes, aldehydes, cycloalkanes, cycloalkenes, diolefins, ketones, MAHs, and PAHs. Compositional data analysis should be used to analyze smoke emissions data. Burning contaminant-free LDPE should produce emissions like wood.