Monitoring Biofilm Thickness Using A Non-Destructive, On-Line, Electrical Capacitance Technique

Abstact The present study was designed to evaluate indirect, non-invasive, on-line measurement of biofilm thickness using an electrical capacitance technique. Several assays were carried out and the results showed that, at a frequency of 1 kHz, electrical capacitance could be used to measure biofilm thickness indirectly (with a correlation coefficient of 0.9495). The reproducibility revealed by the assays was also highly satisfactory.However, in contrast to what was expected, there was an inverse relationship between electrical capacitance and biofilm thickness, i.e. electrical capacitance diminished with the increase in the biofilm thickness.The tests were also carried out at different frequencies (1 kHz, 10 kHz and 100 kHz)     

Preparation of 2-mercaptobenzothiazole-derivatized mesoporous silica and removal of Hg(ii) from aqueous solution

Mesoporous silicas (SBA-15 and MCM-41) have been functionalized by two different methods. Using the heterogeneous route the silylating agent, 3-chloropropyltriethoxysilane, was initially immobilized onto the mesoporous silica surface to give the chlorinated mesoporous silica Cl-SBA-15 or Cl-MCM-41. In a second reaction a multifunctionalized N,S donor compound (2-mercaptobenzothiazol) was incorporated to obtain the functionalized silicas denoted as MBT-SBA-15-Het and MBT-MCM-41-Het. Using the homogeneous route, the functionalization was achieved via the one step reaction of the mesoporous silica with an organic ligand containing the chelating functions, to give the modified mesoporous silicas denoted as MBT-SBA-15-Hom or MBT-MCM-41-Hom. The functionalized mesoporous silicas were employed as adsorbents for the regeneration of aqueous solutions at pH 6 contaminated with Hg(ii) at room temperature. Results obtained indicate that mercury adsorption was higher in the mesoporus silicas prepared by the homogeneous method, and the maximum adsorption value (0.24 +/- 0.02 mmol Hg(ii) g(-1)) was obtained for MBT-SBA-15-Hom. The chemically stability in acid medium of the functionalized silicas, possibility its regeneration washing with concentrate HCl, resulting in the reuse of the adsorbent material for several cycles.     

Variation in posture quality across musical instruments and its impact during performances

Objective. Bad posture increases the risk that a musician may suffer from musculoskeletal disorders. This study compared posture quality required by different instruments or families of instruments. Methods. Using an ad-hoc postural observation instrument embracing 11 postural variables, four experts evaluated the postures of 100 students attending a Spanish higher conservatory of music. Results. The agreement of the experts’ evaluations was statistically confirmed by a Cohen's κ value between 0.855 and 1.000 and a Kendall value between 0.709 and 1.000 (p?χ² tests revealed significant association between instrument families and seated posture with respect to pelvic attitude, dorsal curvature and head alignment in both sagittal and frontal planes. This analysis also showed an association between instrument families and standing posture with respect to the frontal plane of the axis of gravity, pelvic attitude, head alignment in the frontal plane, the sagittal plane of the shoulders and overall posture. Conclusions. While certain postural defects appear to be common to all families of instruments, others are more characteristic of some families than others. The instrument associated with the best posture quality was the bagpipe, followed by percussion and strings.     

Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

Air Quality Modeling Using the PSO-SVM-Based Approach,MLP Neural Network,and M5 Model Tree in the Metropolitan Area of Oviedo (Northern Spain)

The main aim of this study was to construct several regression models of air quality using techniques based on the statistical learning, in the metropolitan area of Oviedo, in northern Spain. In this research, a hybrid particle swarm optimization-based evolutionary support vector regression is implemented to predict the air quality from the experimental dataset (specifically, nitrogen oxides, carbon monoxide, sulfur dioxide, ozone, and dust) collected from 2013 to 2015 in the metropolitan area of Oviedo. Furthermore, a multilayer perceptron network (MLP) and the M5 model tree were also fitted to the experimental dataset for comparison purposes. Finally, the predicted results show that the hybrid proposed model is more robust than the MLP and M5 model tree prediction methods in terms of statistical estimators and testing performances.     

Carbon stocks and losses to deforestation in protected areas in Brazilian Amazonia

Regional Environmental Change - By 2014 approximately 2.2 million km2 (~43%) of Brazil’s Legal Amazonia region had been incorporated into an extensive network of 718 protected areas, which...     

Influence of community-based natural resource management strategies in the resilience of social-ecological systems

Different social-ecological systems around the world are managed under community-based natural resource management (CBNRM) strategies. This paper analyses how CBNRM strategies influence the resilience of social-ecological systems to the disturbances they face, drawing upon the experience of three Latin American cases (two in Mexico and one in Colombia). The cases differ in their CBNRM approach and in the time these governance systems have been in place. By using a mixed-method approach, we review the socio-ecological history and describe each CBNRM characteristics. We then assess their resilience to socioeconomic and environmental disturbances through a set of indicators. We found that CBNRM strategies influence positively and negatively resilience and that internal decisions might address important threats. On the positive side, the social-ecological systems with longer tradition of CBNRM and more local buy-in of commonly agreed objectives appear to be more resilient to environmental challenges. But, internal governance factors such as power imbalances, poor income distribution, and gender inequities linked to CBNRM undermine resilience and foster out migration. Finally, communities appear to have limited capacities to cope with external disturbances such as global drivers of change or national policies that negatively affect their social-ecological resilience.

     

Correction to: Influence of community-based natural resource management strategies in the resilience of social-ecological systems

Regional Environmental Change - The published online version contains mistake. Author name was incorrectly captured. Instead of Maria del Mar Delgado-Serrano was incorrectly captured as Ma del Mar...     

From mixed farming to intensive agriculture: energy profiles of agriculture in Quebec,Canada, 1871–2011

Regional Environmental Change - This article presents an energy analysis of Quebec agroecoystems at five periods of time: 1871, 1931, 1951, 1981, and 2011, calculating for each year the various...     

Trees on the move: using decision theory to compensate for climate change at the regional scale in forest social-ecological systems

Regional Environmental Change - The adaptation of social-ecological systems such as managed forests depends largely on decisions taken by forest managers who must choose among a wide range of...