Interactions of inorganic oxide nanoparticles with sewage biosolids

The use of nanoparticles (NPs) in manufacturing continues to increase despite the growing concern over their potential environmental and health effects. Understanding the interaction of NPs and sewage sludge is crucial for determining the ultimate fate of NPs released to municipal wastewater treatment plants (WWTPs) as those interactions will determine whether the bulk of the material is retained in the sludge or released in the effluent stream. Analyzing the affinity of aluminum oxide, cerium oxide, and silicon oxide NPs, which are commonly used in semiconductor manufacturing processes, for biosolids used in municipal WWTPs provides a basis for estimating their removal efficiency. Batch studies were performed and the NPs were shown to partition onto the cellular surface. At the maximum equilibrium values tested (75-92 mg nanoparticles/L), the concentration of Al(2)O(3), CeO(2) and SiO(2) associated with the sludge was 137, 238, and 28 mg/g-sludge VSS, respectively. These results suggest that electrostatic interactions play a major role in determining NP association with biosolids.     

Influence of photoperiod on carbon dioxide and methane emissions from two pilot-scale stabilization ponds

Greenhouse gas (GHG) emissions (CO(2), CH(4)) from pilot-scale algal and duckweed-based ponds (ABP and DBP) were measured using the static chamber methodology. Daylight and nocturnal variations of GHG and wastewater characteristics (e.g. chemical oxygen demand (COD), pH) were determined via sampling campaigns during midday (12:30-15:30) and midnight (00:30-03:30) periods. The results showed that under daylight conditions in ABP median emissions were -232 mg CO(2) m(-2) d(-1) and 9.9 mg CH(4) m(-2) d(-1), and in DBP median emissions were -1,654.5 mg CO(2) m(-2) d(-1) and 71.4 mg CH(4) m(-2) d(-1), respectively. During nocturnal conditions ABP median emissions were 3,949.9 mg CO(2) m(-2) d(-1), 12.7 mg CH(4) m(-2) d(-1), and DBP median emissions were 5,116 mg CO(2) m(-2) d(-1), 195.2 mg CH(4) m(-2) d(-1), respectively. Once data measured during daylight were averaged together with nocturnal data the median emissions for ABP were 1,566.8 mg CO(2) m(-2) d(-1) and 72.1 mg CH(4) m(-2) d(-1), whilst for DBP they were 3,016.9 mg CO(2) m(-2) d(-) and 178.9 mg CH(4) m(-2) d(-1), respectively. These figures suggest that there were significant differences between CO(2) emissions measured during daylight and nocturnal periods (p < 0.05). This shows a sink-like behaviour for both ABP and DBP in the presence of solar light, which indicates the influence of photosynthesis in CO(2) emissions. On the other hand, the fluxes of CH(4) indicated that DBP and ABP behave as net sources of CH(4) during day and night, although higher emissions were observed from DBP. Overall, according to the compound average (daylight and nocturnal emissions) both ABP and DBP systems might be considered as net sources of GHG.     

A VNS heuristic for escaping local extrema entrapment in normalized cut clustering

Normalized cut is one of the most popular graph clustering criteria. The main approaches proposed for its resolution are spectral clustering methods and a multilevel approach of Dhillon et al. (TPAMI 29:1944–1957, 2007), called graclus. Their aim is to obtain good solutions in a small amount of time for large instances. Metaheuristics are general frameworks for stochastic searches often employed in global optimization to improve the solutions obtained by other heuristics. Variable neighborhood search (VNS) is a metaheuristic which exploits systematically the idea of neighborhood change during the search. In this paper, we propose a VNS heuristic for normalized cut segmentation. Computational experiments show that in most cases this VNS heuristic improves significantly, and in moderate time, the solutions obtained by the current state-of-the-art algorithms, i.e., graclus and a spectral method proposed by Yu and Shi (ICCV, 2003).     

Modelling and characterization of AlN-actuated microcantilevers vibrating in the first in-plane mode

The characterization of the first in-plane mode of aluminum nitride-actuated piezoelectric microcantilevers was carried out by using electrical and optical techniques. The top electrode of the cantilever was specifically designed to allow for an efficient electrical actuation of these in-plane modes. In order to confirm the in-plane nature of the modal vibration, the detection of the electrically induced movement was performed optically with the help of a stroboscopic microscope. In parallel, resonances were also measured electrically by means of an impedance analyzer. The quality factor and the resonant frequencies of the in-plane modes were estimated from the corresponding measurement data when applying both detection techniques. Our results show quality factor values as high as 3,000 for the first in-plane mode in air.     

Combined Petri net modelling and AI-based heuristic hybrid search for flexible manufacturing systems—part II. Heuristic hybrid search

This two-part paper presents modelling and scheduling approaches of flexible manufacturing systems using Petri nets (PNs) and artificial intelligence (AI)-based heuristic search methods. In Part I, PN-based modelling approaches and basic AI-based heuristic search algorithms were presented. In Part II, a new heuristic function that exploits PN information is proposed. Heuristic information obtained from the PN model is used to dramatically reduce the search space. This heuristic is derived from a new concept, the resource cost reachability matrix, which builds on the properties of B-nets proposed in Part I. Two hybrid search algorithms, (1) an approach to model dispatching rules using analysis information provided by the PN simulation and (2) an approach of the modified stage-search algorithm, are proposed to reduce the complexity of large systems. A random problem generator is developed to test the proposed methods. The experimental results show promising results.     

Immunohistochemistry of neuronal nitric oxide synthase and protein nitration in the striatum of the aged rat

To ascertain the possible implications of the nitric oxide (NO*) producing system in striatal senescence, and by using immunohistochemistry and image-processing approaches, we describe the presence of the enzyme nitric oxide synthase (NOS), the NADPH-diaphorase (NADPH-d) histochemical marker, and nitrotyrosine-derived complexes (N-Tyr) in the striatum of adult and aged rats. The results showed neuronal NOS immunoreactive (nNOS-IR) aspiny medium-sized neurons and nervous fibres in both age groups, with no variation in the percentage of immunoreactive area but a significant decrease in the intensity and in the number of somata with age, which were not related to the observed increase with age of the striatal bundles of the white matter. In addition, NADPH-d activity was detected in neurons with morphology similar to that of the nNOS-IR cells; a decrease in the percentage of area per field and in the number of cells, but an increase in the intensity of staining for the NADPH-d histochemical marker, were detected with age. The number of neuronal NADPH-d somata was higher than for the nNOS-IR ones in both age groups. Moreover, N-Tyr-IR complexes were observed in cells (neurons and glia) and fibres, with a significant increase in the percentage of the area of immunoreaction, related to the increase of white matter, but a decrease in intensity for the aged group. On the other hand, we did not detect the inducible isoform (iNOS) either in adult or in aged rats. Taken together, these results support the contention that NADPH-d staining is not such an unambiguous marker for nNOS, and that increased protein nitration may participate in striatal aging.     

A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments

The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %.