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It is concluded that the spatial spread of the landfill gas in the gas distribution layer is predominantly affected by texture and compaction of the overlying methane oxidation layer. In terms of methane oxidation system design, the choice of material and construction method have more impact on gas permeability than seasonal changes in soil moisture in moderate climates. Furthermore, air filled porosity on its own is not adequate to estimate the effective permeability of loamy sand for methane oxidation layers. Further research should address the estimation of effective gas permeability based upon soil texture, bulk density and soil moisture combined. Gaseous potassium chloride (KCl) that constitutes a relatively large portion of the combustion gas of municipal solid waste can condense on the surface of boiler heat exchanger tubes, causing severe corrosion attacks. To reduce the chlorine-induced high-temperature corrosion, sulfate-based additives have been used. In this study, a two-step numerical procedure is proposed to quickly predict the effect of the injection of sulfate-based additives on the removal of gaseous KCl. A computational fluid dynamics (CFD) simulation is first carried out to obtain the temperature distribution. Then, the thermal decomposition of sulfate additives, sulfation of gaseous KCl, and condensation of K2SO4 are calculated to predict the species concentration profiles at the temperature conditions given by the CFD simulation. After validation with a laboratory-scale experiment using [Formula see text] , the procedure is applied to a pilot-scale boiler to examine the effects of [Formula see text] , [Formula see text] , and [Formula see text] . The calculation results show that each additive has an optimal injection temperature range approximately 800 °C for [Formula see text] and 1000 °C for both [Formula see text] and [Formula see text] , which are consistent with the values reported in the literature. The expressions for the stoichiometric KCl removal efficiency of each additive are derived and compared with the calculated efficiencies. Due to insufficient land and energy resources, municipal solid waste incineration plants are used in many countries as a means of addressing the growing volumes of generated municipal solid waste and to recover energy resources. Taiwan’s government allows the private sector to offer municipal solid waste treatment services and electricity to the public. Revenue from the sale of electricity is an important source of income for municipal solid waste incineration plants. Although several studies have examined the technical efficiency of municipal solid waste incineration plants, previous studies have not measured or deconstructed the dynamic electricity revenue inefficiency of incineration plants. For our purposes, this paper presents a data envelopment analysis model that measures and deconstructs the electricity revenue inefficiency while taking into account the slacks and dynamic factors in measuring technical inefficiency levels within the context of assessing MSW incineration plants in Taiwan. This study applied the proposed model to analyze the electricity revenue inefficiency of the municipal solid waste incineration plants in Taiwan over the period of 2013-2018. In this study, we found that the main source of electricity revenue inefficiency is the technical waste from electricity production. Our empirical analysis reveals that the electricity technical, revenue and allocative efficiencies of public plants are lower than those of private plants. Dorsomedial prefrontal cortex (dmPFC) and hippocampus (HPC) are thought to play complementary roles in a spatial working memory and decision-making network, where spatial information from HPC informs representations in dmPFC, and contextual information from dmPFC biases how HPC recalls that information. ZD1839 clinical trial We recorded simultaneously from neural ensembles in rodent dmPFC and HPC as rats performed a rule-switching task, and found that ensembles in dmPFC and HPC simultaneously encoded task contingencies and other time-varying information. While ensembles in HPC transitioned to represent new contingencies at the same time as rats updated their strategies to be consistent with the new contingency, dmPFC ensembles transitioned earlier. Neural representations of other time-varying information also changed faster in dmPFC than in HPC. Our results suggest that HPC and dmPFC represent contingencies while simultaneously representing other information which changes over time, and that this contextual information is integrated into hippocampal representations more slowly than in dmPFC. Although pesticides are widely used in agriculture, industry and households, they pose a risk to human health and ecosystems. Based on target organisms, the main types of pesticides are herbicides, insecticides and fungicides, of which herbicides accounted for 46% of the total pesticide usage worldwide. The movement of pesticides into water bodies occurs through run-off, spray drift, leaching, and sub-surface drainage, all of which have negative impacts on aquatic environments and humans. We sought to define the critical factors affecting the fluxes of contaminants into receiving waters. We also aimed to specify the feasibility of using sorbents to remove pesticides from waterways. In Karun River in Iran (1.21 × 105 ng/L), pesticide concentrations are above regulatory limits. The concentration of pesticides in fish can reach 26.1 × 103 μg/kg, specifically methoxychlor herbicide in Perca fluviatilis in Lithuania. During the last years, research has focused on elimination of organic pollutants, such as pesticides, from aqueous solution. Pesticide adsorption onto low-cost materials can effectively remediate contaminated waters. In particular, nanoparticle adsorbents and carbon-based adsorbents exhibit high performance (nearly 100%) in removing pesticides from water bodies. There is a knowledge gap for the application of one-dimensional graphene in the adsorption process. Our hypothesis was based on the fact that graphene oxide nanoribbons (GONRs) as one-dimensional graphene with more desired edges and specific surface area than other carbonaceous nanomaterials have more oxygen containing functional groups (active sites) on their edges and basal planes and therefore are more capable in adsorption of pollutants. In this regard, we synthesized GONRs by unzipping of multi-walled carbon nanotubes (MWCNTs) and investigated the adsorption behavior of GONRs by ultrasonic-assisted adsorptive removal of As(V) and Hg(II) ions from aqueous solution. The obtained results showed that As(V) ions are more favorably adsorbed onto the GONRs than Hg(II) ions and with increasing initial As(V) and Hg(II) ions concentration to 300 ppm, the equilibrium adsorption uptake of the synthesized GONRs increases to 155.61 and 33.02 mg/g for As(V) and Hg(II) ions, respectively through a rapid separation process in just 12 min.