Gaseous emissions during concurrent combustion of biomass and non-recyclable municipal solid waste

Background: Biomass and municipal solid waste offer sustainable sources of energy; for example to meet heat and electricity demand in the form of combined cooling, heat and power. Combustion of biomass has a lesser impact than solid fossil fuels (e. g. coal) upon gas pollutant emissions, whilst energy recovery from municipal solid waste is a beneficial component of an integrated, sustainable waste management programme. Concurrent combustion of these fuels using a fluidised bed combustor may be a successful method of overcoming some of the disadvantages of biomass (high fuel supply and distribution costs, combustion characteristics) and characteristics of municipal solid waste (heterogeneous content, conflict with materials recycling). It should be considered that combustion of municipal solid waste may be a financially attractive disposal route if a 'gate fee' value exists for accepting waste for combustion, which will reduce the net cost of utilising relatively more expensive biomass fuels. Results: Emissions of nitrogen monoxide and sulphur dioxide for combustion of biomass are suppressed after substitution of biomass for municipal solid waste materials as the input fuel mixture. Interactions between these and other pollutants such as hydrogen chloride, nitrous oxide and carbon monoxide indicate complex, competing reactions occur between intermediates of these compounds to determine final resultant emissions. Conclusions: Fluidised bed concurrent combustion is an appropriate technique to exploit biomass and municipal solid waste resources, without the use of fossil fuels. The addition of municipal solid waste to biomass combustion has the effect of reducing emissions of some gaseous pollutants

Estimation in a multiplicative mixed model involving a genetic relationship matrix

Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments

Intracellular connections between basal bodies promote the coordinated behavior of motile cilia

Hydrodynamic flow produced by multiciliated cells is critical for fluid circulation and cell motility. Hundreds of cilia beat with metachronal synchrony for fluid flow. Cilia-driven fluid flow produces extracellular hydrodynamic forces that cause neighboring cilia to beat in a synchronized manner. However, hydrodynamic coupling between neighboring cilia is not the sole mechanism that drives cilia synchrony. Cilia are nucleated by basal bodies (BBs) that link to each other and to the cell\u27s cortex via BB-associated appendages. The intracellular BB and cortical network is hypothesized to synchronize ciliary beating by transmitting cilia coordination cues. The extent of intracellular ciliary connections and the nature of these stimuli remain unclear. Moreover, how BB connections influence the dynamics of individual cilia has not been established. We show by focused ion beam scanning electron microscopy imaging that cilia are coupled both longitudinally and laterally in the ciliat

Genome-based trait prediction in multi- environment breeding trials in groundnut

Genomic selection (GS) can be an efficient and cost-effective breeding approach which captures both small- and large-effect genetic factors and therefore promises to achieve higher genetic gains for complex traits such as yield and oil content in groundnut. A training population was constituted with 340 elite lines followed by genotyping with 58 K ‘Axiom_Arachis’ SNP array and phenotyping for key agronomic traits at three locations in India. Four GS models were tested using three different random cross-validation schemes (CV0, CV1 and CV2). These models are: (1) model 1 (M1 = E + L) which includes the main effects of environment (E) and line (L); (2) model 2 (M2 = E + L + G) which includes the main effects of markers (G) in addition to E and L; (3) model 3 (M3 = E + L + G + GE), a naïve interaction model; and (4) model 4 (E + L + G + LE + GE), a naïve and informed interaction model. Prediction accuracy estimated for four models indicated clear advantage of the inclusion of marker information which was reflected in better prediction accuracy achieved with models M2, M3 and M4 as compared to M1 model. High prediction accuracies (> 0.600) were observed for days to 50% flowering, days to maturity, hundred seed weight, oleic acid, rust@90 days, rust@105 days and late leaf spot@90 days, while medium prediction accuracies (0.400–0.600) were obtained for pods/plant, shelling %, and total yield/plant. Assessment of comparative prediction accuracy for different GS models to perform selection for untested genotypes, and unobserved and unevaluated environments provided greater insights on potential application of GS breeding in groundnut

Microgels Formed by Spontaneous Click Chemistries Utilizing Microfluidic Flow Focusing for Cargo Release in Response to Endogenous or Exogenous Stimuli

Protein therapeutics have become increasingly popular for the treatment of a variety of diseases owing to their specificity to targets of interest. However, challenges associated with them have limited their use for a range of ailments, including the limited options available for local controlled delivery. To address this challenge, degradable hydrogel microparticles, or microgels, loaded with model biocargoes were created with tunable release profiles or triggered burst release using chemistries responsive to endogenous or exogeneous stimuli, respectively. Specifically, microfluidic flow-focusing was utilized to form homogenous microgels with different spontaneous click chemistries that afforded degradation either in response to redox environments for sustained cargo release or light for on-demand cargo release. The resulting microgels were an appropriate size to remain localized within tissues upon injection and were easily passed through a needle relevant for injection, providing means for localized delivery. Release of a model biopolymer was observed over the course of several weeks for redox-responsive formulations or triggered for immediate release from the light-responsive formulation. Overall, we demonstrate the ability of microgels to be formulated with different materials chemistries to achieve various therapeutic release modalities, providing new tools for creation of more complex protein release profiles to improve therapeutic regimens