Landfill cap models under simulated climate change precipitation::Impacts of cracks and root growth

Desiccation crack formation is a key process that needs to be understood in assessment of landfill cap performance under anticipated future climate change scenarios. The objectives of this study were to examine: (a) desiccation cracks and impacts that roots may have on their formation and resealing, and (b) their impacts on hydraulic conductivity under anticipated climate change precipitation scenarios. Visual observations, image analysis of thin sections and hydraulic conductivity tests were carried out on cores collected from two large-scale laboratory trial landfill cap models (∼80 × 80 × 90 cm) during a year of four simulated seasonal precipitation events. Extensive root growth in the topsoil increased percolation of water into the subsurface, and after droughts, roots grew deep into low-permeability layers through major cracks which impeded their resealing. At the end of 1 year, larger cracks had lost resealing ability and one single, large, vertical crack made the climate change precipitation model cap inefficient. Even though the normal precipitation model had developed desiccation cracks, its integrity was preserved better than the climate change precipitation model.

The role of SRC-CAS interactions in cellular transformation:ectopic expression of the carboxy terminus of CAS inhibits SRC-CAS interaction but has no effect on cellular transformation

Several lines of evidence indicate that the adapter molecule p130CAS (crk-associated substrate (CAS)) is required for src-mediated cellular transformation. CAS has been shown to be heavily tyrosine-phosphorylated in src-transformed cells, and genetic variants of src that are deficient in CAS binding are also unable to mediate cellular transformation. In this report, we investigated whether CAS phosphorylation and/or its association with src are required elements of the transformation process. Expression of the carboxy-terminal src binding domain of CAS in Rat 1 fibroblasts expressing a temperature-sensitive allele of v-src inhibited the formation of src-CAS complexes and also inhibited tyrosine phosphorylation of CAS. However, expression of this protein had no effect on morphological transformation, src-mediated actin rearrangements, or anchorage-independent growth of these cells when grown at the src-permissive temperature. Thus, the ability of activated src to mediate cellular transformation is either largely independent of endogenous CAS phosphorylation and/or its association with CAS or, alternatively, the carboxy-terminus of CAS may substitute for endogenous CAS in the process of src-mediated transformation.

The identification of p130cas-binding proteins and their role in cellular transformation

Adaptor proteins play an important role in signal transduction by regulating the establishment and maintenance of functionally important protein complexes. A recently described member of this group of proteins is p130cas (CAS), which contains numerous sequence motifs predicted to be involved in mediating protein-protein interactions. We propose that adaptor molecules like CAS may help determine the response of a cell to a particular signal by interacting with specific subsets of cellular proteins. To test this hypothesis, we have identified potential binding partners of CAS that may play a rote in cellular transformation by the oncoproteins v-SRC and/or v-CRK. We show that individual domains of CAS associate with specific subsets of proteins in vitro, and that many of these interactions are dependent on the state of tyrosine-phosphorylation of CAS. Sequences necessary for interacting with the focal adhesion kinase pp125FAK (FAK), v-SRC and v-CRK have been mapped to distinct regions of CAS. In addition, the identification of a number of putative CAS-binding partners that are present in crk-transformed cell extracts but undetectable in normal and src-transformed cell extracts supports a model in which unique protein complexes are formed in response to different signals.

Can a carbon nano-coating resist metallic phase transformation in silicon substrate during nanoimpact?

Nanomechanical response of a silicon specimen coated with a sp3 crystalline carbon coating (1.8 nm thickness) was investigated using MD simulation. A sharp conical rigid tip was impacted at the speed of 50 m/sec up to a depth of ~80% of the coating thickness. Unlike pure silicon specimen, no metallic phase transformation was observed i.e. a thin coating was able to resist Si-I to Si-II metallic phase transformation signifying that the coating could alter the stress distribution and thereby the contact tribology of the substrate. The stress state of the system, radial distribution function and the load-displacement curve were all aligned with above observations

Localized Flux Maxima of Arsenic, Lead, and Iron around Root Apices in Flooded Lowland Rice

In wetland-adapted plants, such as rice, it is typically root apexes, sites of rapid entry for water/nutrients, where radial oxygen losses (ROLs) are highest. Nutrient/toxic metal uptake therefore largely occurs through oxidized zones and pH microgradients. However, the processes controlling the acquisition of trace elements in rice have been difficult to explore experimentally because of a lack of techniques for simultaneously measuring labile trace elements and O2/pH. Here, we use new diffusive gradients in thin films (DGT)/planar optode sandwich sensors deployed in situ on rice roots to demonstrate a new geochemical niche of greatly enhanced As, Pb, and Fe(II) mobilization into solution immediately adjacent to the root tips characterized by O2 enrichment and low pH. Fe(II) mobilization was congruent to that of the peripheral edge of the aerobic root zone, demonstrating that the Fe(II) mobilization maximum only developed in a narrow O2 range as the oxidation front penetrates the reducing soil. The Fe flux to the DGT resin at the root apexes was 3-fold higher than the anaerobic bulk soil and 27 times greater than the aerobic rooting zone. These results provide new evidence for the importance of coupled diffusion and oxidation of Fe in modulating trace metal solubilization, dispersion, and plant uptake.

Synergy Between an Improved Covariate Unit Root Test and Cross-sectionally Dependent Panel Data Unit Root Tests, with two Applications

This paper proposes the use of an improved covariate unit root test which exploits the cross-sectional dependence information when the panel data null hypothesis of a unit root is rejected. More explicitly, to increase the power of the test, we suggest the utilization of more than one covariate and offer several ways to select the ‘best’ covariates from the set of potential covariates represented by the individuals in the panel. Employing our methods, we investigate the Prebish-Singer hypothesis for nine commodity prices. Our results show that this hypothesis holds for all but the price of petroleum.

Determinants of root-associated fungal communities within Asteraceae in a semi-arid grassland

Summary

1.While plant–fungal interactions are important determinants of plant community assembly and ecosystem functioning, the processes underlying fungal community composition are poorly understood.
2.Here, we studied for the first time the root-associated eumycotan communities in a set of co-occurring plant species of varying relatedness in a species-rich, semi-arid grassland in Germany. The study system provides an opportunity to evaluate the importance of host plants and gradients in soil type and landscape structure as drivers of fungal community structure on a relevant spatial scale. We used 454 pyrosequencing of the fungal internal transcribed spacer region to analyse root-associated eumycotan communities of 25 species within the Asteraceae, which were sampled at different locations within a soil type gradient. We partitioned the variance accounted for by three predictors (host plant phylogeny, spatial distribution and soil type) to quantify their relative roles in determining fungal community composition and used null model analyses to determine whether community composition was influenced by biotic interactions among the fungi.
3.We found a high fungal diversity (156 816 sequences clustered in 1100 operational taxonomic units (OTUs)). Most OTUs belonged to the phylum Ascomycota (35.8%); the most abundant phylotype best-matched Phialophora mustea. Basidiomycota were represented by 18.3%, with Sebacina as most abundant genus. The three predictors explained 30% of variation in the community structure of root-associated fungi, with host plant phylogeny being the most important variance component. Null model analysis suggested that many fungal taxa co-occurred less often than expected by chance, which demonstrates spatial segregation and indicates that negative interactions may prevail in the assembly of fungal communities.
4.Synthesis. The results show that the phylogenetic relationship of host plants is the most important predictor of root-associated fungal community assembly, indicating that fungal colonization of host plants might be facilitated by certain plant traits that may be shared among closely related plant species.

Root Cause Analysis by a Combined Sparse Classification and Monte Carlo Approach

Classification methods with embedded feature selection capability are very appealing for the analysis of complex processes since they allow the analysis of root causes even when the number of input variables is high. In this work, we investigate the performance of three techniques for classification within a Monte Carlo strategy with the aim of root cause analysis. We consider the naive bayes classifier and the logistic regression model with two different implementations for controlling model complexity, namely, a LASSO-like implementation with a L1 norm regularization and a fully Bayesian implementation of the logistic model, the so called relevance vector machine. Several challenges can arise when estimating such models mainly linked to the characteristics of the data: a large number of input variables, high correlation among subsets of variables, the situation where the number of variables is higher than the number of available data points and the case of unbalanced datasets. Using an ecological and a semiconductor manufacturing dataset, we show advantages and drawbacks of each method, highlighting the superior performance in term of classification accuracy for the relevance vector machine with respect to the other classifiers. Moreover, we show how the combination of the proposed techniques and the Monte Carlo approach can be used to get more robust insights into the problem under analysis when faced with challenging modelling conditions.

BUCKLED LAYER STRUCTURE FOR ATOMIC ADSORPTION ON W(100) - THE (ROOT-2X-ROOT-2)R45-DEGREES NITROGEN STRUCTURE FROM ATLEED

Adsorption of 0.5 monolayer of N adatoms on W{100} results in a sharp (root 2 X root 2)R45 degrees LEED pattern. The only previous quantitative LEED study of this system gave a simple overlayer model with a Pendry R-factor of 0.55. An exhaustive search has been made of possible structures, including a novel vacancy reconstruction, displacive reconstructions and underlayer adsorption. From this work a new overlayer structure is derived with an R(p) value of 0.22, displaying a considerable buckling of 0.27 +/- 0.05 Angstrom within the second W layer and consequently involving large changes in the interlayer spacings of the surface. The N adatom is pseudo-five-fold coordinated to the W surface, bonding to a second-layer W atom with a nearest-neighbour bond length of 2.13 Angstrom and with the four next-nearest-neighbour W atoms in the surface plane at 2.27 Angstrom. The structure does not resolve the work function anomaly observed on this surface.