Analysis of pore-fluid pressure gradient and effective vertical-stress gradient distribution in layered hydrodynamic systems

A theoretical analysis is carried out to investigate the pore-fluid pressure gradient and effective vertical-stress gradient distribution in fluid saturated porous rock masses in layered hydrodynamic systems. Three important concepts, namely the critical porosity of a porous medium, the intrinsic Fore-fluid pressure and the intrinsic effective vertical stress of the solid matrix, are presented and discussed. Using some basic scientific principles, we derive analytical solutions and explore the conditions under which either the intrinsic pore-fluid pressure gradient or the intrinsic effective vertical-stress gradient can be maintained at the value of the lithostatic pressure gradient. Even though the intrinsic pore-fluid pressure gradient can be maintained at the value of the lithostatic pressure gradient in a single layer, it is impossible to maintain it at this value in all layers in a layered hydrodynamic system, unless all layers have the same permeability and porosity simultaneously. However, the intrinsic effective vertical-stress gradient of the solid matrix can be maintained at a value close to the lithostatic pressure gradient in all layers in any layered hydrodynamic system within the scope of this study

Finite driving rate and anisotropy effects in landslide modeling

In order to characterize landslide frequency-size distributions and individuate hazard scenarios and their possible precursors, we investigate a cellular automaton where the effects of a finite driving rate and the anisotropy are taken into account. The model is able to reproduce observed features of landslide events, such as power-law distributions, as experimentally reported. We analyze the key role of the driving rate and show that, as it is increased, a crossover from power-law to non power-law behaviors occurs. Finally, a systematic investigation of the model on varying its anisotropy factors is performed and the full diagram of its dynamical behaviors is presented.Comment: 8 pages, 9 figure

Arsenic movement and fractionation in agricultural soils which received wastewater from an adjacent industrial site for 50 years

Arsenic (As) is an element with important environmental and human health implications due to its toxic properties. It is naturally occurring since it is contained in minerals, but it can also be enriched and distributed in the environment by anthropogenic activities. This paper reports on the historic As contamination of agricultural soils in one of the most important national relevance site for contamination in Italy, the so-called SIN Brescia-Caffaro, in the city of Brescia, northern Italy. These agricultural areas received As through the use of irrigation waters from wastewater coming from a factory of As-based pesticides (lead and calcium arsenates, sodium arsenite). Pesticide production started in 1920 and ended in the '70. Concentrations in the areas are generally beyond the legal threshold values for different soil uses and are up to >200 mg/kg. Arsenic contamination was studied to assess the long-time trend and the dynamics related to the vertical movement of As down to 1 m depth and its horizontal diffusion with surface irrigation in the entire field. Arsenic fractionation analysis (solid phase speciation by sequential extraction procedure) was also performed on samples collected from these areas and employed in greenhouse experiments with several plant species to evaluate the long-term contamination and the role of plant species in modifying As availability in soil. The results of this work can help in the evaluation of the conditions controlling the vertical transfer of As towards surface aquifers, the bioaccumulation likelihood in the agricultural food chain and the selection of sustainable remediation techniques such as phytoextraction

Evaluation of iron overload in nigrosome 1 via quantitative susceptibility mapping as a progression biomarker in prodromal stages of synucleinopathies

Idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies, such as Parkinson's disease (PD), which are characterized by the loss of dopaminergic neurons in substantia nigra, associated with abnormal iron load. The assessment of presymptomatic biomarkers predicting the onset of neurodegenerative disorders is critical for monitoring early signs, screening patients for neuroprotective clinical trials and understanding the causal relationship between iron accumulation processes and disease development. Here, we used Quantitative Susceptibility Mapping (QSM) and 7T MRI to quantify iron deposition in Nigrosome 1 (N1) in early PD (ePD) patients, iRBD patients and healthy controls and investigated group differences and correlation with disease progression. We evaluated the radiological appearance of N1 and analyzed its iron content in 35 ePD, 30 iRBD patients and 14 healthy controls via T2*-weighted sequences and susceptibility (χ) maps. N1 regions of interest (ROIs) were manually drawn on control subjects and warped onto a study-specific template to obtain probabilistic N1 ROIs. For each subject the N1 with the highest mean χ was considered for statistical analysis. The appearance of N1 was rated pathological in 45% of iRBD patients. ePD patients showed increased N1 χ compared to iRBD patients and HC but no correlation with disease duration, indicating that iron load remains stable during the early stages of disease progression. Although no difference was reported in iron content between iRBD and HC, N1 χ in the iRBD group increases as the disease evolves. QSM can reveal temporal changes in N1 iron content and its quantification may represent a valuable presymptomatic biomarker to assess neurodegeneration in the prodromal stages of PD

Pneumococcal Gene Complex Involved in Resistance to Extracellular Oxidative Stress

Streptococcus pneumoniae is a Gram-positive bacterium which is a member of the normal human nasopharyngeal flora but can also cause serious disease such as pneumonia, bacteremia, and meningitis. Throughout its life cycle, S. pneumoniae is exposed to significant oxidative stress derived from endogenously produced hydrogen peroxide (H2O2) and from the host through the oxidative burst. How S. pneumoniae, an aerotolerant anaerobic bacterium that lacks catalase, protects itself against hydrogen peroxide stress is still unclear. Bioinformatic analysis of its genome identified a hypothetical open reading frame belonging to the thiol-specific antioxidant (TlpA/TSA) family, located in an operon consisting of three open reading frames. For all four strains tested, deletion of the gene resulted in an approximately 10-fold reduction in survival when strains were exposed to external peroxide stress. However, no role for this gene in survival of internal superoxide stress was observed. Mutagenesis and complementation analysis demonstrated that all three genes are necessary and sufficient for protection against oxidative stress. Interestingly, in a competitive index mouse pneumonia model, deletion of the operon had no impact shortly after infection but was detrimental during the later stages of disease. Thus, we have identified a gene complex involved in the protection of S. pneumoniae against external oxidative stress, which plays an important role during invasive disease.

Contribution of peat compaction to relative sea-level rise within Holocene deltas

Modern and forecasted flooding of deltas is accelerated by subsidence of Holocene deposits. Subsidence caused by tectonics, isostasy, sediment compaction and anthropogenic processes, combined with eustatic sea-level rise, results in drowning and increased flood risk within densely populated deltas. Many deltaic sedimentary successions include substantial amounts of peat, which is highly compressible compared to clay, silt and sand. Peat compaction, therefore, may contribute considerably to total delta subsidence. Existing studies are inadequate for quantifying peat compaction across deltas. We present a numerical peat compaction model calibrated with an extensive field dataset. The model quantifies spatial and temporal trends in peat compaction within fluvial-dominated Holocene flood basin sequences of different compositions. Subsidence due to peat compaction is highly variable in time and space, with local rates of up to 15 mm/yr, depending on sedimentary sequence. This is extremely important information for developing sound delta management strategies. Artificial groundwater table lowering may cause substantial additional subsidence. Subsidence due to peat compaction might even exceed estimates of relative sea-level rise, and thus, may seriously increase the risk of delta drowning and human vulnerability to floodin

Design and modelling of an engineered bacteria-based, pressure-sensitive soil.

In this paper, we describe the first steps in the design of a synthetic biological system based on the use of genetically modified bacteria to detect elevated pressures in soils and respond by cementing soil particles. Such a system might, for example, enable a self- constructed foundation to form in response to load using engineered bacteria which could be seeded and grown in the soils. This process would reduce the need for large-scale excavations and may be the basis for a new generation of self-assembling and responsive bio-based materials. A prototype computational model is presented which integrates experimental data from a pressure sensitive gene within Escherichia coli bacteria with geotechnical models of soil loading and pore water pressure. The results from the integrated model are visualised by mapping expected gene expression values onto the soil volume. We also use our experimental data to design a two component system where one type of bacteria acts as a sensor and signals to another material synthesis bacteria. The simulation demonstrates the potential of computational models which integrate multiple scales from macro stresses in soils to the expression of individual genes to inform new types of design process. The work also illustrates the combination of in silico (silicon based computing) computation with in vivo (in the living) computation

Development of an estimative model for the optimal tack coat dosage based on aggregate gradation of hot mix asphalt pavements

In this work the performance of tack coats on asphalt pavement layers is analysed. Adjustment models based on experimental measurements were implemented, relating surface layer macro-texture and aggregate content larger than 8 mm. The best fits were obtained with a Gompertz model, which follows the expected physical macro-texture changes outside the test range. Shear strength was analysed, through prediction curves of each evaluated tack coat dosage, with an optimum tack coat performance for aggregate contents larger than 8 mm between 45% and 50%, and no relevant influence of the tack coat dosage used.The authors would like to acknowledge the support provided by the Technologic Research Construction Group (GITECO) and the Group of Roads of Santander at Cantabria University for the development of tests and samples. We would also like to thank the company Emilio Bolado S.L. and the Society for the Development of Cantabria Region (SODERCAN) for the material provided, and the DID Research Department from the Austral University of Chile for the support