993 resultados para Soil-pile Interaction


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The present study was carried out in two different areas of Province of Cordoba, Argentina, where there was a suspicious of endemic mycosis. The previous data were the presence of a clinical case of pulmonary cryptococcosis in one area (Alta Gracia) and the previous findings of a high incidence of coccidioidin and cryptococcin reactors in the population of the second one (Villa Dolores). In both areas soil samples for fungi were studied and Cryptococcus neoformans was found in 2/25 samples from Alta Gracia. In Villa Dolores Coccidioides immitis was isolated in 2/40 samples, and C. neoformans in 1/40 samples. Delayed hypersensitivity test with cryptococcin was determined in the population from Alta Gracia and it was found to be 5.3%. Positive cutaneous tests with coccidioidin (33.8%) and cryptococcin (31.9%) in Villa Dolores were obtained. With these findings two endemic areas of systemic mycoses in Cordoba, Argentina were delimited.

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In order to decrease the risk of severe wildfire, prescribed fire has recently been adopted in Portugal and elsewhere in the Mediterranean as a major tool for reducing the fuel load instead of manual or mechanical removal of vegetation. There has been some research into its impact on soils in shrublands and grasslands, but to date little research has been conducted in forested areas in the region. As a result, the impact of prescribed fire on the physico-chemical soil characteristics of forest soils has been assumed to be minimal, but this has not been demonstrated. In this study, we present the results of a monitoring campaign of a detailed pre- and post-prescribed fire assessment of soil properties in a long-unburnt P. pinaster plantation, NW Portugal. The soil characteristics examined were pH, total porosity, bulk density, moisture content, organic matter content and litter/ash quantity. The results show that there was no significant impact on the measured soil properties, the only effect being confined to minor changes in the upper 1 cm of soil. We conclude that provided the fire is carried out according to strict guidelines in P. pinaster forest, a minimal impact on soil properties can be expected.

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The amoebae's cytotoxicity test and the amoebae's lysis test were used to show possible interactions between rheumatoid factor (RF) and Entamoeba histolytica. Amoebae's cytotoxic activity (ACA) was inhibited by affinity chromatography purified antiamoebae rabbit IgG (RIgG). Enhanced inhibition could be demonstrated with RIgG plus RF. But the same marked inhibition of ACA could be seen when replacing RF by heat inactivated normal human serum as a control. About 50% amoebae's lysis occurred when amoebae were brought together with native normal human serum (NNHS) as a source of complement. Amoebae's lysis increased to 60% when incubated with NHS plus human antiamoebae antibodies. No further augmentation could be obtained by the addition of RF. Using RIgG instead of human antibodies the lysis rate did not increase. Incubation of amoebae, NNHS, RIgG and RF even reduced amoebae's lysis. RF neither has an effect on ACA nor on complement mediated AL in vitro.

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Portuguese northern forests are often and severely affected by wildfires during the summer season. Some preventive actions, such as prescribed (or controlled) burnings and clear-cut logging, are often used as a measure to reduce the occurrences of wildfires. In the particular case of Serra da Cabreira forest, due to extremely difficulties in operational field work, the prescribed (or controlled) burning technique is the the most common preventive action used to reduce the existing fuel load amount. This paper focuses on a Fuzzy Boolean Nets analysis of the changes in some forest soil properties, namely pH, moisture and organic matter content, after a controlled fire, and on the difficulties found during the sampling process and how they were overcome. The monitoring process was conducted during a three-month period in Anjos, Vieira do Minho, Portugal, an area located in a contact zone between a two-mica coarse-grained porphyritic granite and a biotite with plagioclase granite. The sampling sites were located in a spot dominated by quartzphyllite with quartz veins whose bedrock is partially altered and covered by slightly thick humus, which maintains low undergrowth vegetation.

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Prescribed fire is a common forest management tool used in Portugal to reduce the fuel load availability and minimize the occurrence of wildfires. In addition, the use of this technique also causes an impact to ecosystems. In this presentation we propose to illustrate some results of our project in two forest sites, both located in Northwest Portugal, where the effect of prescribed fire on soil properties were recorded during a period of 6 months. Changes in soil moisture, organic matter, soil pH and iron, were examined by Principal Component Analysis multivariate statistics technique in order to determine impact of prescribed fire on these soil properties in these two different types of soils and determine the period of time that these forest soils need to recover to their pre-fire conditions, if they can indeed recover. Although the time allocated to this study does not allow for a widespread conclusion, the data analysis clearly indicates that the pH values are positively correlated with iron values at both sites. In addition, geomorphologic differences between both sampling sites, Gramelas and Anjos, are relevant as the soils’ properties considered have shown different performances in time. The use of prescribed fire produced a lower impact in soils originated from more amended bedrock and therefore with a ticker humus covering (Gramelas) than in more rocky soils with less litter covering (Anjos) after six months after the prescribed fire occurrence.

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Mathematical models and statistical analysis are key instruments in soil science scientific research as they can describe and/or predict the current state of a soil system. These tools allow us to explore the behavior of soil related processes and properties as well as to generate new hypotheses for future experimentation. A good model and analysis of soil properties variations, that permit us to extract suitable conclusions and estimating spatially correlated variables at unsampled locations, is clearly dependent on the amount and quality of data and of the robustness techniques and estimators. On the other hand, the quality of data is obviously dependent from a competent data collection procedure and from a capable laboratory analytical work. Following the standard soil sampling protocols available, soil samples should be collected according to key points such as a convenient spatial scale, landscape homogeneity (or non-homogeneity), land color, soil texture, land slope, land solar exposition. Obtaining good quality data from forest soils is predictably expensive as it is labor intensive and demands many manpower and equipment both in field work and in laboratory analysis. Also, the sampling collection scheme that should be used on a data collection procedure in forest field is not simple to design as the sampling strategies chosen are strongly dependent on soil taxonomy. In fact, a sampling grid will not be able to be followed if rocks at the predicted collecting depth are found, or no soil at all is found, or large trees bar the soil collection. Considering this, a proficient design of a soil data sampling campaign in forest field is not always a simple process and sometimes represents a truly huge challenge. In this work, we present some difficulties that have occurred during two experiments on forest soil that were conducted in order to study the spatial variation of some soil physical-chemical properties. Two different sampling protocols were considered for monitoring two types of forest soils located in NW Portugal: umbric regosol and lithosol. Two different equipments for sampling collection were also used: a manual auger and a shovel. Both scenarios were analyzed and the results achieved have allowed us to consider that monitoring forest soil in order to do some mathematical and statistical investigations needs a sampling procedure to data collection compatible to established protocols but a pre-defined grid assumption often fail when the variability of the soil property is not uniform in space. In this case, sampling grid should be conveniently adapted from one part of the landscape to another and this fact should be taken into consideration of a mathematical procedure.

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In the current context of serious climate changes, where the increase of the frequency of some extreme events occurrence can enhance the rate of periods prone to high intensity forest fires, the National Forest Authority often implements, in several Portuguese forest areas, a regular set of measures in order to control the amount of fuel mass availability (PNDFCI, 2008). In the present work we’ll present a preliminary analysis concerning the assessment of the consequences given by the implementation of prescribed fire measures to control the amount of fuel mass in soil recovery, in particular in terms of its water retention capacity, its organic matter content, pH and content of iron. This work is included in a larger study (Meira-Castro, 2009(a); Meira-Castro, 2009(b)). According to the established praxis on the data collection, embodied in multidimensional matrices of n columns (variables in analysis) by p lines (sampled areas at different depths), and also considering the quantitative data nature present in this study, we’ve chosen a methodological approach that considers the multivariate statistical analysis, in particular, the Principal Component Analysis (PCA ) (Góis, 2004). The experiments were carried out in a soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, NW Portugal, who was able to maintain itself intact from prescribed burnings from four years and was submit to prescribed fire in March 2008. The soils samples were collected from five different plots at six different time periods. The methodological option that was adopted have allowed us to identify the most relevant relational structures inside the n variables, the p samples and in two sets at the same time (Garcia-Pereira, 1990). Consequently, and in addition to the traditional outputs produced from the PCA, we have analyzed the influence of both sampling depths and geomorphological environments in the behavior of all variables involved.

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The Portuguese northern forests are often and severely affected by wildfires during the summer season. These occurrences affect significant and rudely all ecosystems, namely soil, fauna and flora. Preventive actions such as prescribed burnings and clear-cut logging are frequently used and have showed a significant reduction of the natural wildfires occurrences. In Portugal, and due to some technical and operational conditions, prescribed burnings in forests are the most common preventive action used to reduce the existing fuel hazard. The overall impacts of this preventive action on Portuguese ecosystems are complex and not fully understood. This work reports to the study of a prescribed burning impact in soil chemical properties, namely pH, humidity and organic matter, by monitoring the soil self-recovery capacity. The experiments were carried out in soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, Portugal, who was able to maintain itself intact from prescribed burnings from four years. The composed soil samples were collected from five plots at three different layers (0-3cm, 3-6cm and 6-18cm) 1 day before prescribed fire and after the prescribed fire. The results have shown that the dynamic equilibrium in soil was affected significantly.

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The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

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The wide spread use and strong reliance on both fertilizers and pesticides made of agrigenic pollution one of the major contemporary threats to environment and human health. Impacts on the environment vary from local effects, such as eutrophycation1, 2, loss of biodiversity and diminished ecosystem health3, to global effects, such as the aggravation of global warming2, 4 and ozone layer depletion5. The novelty of nanoremediation and its early successes, reported for various contexts, present the prospect for the development of relevant applications for agrigenic contaminants.

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The need to increase agricultural yield led, among others, to an increase in the consumption of nitrogen based fertilizers. As a consequence, there are excessive concentrations of nitrates, the most abundant of the reactive nitrogen (Nr) species, in several areas of the world. The demographic changes and projected population growth for the next decades, and the economic shifts which are already shaping the near future are powerful drivers for a further intensification in the use of fertilizers, with a predicted increase of the nitrogen loads in soils. Nitrate easily diffuses in the subsurface environments, portraying high mobility in soils. Moreover, the presence of high nitrate loads in water has the potential to cause an array of health dysfunctions, such as methemoglobinemia and several cancers. Permeable Reactive Barriers (PRB) placed strategically relatively to the nitrate source constitute an effective technology to tackle nitrate pollution. Ergo, PRB avoid various adverse impacts resulting from the displacement of reactive nitrogen downstream along water bodies. A four stages literature review was carried out in 34 databases. Initially, a set of pertinent key words were identified to perform the initial databases searches. Then, the synonyms of those initial key words were used to carry out a second set of databases searches. The third stage comprised the identification of other additional relevant terms from the research papers identified in the previous two stages. Again, databases searches were performed with this third set of key words. The final step consisted of the identification of relevant papers from the bibliography of the relevant papers identified in the previous three stages of the literature review process. The set of papers identified as relevant for in-depth analysis were assessed considering a set of relevant characterization variables.

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Schistosoma mansoni cercariae were inoculated into the peritoneal cavity of naive mice and recovered 30 minutes later. Ultrastructural studies showed that neutrophils adhere to the larval surface and participate in the removal of glycocalyx by phagocytosis. This finding suggests that the neutrophils can play a role on the cercaria-schistosomulum transformation process.

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Different anthropogenic sources of metals can result from agricultural, industrial, military, mining and urban activities that contribute to environmental pollution. Plants can be grown for phytoremediation to remove or stabilize contaminants in water and soil. Copper (Cu), manganese (Mn) and zinc (Zn) are trace essential metals for plants, although their role in homeostasis in plants must be strictly regulated to avoid toxicity. In this review, we summarize the processes involved in the bioavailability, uptake, transport and storage of Cu, Mn and Zn in plants. The efficiency of phytoremediation depends on several factors including metal bioavailability and plant uptake, translocation and tolerance mechanisms. Soil parameters, such as clay fraction, organic matter content, oxidation state, pH, redox potential, aeration, and the presence of specific organisms, play fundamental roles in the uptake of trace essential metals. Key processes in the metal homeostasis network in plants have been identified. Membrane transporters involved in the acquisition, transport and storage of trace essential metals are reviewed. Recent advances in understanding the biochemical and molecular mechanisms of Cu, Mn and Zn hyperaccumulation are described. The use of plant-bacteria associations, plant-fungi associations and genetic engineering has opened a new range of opportunities to improve the efficiency of phytoremediation. The main directions for future research are proposed from the investigation of published results.

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Railway vehicle homologation, with respect to running dynamics, is addressed via dedicated norms. The results required, such as, accelerations and/or wheel-rail contact forces, obtained from experimental tests or simulations, must be available. Multibody dynamics allows the modelling of railway vehicles and their representation in real operations conditions, being the realism of the multibody models greatly influenced by the modelling assumptions. In this paper, two alternative multibody models of the Light Rail Vehicle 2000 (LRV) are constructed and simulated in a realistic railway track scenarios. The vehicle-track interaction compatibility analysis consists of two stages: the use of the simplified method described in the norm "UIC 518-Testing and Approval of Railway Vehicles from the Point of View of their Dynamic Behaviour-Safety-Track Fatigue-Running Behaviour" for decision making; and, visualization inspection of the vehicle motion with respect to the track via dedicated tools for understanding the mechanisms involved.

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Binary operations on commutative Jordan algebras, CJA, can be used to study interactions between sets of factors belonging to a pair of models in which one nests the other. It should be noted that from two CJA we can, through these binary operations, build CJA. So when we nest the treatments from one model in each treatment of another model, we can study the interactions between sets of factors of the first and the second models.