920 resultados para physical soil characteristics
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In the last decade, population ageing has been registered as a global phenomenon. A relation exists between falling and ageing, since falling frequency increases significantly with age. In fact, one in three older adult falls annually. Although ageing is generically associated with decrease and degeneration of psychological and physical functions, it is still not common for the correct identification of risk factors to lead to a clinical prognosis of the elder being in risk of falling. Therefore, the goal of this review article is to identify, categorise and analyse typical ageing and fall factors mentioned in the literature as well as to quantify the number of times they were referenced. The research considered hundreds of publications, but analysis was then restricted to the 87 most pertinent articles written in English and published in journals or scientific magazines between 1995 and 2010. We concluded that falls among older adults can be characterised by the following: anatomic characteristics and physiological consequences of ageing; the pathologies that induce falls, which can be neurological, musculoskeletal, cardiovascular and other diseases; causes and risk factors of falls that can be behavioural, biological, environmental or socio-economic; type of physical consequences of falls, including fractures, bruises, injuries or other physical consequences; and strategies to prevent, mitigate or rehabilitate, which can be of a physical, environmental or behavioural nature.
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Coffee cultivation via central-pivot fertigation can lead to fertilizer losses by soil profile internal drainage when water application is excessive and soils have low water retention and cation adsorption capacities. This study analyses the deep water losses from the top 1 m sandy soil layer of east Bahia, Brazil, cultivated with coffee at a high technology level (central-pivot fertigation), using above normal N fertilizer rates. The deep drainage (Q) estimation is made through the application of a climatologic water balance (CWB) program having as input direct measures of irrigation and rainfall, climatological data from weather stations, and measured soil water retention characteristics. The aim of the study is to contribute to the understanding of the hydric regime of coffee crops managed by central-pivot irrigation, analyzing three scenarios (Sc): i) rainfall only, ii) rainfall and irrigation full year, and iii) rainfall and irrigation dry season only. Annual Q values for the 2008/2009 agricultural year were: Sc i = 811.5 mm; Sc ii = 1010.5 mm; and Sc iii = 873.1 mm, so that the irrigation interruption in the wet season reduced Q by 15.7%, without the appearance of water deficit periods. Results show that the use of the CWB program is a convenient tool for the evaluation of Q under the cited conditions.
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Studies on the use of silicate correctives in agriculture show that they have great potential to improve soil chemical characteristics, however, little information is available on the reactivity rates of their particle-size fractions. This study investigated whether the reactivity rates obtained experimentally could be considered in the calculation of ECC (effective calcium carbonate) for soil liming, promoting adequate development of alfalfa plants. Six treatments were evaluated in the experiment, consisting of two slag types applied in two rates. The experimental ECC was used to calculate one of the rates and the ECC determined in the laboratory was used to calculate the other. Rates of limestone and wollastonite were based on the ECC determined in laboratory. The rates of each soil acidity corretive were calculated to increase the base saturation to 80%. The treatments were applied to a Rhodic Hapludox and an Alfisol Ferrudalfs. The methods for ECC determination established for lime can be applied to steel slag. The application of slag corrected soil acidity with consequent accumulation of Ca, P, and Si in alfalfa, favoring DM production.
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Dissertação de Mestrado, Engenharia Agronómica, 16 de Outubro de 2015, Universidade dos Açores.
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OBJECTIVE: To estimate the prevalence and identify correlates of physical activity among adolescents. METHODS: Cross-sectional study nested within a cohort of 4,325 subjects from the city of Pelotas, Southern Brazil, aged 14-15 years in 2008. Physical activity was analyzed using three different approaches: (1) prevalence of any leisure-time physical activity; (2) prevalence of any active commuting to school; and (3) prevalence of engaging in at least 300 minutes per week of both (1) and (2) combined. Independent variables included sociodemographic, behavioral, social, and biological characteristics, and number of different leisure-time physical activites practiced. Statistical analyses were carried out using Poisson regression. RESULTS: The proportion of adolescents involved in any type of leisure-time physical activity was 75.6%, while 73.4% displayed some form of active commuting to school. Prevalence of total physical activity score (> 300 min/week) was 48.2%, being greater among boys (62.6%) than among girls (34.5%). Furthermore, prevalence increased along with the number of physical activity modalities practiced (p<0.001). Factors associated with greater physical activity (leisure + commuting) at the recommended levels were: nonwhite skin color, having failed at school, and playing videogames. Lower socioeconomic status, more time spent on the computer, and parental physical activity were associated with the outcome only among girls. CONCLUSIONS: Less than half the adolescents reached recommended levels of physical activity, and this proportion tended to decrease among subjects with higher socioeconomic level. Associated factors were different for leisure-time and commuting. Engaging in a wide variety of physical activities should be encouraged already during childhood.
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The current models are not simple enough to allow a quick estimation of the remediation time. This work reports the development of an easy and relatively rapid procedure for the forecasting of the remediation time using vapour extraction. Sandy soils contaminated with cyclohexane and prepared with different water contents were studied. The remediation times estimated through the mathematical fitting of experimental results were compared with those of real soils. The main objectives were: (i) to predict, through a simple mathematical fitting, the remediation time of soils with water contents different from those used in the experiments; (ii) to analyse the influence of soil water content on the: (ii1) remediation time; (ii2) remediation efficiency; and (ii3) distribution of contaminants in the different phases present into the soil matrix after the remediation process. For sandy soils with negligible contents of clay and natural organic matter, artificially contaminated with cyclohexane before vapour extraction, it was concluded that (i) if the soil water content belonged to the range considered in the experiments with the prepared soils, then the remediation time of real soils of similar characteristics could be successfully predicted, with relative differences not higher than 10%, through a simple mathematical fitting of experimental results; (ii) increasing soil water content from 0% to 6% had the following consequences: (ii1) increased remediation time (1.8–4.9 h, respectively); (ii2) decreased remediation efficiency (99–97%, respectively); and (ii3) decreased the amount of contaminant adsorbed onto the soil and in the non-aqueous liquid phase, thus increasing the amount of contaminant in the aqueous and gaseous phases.
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Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Edificações
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OBJECTIVE: To analyze the putative effect of type of shift and its interaction with leisure-time physical activity on cardiovascular risk factors in truck drivers.METHODS: A cross-sectional study was undertaken on 57 male truck drivers working at a transportation company, of whom 31 worked irregular shifts and 26 worked on the day-shift. Participants recorded their physical activity using the International Physical Activity Questionnaire along with measurements of blood pressure, body mass index and waist-hip ratio. Participants also provided a fasting blood sample for analysis of lipid-related outcomes. Data were analyzed using a factorial model which was covariate-controlled for age, smoking, work demand, control at work and social support.RESULTS: Most of the irregular-shift and day-shift workers worked more than 8 hours per day (67.7% and 73.1%, respectively). The mean duration of experience working the irregular schedule was 15.7 years. Day-shift workers had never engaged in irregular-shift work and had been working as a truck driver for 10.8 years on average. The irregular-shift drivers had lower work demand but less control compared to day-shift drivers (p < 0.05). Moderately-active irregular-shift workers had higher systolic and diastolic arterial pressures (143.7 and 93.2 mmHg, respectively) than moderately-active day-shift workers (116 and 73.3 mmHg, respectively) (p < 0.05) as well as higher total cholesterol concentrations (232.1 and 145 mg/dl, respectively) (p = 0.01). Irrespective of their physical activity, irregular-shift drivers had higher total cholesterol and LDL-cholesterol concentrations (211.8 and 135.7 mg/dl, respectively) than day-shift workers (161.9 and 96.7 mg/dl, respectively (ANCOVA, p < 0.05).CONCLUSIONS: Truck drivers are exposed to cardiovascular risk factors due to the characteristics of the job, such as high work demand, long working hours and time in this profession, regardless of shift type or leisure-time physical activity.
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The Iberian viticultural regions are convened according to the Denomination of Origin (DO) and present different climates, soils, topography and management practices. All these elements influence the vegetative growth of different varieties throughout the peninsula, and are tied to grape quality and wine type. In the current study, an integrated analysis of climate, soil, topography and vegetative growth was performed for the Iberian DO regions, using state-of-the-art datasets. For climatic assessment, a categorized index, accounting for phenological/thermal development, water availability and grape ripening conditions was computed. Soil textural classes were established to distinguish soil types. Elevation and aspect (orientation) were also taken into account, as the leading topographic elements. A spectral vegetation index was used to assess grapevine vegetative growth and an integrated analysis of all variables was performed. The results showed that the integrated climate-soil-topography influence on vine performance is evident. Most Iberian vineyards are grown in temperate dry climates with loamy soils, presenting low vegetative growth. Vineyards in temperate humid conditions tend to show higher vegetative growth. Conversely, in cooler/warmer climates, lower vigour vineyards prevail and other factors, such as soil type and precipitation acquire more important roles in driving vigour. Vines in prevailing loamy soils are grown over a wide climatic diversity, suggesting that precipitation is the primary factor influencing vigour. The present assessment of terroir characteristics allows direct comparison among wine regions and may have great value to viticulturists, particularly under a changing climate.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente,perfil Sanitária
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One of the most important measures to prevent wild forest fires is the use of prescribed and controlled burning actions as it reduce the fuel mass availability. The impact of these management activities on soil physical and chemical properties varies according to the type of both soil and vegetation. Decisions in forest management plans are often based on the results obtained from soil-monitoring campaigns. Those campaigns are often man-labor intensive and expensive. In this paper we have successfully used the multivariate statistical technique Robust Principal Analysis Compounds (ROBPCA) to investigate on the sampling procedure effectiveness for two different methodologies, in order to reflect on the possibility of simplifying and reduce the sampling collection process and its auxiliary laboratory analysis work towards a cost-effective and competent forest soil characterization.
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The Portuguese northern forests are often and severely affected by wildfires during the Summer season. These occurrences significantly affect and negatively impact all ecosystems, namely soil, fauna and flora. In order to reduce the occurrences of natural wildfires, some measures to control the availability of fuel mass are regularly implemented. Those preventive actions concern mainly prescribed burnings and vegetation pruning. This work reports on the impact of a prescribed burning on several forest soil properties, namely pH, soil moisture, organic matter content and iron content, by monitoring the soil self-recovery capabilities during a one year span. The experiments were carried out in soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, Portugal, which was kept intact from prescribed burnings during a period of four years. Soil samples were collected from five plots at three different layers (0–3, 3–6 and 6–18) 1 day before prescribed fire and at regular intervals after the prescribed fire. This paper presents an approach where Fuzzy Boolean Nets (FBN) and Fuzzy reasoning are used to extract qualitative knowledge regarding the effect of prescribed fire burning on soil properties. FBN were chosen due to the scarcity on available quantitative data. The results showed that soil properties were affected by prescribed burning practice and were unable to recover their initial values after one year.
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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.
Physical, chemical and mineralogical properties of fine recycled aggregates made from concrete waste
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This paper assesses the physical, chemical and mineralogical characteristics of fine recycled aggregates obtained from crushed concrete waste, comparing them with two types of natural fine aggregates from different origins. A commercial concrete was jaw crushed, and the effect of different aperture sizes on the particle size distribution of the resulting aggregates was evaluated. The density and water absorption of the recycled aggregates was determined and a model for predicting water absorption over time is proposed. Both natural and recycled aggregates were characterized regarding bulk density and fines content. Recycled aggregates were additionally characterized by XRD, SEM/EDS and DTA/TG of individual size fractions. The results show that natural and recycled fine aggregates have very different characteristics. This should be considered in potential applications, both in terms of the limits for replacing amounts and of the rules and design criteria of the manufactured products. (C) 2015 Elsevier Ltd. All rights reserved.
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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.