980 resultados para ENVIRONMENTAL APPLICATIONS


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Size-selective fishing, environmental changes and reproductive strategies are expected to affect life-history traits such as the individual growth rate. The relative contribution of these factors is not clear, particularly whether size-selective fishing can have a substantial impact on the genetics and hence on the evolution of individual growth rates in wild populations. We analysed a 25-year monitoring survey of an isolated population of the Alpine whitefish Coregonus palaea. We determined the selection differentials on growth rate, the actual change of growth rate over time and indicators of reproductive strategies that may potentially change over time. The selection differential can be reliably estimated in our study population because almost all the fish are harvested within their first years of life, i.e. few fish escape fishing mortality. We found a marked decline in average adult growth rate over the 25 years and a significant selection differential for adult growth, but no evidence for any linear change in reproductive strategies over time. Assuming that the heritability of growth in this whitefish corresponds to what was found in other salmonids, about a third of the observed decline in growth rate would be linked to fishery-induced evolution. Size-selective fishing seems to affect substantially the genetics of individual growth in our study population.

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The development of the field-scale Erosion Productivity Impact Calculator (EPIC) model was initiated in 1981 to support assessments of soil erosion impacts on soil productivity for soil, climate, and cropping conditions representative of a broad spectrum of U.S. agricultural production regions. The first major application of EPIC was a national analysis performed in support of the 1985 Resources Conservation Act (RCA) assessment. The model has continuously evolved since that time and has been applied for a wide range of field, regional, and national studies both in the U.S. and in other countries. The range of EPIC applications has also expanded greatly over that time, including studies of (1) surface runoff and leaching estimates of nitrogen and phosphorus losses from fertilizer and manure applications, (2) leaching and runoff from simulated pesticide applications, (3) soil erosion losses from wind erosion, (4) climate change impacts on crop yield and erosion, and (5) soil carbon sequestration assessments. The EPIC acronym now stands for Erosion Policy Impact Climate, to reflect the greater diversity of problems to which the model is currently applied. The Agricultural Policy EXtender (APEX) model is essentially a multi-field version of EPIC that was developed in the late 1990s to address environmental problems associated with livestock and other agricultural production systems on a whole-farm or small watershed basis. The APEX model also continues to evolve and to be utilized for a wide variety of environmental assessments. The historical development for both models will be presented, as well as example applications on several different scales.

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Various test methods exist for measuring heat of cement hydration; however, most current methods require expensive equipment, complex testing procedures, and/or extensive time, thus not being suitable for field application. The objectives of this research are to identify, develop, and evaluate a standard test procedure for characterization and quality control of pavement concrete mixtures using a calorimetry technique. This research project has three phases. Phase I was designed to identify the user needs, including performance requirements and precision and bias limits, and to synthesize existing test methods for monitoring the heat of hydration, including device types, configurations, test procedures, measurements, advantages, disadvantages, applications, and accuracy. Phase II was designed to conduct experimental work to evaluate the calorimetry equipment recommended from the Phase I study and to develop a standard test procedure for using the equipment and interpreting the test results. Phase II also includes the development of models and computer programs for prediction of concrete pavement performance based on the characteristics of heat evolution curves. Phase III was designed to study for further development of a much simpler, inexpensive calorimeter for field concrete. In this report, the results from the Phase I study are presented, the plan for the Phase II study is described, and the recommendations for Phase III study are outlined. Phase I has been completed through three major activities: (1) collecting input and advice from the members of the project Technical Working Group (TWG), (2) conducting a literature survey, and (3) performing trials at the CP Tech Center’s research lab. The research results indicate that in addition to predicting maturity/strength, concrete heat evolution test results can also be used for (1) forecasting concrete setting time, (2) specifying curing period, (3) estimating risk of thermal cracking, (4) assessing pavement sawing/finishing time, (5) characterizing cement features, (6) identifying incompatibility of cementitious materials, (7) verifying concrete mix proportions, and (8) selecting materials and/or mix designs for given environmental conditions. Besides concrete materials and mix proportions, the configuration of the calorimeter device, sample size, mixing procedure, and testing environment (temperature) also have significant influences on features of concrete heat evolution process. The research team has found that although various calorimeter tests have been conducted for assorted purposes and the potential uses of calorimeter tests are clear, there is no consensus on how to utilize the heat evolution curves to characterize concrete materials and how to effectively relate the characteristics of heat evolution curves to concrete pavement performance. The goal of the Phase II study is to close these gaps.

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Flow cytometry (FCM) is emerging as an important tool in environmental microbiology. Although flow cytometry applications have to date largely been restricted to certain specialized fields of microbiology, such as the bacterial cell cycle and marine phytoplankton communities, technical advances in instrumentation and methodology are leading to its increased popularity and extending its range of applications. Here we will focus on a number of recent flow cytometry developments important for addressing questions in environmental microbiology. These include (i) the study of microbial physiology under environmentally relevant conditions, (ii) new methods to identify active microbial populations and to isolate previously uncultured microorganisms, and (iii) the development of high-throughput autofluorescence bioreporter assays

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The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the U.S. Department of Agriculture (USDA), Agricultural Research Service. SWAT has gained international acceptance as a robust interdisciplinary watershed modeling tool, as evidenced by international SWAT conferences, hundreds of SWAT-related papers presented at numerous scientific meetings, and dozens of articles published in peer-reviewed journals. The model has also been adopted as part of the U.S. Environmental Protection Agency’s BASINS (Better Assessment Science Integrating Point & Nonpoint Sources) software package and is being used by many U.S. federal and state agencies, including the USDA within the Conservation Effects Assessment Project. At present, over 250 peer-reviewed, published articles have been identified that report SWAT applications, reviews of SWAT components, or other research that includes SWAT. Many of these peer-reviewed articles are summarized here according to relevant application categories such as streamflow calibration and related hydrologic analyses, climate change impacts on hydrology, pollutant load assessments, comparisons with other models, and sensitivity analyses and calibration techniques. Strengths and weaknesses of the model are presented, and recommended research needs for SWAT are provided.

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Successive applications of pig slurry to soils under no-tillage can increase the nutrient levels in the uppermost soil layers and part of the nutrients may be transferred to deeper layers. The objective was to evaluate the distribution of nutrients in the profile of a soil after 19 pig slurry applications under no-tillage for 93 months. The experiment was conducted from May 2000 to January 2008 in an experimental area of the Federal University of Santa Maria, southern Brazil, on a Typic Hapludalf. The treatments consisted of pig slurry applications (0, 20, 40 and 80 m³ ha-1) and at the end of the experiment, soil samples were collected (layers 0-2, 2-4, 4-6, 6-8, 8-10, 10-12, 12-14, 14-16, 16-18, 18-20, 20-25, 25-30, 30-35, 35-40, 40-50 and 50-60 cm). The levels of mineral N, available P and K and total N, P and K were evaluated. The 19 pig slurry applications in 93 months promoted migration of total N and P down to 30 cm and available P and K to the deepest layer analyzed. At the end of the experiment, no increase was observed in mineral N content in the deeper layers, but increased levels of available P and K, showing a transfer of N, P and K to layers below the sampled. This evidences undesirable environmental and economic consequences of the use of pig slurry and reinforces the need for a more rational use, i.e., applications of lower manure doses, combined with mineral fertilizers.

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Tannery sludge contains high concentrations of inorganic elements, such as chromium (Cr), which may lead to environmental pollution and affect human health The behavior of Cr in organic matter fractions and in the growth of cowpea (Vigna unguiculata L.) was studied in a sandy soil after four consecutive annual applications of composted tannery sludge (CTS). Over a four-year period, CTS was applied on permanent plots (2 × 5 m) and incorporated in the soil (0-20 cm) at the rates of 0, 2.5, 5.0, 10.0, and 20.0 Mg ha-1 (dry weight basis). These treatments were replicated four times in a randomized block design. In the fourth year, cowpea was planted and grown for 50 days, at which time we analyzed the Cr concentrations in the soil, in the fulvic acid, humic acid, and humin fractions, and in the leaves, pods, and grains of cowpea. Composted tannery sludge led to an increase in Cr concentration in the soil. Among the humic substances, the highest Cr concentration was found in humin. The application rates of CTS significantly increased Cr concentration in leaves and grains.

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Since the development of the first whole-cell living biosensor or bioreporter about 15 years ago, construction and testing of new genetically modified microorganisms for environmental sensing and reporting has proceeded at an ever increasing rate. One and a half decades appear as a reasonable time span for a new technology to reach the maturity needed for application and commercial success. It seems, however, that the research into cellular biosensors is still mostly in a proof-of-principle or demonstration phase and not close to extensive or commercial use outside of academia. In this review, we consider the motivations for bioreporter developments and discuss the suitability of extant bioreporters for the proposed applications to stimulate complementary research and to help researchers to develop realistic objectives. This includes the identification of some popular misconceptions about the qualities and shortcomings of bioreporters.

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The chelating agent EDTA (ethylenediaminetetraacetic acid) is a compound of massive use world wide with household and industrial applications, being one of the anthropogenic compounds with highest concentrations in inland European waters. In this review, the applications of EDTA and its behavior once it has been released into the environment are described. At a laboratory scale, degradation of EDTA has been achieved; however, in natural environments studies detect poor biodegradability. It is concluded that EDTA behaves as a persistent substance in the environment and that its contribution to heavy metals bioavailability and remobilization processes in the environment is a major concern.

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Efforts presented by the scientific community in recent years towards the development of numerous green chemical processes and wastewater treatment technologies are presented and discussed. In the light of these approaches, environmentally friendly technologies, as well as the key role played by the well-known advanced oxidation processes, are discussed, giving special attention to the ones comprising ozone applications. Fundamentals and applied aspects dealing with ozone technology and its application are also presented.

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The purpose of this thesis was to define how product carbon footprint analysis and its results can be used in company's internal development as well as in customer and interest group guidance, and how these factors are related to corporate social responsibility. From-cradle-to-gate carbon footprint was calculated for three products; Torino Whole grain barley, Torino Pearl barley, and Elovena Barley grit & oat bran, all of them made of Finnish barley. The carbon footprint of the Elovena product was used to determine carbon footprints for industrial kitchen cooked porridge portions. The basic calculation data was collected from several sources. Most of the data originated from Raisio Group's contractual farmers and Raisio Group's cultivation, processing and packaging specialists. Data from national and European literature and database sources was also used. The electricity consumption for porridge portions' carbon footprint calculations was determined with practical measurements. The carbon footprint calculations were conducted according to the ISO 14044 standard, and the PAS 2050 guide was also applied. A consequential functional unit was applied in porridge portions' carbon footprint calculations. Most of the emissions from barley products' life cycle originate from primary production. The nitrous oxide emissions from cultivated soil and the use and production of nitrogenous fertilisers contribute over 50% of products' carbon footprint. Torino Pearl barley has the highest carbon footprint due to the lowest processing output. The reductions in products' carbon footprint can be achieved with developments in cultivation and grain processing. The carbon footprint of porridge portion can be reduced by using domestically produced plant-based ingredients and by making the best possible use of the kettle. Carbon footprint calculation can be used to determine possible improvement points related to corporate environmental responsibility. Several improvement actions are related to economical and social responsibility through better raw material utilization and expense reductions.

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Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed.

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Paper-based analytical technologies enable quantitative and rapid analysis of analytes from various application areas including healthcare, environmental monitoring and food safety. Because paper is a planar, flexible and light weight substrate, the devices can be transported and disposed easily. Diagnostic devices are especially valuable in resourcelimited environments where diagnosis as well as monitoring of therapy can be made even without electricity by using e.g. colorimetric assays. On the other hand, platforms including printed electrodes can be coupled with hand-held readers. They enable electrochemical detection with improved reliability, sensitivity and selectivity compared with colorimetric assays. In this thesis, different roll-to-roll compatible printing technologies were utilized for the fabrication of low-cost paper-based sensor platforms. The platforms intended for colorimetric assays and microfluidics were fabricated by patterning the paper substrates with hydrophobic vinyl substituted polydimethylsiloxane (PDMS) -based ink. Depending on the barrier properties of the substrate, the ink either penetrates into the paper structure creating e.g. microfluidic channel structures or remains on the surface creating a 2D analog of a microplate. The printed PDMS can be cured by a roll-ro-roll compatible infrared (IR) sintering method. The performance of these platforms was studied by printing glucose oxidase-based ink on the PDMS-free reaction areas. The subsequent application of the glucose analyte changed the colour of the white reaction area to purple with the colour density and intensity depending on the concentration of the glucose solution. Printed electrochemical cell platforms were fabricated on paper substrates with appropriate barrier properties by inkjet-printing metal nanoparticle based inks and by IR sintering them into conducting electrodes. Printed PDMS arrays were used for directing the liquid analyte onto the predetermined spots on the electrodes. Various electrochemical measurements were carried out both with the bare electrodes and electrodes functionalized with e.g. self assembled monolayers. Electrochemical glucose sensor was selected as a proof-of-concept device to demonstrate the potential of the printed electronic platforms.

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Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented