996 resultados para Water classification


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"Lake and stream classification project."

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Projected air and ground temperatures are expected to be higher in Arctic and sub-Arcticlatitudes and with temperatures already close to the limit where permafrost can exist,resistance against degradation is low. With thawing permafrost, the landscape is modifiedwith depression in which thermokarst lakes emerge. In permafrost soils a considerableamount of soil organic carbon is stored, with the potential of altering climate even furtherif expansion and formation of new thermokarst lakes emerge, as decay releasesgreenhouse gases (C02 and CH4) to the atmosphere. Analyzing the spatial distribution andmorphometry over time of thermokarst lakes and other water bodies, is of importance inaccurately predict carbon budget and feedback mechanisms, as well as to assess futurelandscape layout and these features interaction. Different types of high-spatial resolutionaerial and satellite imageries from 1963, 1975, 2003, 2010 and 2015, were used in bothpre- and post-classification change detection analyses. Using object oriented segmentationin eCognition combined with manual adjustments, resulted in digitalized water bodies>28m2 from which direction of change and morphometric values were extracted. Thequantity of thermokarst lakes and other water bodies was in 1963 n=92, with succeedingyears as a trend decreased in numbers, until 2010-2015 when eleven water bodies wereadded in 2015 (n=74 to n=85). In 1963-2003, area of these water bodies decreased with50 651m2 (189 446-138 795m2) and continued to decrease in 2003-2015 ending at 129337m2. Limnicity decreased from 19.9% in 1963 to 14.6% in 2003 (-5.3%). In 2010 and2015 13.7-13.6%. The late increase in water bodies differs from an earlier hypothesis thatsporadic permafrost regions experience decrease in both area and quantity of thermokarstlakes and water bodies. During 1963-2015, land gain has been in dominance of the ratiobetween the two competing processes of expansion and drainage. In 1963-1975, 55/45%,followed by 90/10% in 1975-2003. After major drainage events, land loss increased to62/38% in 2010-2015. Drainage and infilling rates, calculated for 15 shorelines werevaried across both landscape and parts of shorelines, with in average 0.17/0.15/0.14m/yr.Except for 1963-1975 when rate of change in average was in opposite direction (-0.09m/yr.), likely due to evident expansion of a large thermokarst lake. Using a squaregrid, distribution of water bodies was determined, with an indistinct cluster located in NEand central parts. Especially for water bodies <250m2, which is the dominant area classthroughout 1963-2015 ranging from n=39-51. With a heterogeneous composition of bothsmall and large thermokarst lakes, and with both expansion and drainage altering thelandscape in Tavvavuoma, both positive and negative climate feedback mechanisms are inplay - given that sporadic permafrost still exist.

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Entrainment in flotation can be considered as a two-step process, including the transfer of the suspended solids in the top of the pulp region just below the pulp-froth interface to the froth phase and the transfer of the entrained particles in the froth phase to the concentrate. Both steps have a strong classification characteristic. The degree of entrainment describes the classification effect of the drainage process in the froth phase. This paper briefly reviews two existing models of degree of entrainment. Experimental data were collected from an Outokumpu 3 m(3) tank cell in the Xstrata Mt. Isa Mines copper concentrator. The data are fitted to the models and the effect of cell operating conditions including air rate and froth height on the degree of entrainment is examined on a size-by-size basis. It is found that there is a strong correlation between the entrainment and the water recovery, which is close to lineal. for the fines. The degree of entrainment decreases with increase in particle size. Within the normal range of cell operating conditions, few particles coarser than 50 mu m are recovered by entrainment. In general, the degree of entrainment increases with increase in the ail rate and decreases with increase in the froth height. Air rate and froth height strongly interact with each other and affect the entrainment process mainly via changes in the froth retention time, the froth structure and froth properties. As a result, other mechanisms such as entrapment may become important in recovering the coarse entrained particles. (c) 2005 Elsevier Ltd. All rights reserved.

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We describe the diversity of aquatic invertebrates colonising water-filled final voids produced by an open-cut coal mine near Moura, central Queensland. Ten disused pits that had been filled with water from < 1 year to 22 years prior to the survey and three nearby 'natural' water bodies were sampled in December 1998 and again in March 1999. All invertebrates collected were identified to family with the exception of oligochaetes, cladocerans, ostracods and copepods, which were identified to these coarser taxonomic levels. Sixty-two taxa were recorded from > 20 000 individuals. The greatest familial richness was displayed by the Insecta (33 families) followed by the mites (Acari) with 12 families. While natural water bodies held the greatest diversity, several mine pits were almost as rich in families. Classification analyses showed that natural sites tended to cluster together, but the groupings did not clearly exclude pit sites. Mining pits that supported higher diversity tended to be older and had lower salinity (< 2000 mu S/cm); however, salinity in all water bodies varied with rainfall conditions. We conclude that ponds formed in final voids at this mine have the potential to provide habitat for many invertebrate taxa typical of lentic inland water bodies in central Queensland.

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A broad based approach has been used to assess the impact of discharges to rivers from surface water sewers, with the primary objective of determining whether such discharges have a measurable impact on water quality. Three parameters, each reflecting the effects of intermittent pollution, were included in a field work programme of biological and chemical sampling and analysis which covered 47 sewer outfall sites. These parameters were the numbers and types of benthic macroinvertebrates upstream and downstream of the outfalls, the concentrations of metals in sediments, and the concentrations of metals in algae upstream and downstream of the outfalls. Information on the sewered catchments was collected from Local Authorities and by observation of the time of sampling, and includes catchment areas, land uses, evidence of connection to the foul system, and receiving water quality classification. The methods used for site selection, sampling, laboratory analysis and data analysis are fully described, and the survey results presented. Statistical and graphical analysis of the biological data, with the aid of BMWP scores, showed that there was a small but persistent fall in water quality downstream of the studied outfalls. Further analysis including the catchment information indicated that initial water quality, sewered catchment size, receiving stream size, and catchment land use were important factors in determining the impact. Finally, the survey results were used to produce guidelines for the estimation of surface water sewer discharge impacts from knowledge of the catchment characteristics, so that planning authorities can consider water quality when new drainage systems are designed.

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This thesis presents a thorough and principled investigation into the application of artificial neural networks to the biological monitoring of freshwater. It contains original ideas on the classification and interpretation of benthic macroinvertebrates, and aims to demonstrate their superiority over the biotic systems currently used in the UK to report river water quality. The conceptual basis of a new biological classification system is described, and a full review and analysis of a number of river data sets is presented. The biological classification is compared to the common biotic systems using data from the Upper Trent catchment. This data contained 292 expertly classified invertebrate samples identified to mixed taxonomic levels. The neural network experimental work concentrates on the classification of the invertebrate samples into biological class, where only a subset of the sample is used to form the classification. Other experimentation is conducted into the identification of novel input samples, the classification of samples from different biotopes and the use of prior information in the neural network models. The biological classification is shown to provide an intuitive interpretation of a graphical representation, generated without reference to the class labels, of the Upper Trent data. The selection of key indicator taxa is considered using three different approaches; one novel, one from information theory and one from classical statistical methods. Good indicators of quality class based on these analyses are found to be in good agreement with those chosen by a domain expert. The change in information associated with different levels of identification and enumeration of taxa is quantified. The feasibility of using neural network classifiers and predictors to develop numeric criteria for the biological assessment of sediment contamination in the Great Lakes is also investigated.

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Extensive data sets on water quality and seagrass distributions in Florida Bay have been assembled under complementary, but independent, monitoring programs. This paper presents the landscape-scale results from these monitoring programs and outlines a method for exploring the relationships between two such data sets. Seagrass species occurrence and abundance data were used to define eight benthic habitat classes from 677 sampling locations in Florida Bay. Water quality data from 28 monitoring stations spread across the Bay were used to construct a discriminant function model that assigned a probability of a given benthic habitat class occurring for a given combination of water quality variables. Mean salinity, salinity variability, the amount of light reaching the benthos, sediment depth, and mean nutrient concentrations were important predictor variables in the discriminant function model. Using a cross-validated classification scheme, this discriminant function identified the most likely benthic habitat type as the actual habitat type in most cases. The model predicted that the distribution of benthic habitat types in Florida Bay would likely change if water quality and water delivery were changed by human engineering of freshwater discharge from the Everglades. Specifically, an increase in the seasonal delivery of freshwater to Florida Bay should cause an expansion of seagrass beds dominated by Ruppia maritima and Halodule wrightii at the expense of the Thalassia testudinum-dominated community that now occurs in northeast Florida Bay. These statistical techniques should prove useful for predicting landscape-scale changes in community composition in diverse systems where communities are in quasi-equilibrium with environmental drivers.

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South Florida’s watersheds have endured a century of urban and agricultural development and disruption of their hydrology. Spatial characterization of South Florida’s estuarine and coastal waters is important to Everglades’ restoration programs. We applied Factor Analysis and Hierarchical Clustering of water quality data in tandem to characterize and spatially subdivide South Florida’s coastal and estuarine waters. Segmentation rendered forty-four biogeochemically distinct water bodies whose spatial distribution is closely linked to geomorphology, circulation, benthic community pattern, and to water management. This segmentation has been adopted with minor changes by federal and state environmental agencies to derive numeric nutrient criteria.

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A mosaic of two WorldView-2 high resolution multispectral images (Acquisition dates: October 2010 and April 2012), in conjunction with field survey data, was used to create a habitat map of the Danajon Bank, Philippines (10°15'0'' N, 124°08'0'' E) using an object-based approach. To create the habitat map, we conducted benthic cover (seafloor) field surveys using two methods. Firstly, we undertook georeferenced point intercept transects (English et al., 1997). For ten sites we recorded habitat cover types at 1 m intervals on 10 m long transects (n= 2,070 points). Second, we conducted geo-referenced spot check surveys, by placing a viewing bucket in the water to estimate the percent cover benthic cover types (n = 2,357 points). Survey locations were chosen to cover a diverse and representative subset of habitats found in the Danajon Bank. The combination of methods was a compromise between the higher accuracy of point intercept transects and the larger sample area achievable through spot check surveys (Roelfsema and Phinn, 2008, doi:10.1117/12.804806). Object-based image analysis, using the field data as calibration data, was used to classify the image mosaic at each of the reef, geomorphic and benthic community levels. The benthic community level segregated the image into a total of 17 pure and mixed benthic classes.

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Permanent water bodies not only store dissolved CO2 but are essential for the maintenance of wetlands in their proximity. From the viewpoint of greenhouse gas (GHG) accounting wetland functions comprise sequestration of carbon under anaerobic conditions and methane release. The investigated area in central Siberia covers boreal and sub-arctic environments. Small inundated basins are abundant on the sub-arctic Taymir lowlands but also in parts of severe boreal climate where permafrost ice content is high and feature important freshwater ecosystems. Satellite radar imagery (ENVISAT ScanSAR), acquired in summer 2003 and 2004, has been used to derive open water surfaces with 150 m resolution, covering an area of approximately 3 Mkm**2. The open water surface maps were derived using a simple threshold-based classification method. The results were assessed with Russian forest inventory data, which includes detailed information about water bodies. The resulting classification has been further used to estimate the extent of tundra wetlands and to determine their importance for methane emissions. Tundra wetlands cover 7% (400,000 km**2) of the study region and methane emissions from hydromorphic soils are estimated to be 45,000 t/d for the Taymir peninsula.

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The micellization of a homologous series of zwitterionic surfactants, a group of sulfobetaines, was studied using isothermal titration calorimetry (ITC) in the temperature range from 15 to 65 °C. The increase in both temperature and the alkyl chain length leads to more negative values of ΔGmic(0) , favoring the micellization. The entropic term (ΔSmic(0)) is predominant at lower temperatures, and above ca. 55-65 °C, the enthalpic term (ΔHmic(0)) becomes prevalent, figuring a jointly driven process as the temperature increases. The interaction of these sulfobetaines with different polymers was also studied by ITC. Among the polymers studied, only two induced the formation of micellar aggregates at lower surfactant concentration: poly(acrylic acid), PAA, probably due to the formation of hydrogen bonds between the carboxylic group of the polymer and the sulfonate group of the surfactant, and poly(sodium 4-styrenesulfonate), PSS, probably due to the incorporation of the hydrophobic styrene group into the micelles. The prevalence of the hydrophobic and not the electrostatic contributions to the interaction between sulfobetaine and PSS was confirmed by an increased interaction enthalpy in the presence of electrolytes (NaCl) and by the observation of a significant temperature dependence, the latter consistent with the proposed removal of hydrophobic groups from water.

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Ochnaceae s.str. (Malpighiales) are a pantropical family of about 500 species and 27 genera of almost exclusively woody plants. Infrafamilial classification and relationships have been controversial partially due to the lack of a robust phylogenetic framework. Including all genera except Indosinia and Perissocarpa and DNA sequence data for five DNA regions (ITS, matK, ndhF, rbcL, trnL-F), we provide for the first time a nearly complete molecular phylogenetic analysis of Ochnaceae s.l. resolving most of the phylogenetic backbone of the family. Based on this, we present a new classification of Ochnaceae s.l., with Medusagynoideae and Quiinoideae included as subfamilies and the former subfamilies Ochnoideae and Sauvagesioideae recognized at the rank of tribe. Our data support a monophyletic Ochneae, but Sauvagesieae in the traditional circumscription is paraphyletic because Testulea emerges as sister to the rest of Ochnoideae, and the next clade shows Luxemburgia+Philacra as sister group to the remaining Ochnoideae. To avoid paraphyly, we classify Luxemburgieae and Testuleeae as new tribes. The African genus Lophira, which has switched between subfamilies (here tribes) in past classifications, emerges as sister to all other Ochneae. Thus, endosperm-free seeds and ovules with partly to completely united integuments (resulting in an apparently single integument) are characters that unite all members of that tribe. The relationships within its largest clade, Ochnineae (former Ochneae), are poorly resolved, but former Ochninae (Brackenridgea, Ochna) are polyphyletic. Within Sauvagesieae, the genus Sauvagesia in its broad circumscription is polyphyletic as Sauvagesia serrata is sister to a clade of Adenarake, Sauvagesia spp., and three other genera. Within Quiinoideae, in contrast to former phylogenetic hypotheses, Lacunaria and Touroulia form a clade that is sister to Quiina. Bayesian ancestral state reconstructions showed that zygomorphic flowers with adaptations to buzz-pollination (poricidal anthers), a syncarpous gynoecium (a near-apocarpous gynoecium evolved independently in Quiinoideae and Ochninae), numerous ovules, septicidal capsules, and winged seeds with endosperm are the ancestral condition in Ochnoideae. Although in some lineages poricidal anthers were lost secondarily, the evolution of poricidal superstructures secured the maintenance of buzz-pollination in some of these genera, indicating a strong selective pressure on keeping that specialized pollination system.

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Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

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In this work the archaea and eubacteria community of a hypersaline produced water from the Campos Basin that had been transported and discharged to an onshore storage facility was evaluated by 16S recombinant RNA (rRNA) gene sequence analysis. The produced water had a hypersaline salt content of 10 (w/v), had a carbon oxygen demand (COD) of 4,300 mg/l and contains phenol and other aromatic compounds. The high salt and COD content and the presence of toxic phenolic compounds present a problem for conventional discharge to open seawater. In previous studies, we demonstrated that the COD and phenolic content could be largely removed under aerobic conditions, without dilution, by either addition of phenol degrading Haloarchaea or the addition of nutrients alone. In this study our goal was to characterize the microbial community to gain further insight into the persistence of reservoir community members in the produced water and the potential for bioremediation of COD and toxic contaminants. Members of the archaea community were consistent with previously identified communities from mesothermic reservoirs. All identified archaea were located within the phylum Euryarchaeota, with 98 % being identified as methanogens while 2 % could not be affiliated with any known genus. Of the identified archaea, 37 % were identified as members of the strictly carbon-dioxide-reducing genus Methanoplanus and 59 % as members of the acetoclastic genus Methanosaeta. No Haloarchaea were detected, consistent with the need to add these organisms for COD and aromatic removal. Marinobacter and Halomonas dominated the eubacterial community. The presence of these genera is consistent with the ability to stimulate COD and aromatic removal with nutrient addition. In addition, anaerobic members of the phyla Thermotogae, Firmicutes, and unclassified eubacteria were identified and may represent reservoir organisms associated with the conversion hydrocarbons to methane.