Assessment and classification of Illinois lakes /

"Staff report."

A practical tool to identify water bodies with potential for mosquito habitat under mangrove canopy: Large-scale airborne scanning in the thermal band

We address the practical issue of using thermal image data without adjustment or calibration for projects which do not require actual temperatures per se. Large scale airborne scanning in the thermal band at 8.5–13 μm was obtained for a mangrove and salt marsh in subtropical eastern Australia. For open sites, the raw image values were strongly positively correlated with ground level temperatures. For sites under mangrove canopy cover, image values indicated temperatures 2–4°C lower than those measured on the ground. The raw image was useful in identifying water bodies under canopy and has the potential for locating channel lines of deeper water. This could facilitate modification to increase flushing in the system, thereby reducing mosquito larval survival.

The application of artificial neural networks to the interpretation and classification of freshwater benthic invertebrate communities

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.

On the Algebraic Properties of Convex Bodies

AMS subject classification: 52A01, 13C99.

Robustness of the Estuarine Fish Assessment Index (EFAI) regarding water body definition criteria

According to the Water Framework Directive (WFD) transitional waters should be differentiated according to type and, in some cases, divided into different water bodies. This raises a dilemma in trying to define parts of a continuum. In the sequence of WFD several indices have been proposed including the Estuarine Fish Assessment Index, which can be applied taking an estuary as a whole (EFAI - without water bodies division) or divided in water bodies (EFAI(WB)). The purpose of this work is to analyze the robustness of the Estuarine Fish Assessment Index, based on three different ways of dividing Portuguese estuaries into water bodies according to different criteria (criterion 1 - distance to the estuary mouth, criterion 2 - salinity and criterion 3 - morphology, salinity and human dimension as pressure and state). In this study we evaluated at which degree these three criteria could influence the ecological quality ratio (EQR) results, when the index was applied to water body level (EFAI(WB)). Also, for each estuary, the EQR(WB) results for each criterion of EFAI(WB) were combined and weighted according to the water bodies areas (EFAI overall weighted - EFAI(Ow)). Finally, it was compared if the results obtained for each criterion with the EFAI(OW) were similar to the results of the index application taking the estuary as a whole (EFAI without water bodies division). No significant differences were found in both cases, which indicated that this index is a robust method regarding the division of the estuaries in different water bodies, which is an important element of a fish-based multimetric tool for assessing estuarine ecological quality. However, in some cases, different ecological quality statuses were achieved when applying the EFAI(Ow) or the EFAI. This work addressed several aspects regarding the possible division of water bodies at the WFD context. (C) 2012 Elsevier Ltd. All rights reserved.

Data analysis and hydrological modelling of rainfall and discharge extremes along the Tione River: implications for the design of water structures

There are many natural events that can negatively affect the urban ecosystem, but weather-climate variations are certainly among the most significant. The history of settlements has been characterized by extreme events like earthquakes and floods, which repeat themselves at different times, causing extensive damage to the built heritage on a structural and urban scale. Changes in climate also alter various climatic subsystems, changing rainfall regimes and hydrological cycles, increasing the frequency and intensity of extreme precipitation events (heavy rainfall).  From an hydrological risk perspective, it is crucial to understand future events that could occur and their magnitude in order to design safer infrastructures. Unfortunately, it is not easy to understand future scenarios as the complexity of climate is enormous.  For this thesis, precipitation and discharge extremes were primarily used as data sources. It is important to underline that the two data sets are not separated: changes in rainfall regime, due to climate change, could significantly affect overflows into receiving water bodies. It is imperative that we understand and model climate change effects on water structures to support the development of adaptation strategies.   The main purpose of this thesis is to search for suitable water structures for a road located along the Tione River. Therefore, through the analysis of the area from a hydrological point of view, we aim to guarantee the safety of the infrastructure over time.   The observations made have the purpose to underline how models such as a stochastic one can improve the quality of an analysis for design purposes, and influence choices.

Phylogenetics, Ancestral State Reconstruction, And A New Infrafamilial Classification Of The Pantropical Ochnaceae (medusagynaceae, Ochnaceae S.str., Quiinaceae) Based On Five Dna Regions.

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.

Classification Of Frankfurters By Ft-raman Spectroscopy And Chemometric Methods.

Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

[the New Classification Of Breast Cancers: Finding The Luminal A].

To compare the distributions of patients with clinical-pathological subtypes of luminal B-like breast cancer according to the 2011 and 2013 St. Gallen International Breast Cancer Conference Expert Panel. We studied 142 women with breast cancer who were positive to estrogen receptor and had been treated in São Paulo state, southeast Brazil. The expression of the following receptors was assessed by immunohistochemistry: estrogen, progesterone (PR) and Ki-67. The expression of HER-2 was measured by fluorescent in situ hybridization analysis in tissue microarray. There were 29 cases of luminal A breast cancers according to the 2011 St. Gallen International Breast Cancer Conference Expert Panel that were classified as luminal B-like in the 2013 version. Among the 65 luminal B-like breast cancer cases, 29 (45%) were previous luminal A tumors, 15 cases (20%) had a Ki-67 >14% and were at least 20% PR positive and 21 cases (35%) had Ki-67 >14% and more than 20% were PR positive. The 2013 St. Gallen consensus updated the definition of intrinsic molecular subtypes and increased the number of patients classified as having luminal B-like breast cancer in our series, for whom the use of cytotoxic drugs will probably be proposed with additional treatment cost.

Trichomes Related To An Unusual Method Of Water Retention And Protection Of The Stem Apex In An Arid Zone Perennial Species.

It is well known that trichomes protect plant organs, and several studies have investigated their role in the adaptation of plants to harsh environments. Recent studies have shown that the production of hydrophilic substances by glandular trichomes and the deposition of this secretion on young organs may facilitate water retention, thus preventing desiccation and favouring organ growth until the plant develops other protective mechanisms. Lychnophora diamantinana is a species endemic to the Brazilian 'campos rupestres' (rocky fields), a region characterized by intense solar radiation and water deficits. This study sought to investigate trichomes and the origin of the substances observed on the stem apices of L. diamantinana. Samples of stem apices, young and expanded leaves were studied using standard techniques, including light microscopy and scanning and transmission electron microscopy. Histochemical tests were used to identify the major groups of metabolites present in the trichomes and the hyaline material deposited on the apices. Non-glandular trichomes and glandular trichomes were observed. The material deposited on the stem apices was hyaline, highly hydrophilic and viscous. This hyaline material primarily consists of carbohydrates that result from the partial degradation of the cell wall of uniseriate trichomes. This degradation occurs at the same time that glandular trichomes secrete terpenoids, phenolic compounds and proteins. These results suggest that the non-glandular trichomes on the leaves of L. diamantinana help protect the young organ, particularly against desiccation, by deposition of highly hydrated substances on the apices. Furthermore, the secretion of glandular trichomes probably repels herbivore and pathogen attacks.

Evaluation of the cytotoxic and genotoxic potential of water from the River Paraíba do Sul, in Brazil, with the Allium cepa L. test

This work investigated the cytotoxic and genotoxic potential of water from the River Paraíba do Sul (Brazil) using Allium cepa roots. An anatomo-morphological parameter (root length), mitotic indices, and frequency of micronuclei were analysed. Eight bulbs were chosen at random for treatment for 24 to 120 hours with the River water collected in the years of 2005 and 2006 from sites in the cities of Tremembé and Aparecida (São Paulo state, Brazil). Daily measurements of the length of the roots grown from each bulb were carried out throughout the experiment. Mitotic index (MI) and frequency of micronuclei (MN) were determined for 2000 cells per root, using 3-5 root tips from other bulbs (7-10). Only in the roots treated with samples of the River water collected in 2005 in Tremembé city was there a decrease in the root length growth compared to the respective control. However, a reduction in MI values was verified for both sites analysed for that year. Considering the data involving root length growth and especially MI values, a cytotoxic potential is suggested for the water of the River Paraíba do Sul at Tremembé and Aparecida, in the year of 2005. On the other hand, since in this year the MN frequency was not affected with the river water treatments, genotoxicity is not assumed for the river water sampled at the aforementioned places.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

A new classification of foods based on the extent and purpose of their processing

This paper describes a new food classification which assigns foodstuffs according to the extent and purpose of the industrial processing applied to them. Three main groups are defined: unprocessed or minimally processed foods (group 1), processed culinary and food industry ingredients (group 2), and ultra-processed food products (group 3). The use of this classification is illustrated by applying it to data collected in the Brazilian Household Budget Survey which was conducted in 2002/2003 through a probabilistic sample of 48,470 Brazilian households. The average daily food availability was 1,792 kcal/person being 42.5% from group 1 (mostly rice and beans and meat and milk), 37.5% from group 2 (mostly vegetable oils, sugar, and flours), and 20% from group 3 (mostly breads, biscuits, sweets, soft drinks, and sausages). The share of group 3 foods increased with income, and represented almost one third of all calories in higher income households. The impact of the replacement of group 1 foods and group 2 ingredients by group 3 products on the overall quality of the diet, eating patterns and health is discussed.

Quality of water sources used as drinking water in a Brazilian peri-urban area

The objective of this paper was to assess bacteriological quality of drinking water in a peri-urban area located in the Metropolitan Region of São Paulo, Brazil. A total of 89 water samples were collected from community plastic tanks and 177 water samples from wells were collected bimonthly, from September 2007 to November 2008, for evaluating bacteriological parameters including: Escherichia coli, Enterococcus and heterotrophic plate count (HPC). Clostridium perfringens was investigated in a subsample (40 samples from community plastic tank and 40 from wells). E. coli was present in 5 (5.6%) samples from community plastic tanks (2.0 - 5.1x10(4) MPN/100mL) and in 70 (39.5%) well samples (2.0 - 8.6x10(4) MPN/100mL). Thus, these samples were not in accordance with the Brazilian Regulation. Enterococcus was detected in 20 (22.5%) samples of the community plastic tanks (1 to 79 NC/100mL) and in 142 (80.2%) well samples (1 to >200 NC/100mL). C. perfringens was detected in 5 (12.5%) community plastic tanks samples and in 35 (87.5%) wells samples (2.2 to >16 MPN/100mL). HPC were above 500 CFU/mL in 5 (5.6%) waters from community plastic tanks. In wells samples, the HPC ranged from <1 to 1.6x10(4) CFU/mL. The residual chlorine did not attend the standard established in the drinking water legislation (0.2 mg/L), except in 20 (22.5%) samples. These results confirm the vulnerability of the water supply systems in this peri-urban area what is clearly a public health concern.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.