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Talking to God, under Terrence Malick’s Tree of Life

Talking to God, under Terrence Malick’s Tree of Life

The oak constitutes a symbol of Genesis and of the enduring human, animal and vegetable life (Michaels 89). In mythic terms, the tree represents the cosmic integration, since its roots hide in the substrata (symbolically, the underworld), the trunk is visible in the world, and the branches open to the sky. According to anthropologist Brian Molineaux, numerous legends portray a tree as a sacred element: in Scandinavian mythology, Yggdrasil, a giant ash tree, unites the cosmos, draws water from the fountains and offers it to the Gods; in the southern regions of Africa, the Herero people believe a tree, Omum-borombonga, originated the first humans and the cattle they depend upon to survive; in the paintings that decorate Egyptian tombs, the tree of life, planting next to the fountain of youth, are common motifs; even in scientific speech, more precisely in On the Origin of Species, Charles Darwin represents the human evolution as a tree (Molyneaux 90-91).
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Spider phylogenomics: untangling the Spider Tree of Life

Spider phylogenomics: untangling the Spider Tree of Life

Jarvis ED, Mirarab S, Aberer AJ, Li B, Houde P, Li C, Ho SY, Faircloth BC, Nabholz B, Howard JT, Suh A, Weber CC, Da Fonseca RR, Li J, Zhang F, Li H, Zhou L, Narula N, Liu L, Ganapathy G, Boussau B, Bayzid MS, Zavidovych V, Subramanian S, Gabaldon T, Capella-Gutierrez S, Huerta-Cepas J, Rekepalli B, Munch K, Schierup M, Lindow B, Warren WC, Ray D, Green RE, Bruford MW, Zhan X, Dixon A, Li S, Li N, Huang Y, Derryberry EP, Bertelsen MF, Sheldon FH, Brumfield RT, Mello CV, Lovell PV, Wirthlin M, Schneider MPC, Prosdocimi F, Samaniego JA, Velazquez AMV, Alfaro-Nunez A, Campos PF, Petersen B, Sicheritz-Ponten T, Pas A, Bailey T, Scofield P, Bunce M, Lambert DM, Zhou Q, Perelman P, Driskell AC, Shapiro B, Xiong Z, Zeng Y, Liu S, Li Z, Liu B, Wu K, Xiao J, Yinqi X, Zheng Q, Zhang Y, Yang H, Wang J, Smeds L, Rheindt FE, Braun M, Fjeldsa J, Orlando L, Barker FK, Jonsson KA, Johnson W, Koepfli K-P, O’Brien S, Haussler D, Ryder OA, Rahbek C, Willerslev E, Graves GR, Glenn TC, McCormack J, Burt D, Ellegren H, Alstrom P, Edwards SV, Stamatakis A, Mindell DP, Cracraft J, Braun EL, Warnow T, Jun W, Gilbert MTP, Zhang G. 2014. Whole-genome analyses resolve early branches in the tree of life of modern birds. Science 346(6215):1320–1331 DOI 10.1126/science.1253451.
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THE TREE OF LIFE IN RELIGIOUS AND MYSTICAL LITERATURE OF ISLAM

THE TREE OF LIFE IN RELIGIOUS AND MYSTICAL LITERATURE OF ISLAM

Mesopotamian thought and other ancient civilizations around the world. Later, under the title of Sephirot, it has been reflected as the most pivotal discussion in the mystical literature of the Jews. In this study, the archetype of the tree of life in the mystical literature of Islam has been investigated with the Quranic terms, such as Tuba tree, Sidrat al-Muntaha (Sidra tree), Shajarat al-Mubaraka al-Zaytun (the blessed olive tree), and also with the title of Shajarat al-Kawn (tree of existence) in Sufi texts from the cosmic perspective and titles like seven facetiae in the human dimension. Keywords: Tree of life. Tuba tree. The blessed olive tree. Tree of existence. Seven facetiae.
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Universal scaling in the branching of the tree of life.

Universal scaling in the branching of the tree of life.

The Tree of Life is a synoptic depiction of the pathways of evolutionary differentiation between Earth life forms [1], and contains valuable clues on the key issue of understanding the diversification of life in the planet [2]. The branching pattern of the Tree of Life, which is being captured at increasing resolution by the advent of molecular tools [3], can be examined to investigate fundamental questions, such as whether it follows universal rules, and at what extent random differentiation mechanisms explain the shape of phylogenetic trees. The examination of the structure of the Tree of Life can also help to infer whether evolution acts at intraspecific scales in a way different from the action of evolution at the interspecific scale. Here we address these fundamental questions on the basis of a comprehensive comparative analysis of phylogenetic trees representing different fractions and domains of the Tree of Life, from interspecific to intraspecific scales. We draw from previous analyses of the geometry of the Tree of Life [4], the characterization of other branching systems [5,6], and using tools derived from modern network theory [7–10] to examine the scaling of the branching in the Tree of Life [11,12]. Our analysis is based on a thorough data set of more than 5000 interspecific phylogenies and a sample of 67 intraspecific phylogenies (see Text S1), thereby testing the universality of the results derived across scales.
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Using genes as characters and a parsimony analysis to explore the phylogenetic position of turtles.

Using genes as characters and a parsimony analysis to explore the phylogenetic position of turtles.

The phylogenetic position of turtles within the vertebrate tree of life remains controversial. Conflicting conclusions from different studies are likely a consequence of systematic error in the tree construction process, rather than random error from small amounts of data. Using genomic data, we evaluate the phylogenetic position of turtles with both conventional concatenated data analysis and a ‘‘genes as characters’’ approach. Two datasets were constructed, one with seven species (human, opossum, zebra finch, chicken, green anole, Chinese pond turtle, and western clawed frog) and 4584 orthologous genes, and the second with four additional species (soft-shelled turtle, Nile crocodile, royal python, and tuatara) but only 1638 genes. Our concatenated data analysis strongly supported turtle as the sister-group to archosaurs (the archosaur hypothesis), similar to several recent genomic data based studies using similar methods. When using genes as characters and gene trees as character-state trees with equal weighting for each gene, however, our parsimony analysis suggested that turtles are possibly sister-group to diapsids, archosaurs, or lepidosaurs. None of these resolutions were strongly supported by bootstraps. Furthermore, our incongruence analysis clearly demonstrated that there is a large amount of inconsistency among genes and most of the conflict relates to the placement of turtles. We conclude that the uncertain placement of turtles is a reflection of the true state of nature. Concatenated data analysis of large and heterogeneous datasets likely suffers from systematic error and over-estimates of confidence as a consequence of a large number of characters. Using genes as characters offers an alternative for phylogenomic analysis. It has potential to reduce systematic error, such as data heterogeneity and long-branch attraction, and it can also avoid problems associated with computation time and model selection. Finally, treating genes as characters provides a convenient method for examining gene and genome evolution.
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COMPARING GLOBAL LAND COVER DATASETS THROUGH THE EAGLE MATRIX LAND COVER COMPONENTS FOR CONTINENTAL PORTUGAL

COMPARING GLOBAL LAND COVER DATASETS THROUGH THE EAGLE MATRIX LAND COVER COMPONENTS FOR CONTINENTAL PORTUGAL

Global land cover datasets are vital source of information for variety of disciplines such as agriculture, forestry and transportation. Several global land cover maps are produced recently such as Global Land Cover-Share (GLC-Share) and Globeland30. Each of these land cover datasets are produced by the experts considering the purpose of use. Therefore each of these maps have some temporal, spatial and thematic in/consistencies (Verburg et al., 2011). Comparison of these data sets is important for the users to reveal the inconsistencies between datasets, especially before starting a study on a specific topic using these datasets. (Wu et al., 2008). Thus, they can have good overview about similarities and differences in datasets and it will help in decision making for their specific application. On the other hand, comparison of the maps are important in a producer’s perspective to examine the reasons of disagreements in products, in order to improve the quality of the future products (Caetano and Araújo, 2006).
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Bayesian analysis of congruence of core genes in Prochlorococcus and Synechococcus and implications on horizontal gene transfer.

Bayesian analysis of congruence of core genes in Prochlorococcus and Synechococcus and implications on horizontal gene transfer.

Bayesian phylogenetic analysis of all 379 core genes used in this study. Our results do not conflict with previous studies reporting large amounts of HGT reported within the cyanobacterial phylum [22,39,40], as our study is much more targeted to an ecologically distinct and monophyletic subclade of cyanobacteria. Although it is possible that large amounts of HGT may still exist within the phylum as a whole, the genes we consider here show little incongruence with one another, consistent with previous studies looking at the general trend of congruence between concatenated proteins, both for core and shell proteins from cyanobacteria [41]. Our results validate the suggestion of Hillis et al. [20] that tree- to-tree distances, displayed via NMMDS, would be a useful method for visualizing the relationships between tree clouds. The fact that there is a central phylogenetic tendency in the individual gene treeclouds, and that the UP treecloud plot at the center of this cluster, is immediately revealed by NMMDS plots, and confirmed by statistical tests. This central phylogenetic signal is most likely a reflection of the vertical history of genes, and thus supports previous efforts in finding vertical signal even in the face of pervasive HGT in bacteria [42]. It would appear from our data that the evolutionary history of Core Genes in marine cyanobac- teria are relatively similar and cluster with the UP species tree, which can be interpreted as reflecting a substantial detectable history of vertical inheritance, thus supporting the Core Gene hypothesis in this group.
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Do tree-species richness, stand structure and  ecological factors affect the photosynthetic efficiency  in European forests?

Do tree-species richness, stand structure and ecological factors affect the photosynthetic efficiency in European forests?

Baeten, L., Verheyen, K., Wirth, C., Bruelheide, H., Bussotti, F., Finér, L., Jaroszewicz, B., Selvi, F., Valladares, F., Allan, E., Am- poorter, E., Auge, H., Av˘ac˘ariei, D., Barbaro, B., B˘arnoaiea ,I., Bastias, C. C., Bauhus, J., Beinhoff, C., Benavides, R., Benneter, A., Berger, S„ Berthold,F., Boberg, J., Bonal, D., Brüggemann, W., Carnol, M., Castagneyrol, B., Charbonnier, Y., Chécko, E., Coomes, D., Coppi, A., Dalmaris, E., D˘anil˘a, G., Dawud, S. M., de Vries, W., De Wandeler, H., Deconchat, M., Domisch, T., Duduman, G., Fischer, M., Fotelli, M., Gessler, A., Gimeno, T. E., Granier, A., Grossiord, C., Guyot, V., Hantsch, L., Hätten- schwiler, S., Hector, A., Hermy, M., Holland, V., Jactel, H., Joly, F.-X., Jucker, T., Kolb, S., Koricheva, J., Lexer, M. J., Lieberge- sell, M., Milligan, H., Müller, M., Muys, B., Nguyen, D., Nichi- forel, L., Pollastrini, M., Proulx, R., Rabasa, S., Radoglou, K., Ratcliff, S., Raulund-Rasmussen, K., Seiferling, I., Stenlid, J., Vesterdal, L., von Wilpert, K., Zavala, M. A., Zielinski, D., and Scherer-Lorenzen, M.: A novel comparative research platform designed to determine the functional significance of tree species diversity in European forests, Persp. Pl. Ecol. Evolut. Syst., 15, 281–291, 2013.
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SubClonal Hierarchy Inference from Somatic Mutations: Automatic Reconstruction of Cancer Evolutionary Trees from Multi-region Next Generation Sequencing.

SubClonal Hierarchy Inference from Somatic Mutations: Automatic Reconstruction of Cancer Evolutionary Trees from Multi-region Next Generation Sequencing.

S6 Fig. Performance of Genetic Algorithm in reconstruction of a subclonal phylogeny with large node count (n = 15). A. a phylogenetic tree summarizing clonal evolution in a second simulated patient B. Cellularity values of fifteen mutation clusters (CL0-14) in seven simulated biopsies S1–7 C. CPOV matrix depicting the hypothesis test outcomes. Each red square repre- sents a pair of mutation clusters (I,J) for which the null hypothesis that I could be the parent of J was rejected. Each blue square represents a pair for which the null hypothesis could not be rejected. D. The Jaccard index (S1 Text, Topology Similarity Measure) of the true tree (A) and the maximum fitness tree(s) in population at the end of each GA generation. In cases where more than a single maximum fitness tree was present, the maximum of the Jaccard indices is plotted. Each color trace represent one of ten independent GA runs performed on inputs in (B, C). Only one of the ten GA runs (dark purple trace) identified the true tree (indicated by reach- ing Jaccard Index = 1). E. The Jaccard index of the true tree and the maximum fitness trees at the end of each generation for the successful run. Each transparent circle represents a single maximum fitness tree. This GA run also found 16 other phylogenetic trees sharing the maxi- mum fitness with the true tree. (A). F. The consensus topology of the seventeen trees identified in (E). These trees disagreed in parental lineage of 5 out 15 mutation clusters CL16, CL7, CL8, CL12, CL14.
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Performance monitoring and optimization of industrial processes [abstract]

Performance monitoring and optimization of industrial processes [abstract]

584 Biotechnol. Agron. Soc. Environ. 2010 14(S2), 583-584 Abstracts The total lipids of Tsukamurella paurometabola C-924 were analyzed after freeze-drying. Seven individual lipids classes were identiied namely neutral lipids (NLs), fatty acids (FAs), phospholipids (PLs), sterol ester (SEs), triglycerides (TGs), diglycerides (DGs) and monoglycerides (MGs). The principal fatty acids identiied in most lipid classes were palmitic (C 16:0 ), palmitoleic

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Nutritional deficiency in citrus with symptoms of citrus variegated chlorosis disease

Nutritional deficiency in citrus with symptoms of citrus variegated chlorosis disease

(3A) and the loadings (3B). In the scores plot it is pos- sible to see that the samples A and B (non-symptomatic tree and leaf, respectively – open squares and triangles) were clustered and positioned at the superior part of the plot. Samples E (chlorotic area – black circles) were positioned at the inferior part of the scores. Samples C and D (necrosed and non-symptomatic area, respective- ly – black triangles and open circles) were positioned between both groups commented before. These clusters presented in the scores plot were linked with the follow- ing elements: K (positioned at the superior part of the loadings plot) connected to samples A and B; Zn, Mn, Cu and Fe related to samples E. This behaviour indicates that samples A and B have more K than the other sam- ples. Similarly samples E have more Zn, Mn, Cu and Fe than the others. The samples C and D have intermediate elements concentration. Finally it is concluded that in the chlorotic samples (E) the leaves incorporated these elements. In addition, the low or high content of Zn in leaves can be an indication of a chlorotic state.
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Iron Chelators and Antioxidants Regenerate Neuritic Tree and Nigrostriatal Fibers of MPP+/MPTP-Lesioned Dopaminergic Neurons.

Iron Chelators and Antioxidants Regenerate Neuritic Tree and Nigrostriatal Fibers of MPP+/MPTP-Lesioned Dopaminergic Neurons.

Iron chelation has been introduced as a novel therapy concept for the treatment of PD and other diseases with an iron accumulation component, as detailed in recent reviews [10–12]. Two 8-OH quinoline-based chelators that permeate the blood-brain barrier, M30 and PBT2, are regarded as putative therapeutic agents for the treatment of neurodegenerative diseases with an iron accumulation component [13, 14]. The 8-OH quinoline-based chelator PBT2 was used in a double-blind, randomized, placebo-controlled Phase II trials for Alzheimer’s disease. Patients in the group treated with 250 mg PBT2 daily showed significant improvement on a neuro-psychological test battery within 12 weeks of treatment [15]. Importantly, in a recent placebo-controlled randomized clinical trial, early-stage Parkinson's patients treated with deferiprone (DFP; 30 mg/Kg body weight) showed significantly decreased iron deposits in substantia nigra and significantly improved Unified Parkinson’s Disease Rating Scale motor indicators of disease progression [16]. The authors concluded that these results warrant a com- prehensive evaluation of iron chelation therapy in PD.
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Geostatistical analysis of bacterial blight in coffee tree seedlings in the nursery

Geostatistical analysis of bacterial blight in coffee tree seedlings in the nursery

As there was spatial dependence, i.e., inoculum source for dissemination of the pathogen, interpolated grid or maps of spatial distribution of seedlings with symptoms of bacterial blight of coffee tree in the nursery could be generated (Figure 4). In this case, there was formation, lateral expansion and coalescence of foci. Gottwald et al. (20) and Alves et al. (3) also verified formation and coalescence of secondary foci for pathosystems Xanthomonas campestris pv. citri in citrus seedling nursery and C. lindemuthianum in the culture of beans (Phaseolus vulgaris L.) in the field, respectively. In these cases, the disease progress can be increased if the environment is favorable to the epidemic and the host susceptible to the infection (12, 13, 19, 20, 36, 38), especially in bacterial pathosystems, causing spatial and temporal expansion from diseased plant foci. In a nursery of coffee tree seedlings, both high plant density and sprinkling irrigation provide favorable conditions and environment for the occurrence, as well as high progress of bacterial blight of coffee tree. The direct contact among leaves of seedlings associated with the moisture excess in the environment favors the pathogen dissemination and occurrence of epidemics with high rates of progress of this disease.
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Enhancing the Performance of Entropy Algorithm using Minimum Tree in Decision Tree Classifier

Enhancing the Performance of Entropy Algorithm using Minimum Tree in Decision Tree Classifier

Classification builds a model based on historical data (training data set). Once the model is built, it is used to predict the class for a new instance. Many methods have been proposed to solve the classification problem (referred to as classifiers); one of the most popular and best classifiers proposed so far is the decision tree classifier. Multiple trees can be generated from the same dataset, all the trees yields the same outcome for a given new instance to be classified. The possible trees for a dataset vary in their size where the size of the tree depends on the sequence in which the dataset attributes is used to build the tree. However, we prefer the minimum tree because the minimum tree needs the shortest time to figure out the outcome of the model. One of the best algorithms that have been proposed to find the sequence that yield the minimum tree if used is the entropy algorithm. We proposed in this article a new algorithm (enhanced entropy algorithm) that reduces complexity and execution time of the original entropy algorithm and at the same time yields the same sequence that can be found by applying entropy algorithm.
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Peroxidase Activity and Isoforms in the Leaves of Apple Tree Varieties Differing in Scab Resistance

Peroxidase Activity and Isoforms in the Leaves of Apple Tree Varieties Differing in Scab Resistance

were used as a material. All the studies were carried out in 2012-13 on the basis of Siberian Institute of Plant Physiology and Biochemistry SB RAS, farms of the Irkutsk district of the Irkutsk region. The plant material for the collection lot was grown under identical agrotechnical and climatic conditions. 2- years old plantlets of berry apple tree were used as stock apples.

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Clinics  vol.66 número1

Clinics vol.66 número1

The tree model that consisted of more than three parameters markedly improved sensitivity. It yielded a sensitivity of 84.9 % which was higher that that of single parameter and had an excellent specificity of 82.98% in the training sample. Eight-four percent of patients were correctly classified. Patients may be divided into a high- risk group (83.2%) and low-risk group (15.2%) according to the possibility of presence of LEV by CART analysis. This suggests that patients with a spleen width .44.5 mm or those with a spleen width of #44.5 mm, with a portal vein diameter of .11.75 mm and a prothrombin time of .17.05s would benefit from more frequent endoscopies. However, endoscopies could be postponed in patients with a spleen width of #44.5 mm, a portal vein diameter of #11.75 mm, or in patients with a spleen width of #44.5 mm, a portal vein diameter .11.75 mm and a prothrombin time of #17.05s. Moreover, the tree model proved to be well calibrated (predicted outcomes in the training sample were repro- duced fairly in the test sample) and achieved a comparable diagnostic accuracy of 84.4% in the test sample. Patients in the test sample can also be organized into the high- (83.4%) and low-risk (14.5%) groups (Figure 4). Furthermore, the diagnostic accuracies of the tree model in the various Child- Pugh classes were comparable. The intuitive nature of the tree model allows an easy assessment of the risk of the presence of LEV without the need for complex calculations. Our study has several limitations. Data were collected retrospectively, which may produce a population bias as confirmed by the fact that the prevalence of LEV in our series was higher that that in other studies, 9,14 which may be due, in part, to selected bias. In addition, the sample size of this study was small. Therefore, a large prospective study is mandatory.
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Edge principal components and squash clustering: using the special structure of phylogenetic placement data for sample comparison.

Edge principal components and squash clustering: using the special structure of phylogenetic placement data for sample comparison.

Lactobacillus is associated with a low Nugent score and thus a negative BV diagnosis; in the results presented here L. crispatus dominated samples are not found to have a high Nugent score (indicating BV), while L. iners dominated samples sometimes are. In both the Forney and the Fredricks data sets, the samples with the highest Nugent score lie on a continuum of samples from the left to the lower right (from Sneathia/Prevotella to L. iners -dominant). A similar pattern is observed when the samples are divided by race (Fig. S2). Reviewing the taxonomically classified data from the Fredricks study confirms this trend. These plots indicate the possibility of a medically relevant difference between these two Lactobacillus species in a pattern that is consistent between two large, independent studies. It is also significant that phylogenetic placement on a reference tree containing full-length 16S rRNA gene sequences allows a direct comparison between the two data sets despite the fact that each sequenced a different region of the 16S rRNA gene. We emphasize that the PCA was not informed of either the Nugent score associated with the specimens or the taxonomic classifications of the sequences.
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An individual tree growth model for juvenile cork oak stands in southern Portugal

An individual tree growth model for juvenile cork oak stands in southern Portugal

Abstract. The juvenile and adult stages in cork oak are distinct because of the periodic debarking of the stem and branches that characterizes the adult stage. This fact implies the use of diameter under bark for the adult stage while diameter over bark is the natural variable for juvenile stands in growth and yield studies. Tree growth in the adult stage may also be affected by the periodic debarking. The differences between the two stages justify the development of different models for each of them. The objective of this paper is to develop an individual tree growth and yield model for juvenile cork oak stands for general application on the cork oak distribution area in Southern Portugal. The most important modules of this growth model were developed using data collected from a large number of trees in the juvenile stage, from several plots distributed around the South of Portugal. These modules were: an individual tree diameter growth model, a height-diameter model and a model for crown diameter prediction. Key words: Quercus suber L.; growth and yield model
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Evaluating oral health-related quality of life measure for children and preadolescents with temporomandibular disorder

Evaluating oral health-related quality of life measure for children and preadolescents with temporomandibular disorder

The discriminant construct validity of the question- naires was supported by their ability to detect differ- ences in the impact on QoL, evidenced by the highest scores being seen in children and preadolescents with signs and symptoms of TMD. However, although the difference in scores supported the validity of the mea- sures, the magnitude of these differences was only low to moderate. According to Reissmann et al. [14], the magnitude of TMD impact depends on the definition of the comparison group without TMD diagnoses. Although patients in the general population are the most plausible choice for comparison (which was chosen in the present study), they may have some signs and symptoms of TMD; these are insufficient to warrant an RDC/TMD diagnosis but sufficient to influence QoL. This is consistent with the findings by Reissmann et al. [14], where subjects without diagnosis had a more than 50% higher OHRQoL impact levels compared to sub- jects without any TMD sign or symptom. Other authors suggest that differences in scores of QoL measures can be properly interpreted only after minimally important differences have been recognized [64]. The minimum important difference is defined as the smallest difference in scores that patients perceive as being important, which would suggest a change in the patient’s manage- ment [65]. This score can be determined only following longitudinal studies in which some individuals changed and some did not, either as the result of therapy or nat- ural fluctuations in the disorder. This evaluation has yet to be undertaken with respect to the measures used in this study.
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SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES

SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES

As expected, grassland areas presented lower values of tree cover 25.9% and higher values of bare surface 46.26%. Note that in the case of Deciduous Forest 2 it was verifi ed a decrease in tree cover from 36.46 to 30.24% and an increase in bare surface from 5.50 to 19.35% when compared to Deciduous Forest probably due to a higher degree of disturbance in the former. Savanna formations presented the higher deviation of tree cover, 17.43%, probably because of the variation in vertical structure. On the other hand, forest wetlands showed low density of bare surface 4.99% due to the dense tree Table 2 – Producer’s and user’s errors derived from confusion
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