Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data

Compositional data analysis in archaeometry

We shall call an n × p data matrix fully-compositional if the rows sum to a constant, and sub-compositional if the variables are a subset of a fully-compositional data set1. Such data occur widely in archaeometry, where it is common to determine the chemical composition of ceramic, glass, metal or other artefacts using techniques such as neutron activation analysis (NAA), inductively coupled plasma spectroscopy (ICPS), X-ray fluorescence analysis (XRF) etc. Interest often centres on whether there are distinct chemical groups within the data and whether, for example, these can be associated with different origins or manufacturing technologies

Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.

Biclustering Gene Expression Data using MSR Difference Threshold

Biclustering is simultaneous clustering of both rows and columns of a data matrix. A measure called Mean Squared Residue (MSR) is used to simultaneously evaluate the coherence of rows and columns within a submatrix. In this paper a novel algorithm is developed for biclustering gene expression data using the newly introduced concept of MSR difference threshold. In the first step high quality bicluster seeds are generated using K-Means clustering algorithm. Then more genes and conditions (node) are added to the bicluster. Before adding a node the MSR X of the bicluster is calculated. After adding the node again the MSR Y is calculated. The added node is deleted if Y minus X is greater than MSR difference threshold or if Y is greater than MSR threshold which depends on the dataset. The MSR difference threshold is different for gene list and condition list and it depends on the dataset also. Proper values should be identified through experimentation in order to obtain biclusters of high quality. The results obtained on bench mark dataset clearly indicate that this algorithm is better than many of the existing biclustering algorithms

Compositional data analysis in archaeometry

We shall call an n × p data matrix fully-compositional if the rows sum to a constant, and sub-compositional if the variables are a subset of a fully-compositional data set1. Such data occur widely in archaeometry, where it is common to determine the chemical composition of ceramic, glass, metal or other artefacts using techniques such as neutron activation analysis (NAA), inductively coupled plasma spectroscopy (ICPS), X-ray fluorescence analysis (XRF) etc. Interest often centres on whether there are distinct chemical groups within the data and whether, for example, these can be associated with different origins or manufacturing technologies

Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr) transformation to obtain the random vector y of dimension D. The factor model is then y = Λf + e (1) with the factors f of dimension k < D, the error term e, and the loadings matrix Λ. Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysis model (1) can be written as Cov(y) = ΛΛT + ψ (2) where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as the loadings matrix Λ are estimated from an estimation of Cov(y). Given observed clr transformed data Y as realizations of the random vector y. Outliers or deviations from the idealized model assumptions of factor analysis can severely effect the parameter estimation. As a way out, robust estimation of the covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), see Pison et al. (2003). Well known robust covariance estimators with good statistical properties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), rely on a full-rank data matrix Y which is not the case for clr transformed data (see, e.g., Aitchison, 1986). The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves this singularity problem. The data matrix Y is transformed to a matrix Z by using an orthonormal basis of lower dimension. Using the ilr transformed data, a robust covariance matrix C(Z) can be estimated. The result can be back-transformed to the clr space by C(Y ) = V C(Z)V T where the matrix V with orthonormal columns comes from the relation between the clr and the ilr transformation. Now the parameters in the model (2) can be estimated (Basilevsky, 1994) and the results have a direct interpretation since the links to the original variables are still preserved. The above procedure will be applied to data from geochemistry. Our special interest is on comparing the results with those of Reimann et al. (2002) for the Kola project data

Coding behavioural data for cladistic analysis: using dynamic homology without parsimony

Many of the controversies around the concept of homology rest on the subjectivity inherent to primary homology propositions. Dynamic homology partially solves this problem, but there has been up to now scant application of it outside of the molecular domain. This is probably because morphological and behavioural characters are rich in properties, connections and qualities, so that there is less space for conflicting character delimitations. Here we present a new method for the direct optimization of behavioural data, a method that relies on the richness of this database to delimit the characters, and on dynamic procedures to establish character state identity. We use between-species congruence in the data matrix and topological stability to choose the best cladogram. We test the methodology using sequences of predatory behaviour in a group of spiders that evolved the highly modified predatory technique of spitting glue onto prey. The cladogram recovered is fully compatible with previous analyses in the literature, and thus the method seems consistent. Besides the advantage of enhanced objectivity in character proposition, the new procedure allows the use of complex, context-dependent behavioural characters in an evolutionary framework, an important step towards the practical integration of the evolutionary and ecological perspectives on diversity. (C) The Willi Hennig Society 2010.

Analyzing the dependence structure of microarray data: a copula–based approach

The main aim of this Ph.D. dissertation is the study of clustering dependent data by means of copula functions with particular emphasis on microarray data. Copula functions are a popular multivariate modeling tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses on the K–means (Hartigan, 1975; Hartigan and Wong, 1979), the hierarchical (Everitt, 1974) and the model–based (Fraley and Raftery, 1998, 1999, 2000, 2007) clustering techniques because their performance is compared. Then, the probabilistic interpretation of the Sklar’s theorem (Sklar’s, 1959), the estimation methods for copulas like the Inference for Margins (Joe and Xu, 1996) and the Archimedean and Elliptical copula families are presented. In the end, applications of clustering methods and copulas to the genetic and microarray experiments are highlighted. The second part contains the original contribution proposed. A simulation study is performed in order to evaluate the performance of the K–means and the hierarchical bottom–up clustering methods in identifying clusters according to the dependence structure of the data generating process. Different simulations are performed by varying different conditions (e.g., the kind of margins (distinct, overlapping and nested) and the value of the dependence parameter ) and the results are evaluated by means of different measures of performance. In light of the simulation results and of the limits of the two investigated clustering methods, a new clustering algorithm based on copula functions (‘CoClust’ in brief) is proposed. The basic idea, the iterative procedure of the CoClust and the description of the written R functions with their output are given. The CoClust algorithm is tested on simulated data (by varying the number of clusters, the copula models, the dependence parameter value and the degree of overlap of margins) and is compared with the performance of model–based clustering by using different measures of performance, like the percentage of well–identified number of clusters and the not rejection percentage of H0 on . It is shown that the CoClust algorithm allows to overcome all observed limits of the other investigated clustering techniques and is able to identify clusters according to the dependence structure of the data independently of the degree of overlap of margins and the strength of the dependence. The CoClust uses a criterion based on the maximized log–likelihood function of the copula and can virtually account for any possible dependence relationship between observations. Many peculiar characteristics are shown for the CoClust, e.g. its capability of identifying the true number of clusters and the fact that it does not require a starting classification. Finally, the CoClust algorithm is applied to the real microarray data of Hedenfalk et al. (2001) both to the gene expressions observed in three different cancer samples and to the columns (tumor samples) of the whole data matrix.

Presence-absence species/sample matrix for the measured sections at the area of Maghara, North Sinai, Egypt

As age-diagnostic fossils are rare in the Middle to Upper Jurassic sedimentary succession of Gebel Maghara, North Sinai, Egypt, and in order to ensure maximal stratigraphic resolution, chronostratigraphic boundaries were determined based on quantitative biostratigraphy. A data matrix comprising 231 macrofaunal taxa in 93 samples from four sections has been processed with the Unitary Association (UA) Method. This led to construction of a sequence of 29 UAs (maximal sets of actually or virtually coexisting taxa), which have been grouped into 14 laterally reproducible association zones. The UA method allowed an in-depth analysis of the stratigraphically conflicting taxa, enabled the biostratigraphic subdivision of the studied interval, and also provided stratigraphic correlation among the measured sections and with the Tethyan ammonite zones.

Petroleomics By Electrospray Ionization Ft-icr Mass Spectrometry Coupled To Partial Least Squares With Variable Selection Methods: Prediction Of The Total Acid Number Of Crude Oils.

Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.

A New Baurusuchid (Crocodyliformes, Mesoeucrocodylia) from the Late Cretaceous of Brazil and the Phylogeny of Baurusuchidae

Background: Baurusuchidae is a group of extinct Crocodyliformes with peculiar, dog-faced skulls, hypertrophied canines, and terrestrial, cursorial limb morphologies. Their importance for crocodyliform evolution and biogeography is widely recognized, and many new taxa have been recently described. In most phylogenetic analyses of Mesoeucrocodylia, the entire clade is represented only by Baurusuchus pachecoi, and no work has attempted to study the internal relationships of the group or diagnose the clade and its members. Methodology/Principal Findings: Based on a nearly complete skull and a referred partial skull and lower jaw, we describe a new baurusuchid from the Vale do Rio do Peixe Formation (Bauru Group), Late Cretaceous of Brazil. The taxon is diagnosed by a suite of characters that include: four maxillary teeth, supratemporal fenestra with equally developed medial and anterior rims, four laterally visible quadrate fenestrae, lateral Eustachian foramina larger than medial Eustachian foramen, deep depression on the dorsal surface of pterygoid wing. The new taxon was compared to all other baurusuchids and their internal relationships were examined based on the maximum parsimony analysis of a discrete morphological data matrix. Conclusion: The monophyly of Baurusuchidae is supported by a large number of unique characters implying an equally large morphological gap between the clade and its immediate outgroups. A complex phylogeny of baurusuchids was recovered. The internal branch pattern suggests two main lineages, one with a relatively broad geographical range between Argentina and Brazil (Pissarrachampsinae), which includes the new taxon, and an endemic clade of the Bauru Group in Brazil (Baurusuchinae).

Systematic review and cladistic analysis of the genus Eusarcus Perty 1833 (Arachnida, Opiliones, Gonyleptidae)

Eusarcus Perty 1833 is one of the oldest described genera of Pachylinae, comprising 36 species distributed from northeastern to southern Brazil (including the central west region), northeastern Argentina, eastern Paraguay and Uruguay. The genus is reviewed and a new classification is proposed based on a cladistic analysis. A cladistic analysis was performed with the 34 valid species of Eusarcus and 11 species belonging to certain Gonyleptidae subfamilies. The data matrix has 67 characters: 14 from dorsal scutum and pedipalp, 38 from male legs and 15 from male genitalia. Two equally parsimonious trees were found (L=319; C. I.=0.26, R. I.=0.61). Pygophalangodus gemignanii uruguayensis Ringuelet 1955a and Pygophalangodus gemignanii gemignanii Mello-Leitao 1931b are here elevated to the category of species, and the following new combinations are proposed: E. catharinensis (Mello-Leitao 1927); E. berlae (Mello-Leitao 1932); E. gemignanii (Mello-Leitao 1931b); E. signatus(Roewer 1949); E. sooretamae (Soares & Soares 1946a); E. uruguayensis (Ringuelet 1955a). The following generic synonymies are proposed: Eusarcus Perty 1833 (type species E. armatus Perty 1833) = Metagraphinotus Mello-Leitao 1927 (type species M. catharinensis Mello-Leitao 1927), Pareusarcus Roewer 1929 (type species P. corniculatus Roewer 1929), Pygophalangodus Mello-Leitao 1931b (type species P. gemignanii-gemignanii Mello-Leitao 1931b) and Antetriceras Roewer 1949 (type species A. signatus Roewer 1949). The following specific synonymies are proposed: Eusarcus hastatus Sorensen 1884 = Pucrolioides argentina Roewer 1913, E. guimaraensi H. Soares 1945, Jacarepaguana pectinifemur Piza 1943, Canestrinia canalsi Mello-Leitao 1931a, and E. maquinensis H. Soares 1966b; E. armatus Perty 1833 = E. curvispinosus Mello-Leitao 1923b, and Enantiocentron montis Mello-Leitao 1936; Eusarcus catharinensis (Mello-Leitao 1927) = E. antoninae Mello-Leitao 1936, E. perpusillus Mello-Leitao 1945, E. tripos Mello-Leitao 1940, and Metagraphinotus trochanterspinosus Soares & Soares 1947b; E. nigrimaculatus Mello-Leitao 1924 = Pareusarcus centromelos Mello-Leitao 1935a, E. furcatus Roewer 1929, Orguesia armata Roewer 1913, and Pareusarcus corniculatus Roewer 1929; E. oxyacanthus Kollar in Koch 1839a = Enantiocentron doriphorus Mello-Leitao 1932, and E. spinimanu Mello-Leitao 1932; E. pusillus Sorensen 1884 = E. vervloeti B. Soares 1944c; E. berlae Mello-Leitao 1932 = Metagraphinotus arlei Mello-Leitao 1935a. Metapucrolia armata (Sorensen 1895) is revalidated, transferred to Eusarcus and considered as a species inquirenda. A new name, Eusarcus metapucrolia is proposed for this species to avoid homonymy with the type species of Eusarcus, E. armatus Perty 1833. Eusarcus aberrans Mello-Leitao 1939a is considered as a species inquirenda. The male of E. teresincola Soares & Soares 1946a is described. Female of the following species are described: E. bifidus Roewer 1929; E. dubius B. Soares 1943b; E. insperatus B. Soares 1944a; E. schubarti Soares & Soares 1946a; E. sooretamae (Soares & Soares 1946a). The following new species are described from Brazil: E. acrophthalmus (type locality: Bahia, Ilheus, Parataquice); E. alpinus (Rio de Janeiro, Santa Maria Madalena, Parque Estadual do Desengano); E. caparaoensis (Minas Gerais, Alto Caparao, Parque Nacional do Caparao); E. cavernicola (Goias, Sao Domingos, Parque Estadual de Terra Ronca, Lapa da Angelica); E. didactylus (Rio de Janeiro, Teresopolis, Parque Nacional Serra dos Orgaos); E. garibaldiae (Santa Catarina, Itajai); E. geometricus (Rio de Janeiro, Teresopolis, Parque Nacional Serra dos Orgaos); E. manero (Rio de Janeiro, Marica, Itaipuacu); E. matogrossensis (Mato Grosso, Chapada dos Guimaraes); E. mirabilis (Minas Gerais, Marlieria, Parque Estadual Rio Doce); E. sergipanus (Sergipe, Itabaiana, Parque Nacional de Itabaiana) and E. tripectinatus (Minas Gerais, Rio Preto). The holotype of E. curvispinosus is proposed as the neotype of E. armatus Perty 1833, the type material of which has been lost. Lectotypes for the following species were designated: E. aduncus; E. hastatus; E. oxyacanthus.

Water quality issues in rivers, lakes and reservoirs in Asian countries: an approach to the problems and the methodologies

Water covers over 70% of the Earth's surface, and is vital for all known forms of life. But only 3% of the Earth's water is fresh water, and less than 0.3% of all freshwater is in rivers, lakes, reservoirs and the atmosphere. However, rivers and lakes are an important part of fresh surface water, amounting to about 89%. In this Master Thesis dissertation, the focus is on three types of water bodies – rivers, lakes and reservoirs, and their water quality issues in Asian countries. The surface water quality in a region is largely determined both by the natural processes such as climate or geographic conditions, and the anthropogenic influences such as industrial and agricultural activities or land use conversion. The quality of the water can be affected by pollutants discharge from a specific point through a sewer pipe and also by extensive drainage from agriculture/urban areas and within basin. Hence, water pollutant sources can be divided into two categories: Point source pollution and Non-point source (NPS) pollution. Seasonal variations in precipitation and surface run-off have a strong effect on river discharge and the concentration of pollutants in water bodies. For example, in the rainy season, heavy and persistent rain wash off the ground, the runoff flow increases and may contain various kinds of pollutants and, eventually, enters the water bodies. In some cases, especially in confined water bodies, the quality may be positive related with rainfall in the wet season, because this confined type of fresh water systems allows high dilution of pollutants, decreasing their possible impacts. During the dry season, the quality of water is largely related to industrialization and urbanization pollution. The aim of this study is to identify the most common water quality problems in Asian countries and to enumerate and analyze the methodologies used for assessment of water quality conditions of both rivers and confined water bodies (lakes and reservoirs). Based on the evaluation of a sample of 57 papers, dated between 2000 and 2012, it was found that over the past decade, the water quality of rivers, lakes, and reservoirs in developing countries is being degraded. Water pollution and destruction of aquatic ecosystems have caused massive damage to the functions and integrity of water resources. The most widespread NPS in Asian countries and those which have the greatest spatial impacts are urban runoff and agriculture. Locally, mine waste runoff and rice paddy are serious NPS problems. The most relevant point pollution sources are the effluents from factories, sewage treatment plant, and public or household facilities. It was found that the most used methodology was unquestionably the monitoring activity, used in 49 of analyzed studies, accounting for 86%. Sometimes, data from historical databases were used as well. It can be seen that taking samples from the water body and then carry on laboratory work (chemical analyses) is important because it can give an understanding of the water quality. 6 papers (11%) used a method that combined monitoring data and modeling. 6 papers (11%) just applied a model to estimate the quality of water. Modeling is a useful resource when there is limited budget since some models are of free download and use. In particular, several of used models come from the U.S.A, but they have their own purposes and features, meaning that a careful application of the models to other countries and a critical discussion of the results are crucial. 5 papers (9%) focus on a method combining monitoring data and statistical analysis. When there is a huge data matrix, the researchers need an efficient way of interpretation of the information which is provided by statistics. 3 papers (5%) used a method combining monitoring data, statistical analysis and modeling. These different methods are all valuable to evaluate the water quality. It was also found that the evaluation of water quality was made as well by using other types of sampling different than water itself, and they also provide useful information to understand the condition of the water body. These additional monitoring activities are: Air sampling, sediment sampling, phytoplankton sampling and aquatic animal tissues sampling. Despite considerable progress in developing and applying control regulations to point and NPS pollution, the pollution status of rivers, lakes, and reservoirs in Asian countries is not improving. In fact, this reflects the slow pace of investment in new infrastructure for pollution control and growing population pressures. Water laws or regulations and public involvement in enforcement can play a constructive and indispensable role in environmental protection. In the near future, in order to protect water from further contamination, rapid action is highly needed to control the various kinds of effluents in one region. Environmental remediation and treatment of industrial effluent and municipal wastewaters is essential. It is also important to prevent the direct input of agricultural and mine site runoff. Finally, stricter environmental regulation for water quality is required to support protection and management strategies. It would have been possible to get further information based in the 57 sample of papers. For instance, it would have been interesting to compare the level of concentrations of some pollutants in the diferente Asian countries. However the limit of three months duration for this study prevented further work to take place. In spite of this, the study objectives were achieved: the work provided an overview of the most relevant water quality problems in rivers, lakes and reservoirs in Asian countries, and also listed and analyzed the most common methodologies.

Evolution of Teeth and Quadrate in Non-avian Theropoda (Dinosauria: Saurischia), with the Description of Torvosaurus Remains from Portugal

Theropods form a highly successful and morphologically diversified group of dinosaurs that gave rise to birds. They include most, if not all, carnivorous dinosaurs, yet many theropod clades were secondarily adapted to piscivory, omnivory and herbivory, and theropods show a large array of skull and dentition morphologies. This work aims to investigate aspects of the evolution of theropod dinosaurs by analyzing in detail both the anatomy and ontogeny of teeth and quadrates in non-avian theropods, and by studying embryonic and adult material of a new species of theropod. A standardized list of terms and notations for each anatomical entity of the tooth, quadrate, and maxilla is here proposed with the goal of facilitating descriptions of these important cranial and dental elements. The distribution of thirty dental characters among 113 theropod taxa is investigated, and a list of diagnostic dental characters is proposed. As an example, four isolated theropod teeth from the Lourinhã Formation (Kimmeridgian‒Tithonian) of Portugal are described and identified based on a cladistic analysis performed on a data matrix of 141 dentition-based characters coded in 60 taxa. Two shed teeth are referred to an abelisaurid, providing the first record of Abelisauridae in the Jurassic of Laurasia and the one of the oldest records of this clade in the world, suggesting a possible radiation of Abelisauridae in Europe well before the Upper Cretaceous. The consensus tree resulting from this phylogenetic analysis, the most extensive on theropod teeth, indicates that theropod teeth provide reliable data for identification at approximately family level, and this method will help identifying theropod teeth with more confidence. A detailed description of the dentition of Megalosauridae is also provided, and a discriminant analysis performed on a dataset of numerical data collected on the teeth of 62 theropod taxa reveals that megalosaurid teeth are hardly distinguishable from other theropod clades with ziphodont dentition. This study highlights the importance of detailing anatomical descriptions and providing additional morphometric data on teeth with the purpose of helping to identify isolated theropod teeth. In order to evaluate the phylogenetic potential and investigate the evolutionary transformations of the quadrate, a phylogenetic morphometric analysis as well as a cladistic analysis using 98 discrete quadrate related characters were conducted. The quadrate morphology by its own provides a wealth of data with strong phylogenetic signal, and the phylogenetic morphometric analysis reveals two main morphotypes of the mandibular articulation of the quadrate linked to function. As an example, six isolated quadrates from the Kem Kem beds (Cenomanian) of Morocco are determined to be from juvenile and adult individuals of Spinosaurinae based on phylogenetic, morphometric, and phylogenetic morphometric analyses. Morphofunctional analysis of the spinosaurid mandibular articulation has shown that the posterior parts of the two mandibular rami displaced laterally when the jaw was depressed due to a mediolaterally oriented intercondylar sulcus of the quadrate. Such lateral movement of the mandibular ramus was possible due to a movable mandibular symphysis in spinosaurids, allowing the pharynx to be widened. A new species of theropod from the Lourinhã Formation of Portugal, Torvosaurus gurneyi, is erected based on a right maxilla and an incomplete caudal centrum. This taxon supports the mechanism of vicariance that occurred in the Iberian Meseta during the Late Jurassic when the proto-Atlantic was already well formed. A theropod clutch containing several crushed eggs and embryonic material is also assigned to this new species of Torvosaurus. Investigation on the maxilla ontogeny in basal tetanurans reveals that crown denticles, elongation of the anterior ramus, and fusion of interdental plates appear at a posthatchling stage. On the other hand, maxillary pneumaticity is already present at an embryonic stage in non-avian theropods.