Phylogeny of subtribe Gentianinae (Gentianaceae): biogeographic inferences despite limitations in temporal calibration points

The subtribe Gentianinae comprises ca. 425 species, most of them within the well-studied genus Gentiana and mainly distributed over the Eurasian continent. Phylogenetic relationships between Gentiana and its closest relatives, the climbing gentians (Crawfurdia, Tripterospermum) and the new genus Metagentiana, remain unclear. All three genera were recently found to be polyphyletic, possibly because of poor sampling of Tripterospermum and Crawfurdia. Highest diversity of Gentianinae occurs in the western Himalaya, but the absence of uncontroversial fossil evidence limits our understanding of its biogeography. In the present study, we generated ITS and atpB-rbcL sequences for 19 species of Tripterospermum, 9 of Crawfurdia and 11 of Metagentiana, together representing about 60 percent of the species diversity of these genera. Our results show that only Metagentiana is polyphyletic and divided into three monophyletic entities. No unambiguous synapomorphies were associated with the three Metagentiana entities. Different combinations of three approximate calibration points were used to generate three divergence time estimation scenarios. Although dating hypotheses were mostly inconsistent, they concurred in associating radiation of Gentiana to an orogenic phase of the Himalaya between 15 and 10 million years ago. Our study illustrates the conceptual difficulties in addressing the time frame of diversification in a group lacking sufficient fossil number and quality.

Chromosomal divergence and evolutionary inferences in Rhodniini based on the chromosomal location of ribosomal genes

In this study, we used fluorescence in situ hybridisation to determine the chromosomal location of 45S rDNA clusters in 10 species of the tribe Rhodniini (Hemiptera: Reduviidae: Triatominae). The results showed striking inter and intraspecific variability, with the location of the rDNA clusters restricted to sex chromosomes with two patterns: either on one (X chromosome) or both sex chromosomes (X and Y chromosomes). This variation occurs within a genus that has an unchanging diploid chromosome number (2n = 22, including 20 autosomes and 2 sex chromosomes) and a similar chromosome size and genomic DNA content, reflecting a genome dynamic not revealed by these chromosome traits. The rDNA variation in closely related species and the intraspecific polymorphism in Rhodnius ecuadoriensis suggested that the chromosomal position of rDNA clusters might be a useful marker to identify recently diverged species or populations. We discuss the ancestral position of ribosomal genes in the tribe Rhodniini and the possible mechanisms involved in the variation of the rDNA clusters, including the loss of rDNA loci on the Y chromosome, transposition and ectopic pairing. The last two processes involve chromosomal exchanges between both sex chromosomes, in contrast to the widely accepted idea that the achiasmatic sex chromosomes of Heteroptera do not interchange sequences.

Inferences about the global scenario of human T-cell lymphotropic virus type 1 infection using data mining of viral sequences

Human T-cell lymphotropic virus type 1 (HTLV-1) is mainly associated with two diseases: tropical spastic paraparesis/HTLV-1-associated myelopathy (TSP/HAM) and adult T-cell leukaemia/lymphoma. This retrovirus infects five-10 million individuals throughout the world. Previously, we developed a database that annotates sequence data from GenBank and the present study aimed to describe the clinical, molecular and epidemiological scenarios of HTLV-1 infection through the stored sequences in this database. A total of 2,545 registered complete and partial sequences of HTLV-1 were collected and 1,967 (77.3%) of those sequences represented unique isolates. Among these isolates, 93% contained geographic origin information and only 39% were related to any clinical status. A total of 1,091 sequences contained information about the geographic origin and viral subtype and 93% of these sequences were identified as subtype “a”. Ethnicity data are very scarce. Regarding clinical status data, 29% of the sequences were generated from TSP/HAM and 67.8% from healthy carrier individuals. Although the data mining enabled some inferences about specific aspects of HTLV-1 infection to be made, due to the relative scarcity of data of available sequences, it was not possible to delineate a global scenario of HTLV-1 infection.

Evolving from inferences to decisions in the interpretation of scientific evidence

Le travail d'un(e) expert(e) en science forensique exige que ce dernier (cette dernière) prenne une série de décisions. Ces décisions sont difficiles parce qu'elles doivent être prises dans l'inévitable présence d'incertitude, dans le contexte unique des circonstances qui entourent la décision, et, parfois, parce qu'elles sont complexes suite à de nombreuse variables aléatoires et dépendantes les unes des autres. Etant donné que ces décisions peuvent aboutir à des conséquences sérieuses dans l'administration de la justice, la prise de décisions en science forensique devrait être soutenue par un cadre robuste qui fait des inférences en présence d'incertitudes et des décisions sur la base de ces inférences. L'objectif de cette thèse est de répondre à ce besoin en présentant un cadre théorique pour faire des choix rationnels dans des problèmes de décisions rencontrés par les experts dans un laboratoire de science forensique. L'inférence et la théorie de la décision bayésienne satisfont les conditions nécessaires pour un tel cadre théorique. Pour atteindre son objectif, cette thèse consiste de trois propositions, recommandant l'utilisation (1) de la théorie de la décision, (2) des réseaux bayésiens, et (3) des réseaux bayésiens de décision pour gérer des problèmes d'inférence et de décision forensiques. Les résultats présentent un cadre uniforme et cohérent pour faire des inférences et des décisions en science forensique qui utilise les concepts théoriques ci-dessus. Ils décrivent comment organiser chaque type de problème en le décomposant dans ses différents éléments, et comment trouver le meilleur plan d'action en faisant la distinction entre des problèmes de décision en une étape et des problèmes de décision en deux étapes et en y appliquant le principe de la maximisation de l'utilité espérée. Pour illustrer l'application de ce cadre à des problèmes rencontrés par les experts dans un laboratoire de science forensique, des études de cas théoriques appliquent la théorie de la décision, les réseaux bayésiens et les réseaux bayésiens de décision à une sélection de différents types de problèmes d'inférence et de décision impliquant différentes catégories de traces. Deux études du problème des deux traces illustrent comment la construction de réseaux bayésiens permet de gérer des problèmes d'inférence complexes, et ainsi surmonter l'obstacle de la complexité qui peut être présent dans des problèmes de décision. Trois études-une sur ce qu'il faut conclure d'une recherche dans une banque de données qui fournit exactement une correspondance, une sur quel génotype il faut rechercher dans une banque de données sur la base des observations faites sur des résultats de profilage d'ADN, et une sur s'il faut soumettre une trace digitale à un processus qui compare la trace avec des empreintes de sources potentielles-expliquent l'application de la théorie de la décision et des réseaux bayésiens de décision à chacune de ces décisions. Les résultats des études des cas théoriques soutiennent les trois propositions avancées dans cette thèse. Ainsi, cette thèse présente un cadre uniforme pour organiser et trouver le plan d'action le plus rationnel dans des problèmes de décisions rencontrés par les experts dans un laboratoire de science forensique. Le cadre proposé est un outil interactif et exploratoire qui permet de mieux comprendre un problème de décision afin que cette compréhension puisse aboutir à des choix qui sont mieux informés. - Forensic science casework involves making a sériés of choices. The difficulty in making these choices lies in the inévitable presence of uncertainty, the unique context of circumstances surrounding each décision and, in some cases, the complexity due to numerous, interrelated random variables. Given that these décisions can lead to serious conséquences in the admin-istration of justice, forensic décision making should be supported by a robust framework that makes inferences under uncertainty and décisions based on these inferences. The objective of this thesis is to respond to this need by presenting a framework for making rational choices in décision problems encountered by scientists in forensic science laboratories. Bayesian inference and décision theory meets the requirements for such a framework. To attain its objective, this thesis consists of three propositions, advocating the use of (1) décision theory, (2) Bayesian networks, and (3) influence diagrams for handling forensic inference and décision problems. The results present a uniform and coherent framework for making inferences and décisions in forensic science using the above theoretical concepts. They describe how to organize each type of problem by breaking it down into its différent elements, and how to find the most rational course of action by distinguishing between one-stage and two-stage décision problems and applying the principle of expected utility maximization. To illustrate the framework's application to the problems encountered by scientists in forensic science laboratories, theoretical case studies apply décision theory, Bayesian net-works and influence diagrams to a selection of différent types of inference and décision problems dealing with différent catégories of trace evidence. Two studies of the two-trace problem illustrate how the construction of Bayesian networks can handle complex inference problems, and thus overcome the hurdle of complexity that can be present in décision prob-lems. Three studies-one on what to conclude when a database search provides exactly one hit, one on what genotype to search for in a database based on the observations made on DNA typing results, and one on whether to submit a fingermark to the process of comparing it with prints of its potential sources-explain the application of décision theory and influ¬ence diagrams to each of these décisions. The results of the theoretical case studies support the thesis's three propositions. Hence, this thesis présents a uniform framework for organizing and finding the most rational course of action in décision problems encountered by scientists in forensic science laboratories. The proposed framework is an interactive and exploratory tool for better understanding a décision problem so that this understanding may lead to better informed choices.

Asymptotic robust inferences in the analysis of mean and covariance structures

Structural equation models are widely used in economic, socialand behavioral studies to analyze linear interrelationships amongvariables, some of which may be unobservable or subject to measurementerror. Alternative estimation methods that exploit different distributionalassumptions are now available. The present paper deals with issues ofasymptotic statistical inferences, such as the evaluation of standarderrors of estimates and chi--square goodness--of--fit statistics,in the general context of mean and covariance structures. The emphasisis on drawing correct statistical inferences regardless of thedistribution of the data and the method of estimation employed. A(distribution--free) consistent estimate of $\Gamma$, the matrix ofasymptotic variances of the vector of sample second--order moments,will be used to compute robust standard errors and a robust chi--squaregoodness--of--fit squares. Simple modifications of the usual estimateof $\Gamma$ will also permit correct inferences in the case of multi--stage complex samples. We will also discuss the conditions under which,regardless of the distribution of the data, one can rely on the usual(non--robust) inferential statistics. Finally, a multivariate regressionmodel with errors--in--variables will be used to illustrate, by meansof simulated data, various theoretical aspects of the paper.

Multi-sample analysis of moment-structures: Asymptotic validity of inferences based on second-order moments

In moment structure analysis with nonnormal data, asymptotic valid inferences require the computation of a consistent (under general distributional assumptions) estimate of the matrix $\Gamma$ of asymptotic variances of sample second--order moments. Such a consistent estimate involves the fourth--order sample moments of the data. In practice, the use of fourth--order moments leads to computational burden and lack of robustness against small samples. In this paper we show that, under certain assumptions, correct asymptotic inferences can be attained when $\Gamma$ is replaced by a matrix $\Omega$ that involves only the second--order moments of the data. The present paper extends to the context of multi--sample analysis of second--order moment structures, results derived in the context of (simple--sample) covariance structure analysis (Satorra and Bentler, 1990). The results apply to a variety of estimation methods and general type of statistics. An example involving a test of equality of means under covariance restrictions illustrates theoretical aspects of the paper.

Extending the roughness of the data via transitive closures of similarity indexes

One main assumption in the theory of rough sets applied to information tables is that the elements that exhibit the same information are indiscernible (similar) and form blocks that can be understood as elementary granules of knowledge about the universe. We propose a variant of this concept defining a measure of similarity between the elements of the universe in order to consider that two objects can be indiscernible even though they do not share all the attribute values because the knowledge is partial or uncertain. The set of similarities define a matrix of a fuzzy relation satisfying reflexivity and symmetry but transitivity thus a partition of the universe is not attained. This problem can be solved calculating its transitive closure what ensure a partition for each level belonging to the unit interval [0,1]. This procedure allows generalizing the theory of rough sets depending on the minimum level of similarity accepted. This new point of view increases the rough character of the data because increases the set of indiscernible objects. Finally, we apply our results to a not real application to be capable to remark the differences and the improvements between this methodology and the classical one

The Importance of Semantics: Visual World Studies on Drawing Inferences and Resolving Anaphors

The present thesis investigated the importance of semantics in generating inferences during discourse processing. Three aspects of semantics, gender stereotypes, implicit causality information and proto-role properties, were used to investigate whether semantics is activated elaboratively during discourse comprehension and what its relative importance is in backward inferencing compared to discourse/structural cues. Visual world eye-tracking studies revealed that semantics plays an important role in both backward and forward inferencing: Gender stereotypes and implicit causality information is activated elaboratively during online discourse comprehension. Moreover, gender stereotypes, implicit causality and proto-role properties of verbs are all used in backward inferencing. Importantly, the studies demonstrated that semantic cues are weighed against discourse/structural cues. When the structural cues consist of a combination of cues that have been independently shown to be important in backward inferencing, semantic effects may be masked, whereas when the structural cues consist of a combination of fewer prominent cues, semantics can have an earlier effect than structural factors in pronoun resolution. In addition, the type of inference matters, too: During anaphoric inferencing semantics has a prominent role, while discourse/structural salience attains more prominence during non-anaphoric inferencing. Finally, semantics exhibits a strong role in inviting new inferences to revise earlier made inferences even in the case the additional inference is not needed to establish coherence in discourse. The findings are generally in line with the Mental Model approaches. Two extended model versions are presented that incorporate the current findings into the earlier literature. These models allow both forward and backward inferencing to occur at any given moment during the course of processing; they also allow semantic and discourse/structural cues to contribute to both of these processes. However, while the Mental Model 1 does not assume interactions between semantic and discourse/structural factors in forward inferencing, the Mental Model 2 does assume such a link.

Application of thermal ion-molecule reactions in tackling spectroscopic inferences in inductively coupled plasma mass spectrometry

Part I: Ultra-trace determination of vanadium in lake sediments: a performance comparison using O2, N20, and NH3 as reaction gases in ICP-DRC-MS Thermal ion-molecule reactions, targeting removal of specific spectroscopic interference problems, have become a powerful tool for method development in quadrupole based inductively coupled plasma mass spectrometry (ICP-MS) applications. A study was conducted to develop an accurate method for the determination of vanadium in lake sediment samples by ICP-MS, coupled with a dynamic reaction cell (DRC), using two differenvchemical resolution strategies: a) direct removal of interfering C10+ and b) vanadium oxidation to VO+. The performance of three reaction gases that are suitable for handling vanadium interference in the dynamic reaction cell was systematically studied and evaluated: ammonia for C10+ removal and oxygen and nitrous oxide for oxidation. Although it was able to produce comparable results for vanadium to those using oxygen and nitrous oxide, NH3 did not completely eliminate a matrix effect, caused by the presence of chloride, and required large scale dilutions (and a concomitant increase in variance) when the sample and/or the digestion medium contained large amounts of chloride. Among the three candidate reaction gases at their optimized Eonditions, creation of VO+ with oxygen gas delivered the best analyte sensitivity and the lowest detection limit (2.7 ng L-1). Vanadium results obtained from fourteen lake sediment samples and a certified reference material (CRM031-040-1), using two different analytelinterference separation strategies, suggested that the vanadium mono-oxidation offers advantageous performance over the conventional method using NH3 for ultra-trace vanadium determination by ICP-DRC-MS and can be readily employed in relevant environmental chemistry applications that deal with ultra-trace contaminants.Part II: Validation of a modified oxidation approach for the quantification of total arsenic and selenium in complex environmental matrices Spectroscopic interference problems of arsenic and selenium in ICP-MS practices were investigated in detail. Preliminary literature review suggested that oxygen could serve as an effective candidate reaction gas for analysis of the two elements in dynamic reaction cell coupled ICP-MS. An accurate method was developed for the determination of As and Se in complex environmental samples, based on a series of modifications on an oxidation approach for As and Se previously reported. Rhodium was used as internal standard in this study to help minimize non-spectral interferences such as instrumental drift. Using an oxygen gas flow slightly higher than 0.5 mL min-I, arsenic is converted to 75 AS160+ ion in an efficient manner whereas a potentially interfering ion, 91Zr+, is completely removed. Instead of using the most abundant Se isotope, 80Se, selenium was determined by a second most abundant isotope, 78Se, in the form of 78Se160. Upon careful selection of oxygen gas flow rate and optimization ofRPq value, previous isobaric threats caused by Zr and Mo were reduced to background levels whereas another potential atomic isobar, 96Ru+, became completely harmless to the new selenium analyte. The new method underwent a strict validation procedure where the recovery of a suitable certified reference material was examined and the obtained sample data were compared with those produced by a credible external laboratory who analyzed the same set of samples using a standardized HG-ICP-AES method. The validation results were satisfactory. The resultant limits of detection for arsenic and selenium were 5 ng L-1 and 60 ng L-1, respectively.

Quasi-Transitive and Suzumura Consistent Relations

We examine properties of binary relations that complement quasi-transitivity and Suzumura consistency in the sense that they, together with the original axiom(s), are equivalent to transitivity. In general, the conjunction of quasi-transitivity and Suzumura consistency is strictly weaker than transitivity but in the case of collective choice rules that satisfy further properties, the conjunction of quasi- transitivity and Suzumura consistency implies transitivity of the social relation. We prove this observation by characterizing the Pareto rule as the only collective choice rule such that collective preference relations are quasi-transitive and Suzumura consistent but not necessarily complete.

Environment and Climate Changes During the Late Quaternary: Inferences from Sedimentary Records of Southeastern Arabian Sea

Department of Marine Geology & Geophysics, Cochin University of Science and Technology

Gender Bias and Caste Exclusion in Engineering Admission: Inferences from the Engineering Entrance Examination in Kerala

The major problem of the engineering entrance examination is the exclusion of certain sections of the society in social, economic, regional and gender dimensions. This has seldom been taken for analysis towards policy correction. To lessen this problem a minor policy shift was prepared in the year 2011 with a 50–50 proportion in academic marks and entrance marks. The impact of this change is yet to be scrutinized. The data for the study is obtained from the Nodal Centre of Kerala functioning at Cochin University of Science and Technology under the National Technical Manpower Information System and also estimated from the Centralized Allotment Process. The article focuses on two aspects of exclusion based on engineering entrance examination; gender centred as well as caste-linked. Rank order spectral density and Lorenz ratio are used to cognize the exclusion and inequality in community and gender levels in various performance scales. The article unfolds the fact that social status in society coupled with economic affordability to quality education seems to have significant influence in the performance of students in the Kerala engineering entrance examinations. But it also shows that there is wide gender disparity with respect to performance in the high ranking levels irrespective of social groups