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The present thesis presents a causal approach to transitivity and proposes a model of transitivity based on the view that a single event is a single ‘causal impact’, which consists of a single causation and a single effect. It defines semantic intransitivity as events where the effect is borne by and expressed through the actor and semantic transitivity as events where the effect is borne by and expressed through the patient. It finds evidence for this definition in the phenomenon of ‘selective specification’ of action or result by verbs with actor and patient. Furthermore, it proposes that the verb eat has dual event structures, intransitive and transitive, and uses a Web data test to test and confirm this hypothesis.

This thesis presents an account of the nature of structured propositions and addresses a series of questions that arise from that proposal. Chapter 1 presents the account and explains how it meets standard objections to such views. Chapter 2 responds to the objection that this version of propositionalism is really a form of sententialism by arguing for the distinct advantages of the propositionalist view. Chapter 3 argues against a closely related view of propositions by way of general principles about how to construct such theories. Chapter 4 illustrates how a theory of propositions of the sort proposed can be defended against a recent argument that propositions need not play a central role in linguistic theory.

A processing route for development of hydroxyapatite (Ca10(PO4)6(OH)2 or HAp)-titania (TiO2) hybrid coatings on titanium alloy (Ti6Al4V) has been established. HAp powders of different size and morphology were synthesized by aqueous precipitation techniques using different precursor couples and XRD, SEM and FTIR were performed for complete characterization. Hybrid coatings were then prepared via sol-gel by incorporating presynthesized HAp powders into a titanium-alkoxide dip coating solution. Titania network is formed by hydrolysis and condensation of Ti-isopropoxide (Ti[OCH(CH3)2]4) based sols. The effect of titania sol formulation, specifically the effect of organic solvents on the microstructure of the dip coated films calcined at 500 &ordm / C has been investigated. The coatings exhibit higher tendency for cracking when a high vapor pressure solvent, such as ethanol (C2H5OH) is used causing development of higher macroscopic stresses during evaporation of the sol. Titania sol formulations replacing the solvent with n-propanol (CH3(CH2)2OH) and acetly-acetone (C5H8O) combinations enhanced the microstructural integrity of the coating during evaporation and calcination treatments. Sol-gel processing parameters such as multilayer coating application and withdrawal rate can be employed to change the titania thickness in the range of 0.120 - 1.1 microns and to control the microstructure of HAp-titania hybrid coatings. Slower withdraw rates and multi-layer dip coating lead to coatings more vulnerable to cracking. A high calcination temperature in the range of 400 &ordm / C-600 &ordm / C lead to more cracking due to combined effect of densification originated stresses and thermal stresses upon cooling.

Flavonoids, present in fruits, vegetables and beverages derived from plants, have been described as health-promoting, disease-preventing dietary supplements, and have activity as cancer preventive agents. The cancer protective effects of flavonoids have been attributed to a wide variety of mechanisms, including modulating enzyme activities resulting in the decreased carcinogenicity of xenobiotics. Cytochrome P4501A1 (CYP1A1) is a Phase I enzyme which is known to be involved in the activation of procarcinogens and Glutathione S-Transferase (GST) is a Phase II enzyme which is largely responsible for the detoxification of carcinogens. In this study, it was aimed to investigate the mechanisms of inhibition of CYP1A1 and GST activities of fish by phenolic compounds/flavonoids. Leaping mullet (Liza saliens), captured from highly polluted sites of izmir Bay, expressing high levels of CYP1A, were used in order to investigate these effects. It was demonstrated that all of the phenolic compounds/flavonoids used, exert an inhibitory effect on both CYP1A1 associated 7-Ethoxyresorufin-O-deethylase (EROD) activity and GST activities of fish, although the degree of inhibition was varied with the flavonoid used. Of the flavonoids tested, the most potent inhibitor of CYP1A1 associated EROD activity was found to be quercetin. The potency of the phenolic compounds/flavonoids to inhibit CYP1A1 associated EROD activity follow the sequence of quercetin &gt / resveratrol &gt / naringenin &gt / hesperidin &gt / rutin with IC50 values of 1.32 &micro / M, 3.59 &micro / M, 9.78 &micro / M, 98.5 &micro / M and 0.64 mM respectively. Quercetin, resveratrol, hesperidin and rutin were found to inhibit EROD activity in a competitive manner, on the other hand, naringenin was found to inhibit EROD activity in a non-competitive manner. Inhibition constant (Ki) values of quercetin, resveratrol, naringenin, hesperidin and rutin were calculated from Dixon plots as 0.12 &micro / M, 0.67 &micro / M, 2.63 &micro / M, 18 &micro / M and 0.1 mM, respectively. In the case of GST enzyme, it was demonstrated that all of the phenolic compounds/flavonoids used, exert an inhibitory effect on both total GST and GST-Mu activities of fish. Of the flavonoids tested, the most effective inhibitor of total GST activity was found to be resveratrol. The potency of the phenolic compounds/flavonoids to inhibit total GST activity follow the sequence of resveratrol &gt / quercetin &gt / rutin &gt / naringenin &gt / hesperidin with IC50 values of 7.1 &micro / M, 24.5 &micro / M, 89 &micro / M, 116 &micro / M and 118 &micro / M respectively. Resveratrol, quercetin and hesperidin were found to inhibit total GST activity in a competitive manner, on the other hand, rutin and naringenin were found to inhibit GST activity in a mixed type manner. Ki values of resveratrol, quercetin, hesperidin, naringenin and rutin were calculated from Dixon plots as 3.2 &micro / M, 12.5 &micro / M, 45 &micro / M, 128 &micro / M and 150 &micro / M respectively. In the case of GST-Mu activity, the most potent inhibitor was found to be rutin. The potency of the phenolic compounds/flavonoids to inhibit GST-Mu activity follow the sequence of rutin &gt / resveratrol &gt / quercetin &gt / naringenin &gt / hesperidin with IC50 values of 66.5 &micro / M, 72.3 &micro / M, 113.5 &micro / M, 135.5 &micro / M and 196 &micro / M, respectively. In conclusion, this study indicated that flavonoids were the strong inhibitors of CYP1A1 associated EROD activity and GST activities of mullet liver. The modulation of drug-metabolizing enzymes by flavonoids is important in terms of human health, since these enzymes can activate or inactivate carcinogens. The potential role of xenobiotic metabolizers CYP1 family in the activation of carcinogens and inactivation of chemotherapeutics suggests a potential therapeutic benefits in inhibiting these enzymes. The results of the present study support the hypothesis that flavonoids may be involved in the prevention of malignant transformation, by reducing the formation of carcinogens through inhibition of enzymes such as CYP1A1 which is known to be involved in carcinogen activation.

This dissertation focuses on two aspects of expressive affixes: their morphological/typological properties and their semantics. With regard to the former, it shows that the expressive morphology of many languages (including Bantu, West Atlantic, Walman, Sanskrit, English, Romance, Slavic, and others), has the following properties: 1) it is systematically anomalous when compared to plain morphology, or the ordinary processes of word-formation and inflection. From this, it follows that many familiar morphological arguments that adduce the data of expressive morphology ought to be reconsidered; and 2) it is far more pervasive than has been traditionally thought. For example, the Sanskrit preverb, and the Indo-European aspectual prefix/particle generally, are shown to have systematically expressive functions. With respect to the semantics of expressive affixes, it develops a novel multidimensional account, in the sense of Potts (2005, 2007), of Spanish "connotative affixes," which can simultaneously convey descriptive and expressive meaning. It shows that their descriptive meaning is that of a gradable adjective, viewed as a degree relation which includes a measure function, in the sense of Kennedy (1997). The expressive meanings of connotative affixes, and expressives generally, arise as they manipulate the middle coordinate, <b>I</b>, of expressive indices which, it is proposed, is inherently specified on all lexical items and canonically set to "neutral." It introduces a new mechanism, <b>AFF</b>, which is an algebraic operation for manipulating <b>I</b>, and which accounts for the well-known, and seemingly "contradictory," range of meanings that expressive affixes can express. Whereas prior work assumes that expressive affixes are inherently polysemous, this approach derives their many attested meanings and functions (e.g., "small," "young," "bad," deprecation, appreciation, hypocorism, intensification/exactness, and attenuation/approximation, as well as pragmatic effects like illocutionary mitigation) compositionally, from the interactions of their multidimensionality with the meanings of the roots to which they attach.

Thesis (Ph. D.)--Ohio State University, 2008. / Title from first page of PDF file. Includes vita. Includes bibliographical references (p. 178-183).

With the advancement of the World Wide Web, opinion sharing online has gained a lot of popularity. These opinions are utilized for decision making, market analysis, as well as other applications. The need to harness these opinions, and the motivation behind this need has led to the development and subsequent advancement of the field of Sentiment Analysis. Various issues have arisen from these, such as difficulty in locating these opinions in a body of text, as well as determining the sentiment/polarity of these opinions. To tackle the issue of opinion polarity determination, a number of classification approaches have been developed. These approaches have focused on opinion classification at various levels, such as document, sentence and aspect levels. Most document level approaches treat documents as a bag of words during the classification process, and hence classify them as a whole. The problem with this is that there could be a mixture of opinions directed towards various aspects, within a document. It is therefore imperative to utilize a classification approach which takes into account these constituent opinions. This is the focus of classification approaches which work at the aspect level. Another important factor in the issue of sentiment/polarity classification is the choice of the classification approach. This can be machine learning, lexical/lexicon-based, and more recently, hybrid. The machine learning approaches have the benefits of carrying out classification with high accuracies, and efficiently handling large feature sets, which makes them a favourite choice where high accuracies are desired. They however also have the drawback of difficulty in adaptability, due to the domain dependency of sentiment words. The pure lexicon-based approaches do not achieve the accuracy of the machine learning approaches, but are said to offer more explainable results and take into consideration the information in lexicons. In this work, we present a novel hybrid approach, which incorporates information from lexicons in a machine learning classifier, and takes as features various linguistic knowledge sources. Our novel hybrid approach utilizes transitive dependencies to incorporate the opinions expressed towards different aspects of a document in determining the polarity classification of the whole document. The domain dependency of sentiment words is also addressed through the use of composite features and a domain specific lexicon created in this work. It was found that the use of transitive dependencies in an aspect-focused classification is a promising area, which has the potential of improving aspect based classification once the aspects have been properly determined. It was also found that although using composite features does not necessarily improve the classification accuracy, it gives rise to context rich classifiers, and the domain specific lexicon generated performed on par with the widely used generic lexicon, SentiWordNet.

Doctorat en philosophie et lettres / info:eu-repo/semantics/nonPublished

Many texts we encounter in our everyday lives are lexically and syntactically very complex. This makes them difficult to understand for people with intellectual or reading impairments, and difficult for various natural language processing systems to process. This motivated the need for text simplification (TS) which transforms texts into their simpler variants. Given that this is still a relatively new research area, many challenges are still remaining. The focus of this thesis is on better understanding the current problems in automatic text simplification (ATS) and proposing new data-driven approaches to solving them. We propose methods for learning sentence splitting and deletion decisions, built upon parallel corpora of original and manually simplified Spanish texts, which outperform the existing similar systems. Our experiments in adaptation of those methods to different text genres and target populations report promising results, thus offering one possible solution for dealing with the scarcity of parallel corpora for text simplification aimed at specific target populations, which is currently one of the main issues in ATS. The results of our extensive analysis of the phrase-based statistical machine translation (PB-SMT) approach to ATS reject the widespread assumption that the success of that approach largely depends on the size of the training and development datasets. They indicate more influential factors for the success of the PB-SMT approach to ATS, and reveal some important differences between cross-lingual MT and the monolingual v MT used in ATS. Our event-based system for simplifying news stories in English (EventSimplify) overcomes some of the main problems in ATS. It does not require a large number of handcrafted simplification rules nor parallel data, and it performs significant content reduction. The automatic and human evaluations conducted show that it produces grammatical text and increases readability, preserving and simplifying relevant content and reducing irrelevant content. Finally, this thesis addresses another important issue in TS which is how to automatically evaluate the performance of TS systems given that access to the target users might be difficult. Our experiments indicate that existing readability metrics can successfully be used for this task when enriched with human evaluation of grammaticality and preservation of meaning.