Systemic lupus erythematosus (SLE) is a relatively rare autoimmune disease with no known aetiology or cure. In addition to numerous physical symptoms, those living with SLE have also been shown to experience significant emotional and psychosocial difficulties. There has been little psychological research into SLE despite the rapidly increasing interest in health psychology and quality of life issues over the last two decades. One such issue that has commanded particular attention is that of cognitive bias in individuals with chronic pain and/or chronic illness. Cognitive bias toward illness-related information is theorised to indicate the presence of an illness self-schema, and is a valuable tool of investigation as it permits access to a level of cognitive structure that is inaccessible via self-report instruments. The primary focus of the present study is to investigate recall bias for pain- and illness-related words in SLE patients. This bias is explored relative to the recall of neutral words and depression-related words, and also relative to the responses of rheumatoid arthritis (RA) patients and healthy controls. Two hypotheses are proposed: firstly, that bias is related to disease activity; and secondly, that bias is related to the combination of illness and depression. The findings provide support for the second hypothesis, with the additional caveat that the nature of the pain/illness stimuli used is important in determining the presence of cognitive bias. No recall bias for illness-related words as a whole was found in any of the groups, nor was there evidence of a recall bias in the SLE and RA patients when they were divided according to depression status. However, when the illness words were examined separately according to �sensory pain� and �disability-related� words, a clear bias for disability words was found in the depressed patient group. It is concluded that there is a relationship between depression in chronically ill individuals, and the way in which such individuals process disability-related words. In accordance with the schema-enmeshment model (Pincus & Morley, 2001), it is suggested that both a pain-schema and an illness-schema exist, and it is when these two schemas become enmeshed with the self-schema that depression occurs in chronic pain/chronically ill patients. The cognitive bias assessment paradigm adopted in this study-one that is typically used in similar investigations-is lengthy, requires sophisticated equipment and can be difficult to interpret on an individual level. The present study investigates the relationship between cognitive biases in SLE patients and a recently-developed task, PRISM, which appears to symbolise the enmeshment of illness-, pain- and self-schemas. Analyses confirmed that recall of negative illness words was the only independent predictor of PRISM scores. This suggests that PRISM, a quick and easy task to administer, may have considerable usefulness as a clinical tool to assess information relevant to the enmeshment of illness- and self-schema. A greater understanding of schema and the processing styles of chronically ill patients will allow for more effective psychological treatment such that quality of life can be improved.

<p>This essay examines the differences and similarities, weaknesses and strengths of the two Cognitive Semantic theories Conceptual Metaphor Theory and Principled Polysemy Approach to Meaning Analysis. To illustrate the two theories, the Swedish verb-particle construction "gå upp" is examined and analyzed accordingly. The results showed differences in the number of polysemous meaning found. The methodological evaluation showed that the differences in the underlying ideas concerning meaning-construction behind these two theories make them incompatible.</p>

We propose a framework for semi-automatically verifying relational database schema mappings for data exchange. Schema mappings for data exchange formally describe how to move data between a source and target database. State-of-the-art schema mapping tools propose several mappings, but require user intervention to determine their semantic correctness. For this, the user must understand the domain the schemas represent and the meanings of individual schema elements in relation to the domain. Our framework eases the task of understanding the domain and schemas and performs preliminary mapping verification. We use a readable, expressive, and formal conceptual model - a domain ontology - to model the source and target schema domain. We model the schema semantics by annotating schema elements with ontology elements. Our mapping verification algorithm rewrites mappings as statements in terms of the ontology, and uses a reasoner to check that the statements are entailed by the ontology.

Our thesis investigates a mechanism for representing schema mapping by tabular forms and checking utility of the new representation. Schema mapping is a high-level specification that describes the relationship between two database schemas. Schema mappings constitute essential building blocks of data integration, data exchange and peer-to-peer data sharing systems. Global-and-local-as-view (GLAV) is one of the approaches for specifying the schema mappings. Tableaux are used for expressing queries and functional dependencies on a single database in a tabular form. In our thesis, we first introduce a tabular representation of GLAV mappings. We find that this tabular representation helps to solve many mapping-related algorithmic and semantic problems. For example, a well-known problem is to find the minimal instance of the target schema for a given instance of the source schema and a set of mappings between the source and the target schema. Second, we show that our proposed tabular mapping can be used as an operator on an instance of the source schema to produce an instance of the target schema which is `minimal' and `most general' in nature. There exists a tableaux-based mechanism for finding equivalence of two queries. Third, we extend that mechanism for deducing equivalence between two schema mappings using their corresponding tabular representations. Sometimes, there exist redundant conjuncts in a schema mapping which causes data exchange, data integration and data sharing operations more time consuming. Fourth, we present an algorithm that utilizes the tabular representations for reducing number of constraints in the schema mappings. At present, either schema-level mappings or data-level mappings are used for data sharing purposes. Fifth, we introduce and give the semantics of bi-level mapping that combines the schema-level and data-level mappings. We also show that bi-level mappings are more effective for data sharing systems. Finally, we implemented our algorithms and developed a software prototype to evaluate our proposed strategies.

Schema merging is the process of incorporating data models into an integrated, consistent schema from which query solutions satisfying all incorporated models can be derived. The efficiency of such a process is reliant on the effective semantic representation of the chosen data models, as well as the mapping relationships between the elements of the source data models. Consider a scenario where, as a result of company mergers or acquisitions, a number of related, but possible disparate data marts need to be integrated into a global data warehouse. The ability to retrieve data across these disparate, but related, data marts poses an important challenge. Intuitively, forming an all-inclusive data warehouse includes the tedious tasks of identifying related fact and dimension table attributes, as well as the design of a schema merge algorithm for the integration. Additionally, the evaluation of the combined set of correct answers to queries, likely to be independently posed to such data marts, becomes difficult to achieve. Model management refers to a high-level, abstract programming language designed to efficiently manipulate schemas and mappings. Particularly, model management operations such as match, compose mappings, apply functions and merge, offer a way to handle the above-mentioned data integration problem within the domain of data warehousing. In this research, we introduce a methodology for the integration of star schema source data marts into a single consolidated data warehouse based on model management. In our methodology, we discuss the development of three (3) main streamlined steps to facilitate the generation of a global data warehouse. That is, we adopt techniques for deriving attribute correspondences, and for schema mapping discovery. Finally, we formulate and design a merge algorithm, based on multidimensional star schemas; which is primarily the core contribution of this research. Our approach focuses on delivering a polynomial time solution needed for the expected volume of data and its associated large-scale query processing. The experimental evaluation shows that an integrated schema, alongside instance data, can be derived based on the type of mappings adopted in the mapping discovery step. The adoption of Global-And-Local-As-View (GLAV) mapping models delivered a maximally-contained or exact representation of all fact and dimensional instance data tuples needed in query processing on the integrated data warehouse. Additionally, different forms of conflicts, such as semantic conflicts for related or unrelated dimension entities, and descriptive conflicts for differing attribute data types, were encountered and resolved in the developed solution. Finally, this research has highlighted some critical and inherent issues regarding functional dependencies in mapping models, integrity constraints at the source data marts, and multi-valued dimension attributes. These issues were encountered during the integration of the source data marts, as it has been the case of evaluating the queries processed on the merged data warehouse as against that on the independent data marts.

Our thesis investigates a mechanism for representing schema mapping by tabular forms and checking utility of the new representation. Schema mapping is a high-level specification that describes the relationship between two database schemas. Schema mappings constitute essential building blocks of data integration, data exchange and peer-to-peer data sharing systems. Global-and-local-as-view (GLAV) is one of the approaches for specifying the schema mappings. Tableaux are used for expressing queries and functional dependencies on a single database in a tabular form. In our thesis, we first introduce a tabular representation of GLAV mappings. We find that this tabular representation helps to solve many mapping-related algorithmic and semantic problems. For example, a well-known problem is to find the minimal instance of the target schema for a given instance of the source schema and a set of mappings between the source and the target schema. Second, we show that our proposed tabular mapping can be used as an operator on an instance of the source schema to produce an instance of the target schema which is `minimal' and `most general' in nature. There exists a tableaux-based mechanism for finding equivalence of two queries. Third, we extend that mechanism for deducing equivalence between two schema mappings using their corresponding tabular representations. Sometimes, there exist redundant conjuncts in a schema mapping which causes data exchange, data integration and data sharing operations more time consuming. Fourth, we present an algorithm that utilizes the tabular representations for reducing number of constraints in the schema mappings. At present, either schema-level mappings or data-level mappings are used for data sharing purposes. Fifth, we introduce and give the semantics of bi-level mapping that combines the schema-level and data-level mappings. We also show that bi-level mappings are more effective for data sharing systems. Finally, we implemented our algorithms and developed a software prototype to evaluate our proposed strategies.

Schema merging is the process of incorporating data models into an integrated, consistent schema from which query solutions satisfying all incorporated models can be derived. The efficiency of such a process is reliant on the effective semantic representation of the chosen data models, as well as the mapping relationships between the elements of the source data models. Consider a scenario where, as a result of company mergers or acquisitions, a number of related, but possible disparate data marts need to be integrated into a global data warehouse. The ability to retrieve data across these disparate, but related, data marts poses an important challenge. Intuitively, forming an all-inclusive data warehouse includes the tedious tasks of identifying related fact and dimension table attributes, as well as the design of a schema merge algorithm for the integration. Additionally, the evaluation of the combined set of correct answers to queries, likely to be independently posed to such data marts, becomes difficult to achieve. Model management refers to a high-level, abstract programming language designed to efficiently manipulate schemas and mappings. Particularly, model management operations such as match, compose mappings, apply functions and merge, offer a way to handle the above-mentioned data integration problem within the domain of data warehousing. In this research, we introduce a methodology for the integration of star schema source data marts into a single consolidated data warehouse based on model management. In our methodology, we discuss the development of three (3) main streamlined steps to facilitate the generation of a global data warehouse. That is, we adopt techniques for deriving attribute correspondences, and for schema mapping discovery. Finally, we formulate and design a merge algorithm, based on multidimensional star schemas; which is primarily the core contribution of this research. Our approach focuses on delivering a polynomial time solution needed for the expected volume of data and its associated large-scale query processing. The experimental evaluation shows that an integrated schema, alongside instance data, can be derived based on the type of mappings adopted in the mapping discovery step. The adoption of Global-And-Local-As-View (GLAV) mapping models delivered a maximally-contained or exact representation of all fact and dimensional instance data tuples needed in query processing on the integrated data warehouse. Additionally, different forms of conflicts, such as semantic conflicts for related or unrelated dimension entities, and descriptive conflicts for differing attribute data types, were encountered and resolved in the developed solution. Finally, this research has highlighted some critical and inherent issues regarding functional dependencies in mapping models, integrity constraints at the source data marts, and multi-valued dimension attributes. These issues were encountered during the integration of the source data marts, as it has been the case of evaluating the queries processed on the merged data warehouse as against that on the independent data marts.

En esta tesis, presentamos un nuevo enfoque para validar mappings entre esquemas de datos que permite al diseñador comprobar si el mapping satisface o no ciertas propiedades deseables. La respuesta que obtiene el diseñador no se limita a un simple valor booleano, sino que dependiendo del resultado de la comprobación obtendrá un ejemplo/contraejemplo que ilustre ese resultado, o bien se le indicará el conjunto de restricciones de integridad de los esquemas y formulas del mapping responsables de ese resultado. Una de las características principales de nuestro enfoque es que es capaz de tratar una clase muy expresiva de mappings y esquemas relacionales. En particular, nuestro enfoque es capaz de tratar con formulas de mapping consistentes en inclusiones y igualdades de consultas, además de permitir el uso de negaciones y comparaciones aritméticas tanto en las propias formulas del mapping como en las vistas definidas en los esquemas. Nuestro enfoque también permite tratar restricciones de integridad, las cuales pueden estar definidas no solo sobre las tablas sino también sobre las vistas de los esquemas. Dado que razonar sobre este tipo de mappings y esquemas es, desafortunadamente, indecidible, proponemos realizar un test de terminación previo a la validación del mapping. Si el test de terminación da una respuesta positiva, entonces podremos estar seguros de que la posterior comprobación de la propiedad deseable correspondiente terminará. Finalmente, también extendemos nuestro enfoque más allá del caso relacional y lo aplicamos al contexto de mappings entre esquemas XML. / In this thesis, we present a new approach to the validation of mappings between data schemas. It allows the designer to check whether the mapping satisfies certain desirable properties. The feedback that our approach provides to the designer is not only a Boolean answer, but either a (counter)example for the (un)satisfiability of the tested property, or the set of mapping assertions and schema constraints that are responsible for that (un)satisfiability. One of the main characteristics of our approach is that it is able to deal with a very expressive class of relational mapping scenarios; in particular, it is able to deal with mapping assertions in the form of query inclusions and query equalities, and it allows the use of negation and arithmetic comparisons in both the mapping assertions and the views of the schemas; it also allows for integrity constraints, which can be defined not only over the base relations but also in terms of the views. Since reasoning on the class of mapping scenarios that we consider is, unfortunately, undecidable, we propose to perform a termination test as a pre-validation step. If the answer of the test is positive, then checking the corresponding desirable property will terminate. We also go beyond the relational setting and study the application of our approach to the context of mappings between XML schemas.

¡@Nowadays, spokesperson is a very common advertising strategy. A good spokesperson can favorably attract customers¡¦ attention, produce better recall or precognition of a brand name, create an image for a product etc. In general, advertisers usually consider the fittingness between spokesperson¡¦s gender and product gender image. As gender roles and gender stereotype are changing, some product gender images are blurred as well. Therefore, some cross-over endorsements are emerged (an advertising is targeting a nontraditional user in terms of gender). Past researches have shown that the relationship between spokesperson¡¦s gender and product gender image is inconsistent. Hence, this study focuses on products with ¡§Masculine Image¡¨ and classified products based on FCB Model, exploring how different products types and customers¡¦ gender influence gender endorsement on advertising effectiveness. ¡@The present study uses experimental design to investiage the effects of two types of gender endorsement and four product categories on advertising effectiveness. A 2x4 between-subject design is conducted. All eight scenarios are made through fictional ads, and the advertising effectiveness is measured by attitude toward the ad (AD), attitude toward the product (AP) and purchase intention (PI). ¡@The findings of this study indicate that AD and PI are more favorable when the product¡¦s gender image and spokesperson¡¦s gender are consistent. The interaction between product types and gender endorsement advertisement exits especially in the effective product. Spokespersons¡¦ gender is an effective promotional cue in influencing customers¡¦ perceptions of the gender image of products on the self-satisfaction product. Meanwhile, this study also finds there is no interaction between the gender endorsement advertisement and customer¡¦s gender.

Amy Tan¡¦s The Joy Luck Club and Cristina Garcia¡¦s Dreaming in Cuban propose the matrilineal narrative of woman suffering and spiritual growth. Multiple narrators tell personal stories about the past events to cope with their current concerns and coming difficulties. Their storytelling functions as a way of making sense of experiences and fashioning identity. The first chapter explores how the narrative activity enables the del Pino and Joy Luck women to construct a preferred version of personal experiences. They not only tell stories to create idealized self-images but also live their lives to justify the images. Though they portray themselves as capable women in personal stories, they often appear vulnerable and mentally unstable in reality. Such contradiction results from the traumatic events the women leave untold, and they resist telling partly because of their madness and partly because of their repudiation of the events. The second chapter will examine their traumatic experiences to understand how their emotional problems determine the representation of their personal narratives. Due to the early traumatic experiences, the women develop maladaptive schemas to cope with their negative emotions. The schemas, however, undermine their interpersonal relationships and prevent them from fulfilling the basic needs. While wrestling with their emotional problems, they unwittingly transplant schemas into the next generation. The third chapter examines how certain crucial moments in their lives enlighten the women to have awareness of their schemas at the core of their suffering. The death of the family members and serious mother-daughter disagreements provide the opportunity for the women to move beyond the limited way they used to perceive themselves and others. With an open and positive attitude, they relate the traumatic experiences to understand how their early suffering contributes to their present difficulties and outgrow what has troubled them before.