Doctor of Philosophy / Department of Food, Nutrition, Dietetics, and Health / Kadri Koppel / The pet food industry represents a competitive and growing part of the food industry that is constantly looking for innovation to differentiate products in the market. In recent years, the pet food market has undergone a humanization trend that has transformed pet owners into parents. In the light of this trend, pet owner acceptance has become even more crucial to product developers as the owners are the ones who make purchasing decisions. Performing descriptive sensory analysis on pet foods utilizing a human panel can assist in understanding the sensory characteristic of products. Knowing the sensory profile of pet food can then be useful in product development, in order to relate the descriptive data with palatability data from pets and to understand specific sensory attributes that drive pet liking. At the same time descriptive analysis can help understand what drives consumer acceptance of the products. The first objective of the research was to develop a sensory lexicon that could assist researchers and sensory professionals working in the pet food industry to describe appearance, aroma, flavor, and texture characteristics of dry dog food. More than seventy sensory terms were identified, defined, and referenced. The second objective was to utilize this sensory lexicon to understand relationships between sensory properties of products and pet owners’ liking. Results indicated that appearance played a major role in driving consumer liking of dry pet food. The next objective of the research was to understand sensory qualities and acceptance of extruded dry dog food manufactured with different fractions of red sorghum through some of the developed concepts. Sorghum is an important crop to Kansas that represents the first producer in USA. Sorghum characteristics such as a low glycemic index and antioxidant properties make it a perfect fit for pet food industry. A process such as extrusion may then help improve some negative characteristics such a lower digestibility that has been associated with sorghum in the past. Descriptive sensory analysis was performed and results indicated that aroma and flavor profile of the sorghum diets were not dissimilar to the ones of a control diet manufactured with rice, wheat, and corn, grains that are typically used by the pet food industry. Acceptance of pet owners was then assessed through a Central Location Test involving 105 consumers. The whole sorghum diet resulted to be the most liked sample by consumers, at the same level of the control diet. The next objective was then to understand how the experimental diets would be accepted by pets compared in a home situation. Thirty dogs were fed the diets in their own household environment over 20 consecutive days. No differences in acceptance for the diets were found. The last portion of the research was to determine volatile compounds present in the four diets and try to identify possible relationship with the sensory properties of the samples. Thirty-six compounds were identified with aldehydes being the most abundant volatiles group. Several relationships with sensory characteristics of samples were found.

Every new discovery in science and technology leads to use terms and expressions that form the basis of humans’ representations. In the fields of robotics and artificial intelligence, the words are borrowed from the vocabulary of the living (autonomy, intelligence, consciousness, learning, feeling, thinking, etc.).The state-of-the-art shows that there is an intrinsic link between the cognitive process of the attribution of intentions to moving objects and machines (also known as mentalizing) and the agentive lexicon. Indeed, humans’ perception of movement impacts their representation of the world and the way that they talk about the world. On the other hand, natural language plays an important role in the way that humans represent the movements and actions of robots. Following a review of the main principles that explain how movement is decoded as well as encoded through (and in) natural language, I observe that the agentive lexicon imposes itself, regardless of the state of our beliefs about a possible robot intelligence.Thereupon, many roboticists are concerned about the lexicon of robotics, as they fear that the words used to describe robots (dispositions and actions) create or at least, encourage, the confusion between the machines and the living. As the words of robotics are often considered by the roboticists as ambiguous, the agentive lexicon is analyzed under the general rules of the lexical ambiguity resolution. The results suggest that ambiguity is not at the basis of the problem of interpretation of the discourses in robotics and that the problematic carries on beyond the meaning of the words used to describe robots.Consequently, I assume that the relation between moving machines and language is not a problem of the logos but include also the ethos and the pathos. This observation is verified through the study of a corpus gathering public discourses and a series of speeches produced by roboticists and scientific journalists during a rhetorical experiment conducted at the Cité des Sciences et de l’Industrie of Paris. Hence, I observe that the discourses in robotics fall under a matter of rhetoric in its whole and relate to one’s own conception of rationality.Finally, in order to engage a discussion on alternative rhetorical strategy in robotics, I consider the ancient and practical rhetorical exercice of ekphrasis as a tool to trigger the criteria of an adequate and accurate rhetorical style in the context of robotics. This means that I seek to discover the criteria of the discourse that prove to be useful for society as it allows roboticists and citizens to question and make decisions about concrete matters of robotics. / Doctorat en Langues et lettres / info:eu-repo/semantics/nonPublished

The purpose of this research was to study grammatical categories in the Tagalog mental lexicon using lexical decision tasks. Some linguists question whether words in Tagalog can be classified as nouns and verbs (Foley, 1998; Kaufman, 2011) because most root words can be inflected for any grammatical function and because verbs cannot be used in their uninflected form. Previous studies with English and German (Kauschke and Stenneken 2008) have shown that participants respond differently to nouns and verbs in lexical decision tasks. These studies have also shown that participants respond differently to transitive and intransitive verbs in lexical decision tasks. It was assumed that if nouns and verbs exist in Tagalog, response times to Tagalog lexical decision tasks will show similar patterns to those performed in English and German. Two experiments were performed to examine whether words are classified as nouns and verbs in the Tagalog mental lexicon and whether other factors affected that classification. For the experiments, native speakers of Tagalog participated in lexical decision tasks and response times were measured. The first experiment tested the classification of root nouns and verbs. Contrary to findings in other languages, there was no significant difference between response times to nouns and verbs. However, there were differences in response times to nouns from different semantic categories and to verbs with different morphosyntactic structures. The second experiment examined the classification of inflected nouns and verbs. Again, the results showed no difference between response times to nouns and verbs. There was also no difference between transitive and intransitive verbs. However, there was a slight difference between verbs of different voice inflections. The results of the experiments suggest the while the grammatical classes of nouns and verbs may not be the most important features of words in the Tagalog mental lexicon, they may still play a role since different features, semantics or morphosyntactics, did affect the responses to words from the different categories.

No description available.

In the fields of water safety, food safety, and public communications, the overarching goal is to improve public health. Thus, this dissertation focuses on risk assessment and applying novel methods for exposure assessments and dose responses to contaminants in drinking water and foods. Factors that greatly impact contaminant exposures and human dose response include: population susceptibility (i.e., healthy adults or children), different routes of exposures (i.e., ingestion or inhalation), carrier matrices (i.e., water or food), and intricacies of chemical and biological mixtures. Chemical spills, such as the 2014 crude MCHM spill in Charleston, WV, revealed the complexities of both minor and major components in the chemical mixture. Slight shifts in geometric structures (isomers) can affect the fate and transport properties of the chemical mixture and as a result, the level of human exposure and dose response to each component in the chemical mixture. Odorous properties of both minor and major components can affect human inhalation exposure, especially during showering, and can be as detrimental as the ingestion route exposure and are different for healthy adults versus for children. Food contaminants, such as Shiga toxin producing Escherichia coli (STEC) in beef products, can be mitigated through a quantitative microbial risk assessment (QMRA) framework that follows a farm-to-fork model. Methods to ensure greatest microbial reduction include: employed intervention strategies at slaughter plants (i.e., water washing of beef carcass), improved cooking times and temperature methods at the consumer and retail level, and assessed minimum effective dose response modeling for different population susceptibilities. Current public communication tools, including the Drinking Water Taste-and-Odor Wheel or Consumer Confidence Reports (better known as water quality reports), should be redeveloped to uphold water safety. Furthermore, public health campaigns that uses social media strategies and informative websites can better educate the public on food contaminants. Ultimately, the objective is to prevent human illnesses due to water contaminants and foodborne pathogens and to bridge the communication gap between the consumers and the experts concerned with water and food safety. / Ph. D.

Large variations in writing styles and difficulties in segmenting cursive words are the main reasons for handwritten cursive words recognition for being such a challenging task. An Indian postal document reading system based on a segmentation-free context based stochastic model is presented. The originality of the work resides on a combination of high-level perceptual features with the low-level pixel information considered by the former model and a pruning strategy in the Viterbi decoding to reduce the recognition time. While the low-level information can be easily extracted from the analyzed form, the discriminative power of such information has some limits as describes the shape with less precision. For that reason, we have considered in the framework of an analytical approach, using an implicit segmentation, the implant of high-level information reduced to a lower level. This enrichment can be perceived as a weight at pixel level, assigning an importance to each analyzed pixel based on their perceptual properties. The challenge is to combine the different type of features considering a certain dependence between them. To reduce the decoding time in the Viterbi search, a cumulative threshold mechanism is proposed in a flat lexicon representation. Instead of using a trie representation where the common prefix parts are shared we propose a threshold mechanism in the flat lexicon where based just on a partial Viterbi analysis, we can prune a model and stop the further processing. The cumulative thresholds are based on matching scores calculated at each letter level, allowing a certain dynamic and elasticity to the model. As we are interested in a complete postal address recognition system, we have also focused our attention on digit recognition, proposing different neural and stochastic solutions. To increase the accuracy and robustness of the classifiers a combination scheme is also proposed. The results obtained on different datasets written on Latin and Bengali scripts have shown the interest of the method and the recognition module developed will be integrated in a generic system for the Indian postal automation.

Das "Universal-Lexicon" ist ein gutes Beispiel für die Umwandlung von Wissen, das in Reiseberichten, Zeitungen und Zeitschriften verfügbar war, in eine Lexikongestalt. Es kann als Beispiel für eine bürgerliche Lesekultur verstanden werden, die sehr verschiedene Gegenstände konsumiert und sowohl nach Informationen wie nach deren Zusammenfassung verlangt. Das "Universal-Lexicon" ist schon aus Gründen des enormen Umfangs dem "allgemeinen Wissen" verpflichtet, wobei "Rußland" ein Element des Wissens unter vielen ist: über 288.000 Artikel besetzen etwa 68.000 Folioseiten.

Für ein städtisch-bürgerliches Publikum waren die Konversationslexika gedacht, die seit Beginn des 18. Jahrhunderts der Erläuterung von Zeitungsberichten dienten und rasch zu umfassenden Informationswerken wurden. Das Universal-Lexicon des Leipziger Verlegers Johann Heinrich Zedler ist im Grunde nichts anderes als ein ins Gigantische getriebenes Konversationslexikon. Mit seinen ca. 284 000 Artikeln und 276 000 Verweisungen besetzt es mit Stichwörtern und Druckseiten einen bibliothekarischen Raum, der lange nicht übertroffen wurde: ein Mammutunternehmen

A doença de Alzheimer produz alterações nas funções cognitivas, entre eles, de processos que são responsáveis pela linguagem e memória. Com o intuito de termos uma melhor compreensão das alterações da linguagem, este trabalho investigou características presentes em redes semânticas de pacientes com diagnóstico de provável Alzheimer, com foco nos verbos. Os resultados das comparações entre as redes de indivíduos saudáveis e pacientes com Alzheimer indicam diferenças topológicas entre eles. Neste trabalho, também foram construídos classificadores que poderiam captar as diferenças entre os vários perfis de indivíduos, e que podem ser utilizados para classificar novos indivíduos de acordo com o perfil mais próximo. Esse esforço se deu com o intuito de ajudar no diagnóstico de doenças que afetam a linguagem, como a doença de Alzheimer. / Alzheimer’s disease produces alterations of cognitive functions and of processes that are responsible for language and memory. In order to have a better understanding of language changes, we investigate the characteristics of the semantic networks of patients diagnosed with probable Alzheimer, focusing on verbs. The results of comparisons with networks of healthy individuals and patients with Alzheimer disease highlight some topological differences among them. We also constructed classifiers that could capture the differences between the various profiles of speakers, and that can be used to classify unknown speakers according to the closest profile. We made this effort in order to help the diagnosis of diseases that affect language, such as the Alzheimer’s disease.

A doença de Alzheimer produz alterações nas funções cognitivas, entre eles, de processos que são responsáveis pela linguagem e memória. Com o intuito de termos uma melhor compreensão das alterações da linguagem, este trabalho investigou características presentes em redes semânticas de pacientes com diagnóstico de provável Alzheimer, com foco nos verbos. Os resultados das comparações entre as redes de indivíduos saudáveis e pacientes com Alzheimer indicam diferenças topológicas entre eles. Neste trabalho, também foram construídos classificadores que poderiam captar as diferenças entre os vários perfis de indivíduos, e que podem ser utilizados para classificar novos indivíduos de acordo com o perfil mais próximo. Esse esforço se deu com o intuito de ajudar no diagnóstico de doenças que afetam a linguagem, como a doença de Alzheimer. / Alzheimer’s disease produces alterations of cognitive functions and of processes that are responsible for language and memory. In order to have a better understanding of language changes, we investigate the characteristics of the semantic networks of patients diagnosed with probable Alzheimer, focusing on verbs. The results of comparisons with networks of healthy individuals and patients with Alzheimer disease highlight some topological differences among them. We also constructed classifiers that could capture the differences between the various profiles of speakers, and that can be used to classify unknown speakers according to the closest profile. We made this effort in order to help the diagnosis of diseases that affect language, such as the Alzheimer’s disease.