Cognitive bias can be used when determining emotional states in animals by assessing the animal’s perception of an ambiguous stimulus. In the concept of animal welfare, both physical health as well as mental health of animals are involved. Therefore, cognitive bias can be a valuable tool in order to measure the mental health of an animal. The aim of this paper is to summarize and discuss how cognitive bias tests have been used to assess emotional states in dogs. Cognitive bias tests in dogs have been used to evaluate the emotional state of a dog with behavioural problems. It has also been shown to be useful when studying the effect of enrichment in the form of natural behaviour, such as being allowed to use its olfactory sense to a greater extent. Additionally, the connection between personality and cognitive bias is discussed. Hence, assessing the emotional state of dogs can be valuable in a welfare perspective.

Les réseaux sociaux ont transformé le Web d'un mode lecture, où les utilisateurs pouvaient seulement consommer les informations, à un mode interactif leur permettant de les créer, partager et commenter. Un défi majeur du traitement d'information dans les médias sociaux est lié à la taille réduite des contenus, leur nature informelle et le manque d'informations contextuelles. D'un autre côté, le web contient des bases de connaissances structurées à partir de concepts d'ontologies, utilisables pour enrichir ces contenus. Cette thèse explore le potentiel d'utiliser les bases de connaissances du Web de données, afin de détecter, classifier et suivre des événements dans les médias sociaux, particulièrement Twitter. On a abordé 3 questions de recherche : i) Comment extraire et classifier les messages qui rapportent des événements ? ii) Comment identifier des événements précis ? iii) Étant donné un événement, comment construire un fil d'actualité représentant les différents sous-événements ? Les travaux de la thèse ont contribué à élaborer des méthodes pour la généralisation des entités nommées par des concepts d'ontologies pour mitiger le sur-apprentissage dans les modèles supervisés ; une adaptation de la théorie des graphes pour modéliser les relations entre les entités et les autres termes et ainsi caractériser des événements pertinents ; l'utilisation des ontologies de domaines et les bases de connaissances dédiées, pour modéliser les relations entre les caractéristiques et les acteurs des événements. Nous démontrons que l'enrichissement sémantique des entités par des informations du Web de données améliore la performance des modèles d'apprentissages supervisés et non supervisés. / In the latest years, the Web has shifted from a read-only medium where most users could only consume information to an interactive medium allowing every user to create, share and comment information. The downside of social media as an information source is that often the texts are short, informal and lack contextual information. On the other hand, the Web also contains structured Knowledge Bases (KBs) that could be used to enrich the user-generated content. This dissertation investigates the potential of exploiting information from the Linked Open Data KBs to detect, classify and track events on social media, in particular Twitter. More specifically, we address 3 research questions: i) How to extract and classify messages related to events? ii) How to cluster events into fine-grained categories? and 3) Given an event, to what extent user-generated contents on social medias can contribute in the creation of a timeline of sub-events? We provide methods that rely on Linked Open Data KBs to enrich the context of social media content; we show that supervised models can achieve good generalisation capabilities through semantic linking, thus mitigating overfitting; we rely on graph theory to model the relationships between NEs and the other terms in tweets in order to cluster fine-grained events. Finally, we use in-domain ontologies and local gazetteers to identify relationships between actors involved in the same event, to create a timeline of sub-events. We show that enriching the NEs in the text with information provided by LOD KBs improves the performance of both supervised and unsupervised machine learning models.

>Magister Scientiae - MSc / In principle, an enrichment of resources in predator-prey systems show prompts destabilisation of a framework, accordingly, falling trophic communication, a phenomenon known to as the \Paradox of Enrichment" [54]. After it was rst genius postured by Rosenzweig [48], various resulting examines, including recently those of Mougi-Nishimura [43] as well as that of Bohannan-Lenski [8], were completed on this problem over numerous decades. Nonetheless, there has been a universal none acceptance of the \paradox" word within an ecological eld due to diverse interpretations [51]. In this dissertation, some theoretical exploratory works are being surveyed in line with giving a concise outline proposed responses to the paradox. Consequently, a quantity of di usion-driven models in mathematical ecology are evaluated and analysed. Accordingly, piloting the way for the spatial structured pattern (we denote it by SSP) formation in nonlinear systems of partial di erential equations [36, 40]. The central point of attention is on enrichment consequences which results toward a paradoxical state. For this purpose, evaluating a number of compartmental models in ecology similar to those of [48] will be of great assistance. Such displays have greater in uence in pattern formations due to diversity in meta-population. Studying the outcomes of initiating an enrichment into [9] of Braverman's model, with a nutrient density (denoted by n) and bacteria compactness (denoted by b) respectively, suits the purpose. The main objective behind being able to transform [9]'s system (2.16) into a new model as a result of enrichment. Accordingly, n has a logistic- type growth with linear di usion, while b poses a Holling Type II and nonlinear di usion r2 nb2 [9, 40]. Five fundamental questions are imposed in order to address and guide the study in accordance with the following sequence: (a) What will be the outcomes of introducing enrichment into [9]'s model? (b) How will such a process in (i) be done in order to change the system (2.16)'s stability state [50]? (c) Whether the paradox does exist in a particular situation or not [51]? Lastly, (d) If an absurdity in (d) does exist, is it reversible [8, 16, 54]? Based on the problem statement above, the investigation will include various matlab simulations. Therefore, being able to give analysis on a local asymptotic stability state when a small perturbation has been introduced [40]. It is for this reason that a bifurcation relevance comes into e ect [58]. There are principal de nitions that are undertaken as the research evolves around them. A study of quantitative response is presented in predator-prey systems in order to establish its stability properties. Due to tradeo s, there is a great likelihood that the growth rate, attack abilities and defense capacities of species have to be examined in line with reviewing parameters which favor stability conditions. Accordingly, an investigation must also re ect chances that leads to extinction or coexistence [7]. Nature is much more complex than scienti c models and laboratories [39]. Therefore, di erent mechanisms have to be integrated in order to establish stability even when a system has been under enrichment [51]. As a result, SSP system is modeled by way of reaction-di usion di erential equations simulated both spatially and temporally. The outcomes of such a system will be best suitable for real-world life situations which control similar behaviors in the future. Comparable models are used in the main compilation phase of dissertation and truly re ected in the literature. The SSP model can be regarded as between (2018-2011), with a stability control study which is of an original.

Advances in sequencing technologies constantly improves the throughput andaccuracy of sequencing instruments. Together with this development comes newdemands and opportunities to fully take advantage of the massive amounts of dataproduced within a sequence run. One way of doing this is by analyzing a large set ofsamples in parallel by pooling them together prior to sequencing and associating thereads to the corresponding samples using DNA sequence tags. Amplicon sequencingis a common application for this technique, enabling ultra deep sequencing andidentification of rare allelic variants. However, a common problem for ampliconsequencing projects is formation of unspecific PCR products and primer dimersoccupying large portions of the data sets. This thesis is based on two papers exploring these new kinds of possibilities andissues. In the first paper, a method for including thousands of samples in the samesequencing run without dramatically increasing the cost or sample handlingcomplexity is presented. The second paper presents how the amount of high qualitydata from an amplicon sequencing run can be maximized. The findings from the first paper shows that a two-tagging system, where the first tagis introduced by PCR and the second tag is introduced by ligation, can be used foreffectively sequence a cohort of 3500 samples using the 454 GS FLX Titaniumchemistry. The tagging procedure allows for simple and easy scalable samplehandling during sequence library preparation. The first PCR introduced tags, that arepresent in both ends of the fragments, enables detection of chimeric formation andhence, avoiding false typing in the data set. In the second paper, a FACS-machine is used to sort and enrich target DNA covered emPCR beads. This is facilitated by tagging quality beads using hybridization of afluorescently labeled target specific DNA probe prior to sorting. The system wasevaluated by sequencing two amplicon libraries, one FACS sorted and one standardenriched, on the 454 showing a three-fold increase of quality data obtained. / QC20100907

<p>Coworker friendships refer to interpersonal relationships between peers and overlap across work and personal domains of life. Prior research suggests that these relationships are beneficial in some ways and detrimental in others, and that they are characterized by divergent forms of social bonds (i.e., friendly or affective bond and work-related or instrumental bond), relational expectations, and norms. Yet, the processes through which coworker friendships influence employees’ work outcomes and well-being remains poorly understood. To illuminate the features of coworker friendships and the mechanisms through which they affect employees, I develop the Coworker Friendship-Resource (CFR) Model. Specifically, building from interaction ritual theory, I explore how features of friendship—nonwork socializing and self-disclosure with coworker along with the personal growth function (i.e., benefit or purpose) of the coworker relationship—simultaneously drain and replenish employees resources or energy by shaping work-nonwork (enrichment and conflict), affective (vitality), cognitive (psychological detachment from work), and relational (intrusion) mechanisms, and subsequent employee work behaviors, well-being, and relationship conflict. I also consider the contingencies affecting these pathways, including contextual work features and individual differences. Overall, the CFR model highlights the simultaneous benefits and burdens of coworker friendships for employees and organizations. To test the CFR model, I conducted a pilot study to validate new measures, a vignette experiment, and a two-wave field study. As a set, the results of the vignette and field studies revealed countervailing effects of the friendship features on resource gain and drain.</p>

Environmental enrichment is commonly used to improve the welfare of captive animals by offering options to increase behavioural diversity and normal behaviour patterns. The aim of this study was to assess if environmental enrichment has a positive effect on a group of four zoo-housed reindeer, Rangifer tarandus. Three types of environmental enrichment were used: food enrichment, olfactory enrichment, and tactile enrichment, with a spontaneous rotation to prevent habituation. Following a baseline period of ten days without enrichment, the animals’ behaviour was monitored for four months with enrichment. All behaviours shown by the reindeer during the study were categorized into locomotory behaviour, feeding behaviour, passive behaviour, social interactions, and behaviour towards enrichment. The overall level of activity of the reindeer almost doubled between the baseline period (40.8%) and the enrichment period (75.3%), with a significant increase in feeding behaviour (p &lt; 0.001) and a significant decrease in passive behaviour (p &lt; 0.001). Food enrichment had the strongest impact on the reindeer out of the three types of enrichment presented. Even though the reindeer showed a continuous interest towards tactile enrichment, it was low compared to the interest shown towards food enrichment. They also showed little interest in olfactory enrichment. Neophobia may explain the lack of interest by the reindeer to certain types of enrichment that were novel to them. Overall, the presentation of environmental enrichment made the behaviour of the captive reindeer clearly more similar to the behaviour of wild reindeer.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23199号 / 工博第4843号 / 新制||工||1756(附属図書館) / 京都大学大学院工学研究科材料工学専攻 / (主査)教授 邑瀬 邦明, 教授 宇田 哲也, 教授 作花 哲夫 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Functioning of the living cell is controlled by a complex network of interactions among genes, proteins, and other molecules. A major goal of systems biology is to understand and explain the mechanisms by which these interactions govern the cell's response to various conditions. Molecular interaction networks have proven to be a powerful representation for studying cellular behavior. Numerous algorithms have been developed to unravel the complexity of these networks. Our work addresses the drawbacks of existing techniques. This thesis includes three related research efforts that introduce network-based approaches to bridge current methodological gaps in systems biology. i. Functional enrichment methods provide a summary of biological functions that are overrepresented in an interesting collection of genes (e.g., highly differentially expressed genes between a diseased cell and a healthy cell). Standard functional enrichment algorithms ignore the known interactions among proteins. We propose a novel network-based approach to functional enrichment that explicitly accounts for these underlying molecular interactions. Through this work, we close the gap between set-based functional enrichment and topological analysis of molecular interaction networks. ii. Many techniques have been developed to compute the response network of a cell. A recent trend in this area is to compute response networks of small size, with the rationale that only part of a pathway is often changed by disease and that interpreting small subnetworks is easier than interpreting larger ones. However, these methods may not uncover the spectrum of pathways perturbed in a particular experiment or disease. To avoid these difficulties, we propose to use algorithms that reconcile case-control DNA microarray data with a molecular interaction network by modifying per-gene differential expression p-values such that two genes connected by an interaction show similar changes in their gene expression values. iii. Top-down analyses in systems biology can automatically find correlations among genes and proteins in large-scale datasets. However, it is often difficult to design experiments from these results. In contrast, bottom-up approaches painstakingly craft detailed models of cellular processes. However, developing the models is a manual process that can take many years. These approaches have largely been developed independently. We present Linker, an efficient and automated data-driven method that analyzes molecular interactomes. Linker combines teleporting random walks and k-shortest path computations to discover connections from a set of source proteins to a set of target proteins. We demonstrate the efficacy of Linker through two applications: proposing extensions to an existing model of cell cycle regulation in budding yeast and automated reconstruction of human signaling pathways. Linker achieves superior precision and recall compared to state-of-the-art algorithms from the literature. / Ph. D.

Currently aquaculture is the largest growing food sector in the world, however, its future growth is limited by its heavy reliance on fishmeal (FM). Overfishing of wild marine fish stocks used for FM is putting too much pressure on the stocks, making FM unsustainable as a dominant protein source as aquaculture continues to grow. Plant proteins (PP) are an ideal alternative to FM because of their wide availability and relatively low cost. Soybean meal (SBM) is the most commonly used PP in aquaculture, but its inclusion in feeds is limited due to reduced digestibility and the presence of antinutritional factors ultimately leading to a reduced growth performance of fish that are fed with the SBM-based diet. Therefore, the goal of this thesis was to mitigate the negative effects of PP and improve the growth of fish fed with a PP-based diet, utilizing SBM as our PP in feeds. Three feeding trials were conducted to test the efficacy of 3 approaches towards improving the use of PP in fish. The first trial (Chapter 2), tested the effect of nutritional programming (NP) on the utilization of SBM in zebrafish (Danio rerio). NP is the theory that an organism can be ‘programmed’ to better utilize a dietary component by being exposed to that component in its early life stages. This study also tested the effect of NP through the broodstock by exposing the broodstock to SBM for 4 weeks prior to breeding. In addition, a combination of both programming techniques was also tested. The results found that neither of the programming techniques had a significant effect on the growth performance of the zebrafish. Among the two groups from the programmed broodstock, the group that also received early stage NP had a significantly higher expression of PepT1, a di- and tri- peptide transporter. Also, the dual programmed group had the highest length-to-width ratio of the distal villi among groups that were fed SBM, which signifies an increase in surface area for nutrient absorption in the intestine. The findings from this study suggest that early stage NP may increase the absorption of nutrient from PP-based feeds within the intestine. The second feeding trial (Chapter 3), utilized the supplementation of health-promoting dipeptides to improve the use of SBM-based feeds for zebrafish. The three dipeptides used in this study were alanyl-glutamine, carnosine, and anserine. The five groups in this study consisted of three groups receiving an SBM-based diet with one of the dipeptides supplemented into it, a (-) Control group receiving a non-supplemented SBM-based diet, and a (+) Control group receiving a FM-based diet. Both the alanyl-glutamine and carnosine supplemented groups experienced a significantly higher weight gain compared to the (-) Control group. In addition, the alanyl-glutamine supplemented group had a significantly higher length-to-width ratio of the intestinal villi and, had a numerically higher expression of both nutrient absorption genes measured, PepT1 and fabp2, compared to the (-) Control group. This finding suggests that the supplementation of alanyl-glutamine into SBM-based diets may improve the intestinal absorptive capacity of the fish fed with the SBM. The results from this study also support the use of both alanyl-glutamine and carnosine supplementation as a means of improving the growth performance of fish fed with a SBM-based diet. The third feeding trial (Chapter 4), was conducted on largemouth bass (LMB) (Micropterus salmoides). This study also focused on NP as a means of improving the utilization of dietary SBM, similar to Chapter 2. In this study, live feed was used as a vector to program the larval LMB to SBM. The programmed group in this study received Artemia nauplii that were enriched with a SBM solution, during the larval stage. The bass were then fed with a FM-diet for 7 weeks, before being reintroduced to SBM for the final 6 weeks of the study (PP-Challenge). The programmed LMB experienced a significantly higher weight gain compared to the non-programmed fish also undergoing the PP-Challenge, and achieved a weight gain similar to that of the LMB that were being fed with an FM-diet. In addition, the programmed LMB had significantly longer distal villi and a higher length-to-width ratio of the villi, compared to the non-programmed group. The findings from this study support the use of live feed as a vector for NP and improving the growth performance of a carnivorous aquaculture species fed with a SBM-based diet. The overall findings from these studies suggest that both NP and dipeptide supplementation are feasible means of improving the utilization of SBM in fish. The mechanism behind NP seems to lie in the intestine. In both zebrafish and LMB, NP was found to reduce the inflammatory impact on the intestine and increase the surface area for absorption of the intestinal villi. The supplementation of alanyl-glutamine had similar effects on the intestine as NP and improved the growth performance of zebrafish. The observations from these studies seem to point to mitigating the negative effects of SBM on the intestine as the key to improving the growth performance of fish fed with a SBM-based diet.

In this dissertation we define an analogue, in the setting of infinity categories, of the classical notion of an enriched operad. We introduce six different models of enriched infinity operads. In particular, we generalize the operator category approach of Clark Barwick to the enriched setting as well as Moerdijk-Weiss' notion of dendroidal sets. The main part of the thesis consists of the comparison between different approaches to enriched operads.