This work focuses on anorexigenic neuropeptides, cocaine- and amphetamine-regulated transcript (CART) and prolactin-releasing peptide (PrRP), which decrease food intake and body weight. CART peptide is an anorexigenic neuropeptide and, despite many efforts, its receptor has not yet been identified. We found CART peptide specific binding sites in pheochromocytoma PC12 cells. Cells differentiated to neurons increased significantly the number of binding sites. On the other hand, after differentiation to chromaffin cells the number of binding sites was so low that it was impossible to determine their density. To clarify the importance of each of the three disulfide bridges in the CART molecule, analogs with one or two disulfide bridges were synthetized. The biological activity was maintained in analog with two disulfide bridges in positions 74-94 and 88-101. Moreover, we demonstrated the stimulation of JNK and subsequently c-Jun activation in PC12 cells. Neuropeptide PrRP belongs to the RF-amide peptide family and has anorexigenic properties. PrPR has a high affinity to GPR10 and neuropeptide FF (NPFF2) receptor. In our laboratory lipidized analogs of PrRP were synthesized, which are able to decrease food intake after peripheral administration and may cross the blood-brain barrier. We tested biological...

This work focuses on anorexigenic neuropeptides, cocaine- and amphetamine-regulated transcript (CART) and prolactin-releasing peptide (PrRP), which decrease food intake and body weight. CART peptide is an anorexigenic neuropeptide and, despite many efforts, its receptor has not yet been identified. We found CART peptide specific binding sites in pheochromocytoma PC12 cells. Cells differentiated to neurons increased significantly the number of binding sites. On the other hand, after differentiation to chromaffin cells the number of binding sites was so low that it was impossible to determine their density. To clarify the importance of each of the three disulfide bridges in the CART molecule, analogs with one or two disulfide bridges were synthetized. The biological activity was maintained in analog with two disulfide bridges in positions 74-94 and 88-101. Moreover, we demonstrated the stimulation of JNK and subsequently c-Jun activation in PC12 cells. Neuropeptide PrRP belongs to the RF-amide peptide family and has anorexigenic properties. PrPR has a high affinity to GPR10 and neuropeptide FF (NPFF2) receptor. In our laboratory lipidized analogs of PrRP were synthesized, which are able to decrease food intake after peripheral administration and may cross the blood-brain barrier. We tested biological...

Trots att e-handeln har ökat under de senaste decennierna, är konverteringsgraden för onlinebutiker inom modesegmentet fortfarande låg. Detta kan bero på det fenomen som kallas “shopping cart abandonment”, vilket innebär att kunder lägger varor i sina virtuella varukorgar men inte sluför köpet. Det finns många anledningar till varför kunderna agerar på detta sätt. En av de vanligaste orsakerna är att det föredragna betalningsalternativet inte är tillgängligt. Eftersom alla fall av shopping cart abandonment innebär en förlorad försäljning är det viktigt för onlineföretag att arbeta mot en högre konverteringsgrad då även den minsta ökningen av slutförda köp innebär en ökad lönsamhet. Därför bör det vara av intresse för alla onlineföretag att upprätta rutiner för att se till att kunderna kommer att slutföra sina köp. Ett sätt att göra detta är att påminna kunderna via e-mejl om produkterna i den övergivna kundvagnen. Dessa mejl kallas reaktiveringsmejl och innebär i grunden att företaget skickar ett mejl till de kunder som övergivit sin virtuella varukorg. Huvudfokus i denna studie är reaktiveringsmejl med syfte att undersöka hur e-handelsföretag inom mode och textilbranschen använder reaktiveringsmejl och om de i så fall sett en ökning i konverteringsgraden. För att uppfylla syftet har två olika datainsamlingsmetoder använts. Först och främst genomfördes ett experiment bland e-handelsföretag inom det valda segmentet för att på så vis få en bild av hur vanligt det är att använda reaktiveringsmejl. Efter detta genomfördes telefonintervjuer med ett antal av dessa företag för att få en mer djupgående förståelse kring reaktiveringsmejl. Undersökningens resultat visar att användningen av dessa e-postmeddelanden inte är så vanlig, men däremot att det är ett framgångsrikt sätt att minska förekomsten av shopping cart abandonment samt öka konverteringsgraden. / Even though e-retail has increased over the last few decades, the conversion rate for online stores in the fashion segment is still relatively low. This might be due to a phenomenon called “shopping cart abandonment”, which means that online customers place products in their virtual carts but never follow through with a purchase. There are many reasons why customers balk before the very last click. One of the more common causes is that the preferred payment option is not available. However, since all cases of shopping cart abandonment mean lost sales, it is important for online companies to work towards a higher conversion rate since even the smallest increase in completed purchases results in increased profitability. Therefore, it should be of interest for all online enterprises to establish procedures to ensure that customers will complete their online purchases. One way to do this is to remind the customers via e-mail about the products in the abandoned cart, which is called reactivation e-mails, and basically means that online companies send e-mails to the customers who abandoned their virtual carts. The main focus for this thesis is reactivation e-mails, with the purpose to examine how online enterprises in the fashion and textile segment use reactivation e-mails and if they have seen an increase in their conversion rate. To fulfill the purpose, companies within the chosen segment that offer online retail to their customers, have been interviewed about the subject and the findings show that the use of these e-mails is an effective way to increase the conversion rate and decrease the occurrence of shopping cart abandonment. Two different methods for data collection have been used for this study. Firstly, an experiment was conducted among e-commerce companies within the selected segment in order to determine how common it is to use reactivation emails. Secondly, telephone interviews were conducted with several of these companies to gain a deeper understanding of reactivation emails. The results of this survey show that the use of these emails is not very common, but it is clearly a very effective way to reduce the occurrence of shopping cart abandonment. It also increases conversion rates and given the relatively low cost to implement, it should be embraced industry wide.

Dans cette thèse, nous proposons des modèles probabilistes et statistiques d'analyse de données multidimensionnelles pour la prévision de l'incertitude sur les trajectoires d'aéronefs. En supposant que pendant le vol, chaque aéronef suit sa trajectoire 3D contenue dans son plan de vol déposé, nous avons utilisé l'ensemble des caractéristiques de l'environnement des vols comme variables indépendantes pour expliquer l'heure de passage des aéronefs sur les points de leur trajectoire de vol prévue. Ces caractéristiques sont : les conditions météorologiques et atmosphériques, les paramètres courants des vols, les informations contenues dans les plans de vol déposés et la complexité de trafic. Typiquement, la variable dépendante dans cette étude est la différence entre les instants observés pendant le vol et les instants prévus dans les plans de vol pour le passage des aéronefs sur les points de leur trajectoire prévue : c'est la variable écart temporel. En utilisant une technique basée sur le partitionnement récursif d'un échantillon des données, nous avons construit quatre modèles. Le premier modèle que nous avons appelé CART classique est basé sur le principe de la méthode CART de Breiman. Ici, nous utilisons un arbre de régression pour construire une typologie des points des trajectoires des vols en fonction des caractéristiques précédentes et de prévoir les instants de passage des aéronefs sur ces points. Le second modèle appelé CART modifié est une version améliorée du modèle précédent. Ce dernier est construit en remplaçant les prévisions calculées par l'estimation de la moyenne de la variable dépendante dans les nœuds terminaux du modèle CART classique par des nouvelles prévisions données par des régressions multiples à l'intérieur de ces nœuds. Ce nouveau modèle développé en utilisant l'algorithme de sélection et d'élimination des variables explicatives (Stepwise) est parcimonieux. En effet, pour chaque nœud terminal, il permet d'expliquer le temps de vol par des variables indépendantes les plus pertinentes pour ce nœud. Le troisième modèle est fondé sur la méthode MARS, modèle de régression multiple par les splines adaptatives. Outre la continuité de l'estimateur de la variable dépendante, ce modèle permet d'évaluer les effets directs des prédicteurs et de ceux de leurs interactions sur le temps de passage des aéronefs sur les points de leur trajectoire de vol prévue. Le quatrième modèle utilise la méthode d'échantillonnage bootstrap. Il s'agit notamment des forêts aléatoires où pour chaque échantillon bootstrap de l'échantillon de données initial, un modèle d'arbre de régression est construit, et la prévision du modèle général est obtenue par une agrégation des prévisions sur l'ensemble de ces arbres. Malgré le surapprentissage observé sur ce modèle, il est robuste et constitue une solution au problème d'instabilité des arbres de régression propre à la méthode CART. Les modèles ainsi construits ont été évalués et validés en utilisant les données test. Leur application au calcul des prévisions de la charge secteur en nombre d'avions entrants a montré qu'un horizon de prévision d'environ 20 minutes pour une fenêtre de temps supérieure à 20 minutes permettait d'obtenir les prévisions avec des erreurs relatives inférieures à 10%. Parmi ces modèles, CART classique et les forêts aléatoires présentaient de meilleures performances. Ainsi, pour l'autorité régulatrice des courants de trafic aérien, ces modèles constituent un outil d'aide pour la régulation et la planification de la charge des secteurs de l'espace aérien contrôlé.

Classification of data from repeated measurements is useful in various disciplines, for example that of medicine. This thesis explores how classification trees (CART) can be used for classifying repeated measures data. The reader is introduced to variations of the CART algorithm which can be used for classifying the data set and tests the performance of these algorithms on a data set that can be modelled using bilinear regression. The performance is compared with that of a classification rule based on linear discriminant analysis. It is found that while the performance of the CART algorithm can be satisfactory, using linear discriminant analysis is more reliable for achieving good results. / Klassificering av data från upprepade mätningar är användbart inom olika discipliner, till exempel medicin. Denna uppsats undersöker hur klassificeringsträd (CART) kan användas för att klassificera upprepade mätningar. Läsaren introduceras till varianter av CART-algoritmen som kan användas för att klassificera datamängden och testar prestandan för dessa algoritmer på en datamängd som kan modelleras med hjälp av bilinjär regression. Prestandan jämförs med en klassificeringsregel baserad på linjär diskriminantanalys. Det har visar sig att även om prestandan för CART-algoritmen kan vara tillfredsställande, är användning av linjär diskriminantanalys mer tillförlitlig för att uppnå goda resultat.

Farmworkers and their families may experience increased levels of agricultural pesticides in their homes due to both (1) take-home/soil track-in on shoes, clothes and skin, and (2) air infiltration from nearby agriculture fields via agricultural pesticide drift in the vapor phase or adhered to resuspended soil particles. This dissertation estimates the relative contributions o the take-home/soil track-in and air infiltration pathways of agricultural pesticides into homes, as well as identifies the risk factors for increased in-home agricultural pesticide levels for farmworkers and their families living near agriculture fields. Samples of outdoor air, yard soil, and house dust from 21 farmworkers' homes in Yuma County, Arizona were collected and analyzed for a suite of agricultural pesticides. To capture household information, such as behaviors, demographics, and housing structure, a participant questionnaire was administered at the time of the sampling. A pesticide transport model was developed, evaluated, and applied to quantify relative contributions of the air infiltration and the take-home/soil track-in pathways of agricultural pesticides into the house dust of the farmworkers' homes. To explore a wide-range of potential risk factors for increased agricultural pesticide levels in the homes, traditional statistical methods and Classification and Regression Tree (CART) analyses were used. The results of this study, found that the air infiltration pathway contributes to over 90% of some agricultural pesticides in the house dust found in the farmworkers' homes. In addition, among the influential risk factors for increased in-home agricultural pesticide levels was the home being a closer distance to an agricultural field, as well as the home having carpeted floors, more farmworkers per square footage of the home, and less months of heating and cooling the home. It is suggested that future intervention efforts to reduce in-home agricultural pesticide levels put more emphasis on targeting the air infiltration pathway, and take into consideration relevant risk factors for increased pesticide levels in the home.

The shopping trolley have been frequently used in our daily life. However, the hygiene condition of cart makes people worry a lot, especially the handle brothers. Nowadays, several methods have been proposed to clean the shopping carts but considered uneconomic and inflexible. In this study, we aim to design an integrated cart washing system based on a trailer applied to medium or small supermarket. This system should be more efficient, economic, easily to operate, safer and les water consummation. The integrated cart washing system has three basic functions of washing, disinfection and drying. The system is controlled by PLC program, all steps in the cleaning process are fully automatic insider the trailer and each component are adjustable according to various shopping carts. The system only requires one person to operate and it costs 30 seconds to wash a single cart, able to wash up to 120 cart/hour. Disinfection and drying steps provide high washing quality. Moreover, water-recycling design can save part of wasted water. The modelling and assembly was designed in Autodesk Inventor 2016, the hardware design circuit-writing diagram was performed in AutoCAD, the software design of Programmable logic controller (PLC) was made in STEP 7-Micro/Win. Theoretical calculation and simulation prove the safety and possibility of our system. We concluded that this system might have commercial interests in the market.

摘要 本研究是利用某保險公司在大台北地區的壽險保單資料，進行知識發現過程。常見的資料採礦技術為類神經網路模型、CART及C4.5，利用這三種模型，來探討保單貸款行為模式。在抽樣過程中，藉由改變抽樣方法、樣本數大小及樣本中有貸款保單的比例，來選擇樣本的結構，並討論不同的樣本結構對模型的影響。研究過程中，也討論了連續變數轉換與否對各個模型的影響。 結果發現樣本中有貸款保單的比例對於模型的影響較大，而樣本數及抽樣方法對模型的影響都會隨著有貸款保單的比例不同而不同，每種模型適用的樣本結構並不一致。 連續變數的影響中，類神經網路受到連續變數轉換的影響較大，研究結果發現轉換連續變數可以使得類神經網路模型結果較好；對於CART或C4.5模型，受到連續變數轉換的影響小，CART模型連續變數轉換前後結果不變，而C4.5受連續變數影響在不同樣本結構並不一致，但改變量都很小。 從模型結果來看影響保單是否有貸款的變數，在類神經網路模型的靈敏度分析結果中，對模型影響較大的變數為體位別、被保人職業別級數、保險型態及地區；在CART模型結果中，影響較大的變數為繳別、保單年度、保單價值金、繳費方式及投保面額；在C4.5模型結果中，影響較大的變數為主約保單預定利率、年繳化保費、保單年度及繳別。對於CART、C4.5模型，選擇有較高正確率的規則，以提供保險公司決策方針。 / In this study, data mining is being applied on data taken from one of the life insurance company in Taipei. The techniques used are neural network, CART and C4.5 which are widely used models in data mining. In the process of acquiring samples, we comprised groups of samples by using different kind of sampling methods, different sample sizes, different ratios of loaned to un-loaned policies. In addition another groups of samples are created based on whether the continuous variables have been transformed. We then applied the three models into each of our various samples combinations to see which samples combination best described consumer behaviors with respect to their borrowing attitudes against their policies and its effects on different data mining models. The results we found based on our study are summarized as following: 1. The assigned ratios have great influences on the model. However the magnitude of influences of sampling method and sample size on the model depends largely on the sample combination. 2. The sample combinations having transformed continuous variables affect and improve the results of neural network model significantly. However for CART model, the affects are insignificant whether the continuous variables having been transformed or not. The effect of transformed continuous variables on C4.5 is of limited. 3. The variables used to describe the behavior of the consumers as to taking the loan against the insurance policy vary for the three models.

This thesis considers the practical problem of constrained and unconstrained local optimization. This subject has been well studied when the objective function f is assumed to smooth. However, nonsmooth problems occur naturally and frequently in practice. Here f is assumed to be nonsmooth or discontinuous without forcing smoothness assumptions near, or at, a potential solution. Various methods have been presented by others to solve nonsmooth optimization problems, however only partial convergence results are possible for these methods. In this thesis, an optimization method which use a series of local and localized global optimization phases is proposed. The local phase searches for a local minimum and gives the methods numerical performance on parts of f which are smooth. The localized global phase exhaustively searches for points of descent in a neighborhood of cluster points. It is the localized global phase which provides strong theoretical convergence results on nonsmooth problems. Algorithms are presented for solving bound constrained, unconstrained and constrained nonlinear nonsmooth optimization problems. These algorithms use direct search methods in the local phase as they can be applied directly to nonsmooth problems because gradients are not explicitly required. The localized global optimization phase uses a new partitioning random search algorithm to direct random sampling into promising subsets of ℝⁿ. The partition is formed using classification and regression trees (CART) from statistical pattern recognition. The CART partition defines desirable subsets where f is relatively low, based on previous sampling, from which further samples are drawn directly. For each algorithm, convergence to an essential local minimizer of f is demonstrated under mild conditions. That is, a point x* for which the set of all feasible points with lower f values has Lebesgue measure zero for all sufficiently small neighborhoods of x*. Stopping rules are derived for each algorithm giving practical convergence to estimates of essential local minimizers. Numerical results are presented on a range of nonsmooth test problems for 2 to 10 dimensions showing the methods are effective in practice.

This thesis is comprised of four studies. The first study aimed to examine the measurement invariance of the Coach-Athlete Relationship Questionnaire (11-item, athlete version CART-Q) employing a total of 1,363 athletes from Belgium (n =200), Britain (n =382), China (n =200), Greece (n =115), Spain (n =120), Sweden (n =169), and the United States of America (n =177). Multi-group mean and covariance structure (MACS) analyses supported the factorial validity of the CART-Q in a three-first order factor model across the seven countries. An examination of the latent mean differences of the CART-Q revealed that there are some variations in terms of the intensity athletes perceive in the quality of the relationship with their coach across the different countries. Overall, these results supply additional evidence of the psychometric properties of the CART-Q and highlight that it is a sound instrument that can be applied cross-culturally. The second study attempted to identify the cultural nuances that exist in Chinese coach-athlete relationships from an derived-emic perspective. Eight-hundred Chinese coaches and athletes completed the long and short versions of the CART-Qs. Results supported the reliability across the CART-Q versions examined, while confirmatory factor analyses only supported the factorial validity of the three-first order factor model of the 11-item CART-Q. The findings indicated that the corresponding aspect of complementarity may not best capture the Chinese coach-athlete behavioural interactions. Thus, it suggested that future research should consider conceptualising and measuring the coach-athlete reciprocal interactions in terms of coaches dominant behaviours and athletes submissive behaviours within Chinese sports context. The third study examined the nomological validity of the 11-item CART-Qs with 350 Chinese coach-athlete dyads. Big-Five personality traits and relationship satisfaction were employed as the criterion variables of coach-athlete relationships. Results revealed: (a) actor effects of personality traits, namely, conscientiousness, extroversion, and neuroticism, on both coaches and athletes perceptions of relationship quality and (b) partner effects of only athletes personality, namely, conscientiousness, extroversion, and neuroticism, on their coaches perceptions of relationship quality. The findings suggested that each relationship member s personality trait contributed independently to relationship quality, because no interaction effects of the coach s and the athlete s personality traits on relationship quality were found. In addition, the findings also supported both actor and partner effects of the coach s and the athlete s perceptions of relationship quality on their satisfaction with training. Based upon the relevant theory and findings generated from the previous three studies, the fourth and final study aimed to fill the gap in the relevant literatures by expanding the construct of complementarity to include coach-athlete reciprocal behaviours, namely the coach s dominant and the athlete s submissive behaviours. Study 4 included 4 phases reflecting the process undertaken to develop and validate the Dominant-Submissive Behaviours Scales. Phase 1 generated a pool of items based on the relevant literatures and feedback from the coaches and athletes; these items were then assessed by three panel groups including academic experts, coaches and athletes. In phase 2 and phase 3, confirmatory factor analysis was used to examine the construct validity, nomological validity, and internal reliability of the developed scales. As a result, the 10-item coach s dominant behaviour scale and the 10-item athlete s submissive behaviour scale were derived. Phase 4 employed athletes from five different countries to assess the cross-cultural validity of the submissive scale, and results supported the full structural invariance of the athlete s submissive behaviour scale across the five countries. Overall, results confirmed the dominant-submissive scale is a valid measure for assessing another dimension of complementarity in coach-athlete relationships. Collectively, this thesis has expanded the current knowledge of coach-athlete relationships to a broader social-cultural context by recruiting coaches and athletes from eight different countries across two continents. It is therefore plausible to conclude that the conceptualisation of the 3+1Cs model and the CART-Q seem to be universal across diverse cultures at a generic level. However, future research needs to continue discovering the universals as well as the variations of human behaviours in the content and the quality of coach-athlete relationships. Key Words: Chinese, dominant, submissive, coach-athlete, relationships, cross-cultural, CART-Q