The amphetamine derivative, 3,4-methylenedioxymethamphetamine (MDMA), is a popular drug often taken by young adults at dance clubs or rave parties. Laser light shows, fast-paced electronic music, and hot crowded dance floors are characteristic of these events, and Ecstasy users report that the acute effects of the drug are potentiated by these stimulatory conditions. However, it remains largely unknown how environmental stimuli impact the neurochemical and physiological effects of MDMA. The aim of the first study presented in this dissertation was to investigate how auditory stimuli (music, white noise, and no additional sound) influence MDMA conditioned place preference (CPP), self-administration, and nucleus accumbens (NAcc) dopamine (DA) and serotonin (5-HT) responses. Findings revealed a significant CPP for animals exposed to white noise during MDMA conditioning trials. After self-administration of MDMA (1.5 mg/kg), NAcc DA and 5-HT were highest in rats exposed to music during the test session. The second study aimed to investigate the effects of ambient temperature (23°or 32°C) on long-term MDMA self-administration and neurochemical responses. Results indicated no difference in self-administration or locomotor activity rates for the high versus room temperature groups across sessions. However, MDMA (3.0 mg/kg) administered in high ambient temperature resulted in significantly greater NAcc serotonin release compared to when taken at room temperature, but no differences in dopamine response was determined between the two conditions. Overall, these results indicate that auditory and thermal stimuli can effect MDMA-induced behavioral and neurochemical responses. The last aim tested a novel apparatus and method for use in animal models of drug reinforcement. By combining traditional CPP and self-administration procedures, this approach provided more informative data and circumvented some inherent drawbacks of each method alone. In addition to confirming the ability to produce drug conditioned place preferences after short- and long-term experiments, the long-term version of the procedure revealed a significant positive relationship between lever response rate and CPP magnitude. Therefore, this experimental design can be used to identify subgroups of rats that may vary in sensitivity to drug motivational effects. Further study of these populations may be useful in the development of behavioral and pharmacological therapies for drug addiction. / text

In today’s world of volatile fuel prices and climate concerns, there is little study on the relation between vehicle ownership patterns and attitudes toward potential policies and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s household-fleet evolution. Results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are vehicle purchase price, type/class, and fuel economy (with 30%, 21% and 19% of respondents placing these in their top three). Most (56%) respondents also indicated that they would seriously consider purchasing a Plug-In Hybrid Electric Vehicle (PHEV) if it were to cost $6,000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings. 25-year simulations suggest that 19% of Austin’s vehicle fleet could be comprised of Hybrid Electric Vehicles (HEVs) and PHEVs under adoption of a feebate policy (along with PHEV availability in Year 1 of the simulation, and current gas prices throughout). Under all scenarios vehicle usage levels (in total vehicle miles traveled [VMT]) are predicted to increase overall, along with average vehicle ownership levels (per household, and per capita); and a feebate policy is predicted to raise total regional VMT slightly (just 4.43 percent, by simulation year 25), relative to the trend scenario, while reducing CO2 emissions only slightly (by 3.8 percent, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 17% and CO2 emissions by 22% (relative to trend). Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. And HEVs, PHEVs and Smart Cars are estimated to represent a major share of the fleet’s VMT (25%) by year 25 under the feebate scenario. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet), yet feebate-policy receipts exceed rebates in each simulation year. A 15% reduction in the usage levels of SUVs, CUVs and minivans is observed in the $5/gallon scenario (relative to trend). Mean use levels per vehicle of HEVs and PHEVs are simulated to have a variation of 753 and 495 across scenarios. In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have even more significant effects on energy dependence and greenhouse gas emissions. / text

台灣為一海島，自然資源缺乏而人口密度極高，因此僅能對外開拓貿易以發展經濟； 由民國四十年代之進口替代階段，到民國五十年代之出口導向階段，以迄目前，出口 在我國經濟中仍扮演著一大動力角色。 一般而言，影響出口之因素很多，諸如國民所得、人口、距離、相對價格水準及相對 要素密集程度等皆是，但卻很少人以「普遍化優惠關稅」作為經濟變數，就其對出口 所造成的影響進行分析探討。 所謂「普遍化優惠關稅」（THE GENERALIZED SYSTEM OF PREFERENCE）係指已開發國 家為了促進開發中國家之貿易，進而促進其工業化、加速經濟成長，對於來自開發中 國家的產品輸入，給予一般性、非互惠性及非歧視性的優惠關稅待遇的制度，此制度 首由EEC 於１９７１年７月１日施行，美國則至１９７６年１月始實行，我國為受惠 國之一。其他授我GSP 者，計有澳大利亞、日本、紐西蘭及奧地利四國。 由我國出口產品之主要市場分佈看，大多數集中於美日地區，而以美國居首位；此種 情況在以往我國經濟未受舉世矚目之年代，尚不成問題，然而目前我國擁有巨額外匯 存底，對美又享有巨額貿易順差之情況下，此種出口市場過份集中情況，卻可能危及 我出口之成長。因為美國為迫使新台幣升值，對我採取一連串施壓行動，而其中之一 即取消授我之「普遍化優惠關稅」待遇，且於１９８９年１月開始生效。 本文即欲檢討「普遍化優惠關稅」對我國出口所產生的影響效果，利用我國現有資料 ，以迴歸模型加以分析。在本論文中，「普遍化優惠關稅」分別以虛擬變數（DUMMY UARIABLE）及實際減免稅額表示。由於我國歷年享受美國GSP 的程度大都居首位，因 此預期分析結果可得GSP 對我歷年出口有顯著效果，但近年來因競爭需要限制（COMP ETITIVE NCED LIMITATIONS）之規定，享受GSP 之產品項目已漸減，其對出口之影響 力量漸弱，是故美國取消授我之GSP 待遇，整體而言對我出口廠商所可能產生的影響 ，應不至於太大！

Cognitive dissonance theory and selective information exposure literature postulate that individuals ignore preference-inconsistent information and selectively process new information. Previous studies on selective information exposure have shown that preference-inconsistent information is not persuasive for consumer decision making. Given the limited amount of past research about the effect of preference-inconsistent information on decision-making in broad domains of consumer behavior studies, the current study investigated how preference-inconsistent information can persuade consumers to switch to a sustainable product alternative. The purpose of this study is to investigate the process how preference-inconsistent sustainability-related information can be considered as important, consequently changing consumers' initial preference to green alternatives. A series of online experiments was conducted using a shampoo product category. Study 1 tested a baseline effect on whether consumers in the preference-inconsistent condition were persuaded to change their initial choice significantly compared to those in the preference-consistent condition. Study 2 tested the effect of preference-inconsistent sustainability-related information in the acceptance process, focusing on the role of brand commitment and information quality. Study 3 examined the effect of preference-inconsistent sustainability-related information in the evaluation process, investigating the impact of consumer environmental concern and PCE. Findings of Study 1 revealed that consumers in the preference-inconsistent condition were significantly persuaded to change choice to a sustainable alternative, which is not consistent with selective exposure literature. However, Study 1 findings were not sufficient to determine what specific factors influenced respondents to be persuaded, which provides justifications for Study 2 and Study 3. Findings in Study 2 and Study 3 conclusively demonstrated the importance of the credibility of preference-inconsistent information in the acceptance process. Also, findings suggested that the effect of credibility is stronger than that of brand commitment in the acceptance process. Regarding brand commitment, the results have shown that high commitment consumers had a higher acceptance of inconsistent information which is opposite to expectations. Further, the findings demonstrated the importance of environmental concern and the conditional effect of PCE in the evaluation process. Moreover, results supported that the relative weighting of sustainability attributes is driving the effects of environmental concern and PCE as a mediator on persuasion outcomes in the evaluation process. The current study contributes to understanding the process in which the preference-inconsistent information can be effective in influencing consumer choice. Moreover, findings from this research can provide implications for selective exposure literature and sustainable consumption literature. Practically, the results of the study provide implications to guide marketers and information providers in establishing effective ways to change consumers' behavior in sustainable consumption context.

The thesis examines the ability of DSGE models with financial elements to explain financial asset prices. A neoclassical macroeconomic model is used, in- cluding a financial constraint in the form of a restriction on external financing. Moreover, the strictness of the restriction is affected by an external financial shock. It is shown, that the combination of the financial constraint and the fi- nancial shock contributes to understanding of the macroeconomic fluctuations, asset price dynamics and their mutual impact. The calibration for the United States demonstrates that the financial shock is an important source of the as- set price volatility. Contrary, when calibrated to the Czech data, the financial shock generates only moderate asset price volatility, as a consequence of a posi- tive correlation with the productivity shock. To address the issue, the model is further extended by a sector of financial intermediaries and a preference shock related to the risk-aversion of economic subjects, and the extension is shown to improve the result.

In recent years the market share of major real estate companies, at least the Czech ones, has not changed much. Statistical data don't reflect any significal upward trend in volumes of properties for rent or sale. In case the real estate company would like to access larger market share, they have to secure a competitive advantage over the others. One of the ways how to attract more potential customers might be speeding up the company website's property search process. In many cases the website visitors are facing hundreds or thousands of property offers before finding couple satisfactories. The aim of the thesis is to explore possibilities of applicating customer preferences in property trading. The focus is put on research of recommender system algorithms, their characteristics and limtations. The author is evaluating usage of each algorithm variant and its suitability for a real world deployment in a real estate area. Apart from the theoretical part of the work one can find a part, where real estate information system is extended with a framework for implementing recommendation system algorithms. The author is in possesion of production data of a medium sized real estate company. He uses the recommender system framework to build and evaluate example algorithm. Powered by TCPDF (www.tcpdf.org)

The main object of this thesis was to find out whether grammar school students prefer zoological objects in biology lessons presented a) on photo in their natural habitat or b) the real specimen presented in liquid in glass cylinders and burettes. I have chosen these research questions: 1. In which form do pupils prefer zoological objects, the real specimen presented in liquid in glass cylinders or burettes or in their natural habitat on a photograph? 2. How do these preferences differ during the course of their high school study? 3. How do these preferences differ according to gender? 4. Are these preferences influenced by a specific animal? 5. Are these preferences influenced by other factors, e.g. by the appearance and personal experiences with live nature or frequency of using these objects in biology lessons. The research was implemented by using a questionnaire and a preferential test and was given to first and third year students from five Prague high schools. The conclusion of my research study shows that students prefer neither animals on photographs nor the real specimen presented as a liquid preparation. My research did not show that the preferences of the tested students were influenced by any of the tested factors, e.g. type of living, popularity of biology or students' grade in...

1 Title: Manifestation of cerebellar dominance in the form of extinction physiological syndrome on upper and lower limbs and its relationship to human laterality. Objectives: The aim of this diploma thesis is to determinate size of relationship between manifestation of cerebellar dominance in the form of extinction physiological syndrome and preference of limbs. Methods: A total of 27 individuals (male and female students of UK FTVS) were involved in the current quantitative research. We used indicators which were selected from Musalek's test battery (2013) to assess limb preferences. The evaluation of joint passivity asymmetry was based on angle and time parameters during walk and during controlled falls of forearm and shank on a constructed fall-machine. The movement was registered in real time by Qualisys Motion Capture System. For data analysis, descriptive statistics methods, paired t-test, level of statistical and substantive significance (Cohen's d) and tetrachoric coefficient of correlation were used. Results: Our research suggests that there is no significant difference in joint passivity when comparing preferred and non preferred limbs. Though it is necessary to take into consideration specifics and the size of research sample in which everybody was an active athlete. The result of tetrachoric...

Agricultural technology adoption in developing countries is an interesting topic for two reasons: there is often a gap between the realized and potential hectare yields, and agriculture is an important source of livelihood for a signi_cant part of the third world population. This thesis is attempting to analyze the relationships between time preferences of the Ghanaian cocoa farmers and their willingness to use fertilizers provided on a microcredit basis. It is using mainly basic statistical tests, contingent tables analysis and the logistic regression to find out whether the farmers who are patient and time consistent have different approach to technology adoption than the impatient and time inconsistent farmers. We also test for differences in time preferences between farmers with different gender, age and education, and we find that the younger farmers tend to be more impatient. The main conclusion of this work is that impatient and hyperbolic farmers are more likely to enter a microcredit program. We cannot present any significant inference about the link between the farmers' time preferences and their decision to leave a microcredit program. JEL Classification C12, C14, D9, G2, O13, Q14 Keywords Technology adoption, time preferences, mirco- credit, developing economics, cocoa cultivation...

Les contributions de la thèse sont centrées sur la prise de décisions séquentielles et plus spécialement sur l'Apprentissage par Renforcement (AR). Prenant sa source de l'apprentissage statistique au même titre que l'apprentissage supervisé et non-supervisé, l'AR a gagné en popularité ces deux dernières décennies en raisons de percées aussi bien applicatives que théoriques. L'AR suppose que l'agent (apprenant) ainsi que son environnement suivent un processus de décision stochastique Markovien sur un espace d'états et d'actions. Le processus est dit de décision parce que l'agent est appelé à choisir à chaque pas de temps du processus l'action à prendre. Il est dit stochastique parce que le choix d'une action donnée en un état donné n'implique pas le passage systématique à un état particulier mais définit plutôt une distribution sur l'espace d'états. Il est dit Markovien parce que cette distribution ne dépend que de l'état et de l'action courante. En conséquence d'un choix d'action, l'agent reçoit une récompense. Le but de l'AR est alors de résoudre le problème d'optimisation retournant le comportement qui assure à l'agent une récompense maximale tout au long de son interaction avec l'environnement. D'un point de vue pratique, un large éventail de problèmes peuvent être transformés en un problème d'AR, du Backgammon (cf. TD-Gammon, l'une des premières grandes réussites de l'AR et de l'apprentissage statistique en général, donnant lieu à un joueur expert de classe internationale) à des problèmes de décision dans le monde industriel ou médical. Seulement, le problème d'optimisation résolu par l'AR dépend de la définition préalable d'une fonction de récompense adéquate nécessitant une expertise certaine du domaine d'intérêt mais aussi du fonctionnement interne des algorithmes d'AR. En ce sens, la première contribution de la thèse a été de proposer un nouveau cadre d'apprentissage, allégeant les prérequis exigés à l'utilisateur. Ainsi, ce dernier n'a plus besoin de connaître la solution exacte du problème mais seulement de pouvoir désigner entre deux comportements, celui qui s'approche le plus de la solution. L'apprentissage se déroule en interaction entre l'utilisateur et l'agent. Cette interaction s'articule autour des trois points suivants : i) L'agent exhibe un nouveau comportement ii) l'expert le compare au meilleur comportement jusqu'à présent iii) l'agent utilise ce retour pour mettre à jour son modèle des préférences puis choisit le prochain comportement à démontrer. Afin de réduire le nombre d'interactions nécessaires entre l'utilisateur et l'agent pour que ce dernier trouve le comportement optimal, la seconde contribution de la thèse a été de définir un critère théoriquement justifié faisant le compromis entre les désirs parfois contradictoires de prendre en compte les préférences de l'utilisateur tout en exhibant des comportements suffisamment différents de ceux déjà proposés. La dernière contribution de la thèse est d'assurer la robustesse de l'algorithme face aux éventuelles erreurs d'appréciation de l'utilisateur. Ce qui arrive souvent en pratique, spécialement au début de l'interaction, quand tous les comportements proposés par l'agent sont loin de la solution attendue. / The thesis contributions resolves around sequential decision taking and more precisely Reinforcement Learning (RL). Taking its root in Machine Learning in the same way as supervised and unsupervised learning, RL quickly grow in popularity within the last two decades due to a handful of achievements on both the theoretical and applicative front. RL supposes that the learning agent and its environment follow a stochastic Markovian decision process over a state and action space. The process is said of decision as the agent is asked to choose at each time step an action to take. It is said stochastic as the effect of selecting a given action in a given state does not systematically yield the same state but rather defines a distribution over the state space. It is said to be Markovian as this distribution only depends on the current state-action pair. Consequently to the choice of an action, the agent receives a reward. The RL goal is then to solve the underlying optimization problem of finding the behaviour that maximizes the sum of rewards all along the interaction of the agent with its environment. From an applicative point of view, a large spectrum of problems can be cast onto an RL one, from Backgammon (TD-Gammon, was one of Machine Learning first success giving rise to a world class player of advanced level) to decision problems in the industrial and medical world. However, the optimization problem solved by RL depends on the prevous definition of a reward function that requires a certain level of domain expertise and also knowledge of the internal quirks of RL algorithms. As such, the first contribution of the thesis was to propose a learning framework that lightens the requirements made to the user. The latter does not need anymore to know the exact solution of the problem but to only be able to choose between two behaviours exhibited by the agent, the one that matches more closely the solution. Learning is interactive between the agent and the user and resolves around the three main following points: i) The agent demonstrates a behaviour ii) The user compares it w.r.t. to the current best one iii) The agent uses this feedback to update its preference model of the user and uses it to find the next behaviour to demonstrate. To reduce the number of required interactions before finding the optimal behaviour, the second contribution of the thesis was to define a theoretically sound criterion making the trade-off between the sometimes contradicting desires of complying with the user's preferences and demonstrating sufficiently different behaviours. The last contribution was to ensure the robustness of the algorithm w.r.t. the feedback errors that the user might make. Which happens more often than not in practice, especially at the initial phase of the interaction, when all the behaviours are far from the expected solution.