Doctor of Philosophy / Curriculum and Instruction Programs / Rosemary S. Talab / The goal of this exploratory case study was to answer two questions: 1. How does an exemplary on-campus undergraduate large Introduction to Cultural Anthropology course encompass the PBL learning model characteristics, specifically focusing on the following: 1.1) Driving question, 1.2) Student construction of an artifact, 1.3) Teachers’ role, and 1.4) Assessment? 2. How is technology used by the professor, teacher assistants, and students to support project-based learning? To answer these questions, the researcher studied a large Introduction to Cultural Anthropology class, which consisted of the professor, ten teaching assistants (TAs), and 400 students. The students were divided into 20 recitation sections, with 20 students in each section. Each TA was assigned two recitation sections. Observations were conducted on twice-weekly Professor’s lectures and three once-weekly recitation sessions. Additionally, interviews and follow-up interviews were conducted of the professor, three teaching assistants (TA), and nine students. Finally, documents analyzed included the professor’s course materials and course management documents. With respect to Research Question 1, “How does an exemplary on-campus undergraduate large Introduction to Cultural Anthropology course encompass the PBL learning model characteristics, specifically focusing on the following: 1.1) Driving question, 1.2) Student construction of an artifact, 1.3) Teachers’ role, and 1.4) Assessment?”, research findings indicated that all four elements of the PBL model were present in this class and were executed well. Research Question 2, “How is technology used to support PBL,” findings indicated that advanced technologies were used by the professor for course purposes. These technologies included Wetpaint (the wiki course management system) and Facebook. More conventional technologies, such as e-mail, were also used for this purpose. Though students were hesitant to use course technology in the beginning. However, with the help of the professor and TA’s, the students learned to use the course technology and grew to enjoy it. Two additional themes emerged through open coding: Emotional Involvement and Non-Participation. First, the TA’s and students developed emotional ties to the cultures that they created in their recitation sections. Second, some students did not participate in either the lecture or the recitation sessions. The TAs took non-participation seriously, both in terms of class participation, individually, and in terms of student responsibilities to the group recitation session in culture construction.

Before market authorization of new medicines, their efficacy and safety are evaluated using randomized controlled trials. While there is no doubt about the scientific value of randomized trials, they are usually conducted in selected populations with questionable generalizability to routine care.  In the digital data revolution era, with healthcare data growing at an unprecedented rate, drug monitoring in routine care is still highly under-utilized. Although many countries have access to data on prescription drugs at the individual level in ambulatory care, such data are often missing for hospitals. This is a growing problem considering the clear trend towards more new and expensive drugs administered in the hospital setting. The aim of this thesis was therefore to develop methods for extracting data on drug use from a hospital-based electronic health record system and further to build and evaluate models for real-time monitoring of effectiveness and safety of new drugs in routine care using data from electronic health records and regional and national health care registers. Using the developed techniques, we were able to demonstrate drug use and health service utilization for inflammatory bowel disease and to evaluate the comparative effectiveness and safety of antiarrhythmic drugs. With a rapidly evolving drug development, it is important to optimize the evaluation of effectiveness, safety and health economic value of new medicines in routine care. We believe that the models described in this thesis could contribute to fulfil this need.

With increasing costs of fossil fuels and intensified environmental awareness, low carbon vehicles, including hybrid electric vehicles (HEVs), are becoming more popular for car buyers due to their lower running costs. HEVs are sensitive to the driving conditions under which they are used however, and real-world driving can be very different to the legislative test cycles. On the road there are higher speeds, faster accelerations and more changes in speed, plus additional factors that are not taken into account in laboratory tests, all leading to poorer fuel economy. Future trends in the automotive industry are predicted to include a large focus on increased hybridisation of passenger cars in the coming years, so this is an important current research area. The aims of this project were to determine the energy consumption of a HEV in real-world driving, and investigate the differences in this compared to other standard drive cycles, and also compared to testing in laboratory conditions. A second generation Toyota Prius equipped with a GPS (Global Positioning System) data logging system collected driving data while in use by Loughborough University Security over a period of 9 months. The journey data was used for the development of a drive cycle, the Loughborough University Urban Drive Cycle 2 (LUUDC2), representing urban driving around the university campus and local town roads. It will also have a likeness to other similar driving routines. Vehicle testing was carried out on a chassis dynamometer on the real-world LUUDC2 and other existing drive cycles for comparison, including ECE-15, UDDS (Urban Dynamometer Driving Schedule) and Artemis Urban. Comparisons were made between real-world driving test results and chassis dynamometer real-world cycle test results. Comparison was also made with a pure electric vehicle (EV) that was tested in a similar way. To verify the test results and investigate the energy consumption inside the system, a Prius model in Autonomie vehicle simulation software was used. There were two main areas of results outcomes; the first of which was higher fuel consumption on the LUUDC2 compared to other cycles due to cycle effects, with the former having greater accelerations and a more transient speed profile. In a drive cycle acceleration effect study, for the cycle with 80% higher average acceleration than the other the difference in fuel consumption was about 32%, of which around half of this was discovered to be as a result of an increased average acceleration and deceleration rate. Compared to the standard ECE-15 urban drive cycle, fuel consumption was 20% higher on the LUUDC2. The second main area of outcomes is the factors that give greater energy consumption in real-world driving compared to in a laboratory and in simulations being determined and quantified. There was found to be a significant difference in fuel consumption for the HEV of over a third between on-road real-world driving and chassis dynamometer testing on the developed real-world cycle. Contributors to the difference were identified and explored further to quantify their impact. Firstly, validation of the drive cycle accuracy by statistical comparison to the original dataset using acceleration magnitude distributions highlighted that the cycle could be better matched. Chassis dynamometer testing of a new refined cycle showed that this had a significant impact, contributing approximately 16% of the difference to the real-world driving, bringing this gap down to 21%. This showed how important accurate cycle production from the data set is to give a representative and meaningful output. Road gradient was investigated as a possible contributor to the difference. The Prius was driven on repeated circuits of the campus to produce a simplified real-world driving cycle that could be directly linked with the corresponding gradients, which were obtained by surveying the land. This cycle was run on the chassis dynamometer and Autonomie was also used to simulate driving this cycle with and without its gradients. This study showed that gradient had a negligible contribution to fuel consumption of the HEV in the case of a circular route where returning to the start point. A main factor in the difference to real-world driving was found to be the use of climate control auxiliaries with associated ambient temperature. Investigation found this element is estimated to contribute over 15% to the difference in real-world fuel consumption, by running the heater in low temperatures and the air conditioning in high temperatures. This leaves a 6% remainder made up of a collection of other small real-world factors. Equivalent tests carried out in simulations to those carried out on the chassis dynamometer gave 20% lower fuel consumption. This is accounted for by degradation of the test vehicle at approximately 7%, and the other part by inaccuracy of the simulation model. Laboratory testing of the high voltage battery pack found it constituted around 2% of the vehicle degradation factor, plus an additional 5% due to imbalance of the battery cell voltages, on top of the 7% stated above. From this investigation it can be concluded that the driving cycle and environment have a substantial impact of the energy use of a HEV. Therefore they could be better designed by incorporating real-world driving into the development process, for example by basing control strategies on real-world drive cycles. Vehicles would also benefit from being developed for use in a particular application to improve their fuel consumption. Alternatively, factors for each of the contributing elements of real-world driving could be included in published fuel economy figures to give prospective users more representative values.

Natürliches Verhalten findet in diversen sensorischen und motorischen Modalitäten statt, und hängt vom sensorischen Feedback ab, welches das Verhalten kontinuierlich anpasst. Um die zu Grunde liegenden neuronalen Korrelate natürlichen Verhaltens untersuchen zu können, ist die Nutzung moderner Aufnahmetechniken notwendig, die oft die Kopffixierung des Tieres erfordern. Diese Einschränkung wurde mit verschiedenen Methoden angegangen, unter anderem mit virtueller Realität in Kombination mit einem luftgelagerten Ball oder Laufradsystemen. Diese Systeme haben jedoch zahlreiche Nachteile. Wir haben das Air-Track-System entwickelt, eine neue Methode für eine leicht zu bauende und nur minimale Computerverarbeitung erfordernde Verhaltensumgebung. Der Air-Track ist ein leichtgewichtiges physisches Labyrinth, das auf einem Lufttisch schwebt und alle Eigenschaften der "echten" Welt hat, einschließlich mehrerer sensorischer Modalitäten, die eng an die motorischen Handlungen gekoppelt sind. Um dieses System zu testen, trainierten wir Mäuse in Go/No-Go- und two-alternative forced choice-Aufgaben. Mäuse wählten Arme und unterschieden. Ein Kamerasystem mit eigens entwickelter Kontrolle zeichnete die Position des Tieres auf und generierte Daten, die zur Berechnung von Reaktionszeiten in den visuellen und somatosensorischen Unterscheidungsaufgaben verwendet werden konnten. Um die Bewegung des Air-Track-Systems aufzuzeichnen, entwickelten wir ein "Pixy"-System zur Bewegungsverfolgung. Wir erweiterten die Entwicklung dann zu einer allgemeinen und automatisierten optischen Methode für die Echtzeit- ebenso wie die nachträgliche Verfolgung der Mausbewegungen, und zwar sowohl für kopffixierte als auch frei bewegliche Tiere. Das Air-Track-System und die Pixy-Bewegungsverfolgung sind zweckdienliche Einheitslösungen, die die Kombination von quantitativem natürlichen Verhalten mit nahezu jedem System zur Aufzeichnung und Manipulation der Hirnaktivität in einem Hirnforschungs-Labor ermöglichen. / Natural behavior occurs in multiple sensory and motor modalities and is dependent on sensory feedback that constantly adjusts behavior. To investigate the underlying neuronal correlates of natural behavior, it is useful to have access to state-of-the-art recording equipment that frequently requires head-fixation. This limitation has been addressed with various approaches such as virtual reality with air ball or treadmill systems. However, these systems have several disadvantages. Here we developed a novel tool, the Air-Track system, an easy to build, head-fixed behavioral environment that requires only minimal computational processing. The Air-Track is a lightweight, physical maze floating on an air table that has all the properties of the “real” world, including multiple sensory modalities tightly coupled to motor actions. To test this system, we trained mice in Go/No-Go and two-alternative forced choice tasks. A custom-controlled camera system monitored animal location, and generated data that could be used to calculate reaction times in the visual and somatosensory discrimination tasks. To track the motion of the Air Track system we developed a “Pixy” tracking system based on an off-the-shelf camera system (Pixy). We then expanded the development into a generalized and automated optical method for real-time and post-hoc tracking of mice motor behavior in both head-fixed and freely moving conditions. Air-Track and Pixy-Tracking systems are convenient “one-size-fits-all” solutions that facilitate the combination of quantitative natural behavior with virtually any system for monitoring or manipulating brain activity in a neuroscience laboratory.

Estimation of Distribution Algorithm (EDA) is a branch of evolutionary computation that learn a probabilistic model of good solutions. Probabilistic models are used to represent relationships between solution variables which may give useful, human-understandable insights into real-world problems. Also, developing an effective PM has been shown to significantly reduce function evaluations needed to reach good solutions. This is also useful for real-world problems because their representations are often complex needing more computation to arrive at good solutions. In particular, many real-world problems are naturally represented as permutations and have expensive evaluation functions. EDAs can, however, be computationally expensive when models are too complex. There has therefore been much recent work on developing suitable EDAs for permutation representation. EDAs can now produce state-of-the-art performance on some permutation benchmark problems. However, models are still complex and computationally expensive making them hard to apply to real-world problems. This study investigates some limitations of EDAs in solving permutation and scheduling problems. The focus of this thesis is on addressing redundancies in the Random Key representation, preserving diversity in EDA, simplifying the complexity attributed to the use of multiple local improvement procedures and transferring knowledge from solving a benchmark project scheduling problem to a similar real-world problem. In this thesis, we achieve state-of-the-art performance on the Permutation Flowshop Scheduling Problem benchmarks as well as significantly reducing both the computational effort required to build the probabilistic model and the number of function evaluations. We also achieve competitive results on project scheduling benchmarks. Methods adapted for solving a real-world project scheduling problem presents significant improvements.

文化的重要性，巳躍居為國家戰略級的地位。兩岸政府都將文化創意產業的發展列入下一波的新興產業，期許它能成為推動下一波經濟的新引擎。然而，文創產業除了強調文化在地性之價值，更重視與國際接軌，才有機會跨越國界，創造出如韓劇《大長今》遍及全球60國家的900億新台幣的週邊效益（超越750萬台EeePC的產值）。 八十年代起，各國政府對媒體解除管制，及新科技的推波助瀾，美國電視集團紛紛前進海外市場佈局。本研究針對Discovery傳播集團如何建立全球品牌，在國際化的過程將節目及行銷依不同市場選擇不同的在地化策略，最終將紀實影片的利基市場，從美國擴大到歐洲、亞洲、拉丁美洲等國際市場，成為全球性的紀實娛樂頻道的領導品牌。 Discovery傳播集團因其知識性與教育性的內容，天生具備「政府友善」(Government Friendly)的特質，迅速在美國成長。但其國際化初期，因節目版權、各國政府法令限制在地製作內容的比例、觀眾偏好不同等挑戰，進而推出尋求在地人才製作在地節目的《新銳導演計畫》，並舉辦紀實影片研討會廣納人才。隨後又與BBC合作推出大成本、大製作的紀實影片，推出「與世界同步觀賞」的世界級節目，建立全球一致的品牌形象。過程中，Discovery累積並發展出其核心能力，並複製到其他市場，是最終建立其全球品牌價值、優勢、及持續成長的重要關鍵。 透過四個個案的分析－《流言終結者》、《新銳導演計畫》、《聖母峰：攀越巔峰》及《瘋台灣》，探討Discovery「節目與行銷」vs.「標準化及在地化」四種策略的成效，進一步確認「在地化」因子，在國際化過程極為重要的關鍵。「在地化」架構一個平台，讓在地的觀眾、媒體、廣告主、政府能有進一步參與的角色，並達成以5R的綜效（Local Relevant、Rating、Relationship、Revenue、Recognition）。 關鍵詞：國際化、標準化與在地化、紀實娛樂、Discovery頻道。 / The huge success of Cool Britannia, Korean drama & K-pop, cultural and creative industries, aka soft power, are considered key drivers in booting economic growth by Taiwan & Mainland China governments. The key factor behind this success is internationalizing the unique local culture. The objective of this study is to reveal the internationalization history, the factor & the formula behind the World’s number one real-world entertainment media - Discovery Communications Inc. What challenges did Discovery confronted back to early 90s, and what competence the company built up through limited resources over the past 27 years, and how it adopted the success formula from Europe to Asia and make Discovery a global brand. The research analyzes four cases which include Mythbusters, First Time Filmmakers, Everest and Fun Taiwan by the framework of standardization and localization vs. programming & marketing. Through the process, this work reveals the key successful factor is localization either in programing or marketing. Therefore it creates a local-friendly platform to further engage local partners- viewer, advertiser, media & government to take part in and achieve a multi-purposes success – the 5R synergy- Local Relevant, Rating, Relationship, Recognition & Revenue. Key words: internationalization, Discovery Channel, real-world entertainment, standardization & localization

A wireless ad hoc network consists of a number of mobile nodes that temporarily form a dynamic infrastructure-less network. New routing protocols that can adapt to the frequent topology changes induced by node mobility and varying link qualities are needed. During the last decade dozens of different ad hoc routing protocols have been proposed, optimized and partially compared, mainly through simulation studies. This thesis takes an experimental approach to the evaluation of ad hoc routing protocols. We argue that real world experiments are needed in order to complement simulation studies, and to gain practical experience and insights that can provide feedback to routing protocol design and existing simulation models. For example, we discovered a performance discrepancy for the AODV protocol between real world experiments and corresponding simulation studies. This so called ``communication gray zone'' problem was explored and countermeasures were implemented. As a result we could eliminate this performance problem to a large extent. We have implemented a software-based testbed called APE to carry out efficient and systematic experimental evaluation of ad hoc routing protocols. Experiments with up to 37 participating ad hoc nodes have demonstrated APE's ability to scale efficiently and assess repeatability between test runs. APE is part of our methodology for test repeatability in a real world ad hoc routing protocol testbed. It addresses the repeatability issue induced by stochastic factors like the radio environment and node mobility. Using APE, we have performed a systematic experimental evaluation of three ad hoc routing protocols (AODV, OLSR and LUNAR). Our results show that TCP does not work satisfactorily even in very small networks with limited mobility.

The concept of function is crucial to a great extent in modern mathematics and is considered a major barrier to many mathematics students. Students have difficulty interpreting information related to functions in general, and quadratic functions in particular. Quadratic Function is one of the topics which are covered in a course which is compulsory for a large number of students in the General Education Program of Zayed University. This program leads to different majors, including Mathematics Education, Business, Information Technology, and other majors. The challenge in teaching Quadratic Function in a course like this is mostly based on the fact that many students think that Quadratic Function is a difficult topic to understand and learn, and some teachers would agree with them that it is difficult to teach. In this paper, I demonstrate real world problems aimed to improve the students understanding of Quadratic Functions; life problems on this topic support developing student’s knowledge, critical thinking, quantitative reasoning, and analytical skills. This paper also includes examples of the techniques used with graphing of quadratic function, the algebra, and inverses of the same function. International move to improve mathematics curriculum have supported new goals for student’s learning which highlights problem solving skills, reasoning, ability to work in groups and individually, and use of technology. Knowing that information technology plays considerable role in achieving the above goals, teaching students the concept of Quadratic Functions can be smoothly achieved by using Information Technology in solving real world problems.

La sécurité et le confort dans une tâche de conduite automobile sont des facteurs clés qui intéressent plusieurs acteurs (constructeurs, urbanistes, départements de transport), en particulier dans le contexte actuel d’urbanisation croissante. Il devient dès lors crucial d'évaluer l'état affectif du conducteur lors de la conduite, en particulier son niveau de stress qui influe sur sa prise de décision et donc sur ses performances de conduite. Dans cette thèse, nous nous concentrons sur l'étude des changements de niveau de stress ressenti durant une expérience de conduite réelle qui alterne ville, autoroute et repos. Les méthodes classiques sont basées sur des descripteurs proposés par des experts, appliquées sur des signaux physiologiques. Ces signaux sont prétraités, les descripteurs ad-hoc sont extraits et sont fusionnés par la suite pour reconnaître le niveau de stress. Dans ce travail, nous avons adapté une méthode de sélection de variables fonctionnelles, basée sur les forêts aléatoires, avec élimination récursive des descripteurs (RF-RFE). En effet, les biosignaux, considérés comme variables fonctionnelles, sont tout d’abord projetés sur une base d’ondelettes. L’algorithme RF-RFE est ensuite utilisé pour sélectionner les groupes d’ondelettes, correspondant aux variables fonctionnelles, selon un score d’endurance. Le choix final de ces variables est basé sur ce score proposé afin de quantifier la capacité d’une variable à être sélectionnée et dans les premiers rangs. Dans une première étape, nous avons analysé la fréquence cardiaque (HR), électromyogramme (EMG), fréquence respiratoire (BR) et activité électrodermale (EDA), issus de 10 expériences de conduite menées à Boston, de la base de données du MIT, drivedb. Dans une seconde étape, nous avons conduit 13 expériences in-vivo similaires, en alternant conduite dans la ville et sur autoroute dans la région de Grand Tunis. La base de données résultante, AffectiveROAD contient -comme dans drivedb- les biosignaux tels que le HR, BR, EDA mais aussi la posture. Le prototype de plateforme de réseau de capteurs développé, a permis de collecter des données environnementales à l’intérieur du véhicule (température, humidité, pression, niveau sonore et GPS) qui sont également inclues dans AffectiveROAD. Une métrique subjective de stress, basée sur l’annotation d’un observateur et validée a posteriori par le conducteur au vu des enregistrements vidéo acquis lors de l’expérience de conduite, complète cette base de données. Nous définissons ici la notion de stress par ce qui résume excitation, attention, charge mentale, perception de complexité de l'environnement par le conducteur. La sélection de variables fonctionnelles dans le cas de drivedb a révélé que l'EDA mesurée au pied est l'indicateur le plus révélateur du niveau de stress du conducteur, suivi de la fréquence respiratoire. La méthode RF-RFE associée à des descripteurs non experts, conduit à des performances comparables à celles obtenues par la méthode basée sur les descripteurs sélectionnés par les experts. En analysant les données d’AffectiveROAD, la posture et l’EDA mesurée sur le poignet droit du conducteur ont émergé comme les variables les plus pertinentes. Une analyse plus approfondie de l'EDA a par la suite été menée car ce signal a été retenu, pour les deux bases de données, parmi les variables fonctionnelles sélectionnées pour la reconnaissance du niveau de stress. Ceci est cohérent avec diverses études sur la physiologie humaine qui voient l’EDA comme un indicateur clé des émotions. Nous avons ainsi exploré le caractère fractal de ce biosignal à travers une analyse d'auto-similarité et une estimation de l'exposant de Hurst basée sur les ondelettes. L'analyse montre un comportement d’auto-similarité des enregistrements de l'EDA pour les deux bases de données, sur une large gamme d’échelles. Ceci en fait un indicateur potentiel temps réel du stress du conducteur durant une expérience de conduite réelle. / The safety and comfort in a driving task are key factors of interest to several actors (vehicle manufacturers, urban space designers, and transportation service providers), especially in a context of an increasing urbanization. It is thus crucial to assess the driver’s affective state while driving, in particular his state of stress which impacts the decision making and thus driving task performance. In this thesis, we focus on the study of stress level changes, during real-world driving, experienced in city versus highway areas. Classical methods are based on features selected by experts, applied to physiological signals. These signals are preprocessed using specific tools for each signal, then ad-hoc features are extracted and finally a data fusion for stress-level recognition is performed. In this work, we adapted a functional variable selection method, based on Random Forests Recursive Feature Elimination (RF-RFE). In fact, the biosignals considered as functional variables, are first decomposed using wavelet basis. The RF-RFE algorithms are then used to select groups of wavelets coefficients, corresponding to the functional variables, according to an endurance score. The final choice of the selected variables relies on this proposed score that allows to quantify the ability of a variable to be selected and this, in first ranges. At a first stage, we analyzed physiological signals such as: Heart Rate (HR), Electromyogram (EMG), Breathing Rate (BR), and the Electrodermal Activity (EDA), related to 10 driving experiments, extracted from the open database of MIT: drivedb, carried out in Boston area. At a second stage, we have designed and conducted similar city and highway driving experiments in the greater Tunis area. The resulting database, AffectiveROAD, includes, as in drivedb, biosignals as HR, BR and EDA and additional measurement of the driver posture. The developed prototype of the sensors network platform allowed also to gather data characterizing the vehicle internal environment (temperature, humidity, pressure, sound level, and geographical coordinates) which are included in AffectiveROAD database. A subjective stress metric, based on driver video-based validation of the observer’s annotation, is included in AffectiveROAD database. We define here the term stress as the human affective state, including affect arousal, attention, mental workload, and the driver’s perception of the environment complexity. The functional variable selection, applied to drivedb, revealed that the EDA captured on foot followed by the BR, are relevant in the driver’s stress level classification. The RF-RFE method along with non-expert based features offered comparable performances to those obtained by the classical method. When analyzing the AffectiveROAD data, the posture and the EDA captured on the driver’s right wrist emerged as the most enduring variables. For both databases, the placement of the EDA sensor came out as an important consideration in the stress level assessment. A deeper analysis of the EDA was carried out since its emergence as a key indicator in stress level recognition, for the two databases. This is consistent with various human physiology studies reporting that the EDA is a key indicator of emotions. For that, we investigated the fractal properties of this biosignal using a self-similarity analysis of EDA measurements based on Hurst exponent (H) estimated using wavelet-based method. Such study shows that EDA recordings exhibits self-similar behavior for large scales, for the both databases. This proposes that it can be considered as a potential real-time indicator of stress in real-world driving experience.

Proton pump inhibitors (PPIs) are commonly coadministered with clopidogrel, an antiplatelet agent, to patients with acute coronary syndrome (ACS). Mechanistic studies suggest that PPIs have the potential to competitively inhibit the bioactivation of clopidogrel and may attenuate its antiplatelet action in the body. The clinical implications of this drug-drug interaction have been extensively studied; however reported findings are inconsistent. More recently, several studies have questioned whether PPIs are associated with adverse cardiovascular events independent of clopidogrel. Given that PPIs and clopidogrel are widely used, it is critical to better understand the clinical impact of the concomitant treatment with both drugs. This thesis includes four studies that investigate the clinical effects of the drug-drug interaction between clopidogrel and PPIs. Chapter 2, a systematic review and meta-analysis, summarizes findings from 118 studies. Findings do not provide strong evidence for an association between adverse cardiovascular events and the use of PPIs when used alone, in combination with clopidogrel, or in combination with other antiplatelets. Chapters 3, 4, and 5 present analyses of real-world data comprised of electronic medical records. Results of these analyses demonstrate 1) that the concomitant use of clopidogrel and PPIs among inpatients was consistent with clinical guidelines suggested by the FDA (Chapter 3); 2) a lack of association between PPI use vs nonuse and four adverse cardiovascular outcomes among clopidogrel users (Chapter 4); and 3) a lack of association between PPI use vs nonuse and adverse cardiovascular outcomes among prasugrel users or ticagrelor users (Chapter 5). Collectively, our findings do not provide evidence of an elevated risk of adverse cardiovascular outcomes with the combined use of PPIs and clopidogrel. Although pharmacodynamic and pharmacokinetic studies have demonstrated an interaction between these two drugs, our findings support the opinion that the biological interaction does not translate into adverse clinical events among patients with acute coronary syndrome.