Denver Union Station Multimodal Public Transportation Facility & Mixed-Use Development

Denver is quickly becoming the ?Grand Central Station? for transportation for the Western United States. Since the turn of the century Union Station, located on the edge of downtown Denver, has been used as the railroad gateway to the Rocky Mountains. More recently, with the addition of the Denver International Airport (DIA), Denver is being recognized as a major hub for air transportation servicing the Western United States. The city is projecting a population growth of almost one million people within the next 20 to 25 years. With this in mind, Denver?s public transportation provider, Regional Transportation District (RTD), needs to expand their current system in order to meet future demand. For years Union Station has been the main railway station servicing the Rocky Mountains and the west coast. It was recently placed on the National Historic Register and purchased by RTD. It sits on a 19.5-acre parcel of land in the historic district adjacent to downtown Denver making it a prime location for a regional transit facility. This facility will seamlessly accommodate rail, bus, auto, pedestrian and bicycle movement throughout the area and provide space for transit-oriented retail. The focus of this thesis project is to respectfully incorporate the historic Union Station building into the design of a state-of-the-art mixed transit facility that would accommodate the growing needs of Denver and the surrounding area. The main intentions for this facility are to provide easier access to various means of public transportation for residents, commuters and tourists and create a positive awareness for more efficient means of transportation. The underlying premise for this design is that transportation is an essential part of urban life and allows for growth and development within a city. Without a well-planned transportation system, a city would not be able to function on its own

Introducing the Mosaic of Integration Theory

This introductory chapter of the third edition of European Integration Theory (OUP 2018) addresses the rationale for a book on European integration theory and introduces the contributions to the book. It begins by addressing the question of Why Study Integration Theory; it then defines the terms ‘integration’ and ‘theory’ and introduces the ‘mosaic of European integration theory’ as the book’s central concept. The chapter also offers an overview of European integration as a process which has been studied for several decades now. To that end, the chapter recalls distinct phases of integration and the respective parts of the mosaic which have been developed to understand and explain them based on descriptive, analytical and constructive theorising. Each phase is distinguished by historical context, leading questions and relevant theoretical reference points. The book’s extensive section on Studying European Integration by taking account of ‘contexts of theoretical development’ and addressing the question of ‘competing or complementary theoretical approaches’ which also identifies the functions and areas of theory. In concluding, the chapter details the concept of the ‘Mosaic of Integration Theory’ and introduces the chapter structure of the book’s contributions

Impairment in active navigation from trauma and Post-Traumatic Stress Disorder.

The study investigated the impact of trauma exposure and of Post-Traumatic Stress Disorder (PTSD) on spatial processing and active navigation in a sample (n = 138) comprising civilians (n = 91), police officers (n = 22) and veterans (n = 27). Individuals with previous trauma exposure exhibited significantly poorer hippocampal-dependent (allocentric) navigation performance on active navigation in a virtual environment (the Alternative Route task) regardless of whether or not they had PTSD (scoring above 20 on the PTSD Diagnostic Scale). No performance differences were found in static perspective taking (the Four Mountains task). Moreover, an associative information processing bias in those with PTSD interfered with ability to use hippocampal-dependent processing in active navigation. This study provides new evidence of impaired active navigation in individuals with trauma exposure and highlights the importance of considering the relationship between trauma and spatial processing in clinical and occupational settings

The Impact of the Brain-Derived Neurotrophic Factor Gene on Trauma and Spatial Processing.

The influence of genes and the environment on the development of Post-Traumatic Stress Disorder (PTSD) continues to motivate neuropsychological research, with one consistent focus being the Brain-Derived Neurotrophic Factor (BDNF) gene, given its impact on the integrity of the hippocampal memory system. Research into human navigation also considers the BDNF gene in relation to hippocampal dependent spatial processing. This speculative paper brings together trauma and spatial processing for the first time and presents exploratory research into their interactions with BDNF. We propose that quantifying the impact of BDNF on trauma and spatial processing is critical and may well explain individual differences in clinical trauma treatment outcomes and in navigation performance. Research has already shown that the BDNF gene influences PTSD severity and prevalence as well as navigation behaviour. However, more data are required to demonstrate the precise hippocampal dependent processing mechanisms behind these influences in different populations and environmental conditions. This paper provides insight from recent studies and calls for further research into the relationship between allocentric processing, trauma processing and BDNF. We argue that research into these neural mechanisms could transform PTSD clinical practice and professional support for individuals in trauma-exposing occupations such as emergency response, law enforcement and the military

Cross-Modal Health State Estimation

Individuals create and consume more diverse data about themselves today than any time in history. Sources of this data include wearable devices, images, social media, geospatial information and more. A tremendous opportunity rests within cross-modal data analysis that leverages existing domain knowledge methods to understand and guide human health. Especially in chronic diseases, current medical practice uses a combination of sparse hospital based biological metrics (blood tests, expensive imaging, etc.) to understand the evolving health status of an individual. Future health systems must integrate data created at the individual level to better understand health status perpetually, especially in a cybernetic framework. In this work we fuse multiple user created and open source data streams along with established biomedical domain knowledge to give two types of quantitative state estimates of cardiovascular health. First, we use wearable devices to calculate cardiorespiratory fitness (CRF), a known quantitative leading predictor of heart disease which is not routinely collected in clinical settings. Second, we estimate inherent genetic traits, living environmental risks, circadian rhythm, and biological metrics from a diverse dataset. Our experimental results on 24 subjects demonstrate how multi-modal data can provide personalized health insight. Understanding the dynamic nature of health status will pave the way for better health based recommendation engines, better clinical decision making and positive lifestyle changes.Comment: Accepted to ACM Multimedia 2018 Conference - Brave New Ideas, Seoul, Korea, ACM ISBN 978-1-4503-5665-7/18/1

The impact of cockpit automation on crew coordination and communication. Volume 1: Overview, LOFT evaluations, error severity, and questionnaire data

The purpose was to examine, jointly, cockpit automation and social processes. Automation was varied by the choice of two radically different versions of the DC-9 series aircraft, the traditional DC-9-30, and the glass cockpit derivative, the MD-88. Airline pilot volunteers flew a mission in the simulator for these aircraft. Results show that the performance differences between the crews of the two aircraft were generally small, but where there were differences, they favored the DC-9. There were no criteria on which the MD-88 crews performed better than the DC-9 crews. Furthermore, DC-9 crews rated their own workload as lower than did the MD-88 pilots. There were no significant differences between the two aircraft types with respect to the severity of errors committed during the Line-Oriented Flight Training (LOFT) flight. The attitude questionnaires provided some interesting insights, but failed to distinguish between DC-9 and MD-88 crews

Challenges for identifying the neural mechanisms that support spatial navigation: the impact of spatial scale.

Spatial navigation is a fascinating behavior that is essential for our everyday lives. It involves nearly all sensory systems, it requires numerous parallel computations, and it engages multiple memory systems. One of the key problems in this field pertains to the question of reference frames: spatial information such as direction or distance can be coded egocentrically-relative to an observer-or allocentrically-in a reference frame independent of the observer. While many studies have associated striatal and parietal circuits with egocentric coding and entorhinal/hippocampal circuits with allocentric coding, this strict dissociation is not in line with a growing body of experimental data. In this review, we discuss some of the problems that can arise when studying the neural mechanisms that are presumed to support different spatial reference frames. We argue that the scale of space in which a navigation task takes place plays a crucial role in determining the processes that are being recruited. This has important implications, particularly for the inferences that can be made from animal studies in small scale space about the neural mechanisms supporting human spatial navigation in large (environmental) spaces. Furthermore, we argue that many of the commonly used tasks to study spatial navigation and the underlying neuronal mechanisms involve different types of reference frames, which can complicate the interpretation of neurophysiological data

Automata Learning with an Incomplete Teacher (Artifact)

We provide an implementation of the automata learning software described in the associated ECOOP article. In particular, the artifact is a Docker image with the source code for nerode and nerode-learn, along with the scripts and benchmark inputs needed to reproduce the experiments described in the paper

Neutron diffraction reveals sequence-specific membrane insertion of pre-fibrillar islet amyloid polypeptide and inhibition by rifampicin

AbstractHuman islet amyloid polypeptide (hIAPP) forms amyloid deposits in non-insulin-dependent diabetes mellitus (NIDDM). Pre-fibrillar hIAPP oligomers (in contrast to monomeric IAPP or mature fibrils) increase membrane permeability, suggesting an important role in the disease. In the first structural study of membrane-associated hIAPP, lamellar neutron diffraction shows that oligomeric hIAPP inserts into phospholipid bilayers, and extends across the membrane. Rifampicin, which inhibits hIAPP-induced membrane permeabilisation in functional studies, prevents membrane insertion. In contrast, rat IAPP (84% identical to hIAPP, but non-amyloidogenic) does not insert into bilayers. Our findings are consistent with the hypothesis that membrane-active pre-fibrillar hIAPP oligomers insert into beta cell membranes in NIDDM