Making Bicycling Comfortable: Identifying Minimum Infrastructure Needs by Population Segments Using a Video Survey

In this study, researchers use survey data to analyze bicycling comfort and its relationship with socio-demographics, bicycling attitudes, and bicycling behavior. An existing survey of students, faculty, and staff at UC Davis (n=3089) who rated video clips of bicycling environments based on their perceived comfort as a part of the UC Davis annual Campus Travel Survey (CTS) is used. The video clips come from a variety of urban and semi-rural roads (designated California state highways) around the San Francisco Bay Area where bicycling rates vary. Results indicate considerable effects of socio-demographics and attitudes on absolute video ratings, but relative agreement about which videos are most comfortable and uncomfortable across population segments. In addition, presence of bike infrastructure and low speed roads are the strongest video factors generating more comfortable ratings. However, the results suggest that even the best designed on-road bike facilities are unlikely to provide a comfortable bicycling environment for those without a predisposition to bicycle. This suggests that protected and separated bike facilities may be required for many people to consider bicycling. Nonetheless, the results provide guidance for improving roads with on-street bike facilities where protected or separated facilities may not be suitable.View the NCST Project Webpag

Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning

Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which has been hampered by our inability to monitor serotonin release and transport with high spatial and temporal resolution. We developed and applied a binding-pocket redesign strategy, guided by machine learning, to create a high-performance, soluble, fluorescent serotonin sensor (iSeroSnFR), enabling optical detection of millisecond-scale serotonin transients. We demonstrate that iSeroSnFR can be used to detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep/wake transitions. We also developed a robust assay of serotonin transporter function and modulation by drugs. We expect that both machine-learning-guided binding-pocket redesign and iSeroSnFR will have broad utility for the development of other sensors and in vitro and in vivo serotonin detection, respectively

Reduced Degeneracy Statistics for Exponential-family Random Graph Models and Latent Space Network Models for Rating

With a rise in the amount of network data comes increased need for flexible and interpretable network models. Exponential-family random graph models (ERGM) are widely used to analyze small- to medium-sized networks, but suffer from model degeneracy which detracts from their application. In Part I of this dissertation we address this problem by developing novel statistics for ERGM. We focus on the modeling of transitivity in networks as it is a key feature of many real-world networks, but most attempts to account for it within ERGM have induced model degeneracy. The statistics we propose combine the strategies of the transformed statistics proposed by Horvat et al. (2015) and the regularized statistics proposed by Fellows (2012b). They include statistics to capture transitivity, clustering, and a new class of moment statistics to improve goodness of fit. We characterize our newly introduced statistics along with those of Horvat et al. (2015) and Fellows (2012a) using recent theoretical developments regarding ERGM degeneracy. We also compare them theoretically and in practice to the geometrically weighted statistics of Snijders et al. (2006) that are currently the most commonly used to model transitivity in ERGM.In Part II of this dissertation we develop models to rate and rank items based on network data, and demonstrate many advantageous properties of these models. The impetus for this work came from research on ranking statistics journals by Varin et al. (2016). They present a quasi-Stigler model that is a great improvement over the commonly used but statistically indefensible Impact Factor, especially in the quantification of ratings uncertainty. However, the quasi-Stigler model does not fully leverage the network structure of the data and underestimates uncertainty. In addition to applying latent space models to the network rating problem, we identify a fast computational method for fitting the models. We also develop a new latent network model that leverages the symmetric and asymmetric patterns in directed relational data. This model has many potential applications beyond item rating

Evolution and Ecology of Urban Pigeons (Columba livia) in Northeastern North America

Urbanization is drastically changing landscapes across the globe leading to changes in the ecological and evolutionary dynamics within cities. This urban landscape change may restrict, facilitate, or have no effect on gene flow, depending on the organism and extent of urbanization. In human commensals, with high dispersal ability, urbanization can facilitate gene flow by providing continuous suitable habitat across a wide range. Additionally, suburban or rural areas with lower human population density may act as a barrier to gene flow for these human commensals. Spatial population genetic approaches provide a means to understand genetic connectivity across geographically expansive areas that encompass multiple metropolitan areas. Here, I examined the spatial genetic patterns of feral pigeons (Columba livia) living in cities in the Northeastern United States. I focused my sampling on the Northeastern megacity, which is a region covering six large cities (Boston, Providence, New York City, Philadelphia, Baltimore, and Washington, DC). I performed ddRAD‐Seq on 473 samples. My analysis detected higher‐than‐expected gene flow under an isolation by distance model within each city. I conclude that the extreme urbanization characteristic of the Northeastern megacity is likely facilitating gene flow in pigeons. Additionally, spatial genetic patterns may diverge between cities as food accessibility, nesting site availability, and eradication policies differ. Pigeon hobbyists (people who collect, breed, trade, and race pigeons) also vary by region leading to differing degrees of public tolerance for pigeons and impacting the spatial genetic patterns. Fancy and racing pigeons display a variety of characters which are often seen in the feral population, suggesting that these breeds may partially contribute to feral populations. I found that pigeon population structure is influenced by continued introduction of racing/fancy pigeons and the local conditions including attitudes towards pigeons, management practices, and food availability. Furthermore, variation in behavioral traits is especially important in novel habitats where selection forces determine successful colonizers. Prey species must constantly balance the risk versus reward of remaining in an area with threats while gaining possible fitness benefits. Flight initiation distance, the distance at which an animal flees when approached by a human, is a common metric used to assess habituation to stressors and risk behavior. I examined the flight initiation distance of pigeons across New York City, USA. I then assessed this behavioral response across the landscape with respect to multiple urbanization factors related to human activity, the abiotic environment, and the ecological community. I found that flight initiation distance in pigeons decreased with increased human activity demonstrating that pigeon behavior varies with urbanization, human activity, and ecological attributes. Since behavioral changes are often the most rapid phenotypic response to change, this study demonstrates that pigeons are responding to anthropogenic stressors, which may set the stage for adaptive changes. Overall this research demonstrates that urban landscape heterogeneity may contribute to variable spatial genetic and behavioral responses across a single city, therefore researchers must examine patters at different spatial scales. Moreover, organisms such as pigeons that depend on humans, exhibit fine-scale spatial genetic structure that reflects human patterns and distributions, stressing the importance of sampling across urban areas

Making Bicycling Comfortable: Identifying Minimum Infrastructure Needs by Population Segments Using a Video Survey

In this study, researchers use survey data to analyze bicycling comfort and its relationship with socio-demographics, bicycling attitudes, and bicycling behavior. An existing survey of students, faculty, and staff at UC Davis (n=3089) who rated video clips of bicycling environments based on their perceived comfort as a part of the UC Davis annual Campus Travel Survey (CTS) is used. The video clips come from a variety of urban and semi-rural roads (designated California state highways) around the San Francisco Bay Area where bicycling rates vary. Results indicate considerable effects of socio-demographics and attitudes on absolute video ratings, but relative agreement about which videos are most comfortable and uncomfortable across population segments. In addition, presence of bike infrastructure and low speed roads are the strongest video factors generating more comfortable ratings. However, the results suggest that even the best designed on-road bike facilities are unlikely to provide a comfortable bicycling environment for those without a predisposition to bicycle. This suggests that protected and separated bike facilities may be required for many people to consider bicycling. Nonetheless, the results provide guidance for improving roads with on-street bike facilities where protected or separated facilities may not be suitable.View the NCST Project Webpag

Bike Lanes and Slow Car Speeds Can Improve Bicycling Comfort for Some (But Not All) People

Transportation planners in cities across the country are trying to increase bicycling to achieve mobility, public health, and environmental goals. For bicycling to become a mainstream travel mode, however, riders must feel safe and comfortable in the bicycling environment. Thus, cities are changing transportation infrastructure to provide more bicycling-friendly streets.It remains unclear exactly how much infrastructure change is needed to make potential cyclists feel comfortable enough to bicycle regularly. To better understand what road characteristics contribute to more comfortable bicycling, researchers at UC Davis surveyed 3,089 travelers to the UC Davis campus to measure perceived comfort of bicycling in different road environments using video recordings of 25 urban and rural roads from the San Francisco Bay Area. This policy brief summarizes findings from that research, which provide guidance for communities aiming to increase bicycling.View the NCST Project Webpag

The Four Way Reader #2

“It’s all here: the polished candlesticks, wrapped, unused in the silver closet. The skeleton keys, family portrais, and trantrums of childhood . . . There’s a subversive scribbler named Burdyk, and adventurer, Carlitos. A woman putting on lipstick in a parked car’s side mirror … Our pleasure as editors comes as much from rereading these poems and stories as from gathering them together in the first place. These are works of heft and elegance, ricochet and grace—lively voices ranging widely across subject matter and style.”– Carlen Arnet

Bike Lanes and Slow Car Speeds Can Improve Bicycling Comfort for Some (But Not All) People [Policy Brief]

Caltrans 65A0686 Task Order 006 USDOT Grant 69A355In this study, researchers use survey data to analyze bicycling comfort and its relationship with socio-demographics, bicycling attitudes, and bicycling behavior. An existing survey of students, faculty, and staff at UC Davis (n=3089) who rated video clips of bicycling environments based on their perceived comfort as a part of the UC Davis annual Campus Travel Survey (CTS) is used. The video clips come from a variety of urban and semi-rural roads (designated California state highways) around the San Francisco Bay Area where bicycling rates vary. Results indicate considerable effects of socio-demographics and attitudes on absolute video ratings, but relative agreement about which videos are most comfortable and uncomfortable across population segments. In addition, presence of bike infrastructure and low speed roads are the strongest video factors generating more comfortable ratings. However, the results suggest that even the best designed on-road bike facilities are unlikely to provide a comfortable bicycling environment for those without a predisposition to bicycle. This suggests that protected and separated bike facilities may be required for many people to consider bicycling. Nonetheless, the results provide guidance for improving roads with on-street bike facilities where protected or separated facilities may not be suitable