ToScA North America (6 – 8 June 2017, The University of Texas, Austin, TX) Program

ToScA North America will address key areas of science, including Multi-modal Imaging, Geosciences, Forensics, Increasing Contrast, Educational Outreach, Data, Materials Science and Medical and Biological Science.University of Texas High-Resolution X-ray CT Facility (UTCT); Jackson School of Geosciences, The University of Texas at Austin; Natural History Museum (London); Royal Microscopical Society (Oxford, UK)Geological Science

Public Participation GIS for sustainable urban mobility planning: methods, applications and challenges

Sustainable mobility planning is a new approach to planning, and as such it requires new methods of public participation, data collection and data aggregation. In the article we present an overview of Public Participation GIS (PPGIS) methods with potential use in sustainable urban mobility planning. We present the methods using examples from two recent case studies conducted in Polish cities of Poznań and Łodź. Sustainable urban mobility planning is a cyclical process, and each stage has different data and participatory requirements. Consequently, we situate the PPGIS methods in appropriate stages of planning, based on potential benefits they may bring into the planning process. We discuss key issues related to participant recruitment and provide guidelines for planners interested in implementing methods presented in the paper. The article outlines future research directions stressing the need for systematic case study evaluation

e-mission: an open source, extensible platform for human mobility systems

Transportation is the single largest source of carbon emissions in the US. Decarbonizing it is challenging because it depends on individual behaviors, which in turn, depend on local land use planning. The interdisciplinary field of Computational Mobility, focusing on collecting, analysing and influencing human travel behavior, can frame solutions to this challenge.Innovation flows in interdisciplinary fields are bi-directional. The flow to the domain is focused on building a strong foundation for methodological improvements. As the improvements are deployed, they result in use-inspired computational research. This temporal dependency results in our initial focus on the modularity, accuracy and reproducibility of e-mission, an extensible platform for instrumenting human mobility. This open source platform has a modular architecture that supports power efficient duty cycling using virtual sensors, a read-only data model and a pipeline with novel algorithm adaptations for smartphone sensing.We also perform the first empirical evaluations of smartphone-based platforms in this domain. The architectural evaluation is based on three real world deployments: a classic travel diary, a crowdsourcing initiative, and a behavioral study. The accuracy evaluation is based on an novel procedure that uses artificial trips and multiple parallel phones to mitigate concerns over privacy, context sensitive power consumption and inherent sensing error. Data collected from three artifical timelines was used to evaluate the trajectory, segmentation and classification accuracies vs. power for various configurations.On computational side, challenges derived from the deployments can contribute to ongoing CS research in privacy, trustworthiness, incentivization and decision making. On the mobility side, this enables methodological innovations such as Agile Urban Planning for prototyping infrastructure changes

Emerging privacy challenges and approaches in CAV systems

The growth of Internet-connected devices, Internet-enabled services and Internet of Things systems continues at a rapid pace, and their application to transport systems is heralded as game-changing. Numerous developing CAV (Connected and Autonomous Vehicle) functions, such as traffic planning, optimisation, management, safety-critical and cooperative autonomous driving applications, rely on data from various sources. The efficacy of these functions is highly dependent on the dimensionality, amount and accuracy of the data being shared. It holds, in general, that the greater the amount of data available, the greater the efficacy of the function. However, much of this data is privacy-sensitive, including personal, commercial and research data. Location data and its correlation with identity and temporal data can help infer other personal information, such as home/work locations, age, job, behavioural features, habits, social relationships. This work categorises the emerging privacy challenges and solutions for CAV systems and identifies the knowledge gap for future research, which will minimise and mitigate privacy concerns without hampering the efficacy of the functions

High rate of extrapair paternity in a human population demonstrates diversity in human reproductive strategies.

Among nonhuman species, social monogamy is rarely accompanied by complete fidelity. Evolutionary theory predicts that the rate of extrapair paternity (EPP) should vary according to socioecological conditions. In humans, however, geneticists contend that EPP is negligible and relatively invariable. This conclusion is based on a limited set of studies, almost all of which describe European-descent groups. Using a novel, double-blind method designed in collaboration with a community of Himba pastoralists, we find that the rate of EPP in this population is 48%, with 70% of couples having at least one EPP child. Both men and women were very accurate at detecting cases of EPP. These data suggest that the range of variation in EPP across human populations is substantially greater than previously thought. We further show that a high rate of EPP can be accompanied by high paternity confidence, which highlights the importance of disaggregating EPP from the notion of "cuckoldry.

Relationship between spatial proximity and travel-to-work distance : the effect of the compact city

In this paper, an assessment is made of the relationship between selected aspects of spatial proximity (density, diversity, minimum commuting distance, jobs-housing balance and job accessibility) and reported commuting distances in Flanders (Belgium). Results show that correlations may depend on the considered trip end. For example, a high residential density, a high degree of spatial diversity and a high level of job accessibility are all associated with a short commute by residents, while a high job density is associated with a long commute by employees. A jobs-housing balance close to one is associated with a short commute, both by residents and by employees. In general, it appears that the alleged sustainability benefits of the compact city model are still valid in a context of continuously expanding commuting trip lengths