The Cultural Politics of Homeland Security: Negotiating Muslim Identities After Sept. 11

The University Archives has determined that this item is of continuing value to OSU's history.This project is motivated by the premise that the experience of the Muslims in the U.S. after 9/11 can profoundly affect the effectiveness of U.S. homeland security policies and measures in the long run. The project seeks to understand how Muslim identities are negotiated in the especially hostile environment in the U.S. after 9/11, and how individual and community predicaments involved in such negotiations can be destabilizing without being properly understood and addressed at the level of national politics.Mershon Center for International Security Studiesproject summar

Understanding Racial Disparities in Exposure to Traffic-Related Air Pollution: Considering the Spatiotemporal Dynamics of Population Distribution

This study investigates the effect of spatiotemporal distributions of racial groups on disparities in exposure to traffic-related air pollution by considering people’s daily movement patterns. Due to human mobility, a residential neighborhood does not fully represent the true geographic context in which people experience racial segregation and unequal exposure to air pollution. Using travel-activity survey data containing individuals’ activity locations and time spent at each location, this study measures segregation levels that an individual might experience during the daytime and nighttime, estimates personal exposure by integrating hourly pollution maps and the survey data, and examines the association between daytime/nighttime segregation and exposure levels. The proximity of each activity location to major roads is also evaluated to further examine the unequal exposure. The results reveal that people are more integrated for work in high-traffic areas, which contributes to similarly high levels of exposure for all racial groups during the daytime. However, white people benefit from living in suburbs/exurbs away from busy roads. The finding suggests that policies for building an extensive and equitable public transit system should be implemented together with the policies for residential mixes among racial groups to reduce everyone’s exposure to traffic-related air pollution and achieve environmental justice

Natural environments and suicide mortality in the Netherlands: a cross-sectional, ecological study

Background: Natural outdoor environments, such as green spaces (ie, grass, forests, or parks), blue spaces (ie, visible bodies of fresh or salt water), and coastal proximity, have been increasingly shown to promote mental health. However, little is known about how and the extent to which these natural environments are associated with suicide mortality. Our aim was to investigate whether the availability of green space and blue space within people's living environments and living next to the coast are protective against suicide mortality. Methods: In this cross-sectional, ecological study, we analysed officially confirmed deaths by suicide between 2005 and 2014 per municipality in the Netherlands. We calculated indexes to measure the proportion of green space and blue space per municipality and the coastal proximity of each municipality using a geographical information system. We fitted Bayesian hierarchical Poisson regressions to assess associations between suicide risk, green space, blue space, and coastal proximity, adjusted for risk and protective factors. Findings: Municipalities with a large proportion of green space (relative risk 0·879, 95% credibility interval 0·779–0·991) or a moderate proportion of green space (0·919, 0·846–0·998) showed a reduced suicide risk compared with municipalities with less green space. Green space did not differ according to urbanicity in relation to suicide. Neither blue space nor coastal proximity was associated with suicide risk. The geographical variation in the residual relative suicide risk was substantial and the south of the Netherlands was at high risk. Interpretation: Our findings support the notion that exposure to natural environments, particularly to greenery, might have a role in reducing suicide mortality. If confirmed by future studies on an individual level, the consideration of environmental exposures might enrich suicide prevention programmes

Space-time accessibility measures: A geocomputational algorithm with a focus on the feasible opportunity set and possible activity duration.

Abstract. Space-time accessibility measures have received much attention in recent years due to their sensitivity to differences in individual ability to participate in activities in space and time. Despite the conceptual attractiveness and robustness of space-time measures, only few attempts have been made to operationalize them to date. Research that seeks to improve space-time accessibility measures is still sorely needed. This study seeks to enhance space-time accessibility measures through developing a new operational method and GIS-based algorithm that better represents the space-time characteristics of urban opportunities (e.g. their geographical distribution and opening hours) and human activity-travel behavior (e.g. delay times, minimum activity participation time, and maximum travel time threshold). The proposed method not only takes into account the number and size of opportunities, but also the possible activity duration at each activity location given its opening hours and the effect of transport network topology (e.g. one-way streets, turn restrictions and over-pass). Incorporating these elements into space-time measures helps overcome several shortcomings of previous approaches to evaluating space-time accessibility. Key words: Individual accessibility, space-time accessibility measures, spacetime constraint, space-time prism, GIS JEL classification: C60, R40 A version of this paper was presented at the 98th Annual Meeting of the Association of American Geographers, Los Angeles, March 19-23, 2002. We thank Joe Weber for providing the digital transport network with travel speeds and a version of the geocomputational algorithm he used in his study (Weber 2001), upon which our developmental effort has been based. We are also grateful to the helpful comments and suggestions of the reviewers

Curriculum Design of Artificial Intelligence and Sustainability in Secondary School

Artificial Intelligence is revolutionizing numerous sectors with its transformative power, while at the same time, there is an increasing sense of urgency to address sustainability challenges. Despite the significance of both areas, secondary school curriculums still lack comprehensive integration of AI and sustainability education. This paper presents a curriculum designed to bridge this gap. The curriculum integrates progressive objectives, computational thinking competencies and system thinking components across five modules—awareness, knowledge, interaction, empowerment and ethics—to cater to varying learner levels. System thinking components help students understand sustainability in a holistic manner. Computational thinking competencies aim to cultivate computational thinkers to guide the design of curriculum activities

Mobility Census for the analysis of rapid urban development

Traditionally urban structure and development are monitored using infrequent high-quality datasets such as censuses. However, human culture is accelerating and aggregating, leading to ever-larger cities and an increased pace of urban development. Our modern interconnected world also provides us with new data sources that can be leveraged in the study of cities. However, these often noisy and unstructured sources of big data pose new challenges. Here we propose a method to extract meaningful explanatory variables and classifications from such data. Using movement data from Beijing, which is produced as a byproduct of mobile communication, we show that meaningful features can be extracted, revealing for example the emergence and absorption of subcenters. In the future this method will allow the analysis of urban dynamics at a high spatial resolution (here, 500m) and near real-time frequency

Geographic uncertainties in external exposome studies: A multi-scale approach to reduce exposure misclassification

Background: Many studies on environment-health associations have emphasized that the selected buffer size (i.e., the scale of the geographic context when exposures are assigned at people's address location) may affect estimated effect sizes. However, there is limited methodological progress in addressing these buffer size-related uncertainties. Aim: We aimed to 1) develop a statistical multi-scale approach to address buffer-related scale effects in cohort studies, and 2) investigate how environment-health associations differ between our multi-scale approach and ad hoc selected buffer sizes. Methods: We used lacunarity analyses to determine the largest meaningful buffer size for multiple high-resolution exposure surfaces (i.e., fine particulate matter [PM2.5], noise, and the normalized difference vegetation index [NDVI]). Exposures were linked to 7.7 million Dutch adults at their home addresses. We assigned exposure estimates based on buffers with fine-grained distance increments until the lacunarity-based upper limit was reached. Bayesian Cox model averaging addressed geographic uncertainties in the estimated exposure effect sizes within the exposure-specific upper buffer limits on mortality. Z-tests assessed statistical differences between averaged effect sizes and those obtained through pre-selected 100, 300, 1200, and 1500 m buffers. Results: The estimated lacunarity curves suggested exposure-specific upper buffer size limits; the largest was for NDVI (960 m), followed by noise (910 m) and PM2.5 (450 m). We recorded 845,229 deaths over eight years of follow-up. Our multi-scale approach indicated that higher values of NDVI were health-protectively associated with mortality risk (hazard ratio [HR]: 0.917, 95 % confidence interval [CI]: 0.886–0.948). Increased noise exposure was associated with an increased risk of mortality (HR: 1.003, 95 % CI: 1.002–1.003), while PM2.5 showed null associations (HR:0.998, 95 % CI: 0.997–1.000). Effect sizes of NDVI and noise differed significantly across the averaged and prespecified buffers (p < 0.05). Conclusions: Geographic uncertainties in residential-based exposure assessments may obscure environment-health associations or risk spurious ones. Our multi-scale approach produced more consistent effect estimates and mitigated contextual uncertainties