Ohio Department of Transportation

ObjectivesDemographic characteristics of the patient population influence patient reported outcome measures (PROMs) following patellar dislocations. The time from injury and number of dislocations can also vary within the patient population. The hypothesis of the study is that characteristics of the patient population influencing Knee injury and Osteoarthritis Outcome Score (KOOS) measures of pain, function, and quality of life vary with time from patellar dislocation and number of dislocations. MethodsOutcome scores were evaluated for subjects in four groups: within five months of a first patellar dislocation (first-time group, n ​= ​24), within five months of a recurrent dislocation (multiple group, n ​= ​15), five to twelve months after a first dislocation (post-acute group, n ​= ​14), and two years or longer after a first dislocation (two-year group, n ​= ​14). For each group, KOOS pain, physical function, and quality of life scores were compared between males and females. KOOS scores were also correlated against age, body mass index (BMI), and time since first and most recent dislocation. ResultsFor the first-time dislocation group, physical function, and quality of life scores were higher for men than women (p ​< ​0.05). For the multiple dislocation group, pain and physical function improved as BMI decreased (p ​< ​0.025), while quality of life improved as age decreased (p ​= ​0.014). For the post-acute group, all three scores improved as BMI decreased (p ​< ​0.05). For the two-year group, all three scores worsened as time since first dislocation increased (p ​< ​0.01). ConclusionsFollowing patellar dislocation, relationships between characteristics of the patient population and PROMs vary with time from injury and number of dislocations. In the acute phase following a first dislocation, PROMs likely reflect the traumatic injury. Based on relationships with BMI, outcomes likely reflect functional capacity of the knee in the acute phase of multiple dislocations and post-acute phase of a first dislocation. After multiple years, progressive degradation of the knee over time seems to influence PROMs. Level of evidenceRetrospective study with more than one negative criterion (Level 4).

This chapter of the New York City Panel on Climate Change 4 (NPCC4) report considers climate health risks, vulnerabilities, and resilience strategies in New York City's unique urban context. It updates evidence since the last health assessment in 2015 as part of NPCC2 and addresses climate health risks and vulnerabilities that have emerged as especially salient to NYC since 2015. Climate health risks from heat and flooding are emphasized. In addition, other climate-sensitive exposures harmful to human health are considered, including outdoor and indoor air pollution, including aeroallergens; insect vectors of human illness; waterborne infectious and chemical contaminants; and compounding of climate health risks with other public health emergencies, such as the COVID-19 pandemic. Evidence-informed strategies for reducing future climate risks to health are considered.

The continual challenges exist in attaining an equitable allocation of urban amenities. In order to render this objective attainable as well as practical in real-world scenarios, it is imperative to transition from a static conceptualization of equity to a dynamic notion of equity. To assess dynamic equity in the context of Dhaka, we collected data for two distinct time periods, 2005 and 2018, and calculated integrated accessibility indices using enhanced two-step floating catchment area method. We then responded to these questions: a) Has there been an increase in the level of accessibility? b) Is the changed accessibility being shared more equally or unequally? c) Do members of underprivileged groups enjoy greater access than members of privileged groups? d) Is the underprivileged population enjoying progressively increasing access over time? The results indicate the distribution of accessibility exhibits a pattern, wherein individuals belonging to the underprivileged group experience lower accessibility benefits, while individuals in the privileged group enjoy better accessibility. The sole reason for optimism regarding the distribution pattern lies in the narrowing of the accessibility gap between the privileged and underprivileged. Moreover, the accessibility distribution becomes more equal within the underprivileged group, while becoming more unequal within the privileged group.

This paper presents the results of the first study to evaluate the effects of the tack coat and micro-surfacing mix properties on the interlayer bond strength between the micro-surfacing layer(s) and existing pavement surface. Several factors were investigated, which included the type of tack coat material, tack coat application rate, and the residual binder content of the micro-surfacing mix. To this end, a total of 14 field micro-surfacing test sections were installed on Ohio State Route 03 in Wayne County, Ohio. While the first seven sections were constructed with a single micro-surfacing layer, the other seven sections had double micro-surfacing layers. Five tack coat application rates and two residual binder contents were evaluated. The testing plan involved obtaining core samples from the constructed sections 1 week, 4 months, and 12 months after construction. The obtained field cores were tested in the laboratory using two types of pull-off tests and a torque bond strength test. The results of bond strength tests on obtained field cores and the statistical analysis performed on these results indicated that sections with no tack coat had significantly lower bond strength than those with tack coat with at least 0.05 gallons per square yard (gsy) total application (0.0083 gsy residual application rate). Furthermore, results indicated that the use of 0.75% lower residual asphalt binder content in micro-surfacing mixes resulted in significantly lower bond strength between the micro-surfacing and existing pavement. The tack coat material properties had some effect on the interlayer bond strength; however, this effect was statistically insignificant.

How should an agency proactively identify and prioritize rail-highway grade crossings for intervention in relation to their likely performance benefits for the community and the system? Performance is mainly related to two factors: (i) the likelihood and duration of “blockage,” that is, the temporary obstruction of a road link when a train blocks the intersecting grade crossing, and (ii) the “hazard condition” of the crossing itself, with regard to its design and asset quality. Existing analytical grade crossing prioritization models focus almost solely on safety and crash prevention by addressing the “hazard condition” aspect of performance. The paper develops a quantitative multi-criteria approach that not only considers and builds on existing analytical safety-based approaches, but goes beyond and also includes considerations such as blocked crossings. The model calculates a multi-dimensional adaptive capacity score (ACS) for each crossing, which can then be used to rank a set of crossings, as well as test different policy scenarios and their effect on prioritization. The model is applied to approximately 5,700 grade crossings in the State of Ohio and detailed pilot validations with stakeholders in two counties conducted. Based on the validation process, the model provides comprehensive and cohesive results and is being deployed statewide. Next steps involve incorporating considerations for truck traffic and pedestrians/bicycles (non-motorized users) in calculating the ACS as well as developing mitigation measures for blocked crossings that can be considered from the model.