Activity

Despite the importance of intimate partner violence (IPV) and homicide research to women’s health and safety, much remains unknown about risk factors for intimate partner homicide (IPH). This article presents the Arizona Intimate Partner Homicide Study, pilot research that is being conducted in one U.S. state to update and expand on risk factors for IPH. In the context of presenting this study, we summarize the literature on data collection techniques, various marginalized and under researched populations, and the importance of gathering data about the victim-offender relationship and situational IPH risk factors. Additional research is needed to update risk factors for IPH to account for changes in technology and to examine differential risk across diverse populations. Local, community based data collection strategies are likely to provide more comprehensive and nuanced insight into IPH; though, to understand risk factors among marginalized populations, it may be necessary to increase sample size through a national strategy. Although not a panacea, we present this ongoing research as a model for other states to emulate and improve upon, in the hopes of developing more comprehensive data examining risk for IPH among victims of IPV.In the spot market for air cargo, airlines typically adopt dynamic pricing to tackle demand uncertainty, for which it is difficult to accurately estimate the distribution. This study addresses the problem where a dominant airline dynamically sets prices to sell its capacities within a two-phase sales period with only partial information. That partial information may show as the moments (upper and lower bounds and mean) and the median of the demand distribution. We model the problem of dynamic pricing as a distributional robust stochastic programming, which minimizes the expected regret value under the worst-case distribution in the presence of partial information. We further reformulate the proposed non-convex model to show that the closed-form formulae of the second-stage maximal expected regret are well-structured. We also design an efficient algorithm to characterize robust pricing strategies in a polynomial-sized running time. Using numerical analysis, we present several useful managerial insights for airline managers to strategically collect demand information and make prices for their capacities in different market situations. Moreover, we verify that additional information will not compromise the viability of the pricing strategies being implemented. Therefore, the method we present in this paper is easier for airlines to use.SARS-CoV-2 infection has unexpectedly arrived in our society. In pregnant women, the situation has been similar to general population. Some drugs have been used empirically, and obstetricians have to consider whether the same treatments used in the general population were valid for pregnant women with severe disease, according to their safety profile for both the mother and the fetus. There has been a wide experience with the use of hydroxychloroquine and lopinavir/ritonavir in pregnant women. Tocilizumab and interferon beta could be used if benefits exceed risks. There is no experience using remdesivir in pregnancy.Temporarily plugged or “suspended” wells pose environmental and economic risks due to the large volume of methane gas leaked. In the Canadian Province of Alberta, which, by far, has the largest number of petroleum wells in Canada, there are no regulations stipulating the maximum length of time a well can be left suspended. In recent years, an increasing number of wells have been put into the suspended state by owners. We show using a large data set obtained from the Alberta Energy Regulator that leak spells have increased between 1971 and 2019. For the same time period, the probability of an unresolved leak has also increased, and the amount of methane emitted per leak has substantially gone up. Lastly, we provide simple social-cost-of methane computations indicating that responsible policies can incentivize well owners towards remediation and reclamation and support efforts to fight climate change and improve upon economic expedience.

The online version contains supplementary material available at 10.1007/s10584-021-03044-w.

The online version contains supplementary material available at 10.1007/s10584-021-03044-w.Researchers have improved travel demand forecasting methods in recent decades but invested relatively little to understand their accuracy. A major barrier has been the lack of necessary data. We compiled the largest known database of traffic forecast accuracy, composed of forecast traffic, post-opening counts and project attributes for 1291 road projects in the United States and Europe. We compared measured versus forecast traffic and identified the factors associated with accuracy. Ala-Gln We found measured traffic is on average 6% lower than forecast volumes, with a mean absolute deviation of 17% from the forecast. Higher volume roads, higher functional classes, shorter time spans, and the use of travel models all improved accuracy. Unemployment rates also affected accuracy-traffic would be 1% greater than forecast on average, rather than 6% lower, if we adjust for higher unemployment during the post-recession years (2008 to 2014). Forecast accuracy was not consistent over time more recent forecasts were more accurate, and the mean deviation changed direction. Traffic on projects that opened from the 1980s through early 2000s was higher on average than forecast, while traffic on more recent projects was lower on average than forecast. This research provides insight into the degree of confidence that planners and policy makers can expect from traffic forecasts and suggests that we should view forecasts as a range of possible outcomes rather than a single expected outcome.

The online version contains supplementary material available at 10.1007/s11116-021-10182-8.

The online version contains supplementary material available at 10.1007/s11116-021-10182-8.This study examines the opportunities and challenges involved with contactless healthcare services in the post-COVID-19 pandemic era. First, we reviewed the literature to analyze contactless or contact-free healthcare services that have been utilized in pre-and during the COVID-19 pandemic periods. Then, we interviewed medical experts and hospital administrators to gain knowledge about how healthcare providers are currently working to mitigate the spread of COVID and preparing for the post-pandemic period. Thus, we analyzed the evolution and utilization of contactless services during the three different time periods pre-, during-, and post-COVID-19. The results indicated that in the post-COVID-19 era, a new normal of hybrid healthcare services would emerge. While some of the contactless services that have been practiced during the pandemic may revert to the traditional face-to-face services, those innovative contactless healthcare services that have been proven effective during the pandemic would be practiced or even advanced in the post-pandemic period due to the accelerating technological developments.