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The 14th International Topical Meeting on Nuclear Applications of Accelerators (AccApp'21) was held in 2021 as an embedded topical meeting during the ANS Winter Meeting in Washington, D.C. The conference aimed to promote accelerator-based research and development and covered various research topics, including accelerator facilities, nuclear data, medical applications, and industrial applications. A total of 120 abstracts were submitted, and 105 presentations were given. The conference faced challenges due to the COVID-19 pandemic but was successful with the support of participants and sponsors. The conference proceedings were published in Nuclear Science and Engineering (NSE). [Extracted from the article]

Research has demonstrated children in out-of-home care have experienced trauma and a significant proportion are in need of behavioral health services (e.g. Casaneuva et al., NSCAW II baseline report: Child well-being, US Department of Health and Human Services, Washington, DC, 2011). Accessing services requires interagency coordination between child welfare and behavioral health professionals; however, challenges to coordination and collaboration may result in lack of service utilization for many youth (Hanson et al. 2016). Utilizing a mixed methodological approach, this paper describes the results of a study conducted five years after full state-wide implementation of processes designed to promote the use of evidence-based practices to inform decision-making for youth dually served by the child welfare and behavioral health systems. Outcomes from the study were used to develop strategies to address programmatic concerns and reinforce implementation supports. Study findings may aid organizations seeking to reinforce data-informed practices and employ strategies for addressing barriers at the worker and agency level. [ABSTRACT FROM AUTHOR]

In the early 1900s, Washington, D.C. contained many alleys in the interior of blocks inhabited by impoverished Black residents. Elite reformers engaged in an aggressive campaign to eliminate alleys, on the grounds of their purported unsanitary environment and high disease prevalence. In this paper, I combine quantitative, qualitative, and spatial sources to explore new perspectives on segregation, public health, and the racialized efforts of housing reformers during this period. I find that reformers overstated the horrors of conditions in alleys and their effects on residents' health: poorer health among alley residents was in large part due to Black residents' marginalization wherever they might live. Alleys' status as racialized space, coupled with progressive paternalistic racism, facilitated the discursive construction of alleys as pathological "breeding grounds of disease." Further, my findings shed new light on micro-configurations of segregation within racially mixed neighborhoods, as well as the social experience and meaning of such configurations. Far from indicating harmonious coexistence, the proximity of such alleys to white homes and institutions spurred elite Washingtonians' self-interested fear of disease spreading beyond the alleys. Thus, this pattern of segregation helps explain the zeal of the campaign to eradicate alleys: as a means of achieving separation from undesired Black neighbors whom white reformers associated with contagion. [ABSTRACT FROM AUTHOR]

Conservation planners often rely on heuristic indices when challenged with prioritizing potential projects under a constrained budget. This paper presents a comparative analysis of several prioritization indices (PIs) of culvert fish passage barriers, which can contribute to declines in anadromous fish populations. A federal injunction requires Washington state to restore 90% of habitat blocked by state‐owned culverts by 2030, prompting the development of numerous PIs, by various entities (i.e., counties, cities) within the injunction area. Our comparative analysis of PIs within the injunction Case Area investigates their ability to distinguish between barriers, their transferability in terms of scoring metrics, how scoring weights differ, and the preferences implied thereby. We document the use of six distinct PI methods by 10 entities and find that some PIs used many shared metrics, whereas others used a high percentage of unique metrics that would be difficult to replicate outside the entity's jurisdiction. Although habitat potential, habitat quantity, and connectivity were considered across all PIs, we found a high level of variation in terms of the metric weights. Our methods can be employed in other geographies or for other restoration PI planning efforts, and our results may facilitate the development and refinement of future PIs. [ABSTRACT FROM AUTHOR]

The pioneering work of Getis and Ord on local spatial statistics has a counterpart in spatial econometrics in treating spatial heterogeneity. This can be approached from a continuous or a discrete perspective. In a discrete perspective, referred to as spatial regimes, the coefficients vary by discrete subregions of the data. Whereas the estimation of spatial regime regressions is well understood, the delineation of the regimes themselves remains a topic of active interest. Generally speaking, two broad classes of methods can be distinguished, one in which the delineation is carried out separately from the coefficient estimation and one where the two are tightly integrated. Tightly integrated approaches are referred to as endogenous spatial regimes. A number of different methods have been suggested in the literature, including finite mixture models, GWR-based methods, and penalized regression. One drawback of regime delineation is that the results do not necessarily satisfy a spatial contiguity constraint, i.e., observations are grouped despite not being spatially connected. In this paper, we outline a heuristic to determine the spatial regimes endogenously, as an extension of the well-known SKATER algorithm for spatially constrained clustering. This guarantees that the resulting regimes consist of contiguous observations. We outline the method and apply it in the context of the determination of housing submarkets, which is represented by rich literature in applied spatial econometrics. We use a well-known Kaggle data set as the empirical example, which contains observations on house sales in King County, Washington. We compare the estimation of a hedonic house price model using the endogenous spatial regimes approach to a range of more traditional methods, including pooled regression, the use of administrative districts, data-driven regimes based on a-spatial and spatial clustering of explanatory variables, and finite mixture regression. We evaluate the results in terms of fit and assess the trade-offs between the spatial and a-spatial approaches. [ABSTRACT FROM AUTHOR]

Neighborhood parks are important venues to support moderate-to-vigorous (MVPA) activity. There has been a noticeable increase promoting physical activity among youth in neighborhood parks. This paper aims to assess the association between park use and MVPA among low-income youth in a large urban area. We recruited a cohort of 434 youth participants during the COVID pandemic years (2020–2022) from low-income households in Washington, D.C. We collected multiple data components: accelerometry, survey, and electronic health record data. We explored the bivariate relationship between the accelerometer-measured daily MVPA time outcome and survey-based park use measures. A mixed-effect model was fitted to adjust the effect estimate for participant-level and time-varying confounders. The overall average daily MVPA time is 16.0 min (SD = 12.7). The unadjusted bivariate relation between daily MVPA time and frequency of park visit is 1.3 min of daily MVPA time per one day with park visits (p < 0.0001). The model-adjusted estimate is 0.7 daily MVPA minutes for 1 day with park visit (p = 0.04). The duration of a typical park visit is not a significant predictor to daily MVPA time with or without adjustments. The initial COVID outbreak in 2020 resulted in a significant decline in daily MVPA time (− 4.7 min for 2020 versus 2022, p < 0.0001). Park visit frequency is a significant predictor to low-income youth's daily MVPA time with considerable absolute effect sizes compared with other barriers and facilitators. Promoting more frequent park use may be a useful means to improve low-income youth's MVPA outcome. [ABSTRACT FROM AUTHOR]

The NoMA Business Improvement District (BID) is one of Washington DC's fastest developing areas and has one of the city's largest concentrations of unhoused tent camps, many of which are located in underpasses that provide bits of protection and privacy. These underpasses were created during DC's City Beautiful Movement and have been the site of neoliberal antihomeless strategies. In this paper I explore the production of space in the NoMA area and how property owners, business associations, and government actors sanitized public space for wealthy newcomers while excluding poor and unhoused residents. [ABSTRACT FROM AUTHOR]

Background: Public education reforms, such as expanded school choice, have become a critical lever for remaking urban landscapes. These reforms often aim to attract and retain affluent and White families in urban schools, so scholars have examined how these parents navigate the perceived risk of choosing these schools for their children. Purpose: This paper extends this scholarship to understand how other families experience these reforms in gentrifying landscapes. We ask: (1) How do Black parents navigate school selection in a gentrifying and expansive education marketplace? (2) How do Black parents' perceptions of schooling shape their approach to school selection? (3) How do parents' positionalities (e.g., gender, class, place attachments, and tenure in the city) influence their experiences? Research Design: We leverage a qualitative meta-analysis design that pools data from three separately conducted studies of gentrification in Washington, D.C. For this analysis, we center on 34 Black parents' experiences as they navigate school selection. We reanalyzed data through the lens of critical spatial and racial theories. We paid particular attention to participants' attachments to place, their perceptions of their choices, the school and neighborhood attributes participants valued, and how they navigated school selection. Findings: Parents considered a broad range of school and neighborhood characteristics as they constructed their choice sets. As they searched for schools, Black parents made a series of racialized compromises to find schools they perceived to be racially, physically, and socially safe for their children. Parents, for example, negotiated their desire for academic rigor with their perception of schools' social climates and their perceptions that schools would be racially affirming and inclusive. Place and space were essential to parents' choice set construction. Schools' physical locations and perceptions of safety influenced whether parents viewed schools as viable options for their children. Conclusion: Our study underscores the multiple factors that bound choice set construction. Critically, Black parents' experiences as they navigated school selection suggest that the expansive educational marketplace offered a "chance, not a choice" at high-quality educational opportunities. [ABSTRACT FROM AUTHOR]

In the early 1900s, Washington, D.C. contained many alleys in the interior of blocks inhabited by impoverished Black residents. Elite reformers engaged in an aggressive campaign to eliminate alleys, on the grounds of their purported unsanitary environment and high disease prevalence. In this paper, I combine quantitative, qualitative, and spatial sources to explore new perspectives on segregation, public health, and the racialized efforts of housing reformers during this period. I find that reformers overstated the horrors of conditions in alleys and their effects on residents' health: poorer health among alley residents was in large part due to Black residents' marginalization wherever they might live. Alleys' status as racialized space, coupled with progressive paternalistic racism, facilitated the discursive construction of alleys as pathological "breeding grounds of disease." Further, my findings shed new light on micro-configurations of segregation within racially mixed neighborhoods, as well as the social experience and meaning of such configurations. Far from indicating harmonious coexistence, the proximity of such alleys to white homes and institutions spurred elite Washingtonians' self-interested fear of disease spreading beyond the alleys. Thus, this pattern of segregation helps explain the zeal of the campaign to eradicate alleys: as a means of achieving separation from undesired Black neighbors whom white reformers associated with contagion. [ABSTRACT FROM AUTHOR]

This paper attempts to develop statistical modeling for air-conditioning analysis in Jakarta, Indonesia, during an emergency state of community activity restrictions enforcement (Emergency CARE), using a variety of parameters such as PM10, PM2.5, SO2, CO, O3, and NO2 from five IoT-based air monitoring systems. The parameters mentioned above are critical for assessing the air quality conditions and concentration of air pollutants. Outdoor air pollution concentration variations before and after the Emergency CARE, which was held in Indonesia during the COVID-19 pandemic on July 3-21, 2021, were studied. An air quality monitoring system based on the IoT generates sensor data that is collected from a government-integrated data portal, and that can be analyzed statistically. There are two main types of ANOVA (Analysis of Variance): one-way (or unidirectional) and two-way, which are applied to the collected sensor data and hypotheses calculated using ANOVA. ANOVA one-way was found to be more effective for analyzing air quality condition data. During emergency CARE, the average concentrations of PM10, PM2.5, and O3 from the air quality monitoring system show values that have exceeded the standard Air Quality Index (AQI), while the concentrations of CO, NO2, and SO2 are still below the applicable AQI values. It stated that air pollution in Jakarta worsened during the implementation of Emergency CARE. [ABSTRACT FROM AUTHOR]

The first- and last-mile (FM/LM) problem is a major deterrent to public transit use. With the rise of shared micromobility options such as shared e-scooters in recent years, there is a growing interest in understanding their potential to serve as a last-mile transit solution. However, empirical data regarding the integrated use of shared micromobility and public transit have been limited so far. As a result, much is unknown regarding the spatiotemporal patterns and characteristics of shared micromobility trips serving as an FM/LM connection to transit. This paper addresses these knowledge gaps by leveraging a novel dataset (i.e., the Spin post-ride survey dataset) that records thousands of transit-connecting shared e-scooter trips in Washington DC. Specifically, we used the dataset to reveal the spatiotemporal patterns of transit-connecting shared e-scooter trips in Washington DC, resulting in some major policy insights regarding the integral use of shared e-scooters and public transit. We further leveraged the dataset to validate if and to what extent a commonly applied buffer-zone approach can infer FM/LM micromobility trips accurately. Statistical tests showed that the actual FM/LM Spin e-scooter trips differ from inferred FM/LM Spin e-scooter trips in both spatial and temporal dimensions. This indicates that the common practice of inferring FM/LM micromobility trips with a buffer-zone approach can lead to inaccurate estimates of transit-connecting micromobility trips. [ABSTRACT FROM AUTHOR]