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The discrete empirical interpolation method (DEIM) has been shown to be a viable index-selection technique for identifying representative subsets in data. Having gained some popularity in reducing dimensionality of physical models involving differential equations, its use in subset-/pattern-identification tasks is not yet broadly known within the machine learning community. While it has much to offer as is, the DEIM algorithm is limited in that the number of selected indices cannot exceed the rank of the corresponding data matrix. Although this is not an issue for many data sets, there are cases in which the number of classes represented in a given data set is greater than the rank of the data matrix; in such cases, it is impossible for the standard DEIM algorithm to identify all classes. To overcome this issue, we present a novel extension of DEIM, called E-DEIM. With the proposed algorithm, we also provide some theoretical results for using extensions of DEIM to form the CUR matrix factorization in identifying both rows and columns to approximate the original data matrix. Results from applying variations of E-DEIM to two different data sets indicate that the presented extension can indeed allow for the identification of additional classes along with those selected by standard DEIM. In addition, comparing these results to those of some more familiar methods demonstrates that the proposed deterministic E-DEIM approach including coherence performs comparably to or better than the other evaluated methods and should be considered in future class-identification tasks.The revised criteria for posttraumatic stress disorder (PTSD) in the fifth edition of the Diagnostic and Statistical Manual necessitated the development of new screening tools for youth, one of the most widely used of which is the UCLA Posttraumatic Stress Disorder Reaction Index for DSM-5 (RI-5). Thus far, the few studies that have investigated the RI-5's factor structure have supported a four-factor model. However, to date this research has been limited to youth with histories of exposure to single-event traumatic stressors, a significant limitation as evidence suggests many trauma-exposed youth report exposure to multiple types of traumatic stressors, or polyvictimization. Ozanimod supplier It is imperative to determine the generalizability of previous factor models to specific populations which they are purported to represent. We investigated whether the RI-5's four-factor model replicated in a sample of 455 polyvictimized justice-involved adolescents. Initial confirmatory factor analysis demonstrated that the four-factor model did not converge. Therefore, we utilized Bayesian Structural Equations Modeling (BSEM) to determine why the previously proposed factor structure did not converge. The BSEM model suggested that the global factor structure was acceptable and did not require addition or subtraction of any factor or cross-factor loadings. However, small and moderate residual covariances resulted in model misspecification, suggesting there may be additional associations not captured by the current DSM-5 model for polyvictimized youth. Future work should continue examining the RI-5's factor structure in order to better understand whether the current results are unique and how measurements assessing DSM-5 PTSD symptom criteria perform in diverse trauma-exposed youth populations.This paper, which is authored by members of the Japanese Association of Family Therapy (JAFT), describes the COVID-19 pandemic in Japan from a family systems perspective. The authors are active members of JAFT and include current and past presidents and officers. We describe the course of the pandemic and the ways in which government policies to mitigate the pandemic have affected Japanese families. Challenges that affect Japanese families include the inability to participate in family and social rituals, prescribed gender roles that specifically affect women, high suicide rates, and prejudice against those who are at risk of spreading the infection. The need to shelter in place has also forced family homes to function as a workplace for parents, classrooms for children, and day care services for frail elders, which has resulted in psychological distress among individuals and conflicts among families. We discuss ways that therapists have worked with Japanese families using online therapy.

Our goal is to understand the social dynamics affecting domestic and sexual violence in urban areas by investigating the role of connections between area nodes, or communities. We use innovative methods adapted from spatial statistics to investigate the importance of social proximity measured based on connectedness pathways between area nodes. In doing so, we seek to extend the standard treatment in the neighborhoods and crime literature of areas like census blocks as independent analytical units or as interdependent primarily due to geographic proximity.

In this paper, we develop techniques to incorporate two types of proximity, geographic proximity and commuting proximity in spatial generalized linear mixed models (SGLMM) in order to estimate domestic and sexual violence in Detroit, Michigan and Arlington County, Virginia. Analyses are based on three types of CAR models (the Besag, York, and Mollié (BYM), Leroux, and the sparse SGLMM models) and two types of SAR models (the spatial lag and spatial errorviors between places, they may then transfer also the effects of crime prevention efforts.

Overall, the results indicate variations across crime type, urban contexts, and modeling approaches. Nonetheless, in important contexts, commuting ties among neighborhoods are observed to greatly improve our understanding of urban crime. If such ties contribute to the transfer of norms, social support, resources, and behaviors between places, they may then transfer also the effects of crime prevention efforts.Informational materials from psychological associations often encourage parents to seek out "evidence-based therapies" (EBTs) to address their child's behavioral health concerns. This study examined whether parents concerned about their adolescents' substance use had distinct preferences for EBT principles and marketing language based on their adolescent's specific behavioral health problems. Parents (N = 411; 86% female; 88% non-Hispanic White) of adolescents (age 12-19 years) completed an online direct-to-consumer (DTC) marketing survey as part of a larger multi-phase study. Parents reported their adolescents had high rates of current externalizing (66%), internalizing (51%), substance-related (39%), and legal (25%) problems. Parents answered questions about their perceived definition of EBT, whether they valued underlying EBT principles (i.e., reliance on a proven approach vs. a varied approach), their preferred terms for describing EBT, and factors they considered when choosing a therapist. Most parents defined EBT correctly, regardless of their adolescent's behavioral health problems.