Arizona State University

While numerous studies have established relationships between Adverse Childhood Experiences (ACEs) and adult substance use, few qualitative studies have explored the differing ways in which experiences of childhood adversity are emplotted into narratives of drug use and recovery. This paper analyzes qualitative data collected as part of a mixed-methods longitudinal study of people with opioid use disorder. Narratives of adverse childhood experiences emerged unprompted. After coding qualitative data for mention of ACEs, we thematically analyzed coded data using a framework of critical phenomenology and constructed a four-part typology to differentiate the ways that ACEs were emplotted into narratives. Our four sub-types—which we call ‘casual mentioners’, ‘seeking redemption’, ‘haunted by trauma’, and ‘reckoning with inevitability’—did not necessarily cleave along types or number of ACEs, but rather by the manners in which these experiences were conditioned by subsequent life trajectories, and the social, structural, and interpersonal factors that contextualized them. While participants often linked experiences of childhood adversity to adult opioid use, we argue that the differing ways in which individuals understand and process these linkages has implications for both clinical and therapeutic practice. For frameworks like trauma-informed care to be meaningful, we must pay closer attention to these meaningful differences.

Frequency-bin qubits possess unique synergies with wavelength-multiplexed lightwave communications, suggesting valuable opportunities for quantum networking with the existing fiber-optic infrastructure. Although the coherent manipulation of frequency-bin states requires highly controllable multi-spectral-mode interference, the quantum frequency processor (QFP) provides a scalable path for gate synthesis leveraging standard telecom components. Here we summarize the state of the art in experimental QFP characterization. Distinguishing between physically motivated “open box” approaches that treat the QFP as a multiport interferometer, and “black box” approaches that view the QFP as a general quantum operation, we highlight the assumptions and results of multiple techniques, including quantum process tomography of a tunable beamsplitter—to our knowledge the first full process tomography of any frequency-bin operation. Our findings should inform future characterization efforts as the QFP increasingly moves beyond proof-of-principle tabletop demonstrations toward integrated devices and deployed quantum networking experiments.

Alloy based implants have made a great impact in the clinic and in preclinical research. Immune responses are one of the major causes of failure of these implants in the clinic. Although the immune responses toward non-degradable alloy implants are well documented, there is a poor understanding of the immune responses against degradable alloy implants. Recently, there have been several reports suggesting that degradable implants may develop substantial immune responses. This phenomenon needs to be further studied in detail to make the case for the degradable implants to be utilized in clinics. Herein, we review these new recent reports suggesting the role of innate and potentially adaptive immune cells in inducing immune responses against degradable implants. First, we discussed immune responses to allergen components of non-degradable implants to give a better overview on differences in the immune response between non-degradable and degradable implants. Furthermore, we also provide potential areas of research that can be undertaken that may shed light on the local and global immune responses that are generated in response to degradable implants.

Human-AI policy specification is a novel procedure we define in which humans can collaboratively warm-start a robot's reinforcement learning policy. This procedure is comprised of two steps; (1) Policy Specification, i.e. humans specifying the behavior they would like their companion robot to accomplish, and (2) Policy Optimization, i.e. the robot applying reinforcement learning to improve the initial policy. Existing approaches to enabling collaborative policy specification are often unintelligible black-box methods, and are not catered towards making the autonomous system accessible to a novice end-user. In this paper, we develop a novel collaborative framework to allow humans to initialize and interpret an autonomous agent's behavior. Through our framework, we enable humans to specify an initial behavior model via unstructured, natural language (NL), which we convert to lexical decision trees. Next, we leverage these translated specifications, to warm-start reinforcement learning and allow the agent to further optimize these potentially suboptimal policies. Our approach warm-starts an RL agent by utilizing non-expert natural language specifications without incurring the additional domain exploration costs. We validate our approach by showing that our model is able to produce $>$ 80% translation accuracy, and that policies initialized by a human can match the performance of relevant RL baselines in two domains.

Evolutionary biology provides a crucial foundation for medicine and behavioral science that has been missing from psychiatry. Its absence helps to explain slow progress; its advent promises major advances. Instead of offering a new kind of treatment, evolutionary psychiatry provides a scientific foundation useful for all kinds of treatment. It expands the search for causes from mechanistic explanations for disease in some individuals to evolutionary explanations for traits that make all members of a species vulnerable to disease. For instance, capacities for symptoms such as pain, cough, anxiety and low mood are universal because they are useful in certain situations. Failing to recognize the utility of anxiety and low mood is at the root of many problems in psychiatry. Determining if an emotion is normal and if it is useful requires understanding an individual's life situation. Conducting a review of social systems, parallel to the review of systems in the rest of medicine, can help achieve that understanding. Coping with substance abuse is advanced by acknowledging how substances available in modern environments hijack chemically mediated learning mechanisms. Understanding why eating spirals out of control in modern environments is aided by recognizing the motivations for caloric restriction and how it arouses famine protection mechanisms that induce binge eating. Finally, explaining the persistence of alleles that cause serious mental disorders requires evolutionary explanations of why some systems are intrinsically vulnerable to failure. The thrill of finding functions for apparent diseases is evolutionary psychiatry's greatest strength and weakness. Recognizing bad feelings as evolved adaptations corrects psychiatry's pervasive mistake of viewing all symptoms as if they were disease manifestations. However, viewing diseases such as panic disorder, melancholia and schizophrenia as if they are adaptations is an equally serious mistake in evolutionary psychiatry. Progress will come from framing and testing specific hypotheses about why natural selection left us vulnerable to mental disorders. The efforts of many people over many years will be needed before we will know if evolutionary biology can provide a new paradigm for understanding and treating mental disorders.

Introduction: Individuals living in rural communities are at heightened risk for Alzheimer's disease and related dementias (ADRD), which parallels other persistent place-based health disparities. Identifying multiple potentially modifiable risk factors specific to rural areas that contribute to ADRD is an essential first step in understanding the complex interplay between various barriers and facilitators. Methods: An interdisciplinary, international group of ADRD researchers convened to address the overarching question of: "What can be done to begin minimizing the rural health disparities that contribute uniquely to ADRD?" In this state of the science appraisal, we explore what is known about the biological, behavioral, sociocultural, and environmental influences on ADRD disparities in rural settings. Results: A range of individual, interpersonal, and community factors were identified, including strengths of rural residents in facilitating healthy aging lifestyle interventions. Discussion: A location dynamics model and ADRD-focused future directions are offered for guiding rural practitioners, researchers, and policymakers in mitigating rural disparities. Highlights: Rural residents face heightened Alzheimer's disease and related dementia (ADRD) risks and burdens due to health disparities. Defining the unique rural barriers and facilitators to cognitive health yields insight. The strengths and resilience of rural residents can mitigate ADRD-related challenges. A novel "location dynamics" model guides assessment of rural-specific ADRD issues.

Architected materials such as lattices are capable of demonstrating extraordinary mechanical performance. Lattices are often used for their stretch-dominated behavior, which gives them a high degree of stiffness at low-volume fractions. At the other end of the stiffness spectrum, bending-dominated lattices tend to be more compliant and are of interest for their energy absorption performance. Here, we report a class of ultra-compliant interwoven lattices that demonstrate up to an order of magnitude improvement in compliance over their traditional counterparts at similar volume fractions. This is achieved by selectively decoupling nodes and interweaving struts in bending-dominated lattices, inspired by observations of this structural principle in the lattice-like arrangement of the Venus flower basket sea sponge. By decoupling nodes in this manner, we demonstrate a simple and near-universal design strategy for modulating stiffness in lattice structures and achieve among the most compliant lattices reported in the literature.

Astragalus is the largest flowering plant genus. We assembled the plastid genomes of four Astragalus species (Astragalus iranicus, A. macropelmatus, A. mesoleios, A. odoratus) using next-generation sequencing and analyzed their plastomes including genome organization, codon usage, nucleotide diversity, prediction of RNA editing and etc. The total length of the newly sequenced Astragalus plastomes ranged from 121,050 bp to 123,622 bp, with 110 genes comprising 76 protein-coding genes, 30 transfer RNA (tRNA) genes and four ribosome RNA (rRNA) genes. Comparative analysis of the chloroplast genomes of Astragalus revealed several hypervariable regions comprising three non-coding sites (trnQ(UUG)-accD, rps7 -trnV(GAC) and trnR(ACG)-trnN(GUU)) and four protein-coding genes (ycf1, ycf2, accD and clpP), which have potential as molecular markers. Positive selection signatures were found in five genes in Astragalus species including rps11, rps15, accD, clpP and ycf1. The newly sequenced species, A. macropelmatus, has an approximately 13-kb inversion in IR region. Phylogenetic analysis based on 75 protein-coding gene sequences confirmed that Astragalus form a monophyletic clade within the tribe Galegeae and Oxytropis is sister group to the Coluteoid clade. The results of this study may helpful in elucidating the chloroplast genome structure, understanding the evolutionary dynamics at genus Astragalus and IRLC levels and investigating the phylogenetic relationships. Moreover, the newly plastid genomes sequenced have been increased the plastome data resources on Astragalus that can be useful in further phylogenomic studies.

The recent concurrence of electrical grid failure events in time with extreme temperatures is compounding the population health risks of extreme weather episodes. Here, we combine simulated heat exposure data during historical heat wave events in three large U.S. cities to assess the degree to which heat-related mortality and morbidity change in response to a concurrent electrical grid failure event. We develop a novel approach to estimating individually experienced temperature to approximate how personal-level heat exposure changes on an hourly basis, accounting for both outdoor and building-interior exposures. We find the concurrence of a multiday blackout event with heat wave conditions to more than double the estimated rate of heat-related mortality across all three cities, and to require medical attention for between 3% (Atlanta) and more than 50% (Phoenix) of the total urban population in present and future time periods. Our results highlight the need for enhanced electrical grid resilience and support a more spatially expansive use of tree canopy and high albedo roofing materials to lessen heat exposures during compound climate and infrastructure failure events.

A growing body of evidence has documented the effects of discrimination among Latinos. However, little is known about the impacts a noxious sociopolitical climate can have on their health and health care outcomes. The present study explored the associations between perceived anti-immigrant climate, health care discrimination, and satisfaction with care among US Latino adults. We used data from the 2015 Latino National Health and Immigration Survey (n = 1,284), a nationally representative sample of US Latino adults (ages 18 and older). Key predictors included living in a state whose policies are unfavorable towards immigrants, perceived anti-immigrant climate and/or anti-Hispanic climate, and health care discrimination. Ordered logistic regression models evaluated the associations between these predictors (adjusting for other relevant covariates) and satisfaction with care. Latinos living in state that is unfavorable towards immigrants were less likely to be satisfied with medical care they receive. Also, we found that Latinos living in anti-immigrant and anti-Hispanic climates were less likely to be satisfied with care. In both cases, experiencing health care discrimination significantly reduced the odds of satisfaction with care. Latinos' perception of an anti-immigrant & anti-Hispanic climate and state policies can have detrimental effects on their health and health care outcomes. These results highlight the importance of addressing both community-wide and interpersonal discrimination specific to health care settings, which can have concurrent impacts on the health and well-being of Latino and other minoritized populations.

This article seeks to spark a conversation and further debate through the 15 papers and 3 commentaries comprising this special issue entitled “Indigenous Research Sovereignty.” By inviting the authors to publish in this special edition and address Indigenous Research Sovereignty from a variety of viewpoints, we have brought together a collection that inspires, transforms, and expands on the ways in which Indigenous and non-Indigenous researchers are engaging with Indigenous communities to address the research agendas of communities across the globe. Through our work together over the past 8 years, the editorial team have identified eight themes within this broad concept of Indigenous Research Sovereignty. This article provides an introduction to those eight themes in the broadest strokes, while the papers and commentaries explore and refine them with significant depth. We seek to spark a conversation, we do not intend to provide answers to any of the dilemma facing Indigenous communities as they engage, or choose not to engage, in research. Our primary goal is to express an all-encompassing concern for the protection of Indigenous Communities’ inherent rights and knowledges.

White children's effortful control (EC), parents' implicit racial attitudes, and their interaction were examined as predictors of children's prosocial behavior toward White versus Black recipients. Data were collected from 171 White children (55% male, Mage = 7.13 years, SD = 0.92) and their parent in 2017. Prosocial behavior toward White peers was predicted by children's higher EC. When predicting prosocial behavior toward Black peers and prosocial disparity (the difference between White and Black recipients), parents' implicit racial attitudes moderated the relation between children's EC and children's prosocial behavior. Specifically, children's EC was positively associated with prosocial behavior toward Black peers (and negatively related to inequity in prosocial behavior) only when parents exhibited less implicit racial bias.

An independent set (IS) is a set of vertices in a graph such that no edge connects any two vertices. In adiabatic quantum computation [E. Farhi, et al., Science 292, 472-475 (2001); A. Das, B. K. Chakrabarti, Rev. Mod. Phys. 80, 1061-1081 (2008)], a given graph G(V, E) can be naturally mapped onto a many-body Hamiltonian [Formula: see text], with edges [Formula: see text] being the two-body interactions between adjacent vertices [Formula: see text]. Thus, solving the IS problem is equivalent to finding all the computational basis ground states of [Formula: see text]. Very recently, non-Abelian adiabatic mixing (NAAM) has been proposed to address this task, exploiting an emergent non-Abelian gauge symmetry of [Formula: see text] [B. Wu, H. Yu, F. Wilczek, Phys. Rev. A 101, 012318 (2020)]. Here, we solve a representative IS problem [Formula: see text] by simulating the NAAM digitally using a linear optical quantum network, consisting of three C-Phase gates, four deterministic two-qubit gate arrays (DGA), and ten single rotation gates. The maximum IS has been successfully identified with sufficient Trotterization steps and a carefully chosen evolution path. Remarkably, we find IS with a total probability of 0.875(16), among which the nontrivial ones have a considerable weight of about 31.4%. Our experiment demonstrates the potential advantage of NAAM for solving IS-equivalent problems.

Translocation, often a management solution reserved for at-risk species, is a highly time sensitive intervention in the face of a rapidly changing climate. The definition of abiotic and biotic habitat requirements is essential to the selection of appropriate release sites in novel environments. However, field-based approaches to gathering this information are often too time intensive, especially in areas of complex topography where common, coarse-scale climate models lack essential details. We apply a fine-scale remote sensing-based approach to study the 'akikiki (Oreomystis bairdi) and 'akeke'e (Loxops caeruleirostris), Hawaiian honeycreepers endemic to Kaua'i that are experiencing large-scale population declines due to warming-induced spread of invasive disease. We use habitat suitability modeling based on fine-scale lidar-derived habitat structure metrics to refine coarse climate ranges for these species in candidate translocation areas on Maui. We found that canopy density was consistently the most important variable in defining habitat suitability for the two Kaua'i species. Our models also corroborated known habitat preferences and behavioral information for these species that are essential for informing translocation. We estimated a nesting habitat that will persist under future climate conditions on east Maui of 23.43 km2 for 'akikiki, compared to the current Kaua'i range of 13.09 km2 . In contrast, the novel nesting range for 'akeke'e in east Maui was smaller than its current range on Kaua'i (26.29 km2 versus 38.48 km2 , respectively). We were also able to assess detailed novel competitive interactions at a fine scale using models of three endemic Maui species of conservation concern: 'ākohekohe (Palmeria dolei), Maui 'alauahio (Paroreomyza montana), and kiwikiu (Pseudonestor xanthophrys). Weighted overlap areas between the species from both islands were moderate (<12 km2 ) and correlations between Maui and Kaua'i bird habitat were generally low, indicating limited potential for competition. Results indicate that translocation to east Maui could be a viable option for 'akikiki but would be more uncertain for 'akeke'e. Our novel multi-faceted approach allows for the timely analysis of both climate and vegetation structure at informative scales for the effective selection of appropriate translocation sites for at-risk species.

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