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Background: HIV risk behavior in women who use drugs is related to myriad psychosocial issues, including incarceration. The experience of incarceration elevates women’s HIV risk by disrupting social networks, housing, employment, and access to health care. During the COVID-19 pandemic, changes in criminal-legal practices resulted in decreased incarceration, especially among women. These changes may have largely altered HIV risk among women who use drugs, depending on their access to care in the community. Objective: This study seeks to build knowledge about the impact of shifts in criminal-legal practices during the COVID-19 pandemic on HIV risk behaviors of justice-involved women who use drugs. Methods: Qualitative methods are used to gather and analyze women’s narratives about their life experiences before and during the COVID-19 pandemic, with a focus on individual and structural determinants of HIV risk behaviors. Thirty formerly incarcerated women with a history of substance use are being recruited through collaboration with community partners. Each participant completes a sociodemographic survey and two interviews. The first interview uses a life history instrument that invites participants to reflect on key turning points in their lives. The second interview uses a calendar approach to gather information about participants’ lives during the first year of the COVID-19 pandemic (March 2020-March 2021). The interviews (1 hour each) are audio-recorded and transcribed for analysis. Rapid Qualitative Inquiry and thematic analysis are being used to manage, organize, and interpret the data. The study team will collaborate with a subset of participants to develop digital stories about their COVID-19 experiences, a process that allows for member-checking and triangulation. Findings will be disseminated to program and policy makers in academic venues, community settings, and social service agencies. Results: To date, 10 women’s data have been collected. In total, two themes have been identified in this preliminary data: (1)the chaos and instability of participants’ lives increased during the COVID-19 pandemic: participants reported a wide range of psychosocial and health problems and limited engagement with social service systems. Interaction with criminal-legal systems was rife with uncertainty; participants described living in a state of limbo, which was extremely stressful. (2) When asked to describe a “turning point” in their lives, many participants attributed their substance use to the traumatic loss of a child due to death, incarceration, or termination of parental rights. During the COVID-19 pandemic, participants’ struggles to cope with these unresolved experiences of grief and loss were intensified by the widespread death and dying of the pandemic. Conclusions: Preliminary findings suggest that HIV risk factors increased for participants during the COVID-19 pandemic and invite further investment in community-based harm reduction programs, especially housing, that support women who use drugs. Interventions that address experiences of maternal grief and loss may reduce women’s substance use. Trial Registration:

Despite the persistence of breastfeeding racial and ethnic disparities in the United States, little is known about Black fathers' perceptions of breastfeeding and breastfeeding support services (e.g., maternity hospital-based care and lactation management care). This qualitative, community-based participatory research study reports Black fathers' perceptions of barriers and facilitators to breastfeeding, including the provision of breastfeeding support services in Connecticut. A focus group guide was co-developed with community partners and adapted from the Barrier Analysis Tool to identify breastfeeding facilitators, barriers, and service improvement areas. Four focus groups were conducted with 30 Black fathers who were Connecticut residents with a child under 3 years old. Qualitative data were analyzed using rapid template analysis involving deductive and inductive coding. We identified factors influencing breastfeeding and fathers' ability to support breastfeeding across all levels of the Socio-Ecological Model. Facilitators included high paternal breastfeeding knowledge, paternal breastfeeding involvement, parents' shared decision-making, extensive maternity hospital discharge support, ongoing breastfeeding support into the postnatal period, availability of community breastfeeding resources, and designated spaces for public breastfeeding. Barriers included low paternal breastfeeding knowledge, familial discouragement, insufficient prenatal breastfeeding education, exclusion of the father from breastfeeding support services, and stigma against breastfeeding in public. Understanding breastfeeding perceptions among members of a mother's support network, including their partners, is key for developing effective person- and family-centered breastfeeding education and counseling services that are well coordinated from the prenatal to postnatal periods with strong direct engagement from fathers.

This research examines the impact of generative artificial intelligence (AI) on the perception of educational content quality, specifically by comparing AI-generated and human-generated course syllabi in marketing education. Results from four studies indicate a general preference for AI-generated syllabi, attributed to their greater perceived objectivity. This preference is more pronounced in conventional courses but diminishes in unconventional ones, suggesting that the unique aspects of these courses may reduce the advantages of generative AI. In addition, disclosing the AI authorship of syllabi significantly affects their perceived quality negatively, underscoring the impact of transparency on the acceptance of AI-generated educational materials. These findings highlight the potential of generative AI in educational content creation and its limitations in certain contexts. They offer valuable insights for enhancing educational practices and shaping policy decisions to enrich student experiences in the era of AI integration.

The purpose of this study is to learn more about virtual reality (VR) and augmented reality (AR) practices at the United States’ top one hundred university libraries, as well as how they are engaging with the metaverse. We conducted qualitative and descriptive analysis on the websites of the top one hundred university libraries in the United States to determine the application fields and application proportions of VR and AR technologies and found good practice examples of using VR and AR technologies in this field. The findings show that 86 percent of the top one hundred US university libraries have implemented VR and AR technologies, with practice areas focused on: VR/AR studio and VR/AR makerspace; immersive learning services and virtual exhibitions/conference services; visual geographic information system and VR navigation services; virtual reading services and visual retrieval services; and VR reference services. The study provides university library administrators and professionals with the most up-to-date information and best practices of VR and AR engagement areas and the proportion of use, which can aid in the development of strategies to leverage VR and AR technologies to improve patron service and embrace the metaverse for the communities they serve.

Insomnia is more frequently reported in stroke survivors but its independent role in mortality in stroke survivors is unknown. The purpose of this study was to investigate the association of insomnia symptoms with all-cause mortality among stroke survivors.

We report the systematic measurement of protons and light nuclei production in Au +Au collisions at √𝑠𝑁⁢𝑁=3GeV by the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). The transverse momentum (𝑝𝑇) spectra of protons (𝑝), deuterons (𝑑), tritons (𝑡), 3He, and 4He have been measured from midrapidity to target rapidity for different collision centralities. We present the rapidity and centrality dependence of particle yields (𝑑⁢𝑁/𝑑⁢𝑦), average transverse momentum (⟨𝑝𝑇⟩), yield ratios (𝑑/𝑝, 𝑡/𝑝,3He/𝑝, 4He/𝑝), as well as the coalescence parameters (𝐵2, 𝐵3). The 4⁢𝜋 yields for various particles are determined by utilizing the measured rapidity distributions, 𝑑⁢𝑁/𝑑⁢𝑦. Furthermore, we present the energy, centrality, and rapidity dependence of the compound yield ratios (𝑁𝑝×𝑁𝑡/𝑁2𝑑) and compare them with various model calculations. The physics implications of these results on the production mechanism of light nuclei and the QCD phase structure are discussed.

Flow coefficients (𝑣2 and 𝑣3) are measured in high-multiplicity 𝑝+Au, 𝑑+Au, and 3He+Au collisions at a center-of-mass energy of √𝑠𝑁⁢𝑁=200 GeV using the STAR detector. The measurements utilize two-particle correlations with a pseudorapidity requirement of |𝜂|< 0.9 and a pair gap of |Δ⁢𝜂|>1.0. The primary focus is on analysis methods, particularly the subtraction of nonflow contributions. Four established nonflow subtraction methods are applied to determine 𝑣𝑛, validated using the HIJING event generator. 𝑣𝑛 values are compared across the three collision systems at similar multiplicities; this comparison cancels the final-state effects and isolates the impact of initial geometry. While 𝑣2 values show differences among these collision systems, 𝑣3 values are largely similar, consistent with expectations of subnucleon fluctuations in the initial geometry. The ordering of 𝑣𝑛 differs quantitatively from previous measurements using two-particle correlations with a larger rapidity gap, which, according to model calculations, can be partially attributed to the effects of longitudinal flow decorrelations. The prospects for future measurements to improve our understanding of flow decorrelation and subnucleonic fluctuations are also discussed.

This assignment is designed to enhance resilience among students in leadership courses. It leverages the US Army’s Master Resilience Training (MRT) framework and positive psychology to develop resiliency skills.,A three-part experiential workshop integrates academic readings (providing a foundation of resilience concepts), explores the influence of personal identities on leadership and connects leadership skills with resilience concepts.,Participants reflect on self-awareness tools and positive psychology and create personalized action plans. Participants' resilience skills are enhanced with their personalized resiliency plan.,The program provides a structured approach to resilience training, which can be integrated into university curriculums. Students gain self-awareness and psychological tools to manage challenges, which are valuable for personal growth and professional development. There is a persistent gender gap in leadership, and for women to attain greater parity in leadership positions, resilience skills are imperative. By focusing on identity-related factors, the program prepares future leaders for challenges in attaining leadership positions.,This program is uniquely tailored for students aspiring to leadership positions, with an emphasis on the role of identity, such as gender, in leader emergence and overcoming related challenges.

This chapter aimed at exploring how technology-mediated project-based language learning (PBLL) could be leveraged to foster 24 language learners’ awareness of social justice issues. Specifically, the study examined students’ perceptions regarding the potential benefits and challenges of technology-mediated PBLL for promoting social justice in a Spanish course. We used a grounded, iterative design and Teacher Action Research to analyze the data that comprised student-generated products (i.e., memes and written descriptions) and students’ perceptions of the benefits and challenges of using social justice projects in a Spanish course. In addition to revealing an array of perceived benefits and challenges of social justice projects for learning Spanish, the findings suggested the importance of using short, authentic multimodal texts and providing micro-scaffolding.

This article addresses advances in the definition, diagnosis, and clinical features of ASD particularly as they affect adolescents. While advances in early diagnosis and treatment of autism have led to substantial improvements in outcomes (e.g., significantly higher levels of personal self-sufficiency and independence), challenges for adolescents with autism spectrum disorders (ASD) remain. Persistent social-communication abilities and intellectual disabilities can hamper prospects of future employment and increase risk for psychopathology including depression and mood disorder and issues surrounding gender identity. Biological issues emerge, as well, for many adolescents with ASD such as increased risk for seizure disorder. In comparison to the literature on preschool and school age children, the research base is much more limited for adolescents, and studies are needed to identify effective, evidence-based, intervention strategies for this population. © 2024 Elsevier Inc. All rights are reserved.

With the STAR experiment at the BNL Relativistic Heavy Ion Collider, we characterize sNN=200GeV p+Au collisions by event activity (EA) measured within the pseudorapidity range ηϵ[-5,-3.4] in the Au-going direction and report correlations between this EA and hard- and soft-scale particle production at midrapidity (ηϵ[-1,1]). At the soft scale, charged particle production in low-EA p+Au collisions is comparable to that in p+p collisions and increases monotonically with increasing EA. At the hard scale, we report measurements of high transverse momentum (pT) jets in events of different EAs. In contrast with the soft particle production, high-pT particle production and EA are found to be inversely related. To investigate whether this is a signal of jet quenching in high-EA events, we also report ratios of pT imbalance and azimuthal separation of dijets in high- and low-EA events. Within our measurement precision, no significant differences are observed, disfavoring the presence of jet quenching in the highest 30% EA p+Au collisions at sNN=200GeV. © 2024 American Physical Society.

In response to calls for research on the psychological mechanisms, such as perceptions and attitudes toward corporate citizenship, in promoting positive outcomes at work, this research presents a novel approach by empirically testing a calling conditioned path model from P perception of corporate CSR (P-CSR) to work engagement via meaningfulness under the theoretical framework of self-determination theory. Survey data collected from 224 corporate employees in the US were tested using the PROCESS plugin (version 4.3) in SPSS. The regression results supported the positive direct and indirect paths from employees’ P-CSR to meaningfulness and work engagement but not the conditioning effect of calling work orientation. This study’s unique findings, limitations, future research, and implications are discussed, expanding micro-CSR research and unboxing the management assumptions of employees as purposeful autonomous agents seeking consistent interpretations and authentic perceptions of organizational CSR activities during their sense-making processes. Non-confirming of the calling conditioning the path model shed light on it being a dynamic multi-dimensional and multi-level construct to be further researched. © 2024 by the authors.

Frequency importance functions quantify the contribution of spectral frequencies to perception. Frequency importance has been well-characterized for speech recognition in quiet and steady-state noise. However, it is currently unknown whether frequency importance estimates generalize to more complex conditions such as listening in a multi-talker masker or when targets and maskers are spatially separated. Here, frequency importance was estimated by quantifying associations between local target-to-masker ratios at the output of an auditory filterbank and keyword recognition accuracy for sentences. Unlike traditional methods used to measure frequency importance, this technique estimates frequency importance without modifying the acoustic properties of the target or masker. Frequency importance was compared across sentences in noise and a two-talker masker, as well as sentences in a two-talker masker that was either co-located with or spatially separated from the target. Results indicate that frequency importance depends on masker type and spatial configuration. Frequencies above 5 kHz had lower importance and frequencies between 600 and 1900 Hz had higher importance in the presence of a two-talker masker relative to a noise masker. Spatial separation increased the importance of frequencies between 600 Hz and 5 kHz. Thus, frequency importance functions vary across listening conditions.

Across three online studies, we examined the relationship between the Fear of Missing Out (FoMO) and moral cognition and behavior. Study 1 (N = 283) examined whether FoMO influenced moral awareness, judgments, and recalled and predicted behavior of first-person moral violations in either higher or lower social settings. Study 2 (N = 821) examined these relationships in third-person judgments with varying agent identities in relation to the participant (agent = stranger, friend, or someone disliked). Study 3 (N = 604) examined the influence of recalling activities either engaged in or missed out on these relationships. Using the Rubin Causal Model, we created hypothetical randomized experiments from our real-world randomized experimental data with treatment conditions for lower or higher FoMO (median split), matched for relevant covariates, and compared differences in FoMO groups on moral awareness, judgments, and several other behavioral outcomes. Using a randomization-based approach, we examined these relationships with Fisher Tests and computed 95% Fisherian intervals for constant treatment effects consistent with the matched data and the hypothetical FoMO intervention. All three studies provide evidence that FoMO is robustly related to giving less severe judgments of moral violations. Moreover, those with higher FoMO were found to report a greater likelihood of committing moral violations in the past, knowing people who have committed moral violations in the past, being more likely to commit them in the future, and knowing people who are likely to commit moral violations in the future.

We describe photometry improvements in the La Silla-Quest RR Lyrae star (RRLS) survey that enable it to reach distances from the Sun (d⊙) ∼140 kpc. We report the results of surveying ∼300 deg2 of sky around the large, low-surface-brightness Crater II dwarf spheroidal galaxy. At d⊙ &gt;80 kpc, we find a large overdensity of RRLS that extends beyond the traditional isophotal contours used for Crater II. The majority of these RRLS (34) have a linear distribution on the sky, extending over 15°, that runs through Crater II and is oriented along Crater II’s proper motion vector. We hypothesize that this unlikely distribution traces extended tidal streams associated with Crater II. To test this, we search for other Crater II stellar populations that should be in the streams. Using Gaia proper motion data, we isolate ≈ 17 candidate stars outside of Crater II that are consistent with being luminous stars from the Crater II Red Giant Branch (RGB). Their spatial distribution is consistent with the RRLS one. The inferred streams are long, spanning a distance range ∼80–135 kpc from the Galactic Centre. They are oriented at a relatively small-angle relative to our line of sight (∼25°), which means some stream stars are likely projected onto the main body of the galaxy. Comparing the numbers of RRLS and RGB candidate stars found in the streams to those in the main galaxy, we estimate Crater II has lost $\gtrsim 30~{{\rm per\ cent}}$ of its stellar mass.

Establishing an optimal datacenter selection policy within the cloud environment is paramount to maximize the performance of the cloud services. Service broker policy governs the selection of datacenters for user requests. In our research, we introduce an innovative approach incorporating the genetic algorithm with service broker policy to assist cloud services in identifying the most suitable datacenters for specific userbases. The effectiveness of our proposed genetic algorithm was rigorously evaluated through experiments conducted on CloudAnalyst platform. The results clearly indicate that our proposed algorithm surpasses existing service broker policies and previous research works done in this field in terms of reducing response time and data processing time. The results analysis validates its efficacy and potential for enhancing cloud service performance and reducing the cost of overall cloud infrastructure.

Despite being a fundamental concept, the field of supply chain management (SCM) exhibits a significant lack of consensus regarding the definition of supply chain flows (SCFLOWS). Additionally, there has been an over-reliance on three flows – material, information and finance – while various other flows crucial to SCM performance have been overlooked. Hence, the purpose of this study is twofold: (1) to explore the multi-dimensional nature of SCFLOWS and (2) to identify additional flows beyond the commonly acknowledged ones that are vital for SCM performance.,This study employs various qualitative methods as part of the abduction process. The methods include in-depth interviews with logistics professionals, a Delphi study involving SCM scholars and a focus group comprising airline industry practitioners.,Seven SCFLOWS dimensions are identified and presented as SCFLOWS framework. Also, two additional flows, i.e. human and capital equipment, are proposed as vital to SCM performance.,This is the first study to introduce SCFLOWS framework to achieve consensus in the field. By introducing two additional flows, it proposes extending the SCFLOWS boundary to include various flows overlooked previously but pertinent to SCM performance. The SCFLOWS framework serves as a systematic guide to validate additional flows and represents an important step towards building SCM theory.

Marker variables provide an efficacious means of post hoc detection of common method variance (CMV) in data. These variables are measured in the same way as substantive variables, but because they are conceptually unrelated to the variables of interest, they are believed to be a proxy for CMV. Although marker variables have demonstrated effectiveness, questions remain as to what they actually measure, and thus, why they work. This lack of knowledge prevents researchers from choosing appropriate marker variables to include in same source surveys. The purpose of this research is to determine how four different marker variables account for common rater effects which can cause CMV. A metacognitive approach is used to develop an empirical study using two samples, with a focus on the specific rater effects of mood state, transient mood, consistency motif, and illusory correlations. Findings indicate that these marker variables elicit similar respondent reactions and do not create a notable psychological separation between substantive variables. Additionally, there is evidence that respondents’ use of consistency motifs and illusory correlations influence substantive variable relations. Finally, using the confirmatory factor analysis marker technique, data from two samples indicate the presence of CMV, but not bias from CMV, indicating that the problem of artificially inflated results due to CMV may be overstated.

Atomic nuclei are self-organized, many-body quantum systems bound by strong nuclear forces within femtometre-scale space. These complex systems manifest a variety of shapes1–3, traditionally explored using non-invasive spectroscopic techniques at low energies4,5. However, at these energies, their instantaneous shapes are obscured by long-timescale quantum fluctuations, making direct observation challenging. Here we introduce the collective-flow-assisted nuclear shape-imaging method, which images the nuclear global shape by colliding them at ultrarelativistic speeds and analysing the collective response of outgoing debris. This technique captures a collision-specific snapshot of the spatial matter distribution within the nuclei, which, through the hydrodynamic expansion, imprints patterns on the particle momentum distribution observed in detectors6,7. We benchmark this method in collisions of ground-state uranium-238 nuclei, known for their elongated, axial-symmetric shape. Our findings show a large deformation with a slight deviation from axial symmetry in the nuclear ground state, aligning broadly with previous low-energy experiments. This approach offers a new method for imaging nuclear shapes, enhances our understanding of the initial conditions in high-energy collisions and addresses the important issue of nuclear structure evolution across energy scales. © The Author(s) 2024.