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We report directed flow (v1) of multistrange baryons (Ξ and Ω) and improved v1 data for K−, p¯, Λ¯ and ϕ in Au+Au collisions at sNN=27 and 200 GeV from the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). We focus on particles whose constituent quarks are not transported from the incoming nuclei but instead are produced in the collisions. At intermediate impact parameters, we examine quark coalescence behavior for particle combinations with identical quark content, and search for any departure from this behavior (“splitting”) for combinations having non-identical quark content. Under the assumption of quark coalescence for produced quarks, the splitting strength appears to increase with the electric charge difference of the constituent quarks in the combinations, consistent with electromagnetic effect expectations.

An analysis of how national narratives are inevitably forms of epistemic injustice, depriving individuals of epistemic and moral agency. Denying access to knowledge about the past is a tool of all autocratic regimes, commonly used for the purpose of retaining power and exerting dominance over individuals or groups subordinate to the ruling elite. Yet such narratives and the falsifications used to buttress them, are not the exclusive instruments of autocracies but can be found to pervade the national narratives of what we often nominally label as democracies. The denial of crimes against humanity and genocide are the most egregious examples of the harms perpetrated against victims and survivors. Miranda Fricker’s writings on epistemic injustice are employed in the analysis. Turkish and Azerbaijani genocide denial of the Armenian Genocide are used to illustrate how epistemic injustice lies at the heart of denialism. © 2024 Central European Pragmatist Forum. All rights reserved.

We report the differential yields at mid-rapidity of the Breit-Wheeler process (𝛾⁢𝛾→𝑒+⁢𝑒−) in peripheral Au+Au collisions at √𝑠𝑁⁢𝑁=54.4 and 200 GeV with the STAR experiment at the Relativistic Heavy Ion Collider (RHIC), as a function of energy √𝑠𝑁⁢𝑁, 𝑒+⁢𝑒− transverse momentum 𝑝T, 𝑝2T, invariant mass 𝑀𝑒⁢𝑒, and azimuthal angle. In the invariant mass range of 0.4<𝑀𝑒⁢𝑒<2.6GeV/𝑐2 at low transverse momentum (𝑝T<0.15GeV/𝑐), the yields increase while the pair √⟨𝑝2T⟩ decreases with increasing √𝑠𝑁⁢𝑁, a feature that is correctly predicted by the QED calculation. The energy dependencies of the measured quantities are sensitive to the nuclear form factor, infrared divergence and photon polarization. The data are compiled and used to extract the charge radius of the Au nucleus.

The percentage of US youths experiencing mental health and substance use problems has risen rapidly in recent years. Schools are important settings for prevention, but whether preventive programming meets student needs is unknown. This study examined trends in school programming related to mental health and substance use and teacher professional development across US middle and high schools from 2008-2020.

The Gona Paleoanthropological Research Project area in the Afar Region of Ethiopia arguably contains one of the most complete records of archaeological sites anywhere in the world, from the earliest Oldowan dated to 2.6 Ma, to the Later Stone Age (LSA) dated to ca. 12-7 Ka. This makes Gona an ideal place to examine long-term trends in hominin-environment interaction. We revisited archaeological and hominin fossil sites at Gona and characterized the fossil soils using paleopedology and found evidence of paleo-Fluvisols, -Cambisols and -Vertisols. Greater than 70% of those archaeological sites spanning Oldowan to the Later Stone Age are found in buried paleosols with A-C and A-Bk-C paleosol profiles resembling modern-day Fluvisols or Fluvic Cambisols. Fluvisol morphology shows presence of bedding, incipient soil structure development and overprinting after burial. Stratigraphy and lithofacies show that these paleo-Fluvisols were proximal to the ancestral Awash River (Type I depositional system) or a distal fan channel (Type II depositional system). These data suggest that soil burial rates were rapid due to proximal flooding, where this would be a primary factor inhibiting soil development. This style of sedimentation and weathering resembles a narrow (5–10 m width) strip of land in a modern-day channel shelf and bar setting, separating the river from the adjacent gallery forest. A review of the literature shows that the frequent association of artifacts with paleo-Fluvisols may be prevalent throughout eastern Africa and indicates a long history of hominin reliance on a riverine ecosystem edge, proximal stream water and gallery forest resources within broader river valleys. The few older archaeological sites (e.g., Oldowan and Acheulian) found in/on more well-developed paleosols at Gona are an exception to this rule. These latter sites may hint at different land-use patterns and thus differing trajectories of hominin-environmental interactions. Because most paleosol studies at Gona and elsewhere in eastern Africa use paleo-Vertisols or other more well-developed calcareous soils to reconstruct paleoenvironment, there is a potential spatial and temporal decoupling between those well-studied paleosols and the more weakly-developed ones where archaeology is found.

Fieldwork is often cited as one of the most important and effective parts of geography education, despite increasing scrutiny over its environmental and financial cost. As a result, it is imperative that any overseas fieldwork is as impactful as possible, enabling deep experiential learning. Here, we investigate the success of a joint field trip (Liverpool John Moores University, UK and Southern Connecticut State University, USA) to East Iceland. Such field trips are rare but have the potential to be extremely impactful on both cohorts of students. We outline the origins of the field trip, the considerations taken into account during planning, and the student skills we embedded into teaching. Surveys and interviews demonstrated that the field trip was highly successful, with students reporting excellent development of environmental and global awareness as well as research and leadership skills. Students also developed strong, lasting social networks, including those in the alternate university, and in Iceland. Cohorts responded similarly, suggesting that the trip presents similar opportunities to all students. We demonstrate that undertaking a joint field trip can deliver huge benefits to students, becoming a “perspective changing, and a once in a lifetime opportunity” affecting future study and career choices.

In heavy-ion collision experiments, the global collectivity of final-state particles can be quantified by anisotropic flow coefficients (𝑣𝑛). The first-order flow coefficient, also referred to as the directed flow (𝑣1), describes the collective sideward motion of produced particles and nuclear fragments in heavy-ion collisions. It carries information on the very early stage of the collision, especially at large pseudorapidity (𝜂), where it is believed to be generated during the nuclear passage time. Directed flow therefore probes the onset of bulk collective dynamics during thermalization, providing valuable experimental guidance to models of the pre-equilibrium stage. In 2018, the Event Plane Detector (EPD) was installed in STAR and used for the Beam Energy Scan phase-II (BES-II) data taking. The combination of EPD (2.1<|𝜂|<5.1) and high-statistics BES-II data enables us to extend the 𝑣1 measurement to the forward and backward 𝜂 regions. In this paper, we present the measurement of 𝑣1 over a wide 𝜂 range in Au+Au collisions at √𝑠𝑁⁢𝑁= 19.6 and 27 GeV using the STAR EPD. The results of the analysis at √𝑠𝑁⁢𝑁= 19.6 GeV exhibit excellent consistency with the previous PHOBOS measurement, while elevating the precision of the overall measurement. The increased precision of the measurement also revealed finer structures in heavy-ion collisions, including a potential observation of the first-order event-plane decorrelation. Multiple physics models were compared to the experimental results. Only a transport model and a three-fluid hybrid model can reproduce a sizable 𝑣1 at large 𝜂 as was observed experimentally. The model comparison also indicates 𝑣1 at large 𝜂 might be sensitive to the QGP phase transition.

Obstructive Sleep Apnea (OSA) is a prevalent health issue affecting 10-25% of adults in the United States (US) and is associated with significant economic consequences. Machine learning methods have shown promise in improving the efficiency and accessibility of OSA diagnoses, thus reducing the need for expensive and challenging tests. A comparative analysis of Logistic Regression (LR), Support Vector Machine (SVM), Gradient Boosting (GB), Gaussian Naive Bayes (GNB), Random Forest (RF), and K-Nearest Neighbors (KNN) algorithms was conducted to predict Obstructive Sleep Apnea (OSA). To improve the predictive accuracy of these models, Random Oversampling was applied to address the imbalance in the dataset, ensuring a more equitable representation of the minority class. Patient demographics, including age, sex, height, weight, BMI, neck circumference, and gender, were employed as predictive features in the models. The RFC provided outstanding training and testing accuracies of 87% and 65%, respectively, and a Receiver Operating Characteristic (ROC) score of 87%. The GBC and SVM classifiers also demonstrated good performance on the test dataset. The results of this study show that machine learning techniques may be effectively used to diagnose OSA, with the Random Forest Classifier demonstrating the best results.

This chapter explores the impact of implementing a partnership agreement to grant incoming university students credit based on their documented language proficiency. In 2018, an agreement was forged between an urban university and public school district, and, by extension, any high school offering the Seal of Biliteracy (SoBL) to offer students who hold the SoBL university credit for their language proficiency in a world language. This chapter examines the evolution of that agreement over a five-year period and its potential impact on students’ decision to pursue a minor/major in Spanish. Through semi-structured interviews, we also examined multiple university stakeholders’ perceptions and/or experiences about the value of the SoBL, the agreement to grant credit by examination (CBE), as well as other challenges, including the university’s reduction of their language requirement, transitions in leadership, and differing ideas about if and how best to award students credit based on examination.

Objective Preterm birth (PTB) is one of the leading causes of infant and neonatal mortality. Prepregnancy body mass index (BMI; kg/m2) has been linked to PTB but the evidence of this association by weight gain during pregnancy, race, and ethnicity is limited. This study aimed to assess the association between maternal prepregnancy BMI and PTB stratified by weight gain during pregnancy, race, and ethnicity. Study Design The U.S. natality data from 2017 to 2021 were used. In this analysis, we included mothers who had a live singleton birth and available data for prepregnancy BMI, gestational age at birth, weight gain during pregnancy, race, and ethnicity. Logistic regression models were used to assess the association between prepregnancy BMI categories and PTB stratified by weight gain during pregnancy, race, and ethnicity. Results A total of 17,311,509 singleton live births were included of which 1,393,889 (8.05 %) were PTBs. After adjusting for confounders, compared with normal prepregnancy BMI mothers (18.5–24.9), those with underweight BMI (<18.5) were at increased odds of PTB regardless of weight gain during pregnancy, race, and ethnicity. However, for mothers with a prepregnancy BMI above the normal weight (≥25), the association between prepregnancy BMI and PTB differs by weight gain during pregnancy, race, and ethnicity. Asian mothers with obesity II (35.0–39.9) had 93% (odds ratio [OR] = 1.93, 95% confidence interval [CI]: 1.62–2.30) increased odds of PTB for weight gain during pregnancy of 31 to 40 pounds. Their White, Hispanic, and Black counterparts experienced lower odds of PTB for similar weight gain during pregnancy (White: OR = 1.56, 95% CI: 1.51–1.60; Hispanic: OR = 1.48, 95% CI: 1.41, 1.54; and Black: OR = 1.22, 95% CI: 1.17–1.27). Conclusion Mothers with underweight BMI were at increased risk of PTB regardless of weight gain during pregnancy, race, and ethnicity. However, the association between high prepregnancy BMI and PTB varied by weight gain during pregnancy, race, and ethnicity. Key Points

Background: In the United States, chronic obstructive pulmonary disease (COPD) is a significant cause of mortality. As far as we know, it is a chronic, inflammatory lung condition that cuts off airflow to the lungs. Many symptoms have been reported for such a disease: breathing problems, coughing, wheezing, and mucus production. Patients with COPD might be at risk, since they are more susceptible to heart disease and lung cancer. Methods: This study reviews COPD diagnosis utilizing various machine learning (ML) classifiers, such as Logistic Regression (LR), Gradient Boosting Classifier (GBC), Support Vector Machine (SVM), Gaussian Naïve Bayes (GNB), Random Forest Classifier (RFC), K-Nearest Neighbors Classifier (KNC), Decision Tree (DT), and Artificial Neural Network (ANN). These models were applied to a dataset comprising 1603 patients after being referred for a pulmonary function test. Results: The RFC has achieved superior accuracy, reaching up to 82.06% in training and 70.47% in testing. Furthermore, it achieved a maximum F score in training and testing with an ROC value of 0.0.82. Conclusions: The results obtained with the utilized ML models align with previous work in the field, with accuracies ranging from 67.81% to 82.06% in training and from 66.73% to 71.46% in testing.

Meta-heuristic optimization algorithms have become widely used due to their outstanding features, such as gradient-free mechanisms, high flexibility, and great potential for avoiding local optimal solutions. This research explored the grey wolf optimizer (GWO) to find the ideal configuration for a six-element Yagi–Uda antenna. The GWO algorithm adjusted the lengths of the antenna wires and the spacings between them. The goal was to maximize the antenna’s ability to transmit signals (throughput gain). Optimal antenna selection relies on various parameters, including gain, bandwidth, impedance matching, frequency, side-lobe levels, etc. The optimization of a six-element Yagi–Uda antenna presents a challenging engineering design problem due to its multimodal and nonlinear nature. Achieving optimal performance hinges on the intricate interplay between the lengths of the constituent elements and the spacing configurations. To this end, a multiobjective function was adopted to design this antenna. The performance of several meta-heuristic algorithms, including genetic algorithms, biogeography-based optimization, simulated annealing, and grey wolf optimizer, was compared. The GWO-based approach has performed better than its competitors. This optimized antenna design based on GWO reported a gain of 14.21 decibel. Therefore, the GWO-based method optimizes antennas that can be further investigated for other antenna design problems.

Structured faculty development programs focused on integrating health equity into medical education curricula remain limited.

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.