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We measure triangular flow relative to the reaction plane at 3 GeV center-of-mass energy in Au+Au collisions at the BNL Relativistic Heavy Ion Collider. A significant v3 signal for protons is observed, which increases for higher rapidity, higher transverse momentum, and more peripheral collisions. The triangular flow is essentially rapidity-odd with a slope at midrapidity, dv3/dy|(y=0), opposite in sign compared to the slope for directed flow. No significant v3 signal is observed for charged pions and kaons. Comparisons with models suggest that a mean field potential is required to describe these results, and that the triangular shape of the participant nucleons is the result of stopping and nuclear geometry.

Background: Perceptions of the US healthcare system can impact individuals' healthcare utilization, including vaccination intentions. This study examined the association between perceived racial-ethnic inequities in COVID-19 healthcare and willingness to receive the COVID-19 vaccine. Methods: This study used data from REACH-US, a nationally representative online survey of a large, diverse sample of U.S. adults (N=5145 January 26, 2021-March 3, 2021). Confirmatory factor and regression analyses examined a latent factor of perceived racial-ethnic inequities in COVID-19 healthcare, whether the factor was associated with willingness to receive the COVID-19 vaccine, and whether associations varied across racial-ethnic groups reported as probit estimates (B) and 95% confidence intervals (CIs). Results: Perceived racial-ethnic inequities in COVID-19 healthcare were highest among Black/African American adults (mean latent factor score: 0.65 ± 0.43) and lowest among White adults (mean latent factor score: 0.04 ± 0.67). Black/African American (B = -0.08; 95% CI = -0.19, 0.03) and Native Hawaiian/Pacific Islander (B = -0.08; 95% CI = -0.23, 0.07) adults who perceived greater racial-ethnic inequities in COVID-19 healthcare were less willing than participants who perceived lower inequities. In contrast, American Indian/Alaska Native (B = 0.15; 95% CI = -0.01, 0.30), Asian (B = 0.20; 95% CI = 0.08, 0.31), Hispanic/Latino (English language preference) (B = 0.22; 95% CI = 0.01, 0.43), Multiracial (B = 0.23; 95% CI = 0.09, 0.36), and White (B = 0.31; 95% CI = 0.19, 0.43) adults who perceived greater racial-ethnic inequities in COVID-19 healthcare were more willing to receive the COVID-19 vaccine than participants perceiving higher inequities. Conclusions: Greater perceived racial-ethnic inequities in COVID-19 healthcare were associated with less willingness to receive the COVID-19 vaccine among Black/African American and Native Hawaiian/Pacific Islander adults. © 2024 Lippincott Williams and Wilkins. All rights reserved.

Convolutional neural network (CNN) based deep learning is used to analyze spectral data collected by visible resonance Raman (VRR) spectroscopy to distinguish human glioma tumors from healthy brain tissues using binary classification and identify the cancer grades of the glioma tumors using multi-class classification. Classification was performed using both raw spectral data and baseline-subtracted data for comparison. The classification using both datasets yielded high accuracy, with the results obtained from baseline subtracted spectra slightly better than that obtained from raw spectra. The study showed VRR combined with deep learning provides a robust molecular diagnostic tool for accurately distinguishing glioma tumors from normal tissues and glioma tumor tissues at different cancer grades. Deep learning aided VRR technique may be used for in-situ intraoperative diagnosis of brain cancer. It may help a surgeon to identify cancer margins and even cancer grades during surgery. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

Human impacts on wild populations are numerous and extensive, degrading habitats and causing population declines across taxa. Though these impacts are often studied individually, wild populations typically face suites of stressors acting concomitantly, compromising the fitness of individuals and populations in ways poorly understood and not easily predicted by the effects of any single stressor. Developing understanding of the effects of multiple stressors and their potential interactions remains a critical challenge in environmental biology. Here, we focus on assessing the impacts of two prominent stressors associated with anthropogenic activities that affect many organisms across the planet – elevated salinity (e.g., from road de-icing salt) and temperature (e.g. from climate change). We examined a suite of physiological traits and components of fitness across populations of wood frogs originating from ponds that differ in their proximity to roads and thus their legacy of exposure to pollution from road salt. When experimentally exposed to road salt, wood frogs showed reduced survival (especially those from ponds adjacent to roads), divergent developmental rates, and reduced longevity. Family-level effects mediated these outcomes, but high salinity generally eroded family-level variance. When combined, exposure to both temperature and salt resulted in very low survival, and this effect was strongest in roadside populations. Taken together, these results suggest that temperature is an important stressor capable of exacerbating impacts from a prominent contaminant confronting many freshwater organisms in salinized habitats. More broadly, it appears likely that toxicity might often be underestimated in the absence of multi-stressor approaches. © 2024 Elsevier Ltd

Alumni from an Assistive Technology (AT) graduate program were invited to complete a survey and participate in focus groups to share how they are using the knowledge gained from their graduate degree and its impact on their professional careers. The sample of 27 alumni spanned seven years and a variety of professional backgrounds. This qualitative single-case study revealed impacts on careers, professional skill development, and technology skills after graduation. Participants also connected this later skill development to their concrete learning experiences within the graduate program.

The impact of trauma on mental health has led to the increased development of trauma-informed organizations. Little is known, however, about the benefits of using a trauma-informed care perspective within a faith-based setting, particularly among Latino communities. This article reviews the literature and identifies gaps suggesting the problem of a lack of mental health and trauma-informed awareness among places of worship. The need for developing trauma-informed ministries within places of worship is recommended to assist in promoting the psychological, emotional, and spiritual well-being of congregants and community members within faith-based settings. © 2024 Taylor & Francis.

Drug waste poses a real threat to human health and the environment. Therefore, recycling and sustainability scholars have recently sought practical solutions to the drug waste problem. Furthermore, several governments have made significant efforts to reduce the negative effects of waste, such as establishing programs to take back unwanted drugs (expired and unused) for recycling (i.e., drug reuse or drug redispersing). However, many of these programs have failed to achieve their goals. In this context, it is expected that creating green start-ups to collect unwanted drugs will contribute to solving this problem. Accordingly, this study aims to investigate the antecedents of intentions to create green start-ups for collecting unwanted drugs. To this end, the authors integrate start-up self-efficacy and drug waste collection-related knowledge constructs into the theory of planned behavior (TPB). Using a self-administered paper questionnaire and relying on a convenience sample, data were collected from 328 students in six Algerian universities. A hierarchical multiple regression was conducted to test the proposed study model. Theresults revealed that perceived behavioral control (PBC) (β = 0.187, p < 0.001), attitudes (β = 0.182, p = 0.002), start-up self-efficacy (β = 0.169, p = 0.001), drug waste collection-related knowledge (β = 0.161, p < 0.001), and subjective norms (β = 0.088, p < 0.05) have a positive significant effect on the intention to create a start-up to collect unwanted drugs. In conclusion, this paper contributes to reducing drug waste by investigating the drivers of intention to create green start-ups for collecting unwanted drugs. Therefore, our study is expected to provide valuable insights for hospitals, pharmacies, pharmaceutical manufacturers, environmental protection associations, and stakeholders interested in reverse logistics. © 2024 by the authors.

Background: Limited research has been done on nursing students’ awareness of racial disparities and their readiness to address bias and racism in clinical practice. Purpose: This study investigated nursing students' perceptions of how racial disparities affect health outcomes, including maternal outcomes, in the United States. Methods: Interpretive description was used and supported by the critical race theory as a framework to guide the data collection, analysis, and interpretation to understand participants’ perceptions surrounding racism and health disparities. Discussion: Nurse educators should guide students to look beyond individual behavioral and risk factors and consider systemic issues as a leading contributors to health disparities. Conclusion: The most critical finding was the lack of participants’ understanding of systemic racism and its impact on health disparities. While they often attributed racial disparities to low socioeconomic status and lack of education, they did not understand the relationships between social determinants of health and systemic racism. © 2024

This chapter presents Hybrid Whale Optimization Algorithm (HWOA) to tackle the stubborn problems of local optima traps and initialization sensitivity of the K-means clustering technique. This work was inspired by the popularity and robustness of meta-heuristic algorithms in providing compelling solutions, which sparked several effective approaches and computational tools to address challenging real-world problems. The Chameleon Swarm Algorithm (CSA) is embedded with the bubble-net mechanism of WOA to help the search agents of HWOA effectively explore and exploit each potential area of the search space, enhancing the capability of both exploitation and exploration aspects of the classic WOA. Additionally, the search agents of HWOA use a rotation mechanism to relocate to new spots outside of nearby areas to conduct global exploration. This process increases the search efficiency of WOA while also enhancing the diversity and intensity behavior of the search agents. These improvements to HWOA increase its capacity for exploitation and broaden the range of search scopes and directions in performing clustering tasks. To assess the effectiveness of the proposed HWOA on clustering activities, a total of ten distinct datasets from the UCI are used, each with a different level of complexity. According to the experimental findings, the proposed HWOA outperforms eight meta-heuristic algorithms-based clustering and the conventional K-means clustering technique by a statistically significant margin in terms of performance distance metric.

Human mesenchymal stem cells (hMSCs) have great potential in cell-based therapies and regenerative medicine due to their self-renewal and multipotency. hMSCs can be differentiated into several cell types, including adipocytes and osteblast. Conventional approaches for determining adipocyte formation include staining of lipid droplets (i.e., oil-red-O) during adipogenesis, which is time-consuming and uneconomical. Thus, there is an emerging need for a more effective and accurate approach to the prediction of adipogenic differentiation. Here, by combining live-cell imaging with a deep learning method, we developed a convolutional neural network-based approach to precisely predict lipid droplet formation during adipogenic differentiation of hMSCs. © 2023 IEEE.

Diabetes mellitus is a chronic disease affecting over 38.4 million adults worldwide. Unfortunately, 8.7 million were undiagnosed. Early detection and diagnosis of diabetes can save millions of people’s lives. Significant benefits can be achieved if we have the means and tools for the early diagnosis and treatment of diabetes since it can reduce the ratio of cardiovascular disease and mortality rate. It is urgently necessary to explore computational methods and machine learning for possible assistance in the diagnosis of diabetes to support physician decisions. This research utilizes machine learning to diagnose diabetes based on several selected features collected from patients. This research provides a complete process for data handling and pre-processing, feature selection, model development, and evaluation. Among the models tested, our results reveal that Random Forest performs best in accuracy (i.e., 0.945%). This emphasizes Random Forest’s efficiency in precisely helping diagnose and reduce the risk of diabetes.

The nostos, the return home in Greek mythology, is most often a journey over the sea, and it is the god Poseidon who rules the sea, both ensuring the safe passage of fishermen and sailors and causing disasters to individuals like Ajax son of Oileus, sometimes through obstacles like his daughter Charybdis. Most famously, he uses his power to hinder the nostos of Odysseus, all the while knowing he cannot prevent him from reaching home. This example illustrates how a god who may once have been the most powerful deity can no longer control ultimate results. As his power declines over the centuries, that of Zeus increases. It is also by sea that we see the ships in Isaiah 23, attempting to return to their homes in Sidon and Tyre on the eastern Mediterranean coast. In this Biblical passage from the eighth century BCE, the ships wail when they see that their seaport homes have been destroyed; there are no homes to which they can return. The great god of the Sea and the epichoric gods have failed to protect the cities which are considered their progeny. The Israelite prophet mocks their powerlessness and celebrates the power of his One God. There is no nostos, no homecoming for ships because they no longer have homes. Just as Poseidon could not prevent Odysseus from his nostos, the so-called Averter of Disaster has not prevented the disaster that has befallen his children. © 2023 Akadémiai Kiadó, Budapest.

We report results on an elastic cross section measurement in proton–proton collisions at a center-of-mass energy s=510 GeV, obtained with the Roman Pot setup of the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). The elastic differential cross section is measured in the four-momentum transfer squared range 0.23≤−t≤0.67 GeV2. This is the only measurement of the proton-proton elastic cross section in this t range for collision energies above the Intersecting Storage Rings (ISR) and below the Large Hadron Collider (LHC) colliders. We find that a constant slope B does not fit the data in the aforementioned t range, and we obtain a much better fit using a second-order polynomial for B(t). This is the first measurement below the LHC energies for which the non-constant behavior B(t) is observed. The t dependence of B is also determined using six subintervals of t in the STAR measured t range, and is in good agreement with the phenomenological models. The measured elastic differential cross section dσ/dt agrees well with the results obtained at s=540 GeV for proton–antiproton collisions by the UA4 experiment. We also determine that the integrated elastic cross section within the STAR t-range is σelfid=462.1±0.9(stat.)±1.1(syst.)±11.6(scale) μb. © 2024

Angular distributions of charged particles relative to jet axes are studied in sNN=200 GeV Au+Au collisions as a function of the jet orientation with respect to the event plane. This differential study tests the expected path-length dependence of energy loss experienced by a hard-scattered parton as it traverses the hot and dense medium formed in heavy-ion collisions. A second-order event plane is used in the analysis as an experimental estimate of the reaction plane formed by the collision impact parameter and the beam direction. Charged-particle jets with 15<pT,jet<20 and 20<pT,jet<40GeV/c were reconstructed with the anti-kT algorithm with radius parameter setting of R=0.4 in the 20-50% centrality bin to maximize the initial-state eccentricity of the interaction region. The reaction plane fit method is implemented to remove the flow-modulated background with better precision than prior methods. Yields and widths of jet-associated charged-hadron distributions are extracted in three angular bins between the jet axis and the event plane. The event-plane (EP) dependence is further quantified by ratios of the associated yields in different EP bins. No dependence on orientation of the jet axis with respect to the event plane is seen within the uncertainties in the kinematic regime studied. This finding is consistent with a similar experimental observation by ALICE in sNN = 2.76 TeV Pb-Pb collision data. © 2024 American Physical Society.

This paper presents the first curricular landscape analysis of transfer pathways for computer science (CS) transfer students in the public higher education system in California, the largest and most complex higher education system in the United States. Drawing on data from 115 community colleges and 31 public universities in California, this study examines and compares computer science Bachelor's degree requirements, curriculum complexities, and both ideal and existing course articulation coverage between schools. We find considerable variation in the CS degree requirements across the system, particularly in the number of math courses required and the overall flexibility of the course requirements. Articulation agreements between community colleges and four-year schools have the potential to (and sometimes do) reduce the complexity of the degree for transfer students significantly, but articulation agreements are not consistently in place across the system. This research both suggests concrete action items and surfaces important areas of further exploration to create a more seamless process for transfer students to complete their CS Bachelor's degrees.

The rising prevalence of autism spectrum disorder (ASD) has led to increased efforts to support individuals with ASD across numerous aspects of life, including driving. While obtaining a driver’s license substantially impacts quality of life and independence, it also creates distinct challenges for those with ASD. Challenges surrounding social communication, executive functioning, and sensory sensitivities are particularly evident when considering interactions between drivers with ASD and law enforcement personnel. Connecticut’s Blue Envelope Program aims to improve interactions between drivers with and ASD law enforcement by providing instructions for officers and drivers to follow during routine traffic stops on a physical, blue colored, envelope. The instructional guidelines aim to assist officers in understanding and appropriately responding to common ASD-related behaviors which may be otherwise misinterpreted and includes accommodations officers could consider during a stop. Additionally, the envelope outlines clear steps for drivers with ASD to follow through the stop as to support predictability and expectations. The widespread acceptance, efficacy and popularity of the Blue Envelope program underscores the importance of increasing awareness and understanding of ASD among law enforcement and the need for more supports to aid in these increasing interactions. Discussion is offered on a broader implementation of this program to support individuals with ASD and officers, while improving the outcomes of interactions. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

(a) Situation faced: The Tour de France, with more than a century of history, provides great opportunities for raising awareness of socially responsible behaviors among citizens, not only from France but also from other regions in the world; (b) Action taken: The Tour de France is committed to the future. Responsible actions are deployed in three main axons: sustainable transportation, commitment with the charter of 15 eco-friendly commitments, and specific in-route measures; (c) Results achieved: Currently, the Tour de France is a leading sport event in terms of Corporate Social Responsibility. Their actions positively influence large social masses from all over the world; (d) Lessons learned: This case provides good examples of a socially responsible sport event that spreads messages to national and international spectators. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

Ageism, discrimination based on age, particularly against older adults, intersects with other forms of discrimination, including sexism. In long-term care settings, gendered ageism can manifest in various ways, influencing both the quality and type of care older adults receive based on their gender. Understanding and addressing ageism in these settings is essential to ensuring the dignity, respect, and quality of life for older adults. The purpose of this mixed methods study was to explore long-term care (LTC) employees&rsquo; attitudes towards age and gender. A theoretical framework of feminist disability theory and compulsory youthfulness allows for an intersectional critique of ageism, sexism, and ableism and how each contributes to the oppression of long-living adults (age 80 and over) and disabled long-living adults. Triangulation of data was achieved through surveys, interviews, and artifacts. Sixty employees completed an on-line survey consisting of demographic questions (age, race, gender, years employed in LTC, highest level of education, employment) and the Fraboni Scale of Ageism during the Coronavirus pandemic between August 21, 2020 and September 22, 2020. Data were analyzed using an independent samples t-test, One Way ANOVA, and One Sample Median Test. Twenty-one of these employees also participated in a phone interview during the time period of survey collection. Interview data were analyzed using open coding, axial coding, then thematic analysis. Cultural artifacts available to the primary researcher, and relating to the study, were noted. Considering the primary researcher was not allowed to enter the facility, the types of artifacts collected included social media posts via Twitter, Facebook, and the organization&rsquo;s blog. Blog and social media posts ranged from September 1, 2020 to February 1, 2021. Mixing of qualitative and quantitative data was completed for the final results by merging them via side by side comparison table. Quantitative findings indicated there was a statistical difference in FSA scores for younger adults (M = 49.33, SD = 6.08), adults (M = 52.97, SD = 8.66), and older adults (M = 46.76, SD = 7.85). Middle age adults had significantly higher FSA scores than younger adults and older adults. Qualitative data provided the strongest connection that sexist and ageist attitudes exist among employees as it demonstrated that some employees had different expectations of residents based on the residents&rsquo; gender. A review of social media and policy artifacts concluded there was no resident perspective present in research topics, research trials, blog posts, or community events. Overall, findings indicated employees&rsquo; interactions with, and attitudes towards, residents were influenced by themes of compassionate ageism, ableism, and identity, which resulted in meta-theme caregiver validation and reward. Although most employees felt a deep connection with residents, they detached themselves from the aging process, instead seeking affirmation and recognition from residents through gratitude and positive interactions. Results from this study indicated certain power dynamics and suggested that employees actively sought positive care interactions with residents. Most employees preferred to care for residents who appeared to need assistance, were appreciative, and interacted with the employee in a positive way. When this occurred, employees enjoyed relationships with these residents and caring for them on a continuous basis. Essentially, employees preferred to care for someone who conformed to that employee&rsquo;s expectations for care.

Studying ADA accessibility at library websites of top universities selected from the U.S. News and World Report, the authors used WAVE and AChecker to assess data in compliance with WCAG 2.0 standards. Almost 8 out of 10 public university academic libraries reported accessibility errors as one of the major findings. Low color contrast was becoming a more commonly occurring accessibility issue, making it difficult for people with vision impairments to perceive the color of the image. The outcomes of the study suggest that academic libraries around the world should continue improving their website accessibility.