Search Results (549)

Background: Racial discrimination experiences are associated with the activation of stress biology pathways and signs of accelerated biological aging, including alterations in DNA methylation (DNAm). Coping strategies may mitigate stress from racial discrimination and protect against long-term adverse health outcomes. Methods: We conducted a secondary analysis of data from the Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure cohort, an all-African-American sample, to test the hypothesis that social support can protect against accelerated biological aging associated with experiences of racial discrimination. We measured biological aging from saliva DNAm using six epigenetic clocks. Clock values were residualized on participant age and the estimated proportion of epithelial cells contributing to the DNA sample and standardized to M = 0, SD = 1 within the analysis sample. The primary analysis was focused on the second-generation PhenoAge and GrimAge clocks and the third-generation DunedinPACE “speedometer,” which previous studies have linked with racial discrimination. Results: In our sample (n = 234; mean age = 31.9 years; SD = 5.80), we found evidence consistent with our hypothesis in the case of the PhenoAge clock, but not the other clocks. Among mothers who did not seek social support, experiences of racial discrimination were associated with an older PhenoAge (b = 0.26, 95% CI = 0.02–0.50, p = 0.03). However, social-support seeking mitigated this risk; at the highest levels of social support, no adverse consequences of discrimination were observed (interaction b = −0.01, 95% CI = −0.02–−0.00, p = 0.03). Conclusions: The replication of results is needed. Future research should also investigate additional adaptive and maladaptive coping strategies utilized by African American women and mothers to identify protective measures that influence health outcomes. Full article

With the development and application of artificial intelligence (AI) technology, autonomous driving systems are gradually being applied on the road. However, people still have requirements for the safety and reliability of unmanned vehicles. Autonomous driving systems in today’s unmanned vehicles also have to respond to information security attacks. If they cannot defend against such attacks, traffic accidents might be caused, leaving passengers exposed to risks. Therefore, we investigated adversarial attacks on the traffic sign recognition of autonomous vehicles in this study. We used You Look Only Once (YOLO) to build a machine learning model for traffic sign recognition and simulated attacks on traffic signs. The simulated attacks included LED light strobes, color-light flash, and Gaussian noise. Regarding LED strobes and color-light flash, translucent images were used to overlay the original traffic sign images to simulate corresponding attack scenarios. In the Gaussian noise attack, Python 3.11.10 was used to add noise to the original image. Different attack methods interfered with the original machine learning model to a certain extent, hindering autonomous vehicles from recognizing traffic signs and detecting them accurately. Full article

Transfronterizx students and their families cross the U.S.–Mexico border daily for academic, economic, social, cultural, and linguistic reasons. Socioeconomic disparities, deportation, and work have propelled some families to live in Mexico and enroll their U.S.-born children in U.S. schools. Educators of transfronterizx students are uniquely tasked to work with these nontraditional students. This qualitative study aimed to understand the experiences of transfronterizx public school students, families, and educators of transfronterizx to understand the impact of transfronterizx students on strategies that support and foster effective family engagement. Findings include district and school policies that validate the experiences of people of color; transfronterizx community cultural wealth, including endurance and sacrifice wealth; and educators’ commitment to social justice through humanizing practices. Key themes include the following: fear is endemic among transfronterizx; the intersectionality of the global north and south shapes their experiences and interactions with the educational and sociopolitical systems. Lastly, I delineate recommendations for future research on the multilevel systems that impact transfronterizx. Full article

This review focuses on the potential health risks of artificial food additives, especially their effects on lung health. Preservatives, synthetic colorants, and flavor enhancers, which are commonly used in processed foods, play roles in worsening respiratory diseases, such as asthma and chronic obstructive pulmonary disease (COPD). These additives cause oxidative stress, systemic inflammation, and immune dysregulation, often through the gut-lung axis. The preservatives sodium nitrite and sulfites have the risk of causing bronchial hyper-responsiveness and allergic reactions. The synthetic colorant, Ponceau 4R, is also related to immune-mediated lung inflammation. Flavoring agents such as diacetyl contribute to occupational respiratory diseases like bronchiolitis obliterans. In animal models, prenatal exposure to additives, such as titanium dioxide (E171), might disrupt the development of respiratory neural networks, with long-term consequences. Ultra-processed foods (UPFs), which also contain a high concentration of additives, lead to systemic inflammation and impair lung function. Despite their wide usage, the use of these additives has become a warning sign due to their safety issue, particularly in sensitive people like children, pregnant women, and patients with pre-existing respiratory and chronic conditions. The review highlights the serious need for strict regulation and further research on the long-term effects of food additives on respiratory health. Policymakers should ban these food additives that are more harmful to human health. As an alternative to artificial additives, natural flavors and colors from fruits and vegetables, safe preservatives, and minimally processed ingredients can be used. Full article

Background: Clinical trials should benefit all people. Consequently, the National Cancer Institute expects cancer centers to accrue individuals to clinical trials in proportion to the cancer burden experienced by populations that live in their respective catchment areas; unfortunately, many cancer centers fail to meet this expectation. The person who gives consent for individuals in clinical trials frequently has significant contact with potential trial participants. We hypothesized that the race, ethnicity, and language of the consenter may have an important bearing on whether an individual chooses to participate in a clinical trial. Methods: We used mixed methods to investigate the impact of the socio-cultural background of the consenter on the decision of a potential research subject to participate in a clinical trial. Between 01/2018 and 02/2020, 205 women were approached in the sequential order they appeared in our breast clinic; of the 181 participants who agreed to complete the survey questionnaire, 94 (52%) were Northern European, non-Hispanic White (NE White), and 87 (48%) were Women-of-Color (WOC); this category includes participants who self-identified as Asian, Black, Hispanic/Latina, or Native American. Results: There were statistically significant differences according to the importance of the consenter’s characteristics in the decision to enroll or decline participation in the BCT. No NE White enroller (0%, n = 0) reported that consenter race was important versus 11% (n = 9) of WOC enrollers (p = 0.0009). Similarly, none of the NE White enrollers rated the consenter “looking like people in my community” as important versus 12% (n = 10) of the WOC enrollers (p = 0.0004). Conclusions: We find that consenter race and ethnicity are important for clinical trial diversity. Larger studies are needed to evaluate the generalizability of this finding. Full article

The coronavirus pandemic shaped challenges for marginalized groups. Specifically, lesbian, gay, bisexual, transgender, and/or queer (LGBTQ+) people experienced community-building constraints, notably in predominantly rural regions. People are also navigating digital geographies, or online social environments, in novel ways to develop virtual communities in the face of prejudice, discrimination, and potential trauma. Through a minority coping approach, the present study explored LGBTQ+ people’s experiences navigating the dynamics of digital geographies during the pandemic while residing in socially conservative, highly rural physical spaces where they may be exposed to vicarious trauma. Using qualitative semi-structured interviews, data were gathered from 43 LGBTQ+ identifying individuals between 19 and 59 years old (M/SD = 27.7/9.2) between October 2020 and January 2021. Nearly 14% identified as transgender, nonbinary, or queer individuals, 35% as bisexual individuals, and 21% as people of color including Hispanic/Latina/o. Thematic analysis of the narratives described participants’ exposures to online discrimination and stigmatization of minority groups (racial and/or sexual/gender minority groups) during the COVID-19 pandemic, institutional constraints to identity expression, utilizing social technologies to manage their identities, and negotiating digital strategies to promote social ties. Findings emphasize improving marginalized people’s experiences with digital geographies through identity affirmation and community relationship-building to offset potentially traumatic experiences. Furthermore, service providers can utilize the findings to tailor effective virtual LGBTQ+ community programming to support underserved, marginalized populations. Full article

Cyanobacterial blooms are a widespread phenomenon in aquatic ecosystems worldwide, causing significant harm to the ecological environment. Lake Taihu is the third-largest freshwater lake in China. The region has been increasingly affected by cyanobacterial blooms, drawing greater attention from people. Currently, numerous models have been developed for detecting algal bloom based on spectral characteristics. However, the intuitive basis of optical detection lies in water color. Therefore, constructing an algal bloom detecting model from the perspective of chromaticity is worth exploring. This study constructed an algal bloom detecting model based on chromatic parameters, DFLH, and IAVW by using hyperspectral data from Lake Taihu. It further applied the model to the ZY-1E hyperspectral satellite for large-scale algal bloom monitoring. The threshold for detecting cyanobacterial blooms is defined as DFLH > 0.013 sr⁻¹ and Hue Angle > 170.58 degrees; the threshold for the normal water is defined as DFLH < 0.013 sr⁻¹. The parameter thresholds for the floating leaf vegetation range were defined as DFLH > 0.013 sr⁻¹, Saturation < 0.07, and IAVW > 598 nm. Through the validation, in the modeling dataset, the overall accuracy (OA) value is 0.81 and the F₁-score is 0.86. In the validation dataset, the overall accuracy (OA) value is 0.83 and the F₁-score is 0.89. The model demonstrates good detecting performance. Regarding its application on the ZY-1E satellite, we validated the detection results accuracy through matching synchronized in situ algal density data. The results are as follows: OA is 0.95, and the F₁-score is 0.95. The results above indicate that the algal bloom detection method developed in this study had a good accuracy in detecting algal blooms in Lake Taihu on 6 September 2020. This study provided the algae bloom detecting model based on water color characteristics in Lake Taihu, which had high detecting accuracy. Full article

Hair care products that have oxidative hair dye ingredients have been widely used to permanently change hair color for the characteristic and younger appearance of people and/or their companion animals. In the European Union and the Republic of Korea, these ingredients have been carefully used or prohibited for cosmetic products according to their genotoxic potential. There is a growing demand for reliable quantification methods to monitor oxidative hair dye ingredients in hair care products. However, accurately quantifying oxidative dyes in cosmetic samples is challenging due to their high reactivity and chemical instability under both basic and ambient conditions. For this reason, for the quantification methods, elaborate sample preparation procedures should be accompanied by chemical derivatization to avoid chemical reactions between hair dye ingredients, before instrumental analysis. Therefore, this study utilized a gas chromatography–mass spectrometry (GC-MS) method combined with in situ chemical derivatization to quantify 26 oxidative hair dye ingredients in hair care products. In situ derivatization using acetic anhydride provided the characteristic [M-CH₂CO]⁺ ions at m/z (M-42), produced by the loss of a ketene from the hair dye ingredient derivatives. These characteristic ions can be used to establish a selective ion monitoring (SIM) mode of GC-MS. The established method was successfully applied to hair dye products (n = 13) and hair coloring shampoos (n = 12). Most products contained unintended hair dye ingredients including catechol without labeling. It was cautiously speculated that these unintended hair dye ingredients might be caused by biodegradation due to various enzymes in natural product extracts. This study presents a reliable GC-MS method with in situ derivatization to quantify 26 oxidative hair dye ingredients in hair care products, addressing challenges related to their chemical instability. This method is crucial for public health and regulatory compliance. Full article

Students as Partners (SaP) programs have centered student voices since their inception. Student–faculty pedagogical partnerships are grounded in the notion that students have the expertise to contribute to faculty in preparing for, reflecting on, and revising teaching and learning practices in ways that are inclusive and responsive to all learners. This expertise is based in part on their lived experiences—both as students and as members of the student populations that SaP programs were intentionally created to help empower (e.g., first generation, low-income, BIPOC (Black, Indigenous, and people of Color) and others marginalized in higher education). These students, in dialogue with faculty, help to expose equity issues across classrooms. As SaP programs have proliferated in colleges and universities across the globe, the student partners’ role as social justice advocates in these programs have expanded too. This review explores the pedagogical partnership literature over the past 20 years, to establish the ways in which undergraduate students and post-bacs have flourished in leadership roles in SaP programs: (a) acting as leaders for social equity on campus, (b) serving as peer mentors to new student partners in existing programs, (c) co-creating new programs, and (d) publishing in the literature. This review reveals opportunities for new directions with peer mentorship in SaP programs through the role of lead student mentors who can help to scale up SaP programs, support the emotional labor involved in partnership work, and create pathways to future social justice leadership opportunities. Full article

The number of coffee shops in China is rapidly increasing, and they are becoming a gathering place for young people. In order to enhance their competitiveness, the design of coffee shops has become the core force of competition. To clarify the preferences of young people for coffee shop design, this study takes the most intuitive exposure of consumers to building façades as the starting point. Based on the façade model in the previous research, the façade model was reconstructed through expert group discussions. In total, 80 out of 490 design cases were selected and combined with the reconstructed façade model to construct a questionnaire. Then, a questionnaire survey was conducted on 595 Chinese YZ generation members. The results of the classification summary and post hoc multiple comparison analysis showed that façade design was considered an important factor affecting their choices, and if the façade design met their aesthetic preferences, they would visit the store again. In addition, the aesthetic preferences of the YZ generation for coffee shop façade design, including different façade shapes, contours, visual forms, functional forms, decorative material types, textures, tones, brightness, and color matching methods, are consistent. They prefer the modernist style and pursue more visually stimulating exterior design, and this preference does not differ in terms of generational and gender differences. The differences in aesthetic standards for façades are more reflected in income levels. The YZ generation gave a “like” rating to all façade model contents and cases, but their aesthetic differences in different façade models can still be seen through specific numerical differences. Full article

Wheat, a staple crop cultivated for over 8000 years, sustains more than 2.5 billion people globally, as a major source of carbohydrate, protein, fiber, and essential nutrients. Colored wheat, enriched with dietary fiber and antioxidants, offers valuable genetic resources for developing functional wheat varieties. Herein, a mutant pool of 1069 colored wheat lines was developed through gamma-ray irradiation to enhance genetic diversity. Mutant lines were classified into 10 groups based on seed color parameters (L*, a*, and b*), which were measured using the Hunter Lab system. K-means clustering categorized the mutant lines, and four representative lines from each group were analyzed for agronomic traits (plant height, spike length, thousand-seed weight, and kernels per spike) and antioxidant properties (radical-scavenging activity, ferric reducing antioxidant power, and total antioxidant capacity). Principal-component analysis revealed distinct clustering patterns, indicating associations between seed color, agronomic traits, and antioxidant activity. Darker seed color groups exhibited 3–16% higher levels of bioactive compounds and 10–18% higher antioxidant activities, whereas lighter groups showed 8–42% lower functional potential compared to the control wheat. These findings highlight the potential of mutation breeding in generating phenotypic diversity and developing wheat varieties with improved functional traits and bioactive compound content. Full article

Dementia’s escalating incidence, coupled with its economic burden, highlights the need for architectural designs and forms that benefit people living with dementia. This research explores strategies and design principles that focus on establishing supportive spaces for the prolonged autonomy, well-being, and safety of dementia patients. Contemporary research emphasizes the implementation of effective navigational techniques, via visual cues, familiar landmarks, and simplified layouts. For greater navigational signage, the intentional use of contrasting colors, textures, and lighting are recommended to demarcate functional areas within a structure. Incorporating familiar objects in personalized areas enhances treatment outcomes, e.g., reminiscence therapy leverages familiar objects, environmental cues, scents, sounds, and tactile features to trigger and retain memory. Integrating safety precautions such as slip-resistant flooring, handrails, and accessible bathrooms helps mitigate falls for the cognitively impaired. From a therapeutic perspective, this study draws attention towards incorporating gardens and outdoor spaces, which offers sensory stimulation, encourages physical activity, and fosters social engagement. Additionally, the integration of scents, sounds, and tactile features enriches the sensory experience for individuals with dementia. Through comprehensive consideration of design elements, this research highlights how intentionally crafted, dementia-friendly environments can convert spaces into empowering therapeutic settings tailored to address the unique need of this vulnerable group. This architectural approach acts as a valuable complement to the medical and therapeutic interventions in the treatment and care of people living with dementia and their families. Full article

Asian American school leaders in K-20 schools and universities remain underrepresented in the field. As such, it is imperative that we study the experience of Asian American women (AAW) leaders to understand the racialized experiences of this specific group, particularly when they enact innovative leadership. We, the authors, argue that behind these racialized experiences are white emotionalities that are imposed upon AAW in uniquely raced and gendered ways. This conceptual paper addresses the following question: “how do white emotionalities thwart the innovative social justice efforts of female Asian American leaders in K-20 education?” To answer, we drew on the “kuwentos” of two AAW school leaders: one from K-12 administration and one from higher education administration. Kuwentos is derived from the Pinay concept of storytelling; thus, it is a befitting methodology to explicate these two women’s particular racial experiences. To critically interpret invisible operations of whiteness, we employed critical race hermeneutics (CRH) to reveal what is often left to the unconscious when examining the impact of whiteness on people of Color. To reveal how these seemingly natural presumptions are not so natural, CRH must be used. In drawing attention to how white emotionalities impact the innovative leadership of AAWs, the authors first use kuwentos to tell our own stories of experiencing white emotionalities. We then analyze these kuwentos through a CRH lens and end with implications and recommendations to positively impact AAW educational leaders. Full article

As people attempt to elude the environmental issues associated with synthetic dyes, interest in natural dyes has recently increased significantly. Oolong tea stems act as a common agricultural waste yet offer advantages like high production, low cost, and a stable supply. The objectives of this research are to investigate the potential utilization of oolong tea waste, specifically tea stems, as a natural dye source for the development of organic cotton fabrics with added health benefits. In this study, using the Kubelka–Munk (K/S) value as an indicator, the dyeing process was refined through response surface methodology (RSM) by investigating the pH of the dye solution, temperature, and duration. Accordingly, it was demonstrated that the optimal effect was achieved at a pH value of 7.9, a duration of 80 min, and a temperature of 90 °C. Furthermore, under these conditions, the color fastness and functional performance of dyed organic cotton were compared with and without chitosan as a mordant. The results showed that the organic cotton dyed with oolong tea stem extract not only had a good color fastness grade but also presented excellent antibacterial properties, ultraviolet protection properties, and oxidation resistance. Especially with the assistance of chitosan, the dyed fabric achieved excellent performance above grade 4 in all color fastness test items; moreover, its antibacterial activity against Staphylococcus aureus reached more than 90%, the ultraviolet protection coefficient reached 25.3, and the antioxidant activity exceeded 90%. Consequently, considering environmental concerns, natural dyes extracted from discarded oolong tea stems are promising substitutes for synthetic dyes in the textile sector. Full article

Cyberbullying, which manifests in various forms, is a growing challenge on social media, mainly when it involves threats of violence through images, especially those featuring weapons. This study introduces a computational framework to identify such content using convolutional neural networks of weapon-related images. By integrating artificial intelligence techniques with image analysis, our model detects visual patterns associated with violent threats, creating safer digital environments. The development of this work involved analyzing images depicting scenes with weapons carried by children or adolescents. Images were sourced from social media and spatial repositories. The statistics were processed through a 225-layer convolutional neural network, achieving an 86% accuracy rate in detecting weapons in images featuring children, adolescents, and young adults. The classifier method reached an accuracy of 17.86% with training over only 25 epochs and a recall of 14.2%. Weapon detection is a complex task due to the variability in object exposures and differences in weapon shapes, sizes, orientations, colors, and image capture methods. Segmentation issues and the presence of background objects or people further compound this complexity. Our study demonstrates that convolutional neural networks can effectively detect weapons in images, making them a valuable tool in addressing cyberbullying involving weapon imagery. Detecting such content contributes to creating safer digital environments for young people. Full article