Search Results (1,061)

In recent years, the proliferation of fake news and misinformation has grown exponentially, far surpassing that of genuine news and posing a serious threat to social stability. Existing research in fake news detection primarily applies contrastive learning methods with a single-hot labeling strategy. The issue does not lie with contrastive learning as a technique but with its current application in fake news detection systems. Specifically, these systems penalize all negative samples equally due to the use of single-hot labeling, thus overlooking the underlying semantic relationships among negative samples. As a result, contrastive learning models tend to learn from simple samples while neglecting highly deceptive samples located at the boundary between true and false, as well as the heterogeneity of text-image features, which complicates cross-modal fusion. To mitigate these known limitations in current applications, this paper proposes a fake news detection method based on contrastive learning and cross-modal interaction. First, a consistency-aware soft-label contrastive learning mechanism based on semantic similarity is designed to provide more granular supervision signals for contrastive learning. Secondly, a difficult negative sample mining strategy based on a similarity matrix is designed to optimize the symmetry alignment of image and text features, which effectively improves the model’s ability to discriminate boundary samples. To further optimize the feature fusion process, a cross-modal interaction module is designed to learn the symmetric interaction relationship between image and text features. Finally, an attention mechanism is designed to adaptively adjust the contributions of text-image features and interaction features, forming the final multimodal feature representation. Experiments are conducted on two major social media platform datasets, and compared with existing methods, the proposed method effectively improves the detection capability of fake news. Full article

Sexual health constitutes a fundamental aspect of overall well-being, with direct implications for individual development and the broader social and economic progress of communities. Promoting environments that ensure sexual experiences free from coercion, discrimination, and violence is a key public health priority. Sexuality, in this regard, should be understood as an inherent dimension of human experience, shaped by biological, cultural, cognitive, and ideological factors. Accordingly, sexual health education requires a holistic and multidimensional approach that integrates sociocultural, biographical, and professional perspectives. This study aims to examine the level of knowledge and training in sexual health among nursing students and healthcare professionals, as well as to assess the extent to which sexual health content is incorporated into nursing curricula at Spanish universities. A scoping review was conducted using the Dialectical Structural Model of Care (DSMC) as the theoretical framework. The findings indicate a significant lack of knowledge regarding sexual health among both nursing students and healthcare professionals, largely due to educational and structural limitations. Furthermore, sexual health education remains underrepresented in nursing curricula and is frequently addressed from a narrow, fragmented biomedical perspective. These results highlight the urgent need for the comprehensive integration of sexual health content into nursing education. Strengthening curricular inclusion is essential to ensure the preparation of competent professionals capable of delivering holistic, inclusive, and empowering care in this critical area of health. Full article

Background: Health equity can only be achieved when every individual has access to quality healthcare without fear of being discriminated against. This study analyzed the sociodemographic characteristics associated with self-reported racial discrimination when receiving medical care in the United States. Methods: This quantitative cross-sectional study utilized the 2022 National Trends Survey 6. We performed a logistic regression analysis using 6102 survey responses from study participants who answered the question about perceived discrimination. Results: Older adults aged 75 years and above had significantly lower odds of reporting perceived discrimination when receiving medical care compared to those aged 18–34 years (AOR = 0.24; 95% CI: 0.10–0.58). The odds of reporting perceived discrimination were significantly higher among non-Hispanic Blacks (AOR = 7.30; 95% CI: 4.48–11.88), Hispanics (AOR = 3.56; 95% CI: 2.45–5.17), non-Hispanic Asians (AOR = 5.95; 95% CI: 2.25–15.73), and individuals identifying as non-Hispanic Other (AOR = 10.91; 95% CI: 5.42–21.98), compared to non-Hispanic Whites. Compared to individuals from households earning less than USD 20,000, the odds of reporting perceived discrimination when receiving medical care were significantly lower among individuals from households earning between USD 50,000 and <USD 75,000 (AOR = 0.42; 95% CI: 0.23–0.78) and those earning USD 75,000 or more (AOR = 0.43; 95% CI: 0.22–0.83). Conclusions: Despite having a multicultural and ethnically diverse population, racial discrimination persists in the United States and has become a barrier to achieving health equity. Health organizations should implement policies that ensure health workers attend mandatory anti-racism training. Full article

The advanced determination of the type (foreshock–aftershock–swarm) of an ongoing seismic cluster is quite challenging; only retrospective solutions have thus far been proposed. In the period of January–March 2025, a seismic cluster, recorded between Santorini volcano and Amorgos Island, South Aegean Sea, caused considerable social concern. A rapid increase in both the seismicity rate and the earthquake magnitudes was noted until the mainshock of M_L = 5.3 on 10 February; afterwards, activity gradually diminished. Fault-plane solutions indicated SW-NE normal faulting. The epicenters moved with a mean velocity of ~0.72 km/day from SW to NE up to the mainshock area at a distance of ~25 km. Crucial questions publicly emerged during the cluster. Was it a foreshock–aftershock activity or a swarm of possibly volcanic origin? We performed real-time discrimination of the cluster type based on a daily re-evaluation of the space–time–magnitude changes and their significance relative to background seismicity using earthquake statistics and the topological metric betweenness centrality. Our findings were periodically documented during the ongoing cluster starting from the fourth cluster day (2 February 2025), at which point we determined that it was a foreshock and not a case of seismic swarm. The third day after the M_L = 5.3 mainshock, a typical aftershock decay was detected. The observed foreshock properties favored a cascade mechanism, likely facilitated by non-volcanic material softening and the likely subdiffusion processes in a dense fault network. This mechanism was possibly combined with an aseismic nucleation process if transient geodetic deformation was present. No significant aftershock expansion towards the NE was noted, possibly due to the presence of a geometrical fault barrier east of the Anydros Ridge. The 2025 activity offered an excellent opportunity to investigate deciphering the type of ongoing seismicity cluster for real-time discrimination between foreshocks, aftershocks, and swarms. Full article

Mozambique soils are known for having an unbalanced agronomic and environmental composition that results in poor agricultural production yields. However, agriculture is the main economic activity of Mozambique, and soils must be characterised for their elemental deficiencies and/or excesses. This paper sampled nine farms from the Manica and Sussundenga districts (Manica province) in three campaigns in 2021/2022, 2022/2023, and 2023/2024 (before and after the rainy seasons). They were subjected to a physical–chemical analysis to assess their quality from the fertility and environmental contamination point of view. Attending to the physical–chemical properties analysed, and for all the soils and sampling campaigns, a low concentration below the limit of detection for B of <0.2 mg/Kg for the majority of soils and a low concentration of Al < 0.025 mg/Kg for all the soils were obtained. Also, higher concentrations for the majority of soils for the Ca between 270 and 1634 mg/Kg, for the Mg between 41 and 601 mg/Kg, for the K between 17 and 406 mg/Kg, for the Mn between 13.6 and 522 mg/Kg, for the Fe between 66.3 and 243 mg/Kg, and for the P between <20 and 132 mg/Kg were estimated. In terms of texture and for the sand, a high percentage between 6.1 and 79% was found. In terms of metal concentrations and for all the soils of the Sussundenga district and sampling campaigns, a concentration above the reference value concentration for the Cr (76–1400 mg/Kg) and a concentration below the reference value concentration for the Pb (5–19 mg/Kg), Ba (13–120 mg/Kg) and for the Zn (10–61 mg/Kg) were evaluated. A multivariate data analysis methodology was used based on cluster and discriminant analysis. The analysis of twenty-three physical–chemical variables of the soils suggested four clusters of soils characterised by deficiencies and excess elements that must be corrected to improve the yield and quality of agricultural production. Moreover, the multivariate analysis of the metal composition of soil samples from the second and third campaigns, before and after the rainy season, suggested five clusters with a pristine composition and different metal pollutant compositions and concentrations. The information obtained in this study allows for the scientific comprehension of agricultural soil quality, which is crucial for designing agronomic and environmental corrective measures to improve food quality and quantity in the Manica and Sussundenga districts and ensure environmental, social, and economic sustainability. Full article

Research concerning green marketing has predominantly focused on consumer behavior. However, aspects such as the extent to which Small and Medium Enterprises (SMEs) embrace green marketing values, their ability to implement the green marketing mix, and the integration of green marketing into their business culture are critically important. This research aims to provide the 4P (product, price, place, and promotion)-focused green marketing literature with a measurement tool to assess how SMEs implement green marketing practices. The study employed a descriptive design and possesses an exploratory nature. Scale development involved two stages: First, analyses were conducted on a pre-test sample of 159 individuals, revealing the initial scale structure. Second, these analyses were repeated on a larger group of 387 participants. The scale was finalized by confirming the consistency of results across both analyses. Statistical Package for the Social Sciences (SPSS) version 24 and Analysis of Moment Structures (AMOS) version 24 were utilized for descriptive statistics and the scale development process. The final validated 12-item scale demonstrates a robust three-factor structure (“Environmental Promotion”, ”Green Packaging”, and ”Green Distribution”), explaining 62.6% of the total variance. The scale exhibits excellent psychometric properties, including high internal consistency (Cronbach’s α = 0.912), strong model fit from Confirmatory Factor Analysis (CFA), and both convergent and discriminant validity, as indicated by an Average Variance Extracted (AVE) value of 0.605. The scale is deemed applicable to larger populations. Full article

Intersectionality is a concept used to explain the power dynamics and inequalities that some groups experience owing to the interconnection of social differences such as in gender, sexual identity, poverty status, race, geographic location, disability, and education. The relation between software engineering, feminism, and intersectionality has been addressed by some studies thus far, but it has never been codified before. In this paper, we employ the commonly used ABC Framework for empirical software engineering to show the contributions of intersectional software engineering (ISE) as a field of software engineering. In addition, we highlight the power dynamic, unique to ISE studies, and define gender-forward intersectionality as a way to use gender as a starting point to identify and examine inequalities and discrimination. We show that ISE is a field of study in software engineering that uses gender-forward intersectionality to produce knowledge about power dynamics in software engineering in its specific domains and environments. Employing empirical software engineering research strategies, we explain the importance of recognizing and evaluating ISE through four dimensions of dynamics, which are people, processes, products, and policies. Beginning with a set of 10 seminal papers that enable us to define the initial concepts and the query for the systematic mapping study, we conduct a systematic mapping study leads to a dataset of 140 primary papers, of which 15 are chosen as example papers. We apply the principles of ISE to these example papers to show how the field functions. Finally, we conclude the paper by advocating the recognition of ISE as a specialized field of study in software engineering. Full article

Background/Objectives: Despite the importance of parent mental health for child health, there are no global prevalence data on parental mental health symptoms when children are hospitalized. We aimed to describe depression and anxiety symptom prevalence and associated factors among parents of hospitalized children. Methods: We conducted this 14-country prospective cohort survey with parents/primary caregivers staying at a nearby Ronald McDonald House^® during their child’s hospital treatment. We used the Hospital Anxiety and Depression Scale to measure depression and anxiety symptoms and validated scales and theory-based questions to measure parent, family, and child covariates. We calculated the prevalence of clinically significant or concerning symptoms of depression and anxiety, and used multivariable regression analyses to examine associations between covariates and outcomes. Results: Among 3350 participants, 1789 (49.7%) reported depression symptoms and 2286 (69.0%) reported anxiety symptoms. Worry about housing and poorer ratings of their child’s health were associated with increased risk of depression symptoms. Poorer rating of the child’s health, living with a partner, and discrimination in daily life were associated with increased risk of anxiety symptoms. Higher levels of self-care, hospital family-centered care, and social support were associated with reduced risk of depression symptoms. Higher levels of self-care and social support were associated with reduced risk of anxiety symptoms. Conclusions: Clinically significant or concerning depression and anxiety symptoms are common among parents of hospitalized children globally. Hospitals should consider offering routine mental health symptom screening and preventative mental health and support services to all parents. Full article

Background/Objectives: Social worry may appear in preadolescence, causing it to persist in the future, such that adolescents become more avoidant of situations in which they are evaluated by others. Many previous studies have shown that approximately 4% of preadolescent children suffer from high levels of social worry, which may lead to other problems in the future. It is important to take necessary precautions to explore this worry and take the necessary measures to address it. This study aimed to do so by extracting the psychometric properties of the Social Worries Questionnaire (SWQ) for preadolescence in Arab countries. Methods: The sample consisted of 269 children aged 8–12 years. The SWQ, Spence Child Anxiety Scale (SCAS), Child Abuse Self-Reporting Scale (CASRS-12), and Arabic version of the Children’s Depression Inventory (AVCDI) were administered via various social media. Results: Confirmatory factor analysis was used, and the one-factor model showed that the scale consists of 14 items. The results also indicated evidence of discriminant validity, and that the internal consistency was acceptable. For reliability, the test–retest results showed that the value was appropriate. Conclusions: This scale could be valuable in detecting worry in preadolescent children and providing them with therapeutic and psychological services. Full article

Background/Objectives: Traditional dietary screeners face significant limitations: they rely on subjective self-reporting, average intake estimates, and are influenced by a participant’s awareness of being observed—each of which can distort results. These factors reduce both accuracy and reproducibility. The Guide Against Age-Related Disease (GARD) addresses these issues by applying Assembly Theory to objectively quantify food and food behavior (FFB) complexity. This study aims to validate the GARD as a structured, bias-resistant tool for dietary assessment in clinical and research settings. Methods: The GARD survey was administered in an internal medicine clinic within a suburban hospital system in the southeastern U.S. The tool assessed six daily eating windows, scoring high-complexity FFBs (e.g., fresh plants, social eating, fasting) as +1 and low-complexity FFBs (e.g., ultra-processed foods, refined ingredients, distracted eating) as –1. To minimize bias, patients were unaware of scoring criteria and reported only what they ate the previous day, avoiding broad averages. A computer algorithm then scored responses based on complexity, independent of dietary guidelines. Internal (face, convergent, and discriminant) validity was assessed using Spearman rho correlations. Results: Face validation showed high inter-rater agreement using predefined Assembly Index (A_i) and Copy Number (N_i) thresholds. Positive correlations were found between high-complexity diets and behaviors (rho = 0.533–0.565, p < 0.001), while opposing constructs showed moderate negative correlations (rho = –0.363 to −0.425, p < 0.05). GARD scores aligned with established diet patterns: Mediterranean diets averaged +22; Standard American Diet averaged −10. Full article

More than 50 years ago, children were viewed as naturally resilient and often labeled invulnerable or invincible. Resilience is now understood to be the result of dynamic interactions between individual, familial, social, and environmental systems, decentralizing the focus from the individual to the global society. Experiences with adversity may emanate from the youth’s family environment, their community, the school system, and larger structural challenges related to poverty, discrimination, health disparities, and educational inequities. Youth experiences with adversity, trauma, and tragedy have the potential to negatively impact youth well-being, with consequences manifesting across the lifespan. Children and adolescents generally hold limited power to change their circumstances and are often ill-equipped to resolve the adverse or traumatic experiences occurring within their ecosystem. The value of social supports in the young person’s ability to be resilient has been affirmed. This understanding is particularly important for children growing up in poverty or in Low- and Middle-Income Countries (LMICs) where significant challenges occur as a result of economic and social disadvantage. Resilience at the individual level is unlikely to eliminate macrolevel issues. Developing and deploying strategies to enhance the ability of youth to rebound from adversity represents a positive step at the micro level, but the larger issues of economic and social disadvantage are unlikely to change without macro-level interventions. Glancing toward the future, traumatized youth may grow into traumatized adults without appropriate interventions and changes in social policies, programs, and protections. Full article

Blackness, both as a racial identity and a marker of cultural difference, disrupts the hegemonic norms embedded in dominant forms of cultural capital. This article examines how first- and second-generation Haitian and Jamaican communities in Ontario and Quebec negotiate Blackness within a Canadian context. Drawing from international literature, it introduces distinctly Canadian concepts—such as polite racism, racial ignominy, and duplicity of consciousness—to illuminate local racial dynamics. Using Yosso’s (2005) framework of community cultural wealth, the study analyzes six forms of cultural capital—linguistic, aspirational, social, navigational, resistant, and familial—as employed by Afro-Caribbeans to navigate systemic exclusion. The article expands the limited Canadian discourse on Black identity and offers theoretical tools for understanding how cultural capital is shaped and constrained by race in multicultural democracies. Full article

Pregnancy-related discrimination at work is a concern for many employees who navigate the pregnancy and postpartum stages of parenthood while working in the early-to-middle stages of their careers. Although there is legislation prohibiting pregnancy-related discrimination and ensuring accommodations postpartum, empirical evidence indicates many pregnant and postpartum employees still experience such behaviors. In this narrative review, we focus on describing the range of behaviors assessed in studies on pregnancy-related discrimination in several cultures, situating the occurrence of discrimination within theoretical frameworks related to stereotypes and gendered expectations. We also review evidence of employees’ postpartum experiences with a focus on the transition back to work, along with breastfeeding challenges related to pumping and storing milk at work. Regarding coping with pregnancy-related workplace discrimination and postpartum challenges during a return to work, we review the importance of social support, including instrumental and emotional support from allies and role models. Full article

Traditional collision risk warning methods primarily focus on vehicle-to-vehicle collisions, neglecting conflicts between vehicles and vulnerable road users (VRUs) such as pedestrians, while the difficulty in predicting pedestrian trajectories further limits the accuracy of collision warnings. To address this problem, this study proposes a vehicle-to-everything-based (V2X) multi-fusion vehicle–pedestrian collision warning method, aiming to enhance the traffic safety protection for VRUs. First, Unmanned Aerial Vehicle aerial imagery combined with the YOLOv7 and DeepSort algorithms is utilized to achieve target detection and tracking at unsignalized intersections, thereby constructing a vehicle–pedestrian interaction trajectory dataset. Subsequently, key foundational modules for collision warning are developed, including the vehicle trajectory module, the pedestrian trajectory module, and the risk detection module. The vehicle trajectory module is based on a kinematic model, while the pedestrian trajectory module adopts an Attention-based Social GAN (AS-GAN) model that integrates a generative adversarial network with a soft attention mechanism, enhancing prediction accuracy through a dual-discriminator strategy involving adversarial loss and displacement loss. The risk detection module applies an elliptical buffer zone algorithm to perform dynamic spatial collision determination. Finally, a collision warning framework based on the Monte Carlo (MC) method is developed. Multiple sampled pedestrian trajectories are generated by applying Gaussian perturbations to the predicted mean trajectory and combined with vehicle trajectories and collision determination results to identify potential collision targets. Furthermore, the driver perception–braking time (TTM) is incorporated to estimate the joint collision probability and assist in warning decision-making. Simulation results show that the proposed warning method achieves an accuracy of 94.5% at unsignalized intersections, outperforming traditional Time-to-Collision (TTC) and braking distance models, and effectively reducing missed and false warnings, thereby improving pedestrian traffic safety at unsignalized intersections. Full article

This study analyses algorithmic biases in AI-generated images, focusing on aesthetic violence, gender stereotypes, and weight discrimination. By examining images produced by the DALL-E Nature and Flux 1 systems, it becomes evident how these tools reproduce and amplify hegemonic beauty standards, excluding bodily diversity. Likewise, gender representations reinforce traditional roles, sexualising women and limiting the presence of non-normative bodies in positive contexts. The results show that training data and the algorithms used significantly influence these trends, perpetuating exclusionary visual narratives. The research highlights the need to develop more inclusive and ethical AI models, with diverse data that reflect the plurality of bodies and social realities. The study concludes that artificial intelligence (AI), far from being neutral, actively contributes to the reproduction of power structures and inequality, posing an urgent challenge for the development and regulation of these technologies. Full article