Search Results (649)

Every act of design tells a story about who belongs, who is seen, and who is heard. This paper looks at how participatory design-based research (PDR), practiced with relational care and reflexivity, can help shift interactions among marginalized youth from urban Indigenous and newcomer immigrant communities in Canada from othering toward understanding. Moving beyond surface-level celebrations of multiculturalism, the study frames design as a relational and ethical practice, one that surfaces assumptions, holds space for difference, and creates openings for intercultural dialogue. The study draws on a series of design circles (d.circles) in which youth co-created visual communication artefacts reflecting their lived experiences. These artefacts became catalysts for dialogue, enabling participants to challenge stereotypes, articulate concerns, and develop shared perspectives. Reflexivity was integral to the process, guiding both participants and the facilitator to consider power, positionality, and relational accountability throughout. Findings show that participatory design, grounded in Indigenous relational principles and participatory action research, can unsettle dominant narratives, foster mutual recognition, and support youth-led meaning-making. This work contributes to emerging conversations that position design thinking as a practice of ethical engagement rather than a tool for problem-solving alone. The learnings from this study show how critically practiced PDR can cultivate more inclusive and socially responsive pathways for intercultural understanding to take shape. Full article

The unconscious is a core concept in both the Yogācāra Buddhism and psychoanalytic traditions. It is easy to assume that the understanding of the unconscious in Yogācāra cannot coexist with the understanding of the unconscious in psychoanalysis, because the unconscious in Yogācāra (i.e., ālayavijñāna) primarily explains how the world is constructed by it, while the unconscious in psychoanalysis primarily explains how neurosis develops. Due to this difference in the understanding of the unconscious, Yogācāra Buddhism and psychoanalysis have developed different psychotherapeutic methods. Yogācāra’s therapeutic method is to observe emptiness, while psychoanalysis aims to transform the pathogenic unconscious into the conscious. But there is a potential for mutual enrichment between the two in psychotherapy. Psychoanalysis’s emphasis on functions of the self can help people avoid misunderstanding Yogācāra’s doctrine of “non-self”. Yogācāra can help psychoanalysis explore deeper levels of the unconscious. Full article

Due to the damage happening in the nervous system, neuropathic pain occurs and it affects the quality of life of the patient to a great extent. Therefore, some clinical evaluations are required to assess the diagnostic outcomes precisely. A lot of information about the activities of the brain is provided by Electroencephalography (EEG) signals and neuropathic pain can be assessed and classified with the aid of EEG and machine learning. In this work, two approaches are proposed in terms of efficient blended models for the classification of neuropathic pain through EEG signals. In the first blended model, once the features are extracted using Discrete Wavelet Transform (DWT), statistical features, and Fuzzy C-Means (FCM) clustering techniques, the features are selected using Grey Wolf Optimization (GWO), Feature Correlation Clustering Technique (FCCT), F-test, and Bayesian Optimization Algorithm (BOA) and it is classified with the help of three hybrid classification models like Spider Monkey Optimization-based Gradient Boosting Machine (SMO-GBM) classifier, hybrid deep kernel learning with Support Vector Machine (DKL-SVM) classifier, and CatBoost classifier. In the second blended model, once the features are extracted, the features are selected using Hybrid Feature Selection—Majority Voting System (HFS-MVS), Hybrid Salp Swarm Optimization—Particle Swarm Optimization (SSO-PSO), Pearson Correlation Coefficient (PCC), and Mutual Information (MI) and it is classified with the help of three hybrid classification models like Partial Least Squares (PLS) variant classification models combined with Kernel-based SVM, ensemble classification model with soft voting strategy, and Extreme Gradient Boosting (XGBoost) classifier. The proposed blended models are evaluated on a publicly available dataset and the best results are shown when the FCM features are selected with SSO-PSO feature selection technique and classified with Polynomial Kernel-based PLS-SVM Classifier, reporting a high classification accuracy of 92.68% in this work. Full article

Introduction: Incomplete polymerization of in vivo composite resins (CR) poses a significant problem, with monomer-to-polymer conversion rates ranging from around 60 to 75%. Furthermore, oxygen exposure hampers polymerization in the surface layers. This research aims to evaluate the autophagy-inducing potential of three types of CRS and to explore the role of the Akt/mTOR–autophagy–apoptosis crosstalk in composite resin-induced autophagy. The study uses human gingival fibroblasts and three composite materials (M1 and M2, which are 3D printed, and M3, which is milled). Materials and Methods: SEM analysis was performed on the dental materials, and cells kept in contact for 24 h were subjected to tests including the following: MTT, LDH, NO, immunological detection of proteins involved in autophagy and apoptosis, as well as immunofluorescence tests (Annexin V and nucleus; mitochondria and caspase 3/7; detection of autophagosomes). Results: The results showed statistically significant decreases in cell viability with M1 and M2, linked to increases in cytotoxicity and oxidative stress (LDH and NO). Using multiplex techniques, significant increases in glycogen synthase kinase 3 beta (GSK3b) protein were observed in both M1 and M2; a decrease in mTOR (mechanistic target of rapamycin) expression was noted in M1 and M3. Immunofluorescence tests revealed an increase in Annexin V across all materials studied, and an increase in autophagosomes in M1 and M2, whereas a decrease was observed in M3. Conclusions: The relationship between apoptosis and autophagy is highly complex, indicating they may occur sequentially, coexist, or be mutually exclusive. Understanding this complex interplay can help in designing new 3D-printing protocols and monomer compositions to prevent autophagy imbalance. Full article

The authors examine the emotions contained in 2 Cor 7:5–16. They refer to the nativist approach, in particular to Jaak Panksepp’s theory of primary emotions and Jonathan Haidt’s five foundations of morality. The emotions of Paul, Titus, and the Corinthians described in 2 Cor 7:5–16 can be classified into Panksepp’s categories of FEAR/anxiety, GRIEF/separation distress, CARE/nurturing, and RAGE/anger. They serve as a response to the pain and threat posed by the community’s separation from Paul and aim to repair and strengthen the family/parental relationship with the apostle. Following Haidt’s typology, most of the emotions in 2 Cor 7:5–16 can be located in the care/harm module, related to Paul’s care about his spiritual children in Corinth. In addition, other modules can be engaged to link various emotions in 2 Cor 7:5–15: fairness/reciprocity, focused on reciprocal altruism, in-group/loyalty, reinforcing mutual loyalty, authority/respect, working for Paul’s authority in Corinth, and purity/sanctity serving the holiness of the community and their belonging to Christ. The nativist approach to Pauline emotions smoothly transitions into a socio-cultural approach, pointing to their complementarity. This combination allows for the appreciation for the role of emotions in making moral judgments and helps understand the similarities and differences between ancient and modern views of emotionality. It also aids in grasping the interconnectedness and adaptive functions of emotions, serving the individual and the community. Full article

This study examines the combined impact of fintech and financial inclusion on achieving the United Nations’ Sustainable Development Goals (SDGs). Previous research has emphasized the role of financial inclusion in reducing poverty, strengthening resilience, and promoting economic stability; however, its interaction with fintech in advancing sustainability remains less examined. Using four composite indices incorporating updated variables, expanded country coverage, and a broader temporal scope, this analysis evaluates digital financial channels, including formal access, mobile money, digital credit, transfers, and rural finance, across SDGs 3, 4, 8, and 9. The findings indicate that formal access is associated with lower maternal mortality (SDG 3) and contributes positively to decent work and economic growth (SDG 8), as well as industry, innovation, and infrastructure (SDG 9). Digital credit and transfers help ease liquidity constraints in high-inequality regions, while mobile money enhances education outcomes (SDG 4) under robust governance, supporting informal labor markets. Rural finance strengthens innovation and infrastructure development in underserved areas, reinforcing SDG 9. A simultaneous equation model provides evidence of bidirectional relationships among financial inclusion, fintech adoption, and sustainable development, underscoring their mutual reinforcement rather than strict causality. Overall, the study highlights the systemic interconnection between finance and sustainability and emphasizes the importance of governance, infrastructure, and regulation in maximizing developmental benefits. Full article

Developing expertise in physics requires appropriate integration and assimilation of physics and mathematics. Instructors and students often describe physics courses in terms of their emphasis on conceptual and quantitative problem-solving. For example, they may argue that a course emphasizes primarily conceptual over quantitative problem-solving or may emphasize equally on both depending on instructional context and assessment design. In this study, we investigated how students and instructors across different levels of physics instruction perceive the roles and development of conceptual and quantitative problem-solving in student learning and expertise development. Using departmental surveys administered at the beginning and end of each semester, we collected both Likert-scale and open-ended responses from students enrolled in introductory, upper-level undergraduate and graduate physics courses. These surveys assessed students’ self-perceived skills, preferences, and perceptions of instructors and course emphasis. To complement student perspectives, we conducted interviews with instructors, using parallel questions adapted to reflect instructional goals and expectations. Our findings highlight patterns in how students and instructors prioritize conceptual and quantitative problem-solving across course levels, as well as alignment and misalignment between student and instructor perspectives. Also, although the questions were framed around conceptual versus quantitative problem-solving, we do not view them as mutually exclusive; rather we seek to understand perceived course emphasis and student expertise development from student and instructor points of view in a language commonly used in physics. These results can help shape teaching, course design, and assessment practices to better support the development of expert-like problem-solving skills in students in physics and related disciplines. Full article

Prepubescent children and young adolescents (ages 7–14) are in a critical developmental stage for establishing the foundations of healthy sexual behavior. Increasing rates of precocious puberty, combined with limited access to accurate and age-appropriate sexual health education, heighten the vulnerability of this age group to sexual health risks. These risks include early and often coerced sexual initiation, exposure to sexual abuse, and consequent outcomes such as sexually transmitted infections and early pregnancies. However, comprehensive cross-regional analyses and evidence-based interventions addressing the sexual health needs of this age group remain limited. Addressing this gap promotes mutual learning, context-specific adaptation, and global alignment of sexual health support efforts, crucial for achieving the Sustainable Development Goal target of universal access to sexual and reproductive health care. This scoping review aims to map the available evidence on the scope and characteristics of sexual health interventions for prepubescents and young adolescents in the United States and Sub-Saharan Africa. The proposed scoping review will be conducted in accordance with the Arksey and O’Malley framework and Joanna Briggs Institute (JBI) methodology for scoping review. A systematic search of English-language articles published from 2010–2025 will be conducted across PubMed, CINAHL, PsycINFO, Scopus, Web of Science, ERIC, and African Index Medicus. Five reviewers will screen the articles in Covidence and independently assess full-text articles using a standardized data extraction form. Discrepancies will be resolved through discussion and with a sixth reviewer. The review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Data will be summarized and synthesized to identify patterns in interventions, delivery methods, outcomes, and implications for practice, research, and policy. Comparative and gap analyses will highlight similarities, differences, and priorities for future research and interventions. An adolescent sexual health expert will help validate and contextualize findings. Results can guide strategies to address shared challenges and advance universal access to sexual health support for prepubescents and young adolescents. Full article

Transracial adoption (TRA) places children across racial or national borders into non-biological families, raising complex questions about the adoptee’s racial identity. Guided by the bicultural identity integration theory, integrative racial and adoptive identity is defined as a developmental process with transformative variations. Method: With a mixed-design method, this study examines how Asian adoptees and non-Asian American adoptive parents navigated their racial and cultural adjustment journeys. A small and non-representative sample (N = 21) (14 parents and seven adoptees) was recruited for the survey. Eleven participants (seven parents and four adoptees) attended an individual semi-structured interview to describe TRA needs and obstacles. Results: (1) Even though adoptees and parents were comfortable sharing their adoption experiences through social media, adoptees continued their racial identity inquiries, while parents thought of being role models. (2) Integrative findings show adoptees wanted to learn about their “cultural socialization” at a younger age with parental guidance and normalize “reculturation” as they continued exploring their racial identities through external support. Their TRA journeys engage families in a support network appreciating racial/cultural differences and experiencing identity shifts as a part of reculturation. Implications: A social work platform is needed to provide justice-oriented opportunities for adoptees to share integrative identity journeys and for parents to hear adoptees about their lived experiences. Their engagement in mutual communication will help them show appreciation for each other’s efforts in the adjustment process. Full article

Collaborative clustering is an ensemble technique that enhances clustering performance by simultaneously and synergistically processing multiple data dimensions or tasks. This is an active research area in artificial intelligence, machine learning, and data mining. A common approach to co-clustering is based on non-negative matrix factorization (NMF). While widely used, NMF-based co-clustering is limited by its bilinear nature and fails to capture the multilinear structure of data. With the objective of enhancing the effectiveness of non-negative Tucker decomposition (NTD) in image clustering tasks, in this paper, we propose a dual-graph constrained sparse non-negative Tucker decomposition NTD (GDSNTD) model for co-clustering. It integrates graph regularization, the Frobenius norm, and an $l_1$ norm constraint to simultaneously optimize the objective function. The GDSNTD mode, featuring graph regularization on both factor matrices, more effectively discovers meaningful latent structures in high-order data. The addition of the $l_1$ regularization constraint on the factor matrices may help identify the most critical original features, and the use of the Frobenius norm may produce a more highly stable and accurate solution to the optimization problem. Then, the convergence of the proposed method is proven, and the detailed derivation is provided. Finally, experimental results on public datasets demonstrate that the proposed model outperforms state-of-the-art methods in image clustering, achieving superior scores in accuracy and Normalized Mutual Information. Full article

When young children come to the attention of helping professionals because they are experiencing significant behavioral or emotional challenges, effective solutions frequently involve establishing whether there are strains or ruptures in the child’s coparenting network impeding functional communication about the child. Coparenting refers to the shared—and ideally, mutual—parenting efforts of adults working together to socialize, care for, and raise children for whom they share responsibility. Among the most important aims in understanding and strengthening the family’s coparenting alliance is evaluating who the various adults are comprising the functional coparenting network. As part of a coordinated effort to provide guidance in best practices for evaluating coparenting, an International Coparenting Collaborative (ICC) has highlighted the use of a pictoral mapping tool—a child-centered ecomap—as one effective means of assessing coparental engagement and learning more about existing levels of child-related teamwork and conflict. Completed ecomaps provided by multiple coparenting adults in the same family also provide an opening to highlight and explore child focus and to facilitate pivotal information sharing among the multiple caregivers. In this article, we examine the use of child-centered ecomaps in a variety of family-centered cases seen in four different collaborating sites and services partnering in the ICC. The cases highlight the unique value of an assessment tool that goes beyond simply illuminating the nature of the child’s coparenting system to afford the interventionist with a means of refocusing coparents’ attention on the perspective of the child. Closing reflections focus on the child-centered ecomap’s advantages, both as a method for learning more about coparenting in the family and for setting a stage for subsequent child-centered work with the family through more comprehensive and nuanced case conceptualization. Full article

Using used serviceable material (USM), recycled and upcycled, for aircraft is environmentally and financially beneficial in helping the aviation industry achieve sustainability. This study aims to identify determinants of aircraft USM value and assess their significance using the Fuzzy Analytic Hierarchy Process (FAHP) to gain insights for making the USM market more active. Sixteen factors in four categories are selected based on literature and focus group interviews. A survey to analyze factor priority is conducted with 118 industry experts. The results show that maintenance requirements, airworthiness directive status, and maintenance status from the technical category are the most critical determinants of aircraft USM value, followed by traceability, former operator, and former aviation authority from the operational category and new part value. The technical category corresponds to “must-be” traits in the Kano model, requiring compliance by sellers, whereas new part value information can help buyers’ decisions. The implementation of an internationally agreed mutual accreditation system for approved maintenance organizations and a standard for aircraft dismantling is proposed to improve technical and operational determinants to achieve fewer uncertainties in USM valuation. This study aims to offer a new guideline for evaluating USM value to market participants. Price modeling of USM is left for future studies. Full article

This study explores the impact of public elderly care services on social participation among rural older adults and examines the underlying mechanisms, providing empirical evidence for improving the rural elderly care system and promoting sustainable development in rural aging societies in China. Using four waves of panel data from the China Longitudinal Aging Social Survey (CLASS) (2014–2020), this research focuses on home- and community-based elderly care services. Employing a two-way fixed-effects model and an instrumental variable approach, the study finds that the accessibility of public elderly care services significantly promotes social participation among rural older adults. This result remains robust after conducting various checks, such as replacing outcome variables, altering measurement methods, and adjusting sample sizes. Heterogeneity analysis reveals that the positive effects are more pronounced among older adults with higher education, those co-residing with adult children, and those in more economically developed regions. The accessibility of public elderly care services primarily facilitates social participation by alleviating labor supply constraints, improving mental health, and strengthening the willingness to engage. The findings suggest that improving the accessibility of public elderly care services can significantly enhance social participation and recommend expanding service coverage as a core strategy to promote active aging in rural areas, with a focus on fostering localized models like rural mutual aid and neighborhood care. Additionally, addressing information asymmetry by establishing “village-level public elderly care information service stations” and creating time banks for mutual aid care at the township level could help foster a virtuous cycle of intergenerational support. Full article

To mitigate the reduced accuracy of direction-of-arrival (DOA) estimation in scenarios with low signal-to-noise ratios (SNR) and multiple interfering sources, this paper proposes an Auxiliary Classifier Generative Adversarial Network (ACGAN) architecture that integrates a Squeeze-and-Excitation (SE) attention mechanism and a Multi-scale Dilated Feature Aggregation (MDFA) module. In this neural network, a vector hydrophone array is employed as the receiving unit, capable of simultaneously sensing particle velocity signals in three directions $\left(v_x,v_y,v_z\right)$ and acoustic pressure $p$, thereby providing high directional sensitivity and maintaining robust classification performance under low-SNR conditions. The MDFA module extracts features from multiple receptive fields, effectively capturing cross-scale patterns and enhancing the representation of weak targets in beamforming maps. This helps mitigate estimation bias caused by mutual interference among multiple targets in low-SNR environments. Furthermore, an auxiliary classification branch is incorporated into the discriminator to jointly optimize generation and classification tasks, enabling the model to more effectively identify and separate multiple types of labeled sources. Experimental results indicate that the proposed network is effective and shows improved performance across diverse scenarios. Full article

Background/Objectives: Dietary patterns play a crucial role in health, yet most research examines foods individually, overlooking how they interact. This approach provides an incomplete picture of how diet influences health outcomes. Network analysis (e.g., Gaussian graphical models, mutual information networks, mixed graphical models) offers a more comprehensive way to study food co-consumption by capturing complex relationships between dietary components. However, while researchers have applied various network algorithms to explore food co-consumption, inconsistencies in methodology, incorrect application of algorithms, and varying results have made interpretation challenging. The objectives of this scoping review were to systematically map and synthesise studies that have applied network analysis to dietary data, and to establish guiding principles for future research in this area. Methods: Using PRISMA-ScR criteria, our scoping review identified 171 articles published from inception up to 7 March 2025, of which 18 studies met the inclusion criteria. Results: Gaussian graphical models were the most frequent approach, used in 61% of studies, and were often paired with regularisation techniques (e.g., graphical LASSO) to improve clarity (93%). The analysis revealed significant methodological challenges across the literature: 72% of studies employed centrality metrics without acknowledging their limitations, there was an overreliance on cross-sectional data limiting the ability to determine cause and effect, and difficulties in handling non-normal data. While most studies using GGM addressed the issue of non-normal data, either by using the nonparametric extension, Semiparametric Gaussian copula graphical model (SGCGM), or log-transforming the data, 36% did nothing to manage their non-normal data. Conclusions: To improve the reliability of network analysis in dietary research, this review proposes five guiding principles: model justification, design–question alignment, transparent estimation, cautious metric interpretation, and robust handling of non-normal data. To facilitate their adoption, a CONSORT-style checklist is introduced—the Minimal Reporting Standard for Dietary Networks (MRS-DN)—to help guide future studies. This review was preregistered on Open Science Framework. Full article