Search Results (38,985)

Macadamia integrifolia husk (MIH) is a major byproduct of Macadamia integrifolia processing; however, there is limited information available on its rumen fermentation characteristics and associated bacterial communities when used as a feed for ruminants. This study evaluated the effects of different Bacillus subtilis (BS; ≥10¹³ CFU/g) inclusion levels on MIH using an in vitro technique. A total of six healthy goats (female, 7-month-old) with an average body weight of 15.20 ± 0.20 kg were selected as rumen fluid donors, and the rumen fluid was collected before morning feeding. Four BS inclusion levels were studied: a control group with 0 g/kg (CON), and three treatment groups supplemented with 1.5 g/kg (low dose, BSL), 3.0 g/kg (medium dose, BSM), and 4.5 g/kg (high dose, BSH) of BS. MIH supplemented with BS improved the gas production at all the observed incubation times (p < 0.05). The in vitro dry matter degradability was increased by 3.5%, 2.0%, and 3.1% in the BSL, BSM, and BSH groups, respectively, compared to the CON group at a 48 h incubation time (p = 0.049). The in vitro neutral detergent fiber degradability was increased by 6.0% and 7.8% in the BSL and BSM groups, respectively, compared to the CON group at a 48 h incubation time (p = 0.027). The in vitro acid detergent fiber degradability was increased by 11.7%, 16.8%, and 3.2% in the BSL, BSM, and BSH groups, respectively, compared with the CON group at the 48 h incubation time (p = 0.014). The concentrations of ammonia-N, microbial protein, total VFAs, acetate, propionate, butyrate, iso-butyrate, valerate, and iso-valerate were quadratically changed with increasing BS supplementation levels (p < 0.05). The relative abundances of Bacteroidota and Pseudomonadota were highest in the BSL group and lowest in the BSM group (p < 0.05), whereas Bacillota and Kiritimatiellota were highest in the BSH group and lowest in the BSL group (p < 0.05). Synergistota was highest in the BSM group and lowest in the BSH group (p < 0.05). The relative abundances of norank_p_Bacteroidota and norank_o_Bacteroidoles were highest in the BSL group, whereas they were lowest in the BSM group (p < 0.05). The relative abundances Hoyesella and Succinivibrio were highest in the BSL group, whereas they were lowest in the BSH group (p < 0.05). The relative abundances of Prevotella, Succiniclasticum, and Selenomonas were highest in the BSM group, whereas they were lowest in the BSL group (p < 0.05). These in vitro results indicate that supplementation with Bacillus subtilis could improve the utilization of MIH in goats, which is possibly associated with the altered rumen bacteria communities. The supplementation of 1.5 to 3.0 g/kg Bacillus subtilis (≥10¹³ CFU/g) on Macadamia integrifolia husk could improve its utilization as a feasible alternative feed for ruminants using an in vitro technique. Full article

The optical counterpart of the gravitational wave event GW170817, known as kilonova, has provided strong evidence that binary neutron star mergers are favourable sites to host the r-process nucleosynthesis. Kilonova is a quasi-thermal electromagnetic emission powered by the radioactive decay of heavy neutron-rich nuclei produced by the r-process. Considering the variety of elements contributing to kilonova ejecta, essential information about its composition can be achieved through spectral characterisation, radiative transfer simulations, and opacities. The latter represents one of the most challenging aspects of the modelling, as it relies on accurate atomic structure calculations of energy levels and transitions. Since light r-process elements are major opacity contributors in early (<2 days) scenario, this work focuses on atomic calculations for Zr I–IV. Energy levels and bound-bound transitions are determined using the GRASP2018 code, assuming two different datasets for each ionisation stage: one including, and one excluding core-core and core-valence correlations. Results demonstrate that the inclusion of f shell and core correlations impacts on both energy levels and transitions. A systematic assessment of the accuracy is performed through detailed comparisons with the NIST ASD and literature references. Finally, these Zr data are integrated on the open access MARTINI platform. Full article

The present study investigates the semantic structure, dominant themes, and temporal evolution of research on giftedness in early childhood through a comparative topic modeling approach. A final analytic sample (n = 518) of peer-reviewed journal articles indexed in the Scopus and Web of Science databases was analyzed. Three topic modeling methods, Latent Dirichlet Allocation (LDA), Structural Topic Modeling (STM), and BERTopic, were systematically compared using multiple evaluation metrics. BERTopic demonstrated the strongest overall performance, producing approximately 11% higher coherence than STM and approximately 34% higher coherence than LDA. In terms of diversity, it achieved 14% to 17% greater thematic variety and, according to the Gini coefficient, revealed a 58% to 60% more balanced thematic distribution. BERTopic-based analyses identified five major thematic axes: Socio-Linguistic Development and Family Context, Psychometric Intelligence, Identification, and Cognitive Differences, Program Access, Identification, and Educational Equity, Early Academic Skills and Cognitive Development, and Creativity, Higher-Order Thinking, and Enrichment Programs. Thematic mapping and topic similarity analysis were used to examine the semantic structure of the field, while linear regression-based trend analysis over the 1918–2026 publication period showed that family context, socio-linguistic development, and equity-related themes have gained increasing importance over time, whereas psychometric identification largely maintained its central position within the field. These findings indicate that the field is moving toward a more inclusive, semantically grounded, and equity-oriented perspective. However, they should be interpreted in light of the study’s reliance on article abstracts, the sensitivity of BERTopic clustering parameters, and the use of linear trend modeling. Full article

Background/Objectives: Community-based drug rehabilitation is a key component of public health strategies in China, with anti-drug social workers playing a frontline role in relapse prevention, social reintegration, and long-term recovery. However, the sustainability and effectiveness of this workforce remain uncertain due to complex organisational and structural conditions. This study aims to examine the professional roles, work-related challenges, and coping strategies of anti-drug social workers within community-based rehabilitation systems. Methods: A systematic review was conducted in accordance with PRISMA 2020 guidelines and was registered in PROSPERO (Registration ID: 1381833). The literature published between 2009 and 2025 was identified through Google Scholar, PubMed, Web of Science, and the Electronic Library. A total of 35 Chinese and English-language studies met the inclusion criteria and were analysed to synthesise evidence on social work practice in drug rehabilitation contexts. Results: The findings identify three core professional roles: information provider, resource linker, and relationship repairer. These roles highlight the multifaceted contribution of social workers in bridging institutional systems and client needs. However, their effectiveness is constrained by fragmented governance structures, role conflict, professional identity ambiguity, administrative burden, limited training, and sustained emotional labour. These conditions contribute to occupational stress, burnout risk, and workforce instability, which weaken service continuity and client-centred care. Conclusions: Strengthening community-based drug rehabilitation requires addressing workforce and system-level constraints. Clearer role definition, targeted interdisciplinary training, reduced administrative demands, and structured organisational support are essential to enhance professional capacity, improve service delivery, and support long-term recovery outcomes. Full article

Background: Knowledge of place-based communities and the lived experiences of diverse citizens such as disabled people are key to making more inclusive sustainable communities. Yet many voices in public planning and community engagement, such as people with disabilities, neurodivergent people, children and young people, are often not heard. Method: Bringing people together requires an artful approach that amplifies diverse voices and stories while enabling solutions through knowledge exchange. In this article we share the art of designing and doing community chats as an inclusive dialogical method. The community chats used The World Café’s principles and framework adapted with inclusive processes, enabling us to explore the concept of planning inclusive communities and, importantly, solutions for them with community members with and without disabilities. Findings: In this article we firstly critique the current tensions regarding community engagement in public planning and participatory research methods, before outlining our approach. This includes outlining in detail our design approach and applied processes for maximising the participation of diverse people with disabilities and chronic illnesses. We offer critical reflections on our key lessons learnt and the non-negotiables in undertaking community chats. Conclusions: By sharing our thinking, approach and lessons learnt, we offer an inclusive adaptive approach to a popular method—the world café—that can be useful to evoke meaningful and empowering knowledge exchanges with diverse people with disabilities to help progress actions towards making communities more inclusive. Full article

Genetic cardiomyopathies (GCMs) are chronic heart muscle disorders requiring lifelong monitoring and treatment. Although quality of life (QoL) and health-related quality of life (HRQoL) are increasingly recognized as important outcomes in cardiomyopathy care, their conceptualization and measurement remain inconsistent. This scoping review aims to (a) identify the tools most commonly used to assess QoL and HRQoL in adults with genetic cardiomyopathies and (b) map the thematic areas of existing studies, including symptom burden, psychological distress, diagnostic challenges, and the impact of medical and psychological interventions. PubMed, Scopus, and PsycINFO were systematically searched, and the final search was completed in November 2025. Seventeen peer-reviewed studies met the inclusion criteria and were included in this scoping review. The review followed the PRISMA extension for Scoping Reviews and included both quantitative, qualitative and mixed-methods designs. Most studies employed standardized tools such as EQ-5D (N = 5), SF-36/SF36v2 (N = 5), and the Kansas City Cardiomyopathy Questionnaire (N = 3), while others included the Minnesota Living with Heart Failure Questionnaire (N = 2) and disease-specific or ad hoc measures. The most frequently investigated themes included impairments in physical functioning, emotional well-being, symptom burden, psychological distress, and social participation. Several studies showed that patients’ perceived QoL was more closely associated with symptom burden and psychological adjustment than with objective clinical indicators alone. Clinical interventions showed mixed or limited effects on QoL and HRQoL outcomes, even when clinical parameters improved. Qualitative research further emphasized the lived experiences of patients and families, highlighting unmet needs in care. Less commonly addressed findings concerned caregiver perspectives, patient–provider communication, treatment adherence, socioeconomic disadvantage, healthcare costs, productivity loss, and the experiences of patients with rarer cardiomyopathy-related conditions. The results highlight how QoL and HRQoL are central but still inconsistently assessed outcomes in cardiomyopathy research. This review calls for greater conceptual clarity between QoL and HRQoL, greater standardization in measurement tools, broader inclusion of psychosocial variables, and more patient-centred research approaches to better support individuals living with cardiomyopathies. Full article

This study examines motivational and capability barriers to internet non-adoption in Thailand’s near-saturated digital economy. Using the 2025 Q4 ICT Household Survey conducted by Thailand’s National Statistical Office, the analysis focuses on 20,633 adult non-adopters who report either motivational or capability-related barriers. The dependent variable distinguishes capability non-adoption, defined as lack of skill or awareness, from motivational non-adoption, defined as lack of perceived need or privacy/security concerns. Weighted logistic regression with normalised population weights, PSU-clustered robust standard errors, and average marginal effects is used to estimate associations between household ICT access, age, education, employment, smartphone access, and barrier type. Motivational barriers account for 56.2% of the two-category non-adopter population and capability barriers for 43.8%. Although motivational reasons are the more common, household ICT access is positively—if modestly—associated with capability rather than motivational barriers (average marginal effect +1.7 percentage points): capability-constrained non-adopters are concentrated in connected households, the compositional signature predicted by the second-level digital divide. Age does not significantly moderate this association. Among older non-adopters, education, employment, and smartphone access are negatively associated with capability barriers, while household ICT access is not. The findings suggest that in post-access digital economies, household connectivity is insufficient for digital market inclusion; individual-level skills and device access become central to expanding effective digital market reach. Full article

Leftover spaces, often associated with neglected urban corners, bear physical and conceptual similarities to ignored parts of designed wholes. This study proposes an analytical approach to develop resilient intervention strategies by analyzing the production of leftover spaces through users’ emotional experiences. An experimental pilot study was conducted along Söğütlüçeşme Street in Kadıköy, Istanbul, where all corner points were typologically classified based on morphological characteristics. To measure the impact of these configurations on spatial emotional characters, a survey was implemented using Plutchik’s wheel of emotions. Following a quantitative analysis of emotion frequencies and intensities, findings were visualized via radar charts and spatialized using QGIS 3.40 to generate an emotional map. The resulting emotional maps were further used to identify spatial vulnerabilities and resilience priorities across the study area. By making the gaps between point-based emotional clusters continuous through the IDW interpolation method, the emotional topography of the study area was modeled, thereby presenting an analytical framework that identifies emotional thresholds, spatial vulnerabilities, and resilience priorities. Results indicate that as the physical boundaries of corner voids expand, influenced by angling and massing decisions, public diversity increases, creating a positive emotional atmosphere. Conversely, compressed voids demonstrate a higher potential for producing leftover spaces. This study reveals that mapping user emotions as a data layer is critical for constructing more inclusive and resilient urban environments. Full article

Background/Objectives: Accurate post-mortem interval (PMI) estimation remains challenging in forensic pathology. Although potassium (K⁺) is the most well-validated single biomarker in vitreous humor (VH), multivariate approaches may enhance precision by capturing the complex cascade of post-mortem biochemical changes. This study aimed to develop and validate a multivariate PMI estimation model incorporating three biochemical markers—potassium, ammonium (NH₄⁺), and albumin (ALB)—in vitreous humor using automated clinical chemistry platforms for practical forensic application. Methods: Vitreous humor samples from 38 autopsy cases with documented PMIs (39.5–285 h; mean, 105.5 h) were analyzed for K⁺ (Cobas C8000), NH₄⁺ (Cobas C8000), and ALB (Immage 800 nephelometry). Univariate and multivariate regression analyses were performed, with the residual standard error (RSE) as the primary measure of accuracy. Model validation was conducted by back-calculating PMI in four samples completely distinct from the training cohort. Results: All three analytes demonstrated strong individual correlations with PMI (R²: K⁺ = 0.88, ALB = 0.78, NH₄⁺ = 0.69; all p < 0.001). The multivariate regression model [PMI = 40.25[Alb] + 0.01573[NH₄⁺] + 5.339[K⁺] − 53.032] yielded an RMSE of ±15.5 h (MSE = 240.25 h²), outperforming potassium-only models (RMSE = ±22.6 h). Although NH₄⁺ showed limited statistical significance in the multivariate model (p = 0.128), its inclusion improved overall predictive accuracy. External validation in an independent cohort of four subjects (distinct from the 38 subjects in the training set) demonstrated a mean absolute error (MAE) of 20.4 h. Conclusions: The multivariate approach combining K⁺, NH₄⁺, and ALB in VH improves PMI estimation accuracy compared with single-marker methods. The use of automated clinical chemistry platforms enhances reproducibility and facilitates practical implementation in forensic laboratories. Full article

This study examines how mothers raising children with disabilities in American Samoa experience the processes of seeking diagnosis, navigating special education, and advocating for services within an insular rural context. American Samoa, an unincorporated U.S. territory located 2600 miles from Hawaiʻi with a population under 50,000, represents a case of what we term insular rurality—a condition in which the structural disadvantages of rurality are intensified by oceanic isolation, territorial governance, and colonial history. Data were collected through three focus groups with fifteen mothers whose children hold a range of disability diagnoses, with a card sort activity at the outset of each session serving as an idiographic anchor to protect individual voice within the group format. Analysis followed Interpretative Phenomenological Analysis adapted for focus groups (IPA-FG), proceeding from line-by-line exploratory noting through Personal Experiential Themes and Group Experiential Themes within each focus group case to cross-case convergence and divergence analysis, interpreted through the Fonofale model of Pacific wellness. Findings reveal two overarching themes: systemic invalidation, in which mothers encountered deficit-based assumptions, stagnant educational goals, and institutional disengagement; and parent peer support as the primary infrastructure, in which mothers became de facto experts, built community-driven solutions, and envisioned more inclusive futures. Technology emerged as a contradictory force—valuable for parent learning but largely ineffective for children’s remote therapy. These findings suggest how workforce shortages and geographic isolation create conditions in which maternal advocacy becomes a systems-level necessity rather than a personal choice. Implications for rural education policy, IDEA implementation in U.S. territories, and culturally grounded family support are discussed. Full article

The pursuit of sustained economic growth remains a fundamental objective for all nations, as it directly contributes to improving living standards and the overall quality of life for citizens. This research examines how human development, technological innovation and environmental taxation influence long-term economic performance across twenty-two European Union (EU) countries over the 1990 to 2022 period. Method of Moments Quantile Regression (MMQR) is employed for data analysis and the robustness check is achieved by employing the Pooled Mean Group (PMG) and Panel Corrected Standard Errors (PCSE) methods. Key findings reveal the importance of human development, research and development and investment by sector in raising the Gross Domestic Product (GDP) per capita. Moreover, the MMQR findings shows that environmental taxes exhibit positive relationships with GDP per capita in the lower and middle quantiles, while insignificant relationships prevail in the upper quantiles. Therefore, environmental taxes are subject to some upper limits on their influence on GDP per capita. Once the threshold is achieved, environmental taxes tend to harm production. The PCSE findings show that the relationship of environmental taxes and GDP per capita is a weak positive one, while the PMG results shows that these factors are negatively related. Renewable energy is observed to be negatively related with GDP per capita as supported by the MMQR, PMG and PCSE results. These findings offer valuable policy implications, reinforcing the importance of aligning economic strategies with the Sustainable Development Goals (SDGs) to foster inclusive and environmentally sustainable growth within the European context. Full article

Background/Objectives: Non-specific low back pain (NSLBP) is the leading cause of disability worldwide. Artificial intelligence (AI) technologies are increasingly being integrated into healthcare interventions for NSLBP, yet their effectiveness remains uncertain. This systematic review and meta-analysis aimed to evaluate the effectiveness of AI-based Physical therapy (PT) interventions on pain intensity and disability outcomes in patients with NSLBP. Methods: We conducted a comprehensive search across six electronic databases. Randomised controlled trials (RCTs) evaluating AI-based interventions for NSLBP were only included. Mean differences (MD) with 95% confidence intervals (CIs) were calculated using random-effects models. Heterogeneity was assessed using I² statistics and Cochran’s Q test. Results: Five RCTs (n = 1939) met the inclusion criteria for systematic review. Three RCTs (n = 594 participants) provided data for meta-analysis. AI-based interventions significantly reduced pain (pooled MD −0.721, 95% CI −1.047 to −0.395; z = −4.34, p < 0.001; I² = 9.5%). Disability also significantly improved (pooled MD −1.031, 95% CI −2.020 to −0.042; t(2) = −4.48, p = 0.046; I² = 0%). Neither effect reached the minimal clinically important difference (1.0 for pain, 2–4 for disability). No serious adverse events were reported. Conclusions: AI-based PT interventions produce statistically significant but clinically small improvements in pain and disability for NSLBP. Certainty of evidence is low due to risk of bias and imprecision. Larger, blinded RCTs with standardised outcomes are needed. Full article

Software quality assessment in agile projects remains fragmented. Technical, process-related, and team-related indicators are often evaluated through separate models, tools, and reports. This fragmentation limits cross-project comparability and weakens evidence-based decisions for software quality improvement. To address this problem, this study proposes the Overall Software Quality Index (OSQI), a multidimensional decision-support framework for software quality assessment in agile projects. OSQI integrates code quality, process quality, and team quality into a single project-level assessment model. The framework was initially grounded in ISO/IEC 25010:2011 and is discussed in relation to the ISO/IEC 25010:2023 revision, particularly its explicit inclusion of Safety as a product quality characteristic. Since the industrial datasets used in this study were not collected from safety-critical systems, Safety was not modeled as a separate OSQI dimension in the current version; instead, it is addressed as a scope limitation and future extension. The measurement structure was defined using the Goal–Question–Metric (GQM) approach. An initial set of 49 candidate metrics was reduced to 15 core indicators. This reduction was performed using dimension-specific strategies: Random Forest-based feature importance for code quality, Delphi and Analytic Hierarchy Process (AHP) for process quality, and thematic consolidation for team quality. The selected indicators were normalized and integrated through entropy-based weighting. This process generates an interpretable composite quality score. The main contribution of OSQI is not the isolated use of these methods, but their integration into a reproducible and tool-supported framework. The framework converts heterogeneous software engineering signals into a unified decision-support index. OSQI was evaluated using industrial agile project data. The data included static code analysis outputs, issue-tracking records, team assessment results, and product outcome indicators. In an exploratory validation across five industrial projects, OSQI showed a strong positive association with Net Promoter Score ($r=0.97, p=0.0076$) and a strong negative association with churn rate ($r=-0.97, p=0.0061$). A supporting software tool was also developed to automate data integration, score calculation, visualization, and project-level comparison. The findings suggest that OSQI can support quality monitoring, project benchmarking, and evidence-based improvement decisions in agile software engineering contexts. Full article

Fine-dispersed gold is difficult to quantify in natural and technogenic materials because it may occur as micron- and submicron-sized particles, films, inclusions, sorbed forms, and matrix-bound species. This study aims to provide a scientific basis for a two-stage methodology designed for the separate assessment of gravity-recoverable and hidden forms of gold. The proposed workflow includes gravity separation, ultrasonic aerohydraulic desliming, controlled thermal activation with a carbonaceous sorbent, low-temperature HCl-HNO₃-HF acid digestion at 98 °C for 2 h, instrumental Au determination, statistical processing, and SEM-EDS verification. The studied materials included ores, weathering crusts, placer materials, gravity tailings, ash-slag waste, thermally treated products, and sorbents. Two analytical series, each consisting of 50 Au determinations, showed high heterogeneity, with Au contents ranging from 0.10 to 2.80 g/t and from 0.0259 to 5.0330 g/t, respectively. Gravity-separation balance data showed that a substantial proportion of Au may remain in the tailings. SEM-EDS revealed microheterogeneity, porous aggregates, microspheres, and candidate phases; however, it was used only for mineralogical verification rather than as a quantitative method for total Au determination. The proposed workflow improves the informativeness of hidden Au-form assessment and requires further laboratory standardization. Full article

The high dropout rate in massive open online courses (MOOCs) continues to limit their potential in promoting inclusive and sustainable learning. Although many prediction models have been used to identify potential dropouts, most studies view dropout as a static classification problem and fail to clearly reveal the dynamic trajectory of learner participation over time. Therefore, this study introduces a phased analysis perspective, treating MOOC dropout as a process that continuously evolves at different stages. On the basis of the KDDCUP2015 dataset, we constructed behavioral characteristics at three time points: the first week, the third week, and the fifth week. By combining robust feature analysis and interpretable models, we systematically examined the changing patterns of dropout modes. The results revealed significant differences across the different stages. In the early stage of the course, dropout was related mainly to the unstable interaction behaviors of learners, such as restricted access to resources and irregular participation rhythms. In the middle and late stages, task-oriented behaviors, especially those related to video-based learning activities, gradually became key factors. Notably, high-frequency video participation does not always reduce the risk of dropout; when video activity is high but the overall interaction rate is low, it is more likely to indicate an increase in the risk of dropout. These results indicate that the combination of behaviors is more crucial than mere activity levels. By revealing the changing characteristics of behaviors at different stages, this study helps support the design of more practical early warning methods. Full article