Search Results (849)

Carbonation in CO${}_2$-storage solid-waste backfill materials couples CO${}_2$ transport, mineral reaction, and strength evolution, making carbonation-front prediction and transport–reaction inference important for evaluating sequestration performance. This study proposes an evidence-ranked, physics-guided inverse-learning framework for carbonation-front prediction, auxiliary strength reconstruction, PDE-residual assessment, and practical-identifiability analysis. The framework represents carbonation using group-conditioned latent fields of effective CO${}_2$ concentration and remaining reactive capacity, maps latent carbonation degree to measured depth through a differentiable front operator, and reconstructs unconfined compressive strength through a supervised auxiliary head. Empirical front laws and reaction–diffusion physics-informed neural-network variants were evaluated using held-out ranking, repeated stratified splits, residual-weight sweeps, front-operator threshold and smoothing-coefficient sensitivity checks, profile-likelihood and Fisher-information diagnostics, and controlled synthetic tests. Results show that the grouped Weibull front law achieved the best short-range carbonation-depth interpolation, while the retained constant-diffusion PINN was used as a diagnostic formulation within the physics-guided family to improve auxiliary strength reconstruction and to evaluate residual consistency, front-threshold selection, parameter sharing, and inverse-parameter behavior rather than to replace the empirical depth regressor. Increasing the PDE-residual weight substantially reduced residual magnitudes, but profile-likelihood and Fisher-information diagnostics indicated strong parameter trade-offs; the fitted diffusion, reaction, depletion, and diffusion–decay quantities are therefore interpreted as effective, observation-conditional parameters rather than unique material constants. The proposed framework provides a prediction-first and attribution-aware approach for analyzing carbonation evolution in solid-waste backfill materials and supports coordinated assessment of front advancement, strength response, and transport–reaction behavior, while explicitly delimiting the generalization and physical interpretation that can be supported by sparse literature-derived observations. Full article

This study analyses the economic performance, sustainability, and resilience of family farming systems in São Tomé and Príncipe, using an approach that combines quantitative and qualitative data. Primary data were collected through a survey of 50 rural families from the seven districts of the country, focus group discussions, and field observations. Quantitative analysis included descriptive statistics and exploratory comparative procedures, complemented by economic evaluation, while thematic analysis examined the qualitative data. The findings reveal diversified agroforestry systems, integrating up to 33 crops and small-scale livestock production. At the individual and aggregate levels, agroforestry shows viable economic performance, with a net profit margin of 57.4%, capable of generating income and marketable surpluses. This improves rural livelihoods, strengthens resilience to climate and market shocks, and supports both subsistence and market-oriented production. Despite these strengths, structural constraints persist, including fragile value chains, limitations in access to credit and markets, low technology adoption, and climate vulnerability. Human capital, particularly education, emerges as a key factor in improving productivity and value creation. Integrated policies on access to resources and education are needed to promote diversification, multi-activity, and market integration as central strategies for increasing sustainability, food security, and risk reduction in family farming. Full article

Sea Island cotton (Gossypium barbadense L.) is a premium raw material for high-end textiles due to its excellent fiber quality. The AP2/ERF transcription factor family plays critical roles in plant growth and hormone signaling. Here, 161 GbERF family members were identified in Sea Island cotton and classified into nine subgroups, with GbERF13 belonging to Group V. Expression analysis revealed that GbERF13 was specifically and highly expressed in fibers, with transcript abundance peaking at 15–30 days post-anthesis (DPA), coinciding with the transition from fiber elongation to secondary wall thickening. Exogenous abscisic acid (ABA) treatment significantly induced GbERF13 expression and inhibited fiber elongation. Heterologous overexpression of GbERF13 in Arabidopsis increased trichome and root hair numbers while suppressing primary root growth, confirming its role in cell elongation and development. A nonsynonymous SNP (A/C) at the 117th base pair of the GbERF13 coding region (GbERF13-117SNP) was identified in 213 Sea Island cotton accessions. Association analysis showed the C allele was significantly and positively associated with fiber length, strength, and uniformity. An allele-specific PCR marker was further developed for molecular breeding. Collectively, GbERF13 acts as a key ABA-responsive transcription factor regulating fiber development, and its functional SNP marker provides a valuable tool for improving Sea Island cotton fiber quality. Full article

Background/Objectives: Registered nurse (RN) prescribing is increasingly discussed as a strategy to improve primary-care access, medication follow-up, chronic disease management, and service responsiveness. The available evidence, however, does not directly test a single coordinated RN prescriber–family physician/nurse practitioner (FP/NP) model. This integrative review synthesized heterogeneous evidence relevant to how RN prescribing may be organized within team-based primary care. Methods: A structured integrative review approach was used to map evidence from nurse and non-medical prescribing, RN-led primary care, nurse–physician substitution, interprofessional collaboration, chronic disease medication titration, patient-experience, and implementation research. Searches completed on 30 March 2026 included PubMed/MEDLINE, PubMed Central, the Cochrane Library search interface, publisher full-text platforms, targeted scholarly searches, citation chasing, and Canadian regulatory/professional sources. Methodological quality was appraised using AMSTAR 2- and CASP-informed criteria, and the strength of interpretation was assessed narratively. No meta-analysis was performed because of substantial heterogeneity and the risk of double-counting primary studies included in prior evidence syntheses. Results: A total of 286 records were identified. After de-duplication, screening, and eligibility assessment, 37 peer-reviewed records were included: 30 review-level or evidence-synthesis records and 7 primary, mixed-methods, or patient-experience studies. Four official regulatory/professional sources were retained separately for context. Nurse and non-medical prescribing were generally associated with comparable or favourable outcomes for blood pressure, glycated hemoglobin, low-density lipoprotein cholesterol, medication adherence, patient satisfaction, and selected access outcomes in defined contexts. Direct evidence for the exact RN prescriber–FP/NP configuration remains limited. Conclusions: Current evidence is consistent with a coordinated RN prescribing model embedded within primary-care teams, but does not establish causal superiority of this configuration over other models. Coordinated RN prescribing should therefore be understood as an evidence-informed and testable implementation model requiring prospective evaluation, particularly for diagnostic safety, adverse events, continuity, workload, cost, and patient-level outcomes. Full article

Background: Early rehabilitation after pediatric ischemic stroke may support neuroplasticity and improve long-term functional outcomes. However, rehabilitation practices remain heterogeneous, and evidence-based recommendations regarding the optimal timing and intensity of intervention are limited. Objectives: This scoping review aimed to evaluate the available evidence regarding early rehabilitation after pediatric ischemic stroke, identify prognostic factors associated with functional recovery, summarize current therapeutic approaches, and highlight gaps in the existing literature. Eligibility Criteria: Eligible studies included children and adolescents aged 0–18 years diagnosed with ischemic stroke and receiving rehabilitation or therapeutic intervention. Studies addressing the timing, intensity, and effects of physiotherapy, occupational therapy, speech and language therapy, neuropsychological intervention, neuromodulation, or multidisciplinary rehabilitation were considered for inclusion. Sources of Evidence: A structured literature search was conducted in PubMed/MEDLINE, Scopus, Web of Science, the Cochrane Library, and Google Scholar for studies published between 2000 and January 2025. Charting Methods: Data were extracted using a standardized charting form and synthesized narratively because of substantial heterogeneity in study design, populations, interventions, and outcome measures. Results: Twenty-one sources met the inclusion criteria. Direct evidence specifically addressing early rehabilitation after pediatric ischemic stroke was limited and consisted primarily of observational studies. A substantial proportion of the available evidence was indirect, originating from studies of perinatal stroke, unilateral brain injury, cerebral palsy, and related pediatric neurorehabilitation populations, as well as clinical guidelines and expert consensus documents. The available evidence suggests potential benefits across motor, cognitive, communication, and functional domains, although the strength and directness of evidence varied substantially. Several studies identified the early post-stroke period as a potentially important window for neuroplasticity, while family involvement, individualized treatment planning, and interdisciplinary care were consistently highlighted as important components of rehabilitation. Evidence supporting neuromodulation techniques remained preliminary and was largely limited to selected pediatric populations. Conclusions: The available evidence, although heterogeneous and largely indirect, suggests that early coordinated and multidisciplinary rehabilitation may be beneficial in pediatric ischemic stroke care. However, the current evidence base remains limited, and high-quality prospective studies are needed to establish standardized rehabilitation protocols and determine the optimal timing and intensity of therapeutic interventions. Full article

Background: Virtual reality (VR) is a promising technology for the relief of physical and psychosocial burdens. We found that individualised VR videos were well tolerated and accepted and seemed to have a stronger effect on well-being and emotional connection than standardised VR in cancer inpatients under palliative care. For implementation, it is important to actively involve patients, as their input helps to ensure that the VR intervention meets their needs, thus making it more likely to be accepted and effective in practice, while balancing the needs of healthcare professionals. Aim: Exploration of patients’ and healthcare professionals’ perspectives on best practice VR intervention implementation. Design: Workshop-based 360° focus group using a strengths–weaknesses–opportunities–threats (SWOT) model and deductive/inductive qualitative analysis with a ‘framework’ approach. Setting/participants: The focus group took place at the National Centre for Tumour Therapy of a German university hospital. Participants were a local doctor (1) and nurses (3) with VR experience, the cooperating patient advisory board of the study (2), and members of a regional self-help group (3). Results: Eighteen subthemes were identified in the SWOT model. While there was agreement on the ‘strength of distraction’ and ‘opportunities of individualised VR’, concerns remained regarding data protection when using private VR content. There was an argument about gatekeeping by relatives worried about mental distress in patients immersing in home or family VR scenes. In contrast, many ideas were discussed regarding how to overcome rejectionist staff attitudes. However, the high organisational time and staff deployment were addressed as major weaknesses. Conclusions: Involving patient stakeholders and healthcare professionals in the planning of the implementation strategy revealed several issues that require attention. In particular, information needs to be provided not only to patients but also to relatives and hospital staff, alongside ensuring data protection and adequate staffing. Trial registration: Registered at German Clinical Trials Register (Deutsches Register Klinischer Studien; DRKS); registration number: DRKS00032172; registration date: 11 July 2023. Full article

Background/Objectives: Adolescent mental health problems have increased in recent years, with growing concern about the impact of digital behaviors such as problematic video game use and gambling. Internet Gaming Disorder (IGD) and Problem Gambling Symptoms may share psychological risk markers, but evidence in Spanish adolescents is limited. This study aimed to examine the relationship between IGD, problem gambling symptoms, and mental health, and to identify sociodemographic, psychological, and behavioral factors associated, including microtransactions and loot boxes. Methods: A cross-sectional study was conducted with secondary education students from Extremadura (Spain). The final sample included 343 participants. Measures included an ad hoc questionnaire on video game use, the IGDS9-SF, SOGS-RA, and the Strengths and Difficulties Questionnaire (SDQ). Descriptive analyses, Spearman correlations, and multivariable regression (Poisson and negative binomial) were performed. Results: IGD and gambling were positively correlated (Spearman’s ρ = 0.386, p < 0.001) and associated with higher mental health difficulty scores (IGD: ρ = 0.299, p < 0.001; gambling: ρ = 0.214, p < 0.001). Male gender was associated with both outcomes (IGD: incidence rate ratio [IRR] = 1.21 [95% Confidence Interval: 1.13–1.30]; gambling: IRR = 2.90 [1.85–4.60]). Microtransactions were associated with both behaviors (IGD: IRR = 1.17 [1.09–1.25]; gambling: IRR = 1.74 [1.19–2.54]), while loot box use was related only to IGD (IRR = 1.13 [1.05–1.21]). Total SDQ score was positively associated with both IGD (IRR = 1.02 [1.02–1.03]) and gambling (IRR = 1.10 [1.06–1.13]). Younger age was associated with higher IGD scores (IRR = 0.97 [0.96–0.99]). Conclusions: There are similarities in the associations among the examined factors and increased scores of IGD and gambling in adolescents, particularly male gender, higher mental health difficulties scores, and involvement in monetized gaming systems. School-based, family, and public health prevention strategies may benefit from addressing the importance of psychological well-being and increase awareness of the potential risks associated with digital gaming practices. Full article

Background/objectives: To describe and compare Korean AYAs’ and parental perspectives on the family environment in terms of agreement and significant differences and examine which variables were associated with AYAs’ symptom distress. Sample and setting: Self-report data were collected from a total sample of 113 AYAs, recruited from a pediatric-oncology outpatient clinic at a university-affiliated hospital and community group in South Korea. Because each study aim required different data sources, different analytic samples were used. Specifically, 54 AYA–parent dyads were included for Aim 1, whereas self-report data from 111 AYAs with complete data were used for Aim 2. Methods and variables: This subgroup analysis used a quantitative–descriptive, cross-sectional design. AYAs’ and parent perceptions of the family environment (family cohesion and adaptability, family strength, and social support from family) and AYAs’ symptom distress were collected using reliable and validated self-report questionnaires and analyzed using descriptive and inferential statistics. Results: AYAs and their parents showed low (family support) to moderate agreement (family strength, family cohesion, and adaptability) on perceptions of family environment (ICC = 0.374–0.612). AYAs reported significantly lower perceptions of family support than their parents, with a small to moderate effect (p < 0.001, d = 0.48). All family environment variables were correlated with AYAs’ symptom distress (p < 0.05). Among these variables, AYAs’ perceived family strength emerged as the only family environment variable significantly associated with their symptom distress (F = 14.309, p < 0.001, R² = 0.359, R²adj = 0.334), which was stronger during treatment. Conclusions: AYAs’ perceived family strength should be routinely assessed, especially during cancer treatment. Additional nursing interventions focusing on enhancing AYAs’ families as a support group are needed. Full article

Intrusion detection in industrial cyber-physical systems is constrained by small labelled-attack corpora and by the subtler signal of physical-process attacks compared with classical IT-network intrusions, motivating renewed interest in foundation-model-based detectors; classical detectors are typically trained per dataset and degrade under the distribution shift that is common in operational technology, where attack repertoires evolve faster than retraining cycles. Two foundation-model families are now plausible candidates: open-source Large Language Models (LLMs) and recent tabular foundation models (TabPFN, TabICL) pre-trained for in-context tabular inference. We compare the two families head-to-head, alongside Random Forest and XGBoost classical anchors, across three established industrial security benchmarks (SWaT, HAI, WUSTL-IIoT-2021) under a controlled multi-seed full-holdout protocol with paired McNemar and cross-seed Mann–Whitney tests. The empirical picture is dataset-dependent rather than universal: tabular foundation models establish a strong, previously unreported baseline that is competitive with or superior to classical anchors on every dataset evaluated, while LLMs are complementary detectors with a specific advantage on schemas that carry process-engineering semantics (such as SWaT’s named sensor channels). A per-class analysis on the WUSTL five-class attack taxonomy shows that the two families have structurally different strengths: tabular methods dominate traffic-rich attacks (Denial-of-Service, Reconnaissance), whereas LLMs are competitive on rare attack types (Backdoor, Command Injection). A confidence-gated cascade that escalates only low-confidence tabular decisions to an LLM exceeds either detector alone at a small query budget, and a leave-one-attack-type-out analysis shows that foundation-model detectors generalise to unseen attack families substantially better than the classical anchors. The appropriate detector choice in industrial cyber-physical security is therefore informed by the dataset’s feature schema, the attack-type mix, and the operational cost envelope, rather than by a specific performance metric. Full article

High-throughput technologies such as RNA-seq and single-cell transcriptomics generate increasingly large and high-dimensional gene expression datasets in which nonlinear dependence structures are common. Because classical methods primarily capture linear associations, they may fail to characterize many biologically relevant patterns of dependence. To address this limitation, diverse nonlinear dependence measures—including information-theoretic, rank-based, kernel-based, distance-based, copula-based, and clustering-based approaches—have been developed. However, the field remains fragmented, and comparative evaluations are often inconsistent. This review organizes nonlinear methods into major methodological families and critically compares their statistical behavior, strengths, limitations, and characteristic modes of failure. We emphasize that method selection depends on matching inferential objectives to estimator assumptions, analytical constraints, and characteristic failure modes. By identifying recurring trade-offs among flexibility, robustness, interpretability, and computational scalability, we provide scenario-based guidance for method selection in transcriptomics, network inference, and functional genomics. In doing so, we aim to align inferential objectives with analytical requirements, supporting principled and application-specific use of nonlinear dependence methods in modern omics research. Full article

Children in residential care constitute a particularly vulnerable group at high risk of developing emotional and behavioral difficulties as a consequence of adverse experiences and dysfunctional family environments. Identifying risk and protective factors is essential for designing interventions tailored to their needs; however, the available research remains limited and does not always provide the evidence required to guide effective programs within the child protection system. The aim of this study was to examine the prevalence of emotional and behavioral problems among children in residential care and to analyze the role of family factors, sex, and age in these difficulties. The sample consisted of 210 children aged 6 to 18 years institutionalized in residential care centers and supervised apartments. A cross-sectional design was employed, administering the Strengths and Difficulties Questionnaire (SDQ) along with an ad hoc questionnaire to collect socio-family variables. The results reveal a high prevalence of emotional and behavioral difficulties. The multivariable models explained between 8.1% and 29.4% of the variance in emotional and behavioral functioning and showed that age, sex, exposure to gender-based violence, parental substance use, and parental intellectual disability were associated with specific emotional and behavioral dimensions. The study highlights the need to develop and implement educational and therapeutic programs aimed at strengthening children’s emotional regulation, addressing behavioral difficulties, and considering family-related adversity in intervention planning. Full article

Manipulated satellite imagery threatens analytic workflows, policy decisions, and trust in geospatial intelligence. Operational systems increasingly benefit from capabilities for both manipulation detection and manipulation-family attribution to support verification, triage, and downstream analysis. We present a unified benchmark for characterizing three representative manipulation families in geospatial imagery—generative manipulations, pixel-level perturbations, and adversarial patches—using a controlled, class-balanced design and 20 modern vision architectures spanning conventional, Earth-observation-pretrained, and vision-language models. Across architectures, the dominant failure boundary is between authentic imagery and subtle pixel-level perturbations, whereas generative manipulations and adversarial patches are generally more separable under matched in-domain conditions. Additional analyses reveal important generalization limitations under unseen manipulation variants and external-domain transfer, demonstrating that strong benchmark performance does not necessarily translate to reliable operational screening. The framework also enables systematic comparison of unified multi-attack and specialized detection strategies, providing insight into their relative strengths and limitations. Rather than proposing a new defense, this work provides a reproducible methodology for characterizing manipulation artifacts, model failure modes, and deployment-relevant screening behavior in geospatial imagery, with applications to analyst triage, verification workflows, and trustworthy use of satellite data. Full article

This qualitative study examines how Orthodox and ultra-Orthodox Jewish fathers in Israel describe raising a child with autism within the everyday life of a religious family. Although research on autism and family life has expanded, fathers’ voices remain underrepresented, especially in religious families in which family routines, the Sabbat and holidays, and everyday religious practices shape parenting and participation at home. Data were collected from 127 fathers of children aged 3 to 18 through an online Hebrew questionnaire that included open-ended questions and were analyzed using qualitative content analysis. The findings suggest that religiosity shaped fathers’ caregiving not only as a source of meaning, hope, and emotional strength but also as a practical framework for everyday accommodation and belonging. Four themes emerged: (1) religiosity as an anchor for resilience; (2) paternal love as a religious practice of accommodation; (3) paternal adaptation during the Sabbat and holidays; and (4) religious authority as a basis for legitimizing care practices and preserving the child’s place within family and religious life. Together, these findings underscore the importance of culturally responsive support that acknowledges how religious meaning systems shape paternal care, family participation, and children’s inclusion, while also suggesting that fatherhood may function as an ongoing mediating process within religious family life. Full article

The Gompertz distribution is a well-known lifetime model in survival and reliability analysis, but its hazard rate is restricted to monotone increasing behavior, which limits its applicability to more complex data structures. In this study, we investigate the New Extended Gompertz (NEG) distribution, which is obtained by applying the existing NE-X generator framework to the classical Gompertz baseline distribution. Thus, the NEG model is a special case within an already established generator family rather than an entirely new family of distributions. The main contribution of this paper is not the introduction of a new generator, but rather a comprehensive and systematic investigation of this particular Gompertz-based extension, including its statistical properties, estimation procedures, and practical applications. The proposed model introduces an additional shape parameter that provides increased flexibility in modeling skewness, tail behavior, and hazard-rate structures, allowing for increasing, decreasing, bathtub-shaped, and unimodal hazard patterns under different parameter configurations. Several mathematical properties of the NEG distribution are derived, including explicit expressions for the density, distribution, survival, and hazard-rate functions, as well as moments, entropy measures, and series representations. Parameter estimation is performed using both maximum likelihood and Bayesian approaches, with numerical optimization and Metropolis–Hastings MCMC procedures employed due to the absence of closed-form estimators. The finite-sample behavior of the estimators is investigated through extensive Monte Carlo simulation studies under three different parameter settings. The practical usefulness of the NEG distribution is illustrated using two real datasets on carbon-fiber tensile strength. Comparative results with several competing Gompertz-type models indicate that the NEG distribution provides competitive performance. However, all comparisons should be interpreted within the context of the considered datasets and parameter settings, rather than as claims of universal superiority. The findings suggest that the NEG distribution offers a flexible and practical extension of the Gompertz model for lifetime data analysis. Full article

High-density urban parks are essential spaces for residents in core urban areas for restorative experiences and routine leisure. Research on the impact of cross-density contexts on the motivational structure of park recreation remains limited. Empirical identification under a high-density Built Environment remains limited, and cross-density comparison is largely absent. This study examines five high-density parks using 583 valid questionnaires and the Recreation Experience Preference (REP) scale with exploratory factor analysis (EFA) to identify the motivational structure and motivational expression strength of park recreation. Standardized density assessment and cross-density comparison in existing studies generate exploratory hypotheses. Results identify eight motivational dimensions, explaining 62.36% of the variance. Physical well-being, nature enjoyment, relaxation and family bonding, and social connection are consistently recognized across density contexts, while escape, introspection and self-realization, learning and exploration, and autonomy and independence are more likely to emerge as independent dimensions in high-density contexts. Physical well-being and social connection appear at higher proportions in low-density contexts. This study provides direct empirical evidence on the motivational structure of urban park recreation in high-density Built Environments, exploratory evidence for understanding the potential associations between urban spatial contexts and psychological needs, and a foundation for future research in human-centered urban landscape planning and management. Full article