Search Results (1,558)

Background/Objectives: Recovery from schizophrenia-spectrum disorders is increasingly recognized as achievable, yet no synthesis has simultaneously examined long-term outcome rates, intervention effectiveness, cognitive predictors, social determinants, personal-recovery trajectories, and mediating mechanisms within a unified framework. This systematic review aimed to address these six domains and to propose an integrative theoretical model of functional recovery, applying meta-analysis where the evidence permitted and structured narrative synthesis elsewhere. Methods: Seven databases (PubMed/MEDLINE, PsycINFO, Embase, Cochrane CENTRAL, Web of Science, Scopus, CINAHL) were searched through December 2025 following PRISMA 2020 and MOOSE guidance. We extracted eligible records (longitudinal designs, ≥6 months, adults with schizophrenia-spectrum disorders reporting functional outcomes) into two structured databases, then consolidated and de-duplicated them, yielding 467 unique papers. After topical screening and a duplicate audit, we retained 368 studies (1980–2025) and grouped them into six thematic clusters. A pre-specified rule pooled only clusters with at least five independent primary studies. Proportions were pooled with the Freeman–Tukey transformation and associations with Fisher’s z under DerSimonian–Laird random-effects models; certainty was appraised with GRADE. Results: Three pools met the threshold. Long-term functional recovery was 35.4% (95% CI 22.6–49.4; k = 11) and symptomatic remission 39.6% (95% CI 29.3–50.5; k = 7), both with very high heterogeneity (I² = 92–98%) and low certainty. The pooled association between psychological mediators and functional outcome was weak and imprecise (r = 0.23; 95% CI −0.09–0.51; k = 7; very low certainty), reflecting facilitators (positive mental health, social support, self-efficacy, hope) and barriers (internalized stigma, substance-use comorbidity, longer duration of untreated psychosis, persistent negative symptoms) acting in opposite directions. The questions concerning specific interventions, cognitive prediction, rehabilitation, and personal recovery were synthesized narratively: structured psychosocial and combined interventions and integrated rehabilitation were associated with small-to-medium functional gains; cognition, particularly social cognition and motivation, predicted later functioning; and personal recovery followed a course partly independent of clinical status. Conclusions: Recovery and remission are attainable for a substantial minority but remain heterogeneous and modestly certain. The proposed Multi-Pathway Dynamic Recovery Model organizes the evidence into five testable principles—an ordered recovery hierarchy, social-cognitive mediation of the cognition–function link, an early-phase intervention window, social-ecological embedding, and self-reinforcing feedback loops, offered as a hypothesis-generating framework rather than a validated structure. Services should prioritize comprehensive early intervention, target social cognition and stigma, and address structural determinants to optimize long-term recovery. Full article

The macroalga Kappaphycus alvarezii is a renewable source of bioactive compounds with potential in nanobiotechnology, particularly the green synthesis of metallic nanoparticles, where its extracts act as reducing and stabilizing agents. The aim of this study was to investigate the green synthesis of silver nanoparticles (AgNPs) using aqueous extracts of K. alvarezii, evaluating the influence of pH, silver nitrate (AgNO₃) and extract concentration, temperature, and reaction time, through two 2³ factorial designs with central points, as well as characterizing the obtained AgNPs by ultraviolet–visible spectroscopy (UV-Vis), dynamic light scattering (DLS), zeta potential, nanoparticle tracking analysis (NTA), and transmission electron microscopy (TEM). The selected synthesis conditions were identified as pH 13, 5.0 mg mL⁻¹ extract, and 2.5 mM AgNO₃, with two effective combinations of temperature and reaction time: 50 °C for 30 min or 60 °C for 15 min. The formation of AgNPs was confirmed by a surface plasmon resonance band at ~420 nm, showing spherical morphology, a negative zeta potential, and particle sizes ranging from 93–100 nm (NTA) to 174–192 nm (DLS), the latter reflecting the presence of aggregates in suspension. Colloidal behavior indicated partial stability, with a tendency toward aggregation during prolonged storage. Overall, these findings demonstrate the potential of K. alvarezii as a sustainable source of bioactive compounds for the synthesis of AgNPs, supporting its applicability as an antioxidant nanomaterial platform. Further biological validation and comprehensive sustainability assessments are required to evaluate its potential applications in sectors such as health, cosmetics, and agriculture. This approach reinforces the principles of Green Chemistry and aligns with several Sustainable Development Goals (SDGs), including SDG 3, 9, 12, and 14, particularly regarding the sustainable sourcing of the biomass used. Full article

Residential care settings provide not only protection but also therapeutic opportunities for children and adolescents exposed to relational adversity. This study examined attachment-related behaviors, relational dynamics, and perceptions of reference adults in residential care institutions in Portugal. Participants included 33 adolescents aged 12–18 years and 20 adults working in residential care institutions. Adolescents completed the Inventory of Attachment in Childhood and Adolescence, while professionals completed the Observation Checklist and provided qualitative descriptions of adolescents’ functioning and intervention strategies. The results revealed a predominance of non-secure attachment profiles, particularly ambivalent attachment, alongside considerable heterogeneity in observed attachment-related behaviors. Avoidant attachment emerged as a significant predictor of increased observational mental health risk, whereas observed secure attachment-related behaviors were negatively associated with psychological vulnerability. Qualitative findings highlighted the importance of emotionally responsive, consistent, and trusting relationships with reference adults, as well as the value of emotional validation, clear boundaries, and attachment-informed caregiving practices. The high heterogeneity of self-reported attachment representations and observational measures underscores the complexity of attachment functioning in trauma-exposed populations and supports the use of multi-method assessment approaches. Overall, the qualitative findings suggest that resilience in residential care is fundamentally relational and may be strengthened through stable, emotionally attuned relationships with caregivers. This study reinforces the importance of attachment-informed and trauma-informed practices in promoting psychological well-being, emotional regulation, and positive developmental trajectories among adolescents living in residential care. Full article

Generative artificial intelligence (AI) has evolved from a passive information tool into a responsive conversational system. For individuals with obsessive–compulsive and related disorders (OCRDs) that are, in part, maintained by safety behaviors and other negative reinforcement loops, large language models (LLMs) can function as highly available, potentially sycophantic, and readily repeatable sources of reassurance that may undermine the principles of exposure and response prevention (ERP). Measurement paradigms inherited from the early digital era (e.g., screen time and problematic internet use) were not designed to capture these relational dynamics. In this perspective, we propose a cognitive-behavioral framework for conceptualizing and assessing patient–AI relationships in the OCRDs. We argue that generative AI may interfere with exposure-based treatment (by eroding therapeutic friction), the discomfort, delay, and uncertainty on which corrective learning depends. We suggest that this occurs through three interlocking mechanisms: supernormal stimuli, algorithmic sycophancy, and digital accommodation. We propose an assessment architecture that records the context of AI use and rates five functional domains: Emotional Reliance, Reassurance and Checking, Anthropomorphic Attribution, Epistemic Trust, and Displacement. Adjunct ratings capture adaptive benefit, global interference, concealment, and safety-relevant exchanges. Hypothesized digital phenotypes may be derived from the domain-level profiles. We conclude by outlining a cognitive-behavioral approach to treatment planning for AI-facilitated reassurance seeking and discussing implications for safeguarding internal validity in research. We argue that structured inquiry into the patient–AI relationship belongs in OCRD assessment and research design, and we offer the present framework as a testable approach whose measurement properties remain to be established. Full article

Regression testing in continuous integration (CI) helps preserve delivered software value by exposing regressions early, but limited feedback windows make test order consequential. This study evaluates a leakage-safe dynamic test case prioritization framework that reconstructs job–build–commit provenance, combines strictly prior-build history with change–test similarity, applies class-conditional conformal calibration, and evaluates an operator-level deep Q-network (DQN). The primary held-out evaluation contains 273 failure-bearing jobs and 45,774 job–test rows from four Java projects. Pretrained history–semantic fusion achieved an equal-project macro failing-test-entity APFD surrogate (FTE-APFD surrogate) of 0.8840, compared with 0.8689 for history-only and 0.7023 for pretrained semantic-only ranking; the fusion–history difference did not survive Holm correction. A train-only TF–IDF control reached 0.7502 for semantic-only ranking and 0.8871 when fused with history in a seed-averaged diagnostic, so the benchmark does not establish unique superiority of the pretrained representation. A protocol-aligned RETECS reimplementation achieved 0.8296 ± 0.0111 FTE-APFD surrogate across five seeds. Adaptive conformal calibration reduced the candidate fraction from 0.3171 to 0.2598 while retaining 0.9058 failing-test coverage. The candidate-informed gated DQN remained below strong deterministic fusion rankings at 10%, 25%, and 50% budgets; five-seed, short-budget, hyperparameter, pre-execution-budget, and project-exclusion sensitivities did not establish a consistent DQN advantage. An additional three-project operational analysis containing 444 passing test jobs showed high failing-row coverage but strongly project-dependent candidate burden. Overall, the evidence favors strong leakage-safe deterministic rankings with explicit uncertainty control, while the evaluated reinforcement-learning design remains a local negative result rather than a general conclusion about reinforcement learning. Full article

This study proposes a source-study-aware validation framework to estimate the shear capacity of stirrup-free steel-fiber-reinforced concrete corbels and assess the reliability and generalizability of machine-learning models in structural engineering. A database of 108 specimens, compiled from seven independent studies, was analyzed using linear regression, ridge regression, and hyperparameter-optimized XGBoost. The evaluation combined standard specimen-level five-fold cross-validation, predefined source-study holdout evaluation, exhaustive partition-sensitivity analysis, and specimen-level out-of-bag bootstrap uncertainty analysis. In the predefined source-study hold-out evaluation, with hyperparameters selected exclusively from the training portion via an inner group-aware search, the models achieved test R² values of 0.842, 0.866, and 0.912, respectively, with XGBoost providing the highest point estimate of performance. However, an exhaustive sensitivity analysis of source-study partitions, in which hyperparameters were re-selected independently within the training portion of each partition, indicated that this ranking was not maintained: Linear Regression achieved the highest mean and median R² and the narrowest interquartile range, whereas XGBoost exhibited the lowest mean and median R², the widest interquartile range, and the highest incidence of negative R² values and large prediction errors among the three models; this reflects instability introduced by re-tuning under limited, group-diverse training data. The specimen-level out-of-bag bootstrap uncertainty analysis also favored the linear models in terms of mean performance and confidence-interval width. Standardized coefficients and SHAP analyses consistently identified the shear span-to-effective-depth ratio, the longitudinal reinforcement ratio, and the fiber ratio as the dominant predictors. This study provides a transparent and uncertainty-aware framework for determining when predictive performance is transferable across independent experimental studies and when caution is required in engineering applications. Full article

Seismic assessment of reinforced concrete structures requires characterization of member and connection behavior under large cyclic deformations. Moment-resisting frames are widely adopted in seismic regions, but meeting code requirements is problematic when beams are reinforced with prestressing steel strands because their ultimate elongation differs substantially from that of conventional high-ductility reinforcement (e.g., ε_u,k ≈ 3.5% for Y1770S7 strands versus ε_u,k ≈ 7.5% for B500C rebars). This study reports the findings of an experimental program conducted on reinforced concrete beam–column joints (NGS), representative of moment-resisting frame systems typically employed in seismic regions. To explore innovative structural solutions, a biomimetic design strategy was adopted, drawing inspiration from the micromechanics of Picea abies (Norway spruce). Five half-scale (1:2) specimens were subjected to quasi-static, displacement-controlled cyclic loading following the ACI 374.2R-13 (ACI T.1.1R-01) protocol, and their performance was evaluated against prescribed acceptance criteria. Adding one longitudinal steel strand and partially anchoring it in normal concrete (NGS2) and in biomaterial-adapted grout (NGS4) did not increase the amount of dissipated energy when compared to the reinforced concrete conventional solution (NGS1). Moreover, the effects of replacing the rebars with partially anchored steel strands (NGS3 and NGS5) proved to be negative. Full article

Firms are embedded in transaction systems whose organization can generate both coordination benefits and relational exposure. Using disclosed related-party transactions (RPTs), we construct annual weighted bipartite networks for 2674 Chinese A-share listed firms and examine 26,264 RPT-active firm-year observations from 2003 to 2024. The analysis distinguishes three firm-level dimensions—relationship scale, transaction concentration, and projected shared-counterparty position—from local bipartite microstructures. The firm-level evidence reveals a double-edged pattern: broader and more valuable RPT relationships are associated with lower Merton and KMV distance to default (DD), and projected degree is associated with lower Merton DD, whereas a higher top-three-related-party share is associated with higher KMV DD. Direction-specific estimates reinforce this distinction. Scale is negatively associated with DD on both the seller/provider and buyer/recipient sides, concentration is generally positive (especially on the buyer/recipient side), and seller/provider projected degree is negatively associated with KMV DD. At the local level, closed 2 × 2 presence and intensity are negatively associated with Merton DD, while simple degree-based forms and shared-counterparty bridges provide less stable differentiation. Observed closure substantially exceeds degree-sequence-preserving randomized benchmarks, and excess closure remains negatively associated with Merton and Bharath–Shumway DD after relationship opportunities and counterparty popularity are controlled. The results establish transaction scale, value allocation, projected reach, and repeated local sharing as complementary signals for structure-sensitive credit risk monitoring in complex transaction systems. Full article

Short-form video platforms have become deeply embedded in everyday digital life, where algorithmic recommendation enhances user experience but also raises concerns about invasiveness and manipulativeness. Drawing on the Cognitive–Affective–Conative (CAC) framework, this study examines the relationships between users’ cognitive evaluations of recommendation algorithms and continuance intention through algorithm dependence and algorithm aversion, while also identifying configurational pathways associated with high continuance intention. Based on 547 valid responses from short-form video users in China, we measured personalization, diversity, invasiveness, manipulativeness, algorithm dependence, algorithm aversion, and continuance intention. PLS-SEM was used to test direct and mediating effects, and fsQCA was employed to identify sufficient configurations associated with high continuance intention. The results show that personalization and diversity positively predict continuance intention and exert significant indirect effects through algorithm dependence, whereas manipulativeness negatively predicts continuance intention; invasiveness and algorithm aversion show no significant direct effects. The fsQCA results identify three dependence-maintenance pathways—experience-reinforced dependence, risk-buffered dependence, and risk-tolerant dependence—with algorithm dependence serving as a core condition across all four sufficient configurations. Notably, algorithm dependence and algorithm aversion coexist in two risk-tolerant configurations associated with high continuance intention. By distinguishing algorithm dependence from algorithm aversion, this study refines the affective dimension of the CAC framework, clarifies their differentiated roles in continuance intention, and provides configurational insights for responsible recommendation-system governance. Full article

Background: Bulk-fill resin composites have limitations regarding depth of cure and often lack bioactive functionality, which may compromise their long-term clinical performance. Purpose: This in vitro study evaluated the effects of incorporating niobium-doped nanofibers (Nb-NFs) on the physicomechanical properties and bioactive potential of an experimental low-viscosity bulk-fill resin composite. Methods: Three groups were investigated: BF (experimental resin; negative control), BFflow-fiber (experimental resin containing 1 wt% Nb-NFs), and S-PRG (commercial bioactive resin; positive control). Surface hardness (SH) was measured on the top and bottom surfaces using Knoop microhardness testing (n = 6), and depth of cure (DoC) was calculated as the bottom-to-top hardness ratio, with a value of ≥80% considered acceptable. Surface roughness (SR; n = 6) was assessed using profilometry. Mineral deposition was analysed using X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR) after 21 days of immersion in simulated body fluid. The data were analysed using analysis of variance (ANOVA) and Tukey’s test (p < 0.05). Results: The incorporation of Nb-NFs significantly increased SH on both surfaces (p < 0.05) but reduced DoC (p < 0.05). FTIR revealed phosphate bands characteristic of calcium phosphate formation, while XRD indicated initial apatite nucleation. Surface roughness remained comparable to that of the control groups. Conclusions: Nb-NFs represent a promising reinforcement strategy for bioactive bulk-fill composites; however, further optimisation is required to improve the depth of cure before clinical application. Full article

Measles remains a public-health concern where immunity gaps and incomplete vaccination coverage persist. This study assessed household and geographic factors associated with laboratory-confirmed measles among suspected cases in three Zambian provinces. A prospective cross-sectional study was conducted during measles outbreaks in five selected districts across Luapula, Northern and Northwestern provinces. Suspected cases meeting the IDSR case definition were consecutively enrolled. Blood samples were collected, transported to the UTH Virology Laboratory, and tested using procured IgG test kits. Participant characteristics were summarised descriptively. Bayesian logistic regression estimated associations between laboratory-confirmed (IgG positive) measles and age, sex, vaccination status, household size and previous measles history, with province added in a second model. Results were reported as posterior odds ratios with 95% credible intervals. Among the 172 suspected cases, 45 (26.2%) were laboratory confirmed (IgG positive). Vaccination status was verified using caregiver-provided immunization cards; status was unknown for 110 (64.0%) participants (all of whom tested negative), reflecting missing vaccination documentation. Vaccinated participants had 93% lower adjusted odds of laboratory-confirmed measles than unvaccinated participants (adjusted posterior OR: 0.07, 95% CrI: 0.02–0.18). Adjusted posterior probabilities were consistently lower among vaccinated participants across all three provinces (34% to 49%) than among unvaccinated participants (86% to 92%). Age, sex and household size were not clearly associated with measles positivity. All four participants reporting a previous measles history tested positive, and the unadjusted association was significant using Fisher’s exact test (p = 0.004). Vaccination status was most strongly associated with laboratory-confirmed measles, with substantially lower adjusted odds among vaccinated participants. These findings reinforce the importance of measles vaccination in outbreak prevention and control. Full article

The influence of chitosan (CS) molecular weight on the interfacial architecture of Ti₃C₂T_x MXene (MX)/chitosan composites (CS/MX) was investigated using complementary spectroscopic and microscopic techniques. Two commercial chitosans with distinct molecular weights and degrees of deacetylation (DD) were evaluated, CS-1 (91 kDa, 73.05% DD) and CS-2 (153 kDa, 69.52% DD). Ti₃C₂T_x MXene was synthesized by selective etching of Ti₃AlC₂ and characterized by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR), and Raman spectroscopy. XPS and Raman analyses provided evidence for successful MXene formation through a 45.4% reduction in surface aluminum content, a substantial increase in fluorine-containing surface terminations, and the emergence of the characteristic A₁g(Ti,C) Raman mode at ~200 cm⁻¹. Composite membranes containing different MXene loadings (MX-25, MX-50, and MX-75) were prepared by vacuum-assisted filtration and characterized. Morphological and spectroscopic analyses revealed that the lower-molecular-weight chitosan promoted more effective intercalation between MXene layers, resulting in expanded accordion-like structures and greater surface accessibility. In contrast, the higher-molecular-weight chitosan formed a thicker polymer coating that partially encapsulated the MXene sheets. ATR-FTIR, Raman, and XPS results demonstrated that CS-MX composite formation was governed by non-covalent interactions, primarily electrostatic attraction between protonated chitosan –NH₃⁺ groups and negatively charged MXene surface terminations, reinforced by hydrogen bonding. These findings demonstrate that chitosan molecular weight is a key design parameter governing the interfacial architecture and surface accessibility of Ti₃C₂T_x-based composites. Full article

This work investigates the development of multifunctional bioceramic composites based on hydroxyapatite reinforced with the lead-free piezoelectric phase sodium potassium niobate, Na_0.5K_0.5NbO₃. Hydroxyapatite powder was synthesized by aqueous precipitation and combined with sodium potassium niobate synthesized by solid-state reaction to produce bulk ceramics containing 0, 10, 20, and 30 wt.% sodium potassium niobate, consolidated by conventional sintering. The materials were characterized in terms of density, linear shrinkage, phase composition, microstructure, elemental composition, flexural strength, and antibacterial response. X-ray diffraction analysis confirmed the coexistence of hydroxyapatite and orthorhombic sodium potassium niobate, with the intensity of sodium potassium niobate-related reflections increasing with its content, together with minor secondary phases. Scanning electron microscopy revealed the progressive incorporation of sodium potassium niobate grains into the hydroxyapatite matrix and showed a strong dependence of porosity on sodium potassium niobate content. Flexural tests showed that intermediate sodium potassium niobate additions improved strength compared with monolithic hydroxyapatite, whereas highly porous compositions exhibited reduced mechanical performance. Agar-diffusion tests against representative Gram-positive and Gram-negative strains showed measurable inhibition zones, although the differences between pure hydroxyapatite and composites containing sodium potassium niobate were limited and species-dependent. Slight increases were observed for P. aeruginosa and S. aureus, whereas no appreciable changes were detected for the other strains. Therefore, these findings should be regarded as preliminary evidence of antibacterial response rather than as confirmation of an intrinsic antibacterial effect of sodium potassium niobate. Overall, the structural and mechanical results indicate that hydroxyapatite/sodium potassium niobate composites are promising lead-free candidates for the development of multifunctional bioceramics, while their antibacterial response requires further validation. Full article

Square steel tube–high-strength spiral stirrup composite confined concrete (SHSCC) columns combine the advantages of external steel tube confinement and internal high-strength spiral reinforcement, offering considerable potential for improving the seismic performance of composite columns. However, systematic investigations of their cyclic compression–bending behaviour over a broad range of key design parameters remain limited, and the relative importance of these parameters has not been sufficiently clarified. In this study, a three-dimensional nonlinear finite element model was established in ABAQUS and validated against one experimental specimen in terms of hysteretic response, skeleton curves, ultimate lateral load and failure mode. The differences between the numerical and experimental peak lateral loads were 3.6% and 16.8% in the positive and negative loading directions, respectively, while the difference between the average absolute peak loads was approximately 7.5%. Based on the validated model, a comprehensive parametric study was conducted to investigate the influences of axial compression ratio, concrete strength, spiral spacing, spiral bar diameter and steel tube thickness on the cyclic behaviour of SHSCC columns. The results showed that increasing the steel tube thickness from 4 to 7 mm increased the ultimate lateral load, ductility coefficient and initial stiffness by 62.3%, 26.9% and 52.0%, respectively, indicating a pronounced beneficial effect of steel tube thickness within the investigated range. Increasing the axial compression ratio to 0.90 reduced the ultimate lateral load by 37.8% and the ductility coefficient by 31.8%, indicating a pronounced deterioration in cyclic performance at high axial compression levels. Increasing the concrete strength from C30 to C60 increased the ultimate lateral load and initial stiffness by 12.2% and 22.9%, respectively. In contrast, increasing the spiral spacing from 20 to 200 mm reduced the ultimate lateral load and ductility coefficient by 5.2% and 30.8%, respectively, whereas changing the spiral bar diameter from 8 to 12 mm produced only a 2.5% increase in ultimate lateral load. These results quantitatively clarify the relative effects of the principal design parameters on the cyclic response of SHSCC columns and provide numerical evidence for parameter selection and seismic performance optimization. Full article

Wildfire and atmospheric nitrogen (N) deposition are increasingly important drivers of forest recovery under global change, yet their combined effects on understory shrub dynamics remain poorly understood in subtropical forests. We quantified temporal changes in shrub aboveground biomass (AGB) following low-severity fire and N addition in a subtropical conifer–broadleaf mixed forest in Central China, and evaluated the underlying mechanisms of resource and trait. Burning reduced shrub AGB by 58.3% in the first post-fire year, but this negative effect rapidly weakened, disappeared within two years, and shifted to a net positive effect (+28.2%) by year four. Nitrogen addition increased shrub AGB by 26.5%, with gradually strengthening effects over time. Understory light availability, soil available N, and community-weighted leaf area were the key predictors explaining variation in shrub AGB. Fire induced changes in shrub AGB was most strongly associated with leaf area rather than specific leaf area or foliar nutrient concentrations. Nitrogen addition improved shrub growth primarily through increased soil N availability and foliar N enrichment. Overall, post-fire shrub recovery was governed by a successional shift in limiting factors, transitioning from initial disturbance constraint to light-driven structural control with increasing importance of soil nutrient supply. These findings demonstrate that post-fire shrub recovery in subtropical forests is increasingly governed by canopy-mediated structural strategies rather than acquisitive leaf economics during succession. Therefore, increasing wildfire activity and atmospheric N deposition may reinforce shrub-dominated understory states, with important implications for post-fire regeneration trajectories and long-term forest carbon dynamics. Full article