Search Results (3,741)

Data silos and topological incompatibility between building information modeling (BIM) geometric models and finite element method (FEM) analysis models in transportation infrastructure engineering represent critical bottlenecks that impede real-time digital twin analysis and the intelligent transformation of the industry. Based on a critical review of existing BIM-to-FEM conversion methods and their limitations, this study proposes a “BIM-FEM” seamless conversion and dynamic twin mapping method that integrates parametric modeling with finite element meshing, with modeling and repair time reduced from 16 h to 3 h, and the maximum element aspect ratio improved from 84.78 to 16.59. In terms of geometric topology, we propose a collaborative construction method in which finite element hexahedral meshing rules drive BIM parametric modeling in reverse. By regularizing the decomposition of axis lines and cross-sectional feature points of linear transportation structures and optimizing their topology, we achieve fully automated hexahedral meshing without topological errors. In terms of mechanical analysis, an “offline pre-solution, online superposition” computational order-reduction model is proposed. This reduces the high-dimensional full-range finite element solution of dynamic traffic loads to a dot product operation between the influence line matrix and real-time load vectors, enabling sub-second computational response under high-concurrency dynamic traffic conditions—specifically, single-point mapping takes less than 0.27 ms, incremental updates are controlled within 0.2 s. In terms of spatiotemporal mapping and system applications, a high-fidelity “FEM-BIM” mapping mechanism based on inverse isoparametric transformation and AABB (Axis-Aligned Bounding Box) spatial indexing has been established, supporting real-time rendering of 3D cloud maps on the web and digital twin applications in engineering. Applications of this method in real-world bridge engineering digital twin systems have demonstrated its ability to perform automatic structural safety assessments and health condition predictions with an overall computation time reduction of approximately 73% compared to conventional approaches. This addresses the shortcoming of traditional structural health monitoring—which emphasizes sensor-based identification over mechanistic evaluation—and provides a viable path for intelligent, precise management and maintenance of transportation infrastructure throughout its entire life cycle. Full article

Pressurized seepage alters the water-accessible pore system of clay-mineral-rich slate, but its scale-dependent response remains unclear. Argillaceous calcareous slate from the Lower Cambrian Qiongzhusi Formation (Є₁q) was investigated using paired low-field NMR measurements on two specimen batches before and after 72 h treatments at nominal 0 MPa (low-head seepage), 1, 3, and 5 MPa. Total pore volume, pore-size composition, characteristic radii, and pore-size non-uniformity were evaluated. The total pore-volume increment increased from 0.98% to 1.43% in Batch I and from 0.88% to 1.56% in Batch II between 0 and 5 MPa. The dominant peak remained near 1.2 × 10⁻² μm, whereas its amplitude and large-pore spectral tail increased. The combined nanopore and micropore proportion decreased from 90.16–95.28% before treatment to 83.13–89.69% after treatment. The macropore increment increased from 0.15%/0.16% to 0.52%/0.52% in Batches I/II, while r₅₀, r₆₀, and C_u increased and r₁₀ changed only slightly. Sensitivity analysis over ρ₂ = 5–50 μm/s preserved the larger-pore enhancement. These results indicate pressure-enhanced opening, water accessibility, and local redistribution of pre-existing pores rather than extensive pore-system reconstruction, providing a pore-scale reference for seepage-related deterioration assessment. Full article

This study quantitatively analyzed the dynamic changes in the evaluation scores of ecological carrying capacity (ECC_it) and per capita ecological footprint (ef) across six counties in the Qinghai Lake Ecological Functional Zone from 2000 to 2024. A coupling coordination prediction model and cluster analysis were employed to classify the six counties within the Qinghai Lake Ecological Functional Zone and to identify appropriate industrial development pathways. In addition, a system dynamics approach was used to verify the rationality of the county clustering and industrial pathway selection and to predict the dynamic changes in ecological carrying capacity (ECC_it), per capita ecological footprint (ef), and their coupling coordination degree (CCDM) for each county through 2035. The results indicate that: (1) Significant differences existed in the ecological carrying capacity evaluation scores (ECC_it) among the counties in the Qinghai Lake Ecological Functional Zone. The average score was the highest in Huangyuan County (56.81), the next was in Gonghe County (51.73), and the lowest was in Wulan County (34.76) from 2000 to 2024. (2) There are significant differences in the per capita ecological footprint (ef) within the Qinghai Lake Ecological Functional Zone. From 2000 to 2024, the lowest average value was in Gonghe County (0.53), and the highest was in Huangyuan County (1.55), which indicates a clear mismatch between ecological carrying capacity and ecological footprint. (3) The coupling coordination between ecological carrying capacity and ecological footprint remained relatively low across all six counties during 2000–2024. Among them, the D value of Haiyan County was the lowest (0.64), while that of Gonghe County was the highest (0.86). (4) The six counties were divided into Key conservation zones (Gangcha County, Gonghe County, Tianjun County, Wulan County), a General conservation-oriented development zone (Haiyan County), and a Transfer-development zone (Huangyuan County). This study provides policy suggestions and practical guidance for the sustainable development of industrial zoning in the Qinghai Lake Ecological Functional Zone: Key conservation zones should strengthen the matching of ecological investment and industrial structure, the General conservation-oriented development zone urgently needs to establish a fiscal mechanism that uses tourism revenue to support ecology, and the Transfer-development zone must seek a dynamic balance between industrial increment and emission reduction technologies. Full article

Background: In Japan, official prices of pharmaceuticals have been determined by efficacy and safety. In 2019, Cost-Effectiveness Evaluation (CEE) was introduced to adjust these prices according to Incremental Cost-Effectiveness Ratios (ICERs). Objectives: To analyze the differences in the factors influencing drug price between the initial official drug pricing and subsequent price adjustments based on CEE. Methods: Twenty-three drugs evaluated in Japan between 2019 and May 2025 were descriptively analyzed using public reports on official drug pricing and CEE. Results: Four differences were identified: (1) Official initial drug pricing grants premiums for certain characteristics that are not directly associated with improvements in Health-Related Quality of Life (HRQoL), whereas such premiums are not considered in CEE. (2) Official drug pricing limits comparators to existing drugs, whereas CEE did not impose such restrictions. (3) Official drug pricing excludes older drugs as comparators to reward innovation, whereas they were not excluded in CEE. (4) CEE requires sufficient data for CE analysis, such as clinical trial or real-world data, for comparators, unlike official drug pricing. Factors (1) and (3) were most frequent. Conclusion: Reducing these differences and maintaining consistent innovation evaluations may enhance price predictability and support sustainable pharmaceutical investments in the Japanese market. Full article

Research suggests that anxiety predicts student performance, and that this relationship is mediated at least in part through self-defeating behavior. However, the nature of this relationship has yet to be fully understood. While substantial research has characterized the ways that anxiety affects student performance directly, at the point where it occurs (e.g., test anxiety, stage anxiety), less research has addressed the ways anxiety affects student performance indirectly, as students prepare for a performance. The first type is commonly referred to as performance anxiety. We refer to the second as preparation anxiety, and suggest that it is a necessary counterpoint, and that the relationship between anxiety and student outcomes cannot be fully understood without it. In the present study, we seek to characterize preparation anxiety, distinguishing it from performance anxiety and developing a scale to measure it: The Preparation Anxiety Scale (PAS). We report three studies, each conducted with undergraduate students at a large west-coast university: In the first study, focus groups were conducted to generate items representing the preparation anxiety construct. In the second study, exploratory factor analysis identified a 32-item, three-factor solution, with factors assessing affective nerves (PAS-AN), behavioral avoidance (PAS-BA), and cognitive agitation (PAS-CA). The scale displayed good test–retest reliability and demonstrated adequate convergent and discriminant validity. In the third study, confirmatory factor analysis supported the three-factor solution and bifactor analysis indicated a strong general factor, supporting the use of a summary score. Further analyses demonstrated both criterion and incremental validity, showing that the PAS and its subscales predict relevant behaviors (procrastination), correlates (academic self-efficacy), and outcomes (GPA) beyond other constructs. Additionally, regression analysis reveals a suppressor relationship: When the PAS-BA and PAS-AN subscales are controlled for, the PAS-CA subscale emerges as a negative predictor of procrastination and a positive predictor of academic self-efficacy. Full article

Forecasting USD/CNY exchange rate volatility is of substantial practical significance for the management of cross-border capital flows and the formulation of monetary policies. In recent years, multiple external shocks arising from China–US geopolitical tensions and sharp fluctuations in the international crude oil market have become increasingly intertwined. Traditional forecasting models are often unable to capture such sudden risk signals in a timely manner, while a single model is also insufficiently adaptable to multi-scale volatility structures. To address these challenges, this paper develops a deep-learning-based dynamic forecasting framework that integrates a China–US geopolitical risk feature system (CUGRI) with international oil price shock signals. Specifically, CUGRI is constructed from news texts published by 15 authoritative Chinese and US media outlets, combining a finance-specific language model with a geopolitical-domain sentiment lexicon to build a five-dimensional daily risk quantification feature system. At the modeling level, this paper proposes a GRU-BiLSTM-Transformer dynamic fusion model, which adaptively assigns fusion weights according to the recent forecasting performance of each sub-model. All empirical analyses are implemented under the Python programming environment with the PyTorch deep learning framework. Using nearly ten years of daily data, this paper conducts out-of-sample forecasting tests. The empirical results show that the proposed dynamic fusion model achieves an out-of-sample $R^2$ of 0.342, while reducing RMSE and MAE by 4.01% and 3.72%, respectively, relative to the best-performing baseline model. CUGRI exhibits significant incremental predictive value, with forecasting gains substantially higher during periods of elevated geopolitical risk than under normal conditions. Oil price shocks provide complementary predictive information, and the dynamic weighting mechanism further improves the accuracy of combined forecasts. In practice, the findings are relevant to cross-border firms and financial institutions when tracking changes in geopolitical and energy-market risks and adjusting foreign-exchange hedging strategies. For monetary and regulatory authorities, the model helps identify periods when external shocks may amplify USD/CNY volatility and supports exchange-rate risk surveillance and macro-financial stability analysis. Full article

Doomscrolling has emerged as a specific pattern of digital engagement involving habitual and immersive exposure to negative online news, yet no published Arabic validation of the Doomscrolling Scale has been identified. This study aimed to translate the Doomscrolling Scale into Arabic and evaluate preliminary psychometric evidence for its use among Saudi young-adult social media users by examining its factor structure, reliability, measurement invariance across gender, and convergent, discriminant, and incremental validity. A cross-sectional online survey was conducted with 793 Saudi social media users aged 18–25 years. The sample was randomly split into exploratory factor analysis (EFA; n = 396) and confirmatory factor analysis (CFA; n = 397) subsamples. Parallel analysis and EFA supported a one-factor structure. Ordinal CFA using WLSMV in the independent CFA subsample supported the 15-item one-factor model, scaled χ²(90) = 216.48, p < 0.001, CFI = 0.976, TLI = 0.972, RMSEA = 0.060, 90% CI [0.050, 0.070], and SRMR = 0.040; standardized loadings ranged from 0.585 to 0.787. Internal consistency was high in the full sample (Cronbach’s α = 0.921), and model-based reliability was strong (McDonald’s ω/composite reliability = 0.924). Ordinal measurement invariance across gender was supported up to the strict level. Doomscrolling correlated positively with fear of missing out, problematic social media use, daily social media use, and news-checking frequency, and negatively with perceived digital well-being. In a latent incremental-validity model, doomscrolling retained a unique negative association with perceived digital well-being (β = −0.269, p < 0.001). The 15-item Arabic Doomscrolling Scale has preliminary support as an internally consistent and valid research measure for assessing doomscrolling among Saudi young-adult social media users. Full article

Background: HPV genotype-based stratification estimates cervical disease risk but does not directly measure cellular transformation. We assessed whether p16 and Ki-67 improve prediction of CIN2+ beyond HPV genotype and age in a biopsy-confirmed referral cohort. Methods: This retrospective study included 531 high-risk HPV-positive women evaluated between December 2023 and January 2026 who had either margin-negative excisional histopathology or completed 12-month surveillance after conservative management. HPV genotypes were grouped as HPV16, HPV18, or other high-risk types. Independent associations were examined using prespecified multivariable logistic models; discrimination, calibration, 2000-resample bootstrap validation, and a uniform index-biopsy-reference sensitivity analysis were evaluated. Results: CIN2+ was confirmed in 191/531 women (36.0%). HPV16 positivity (adjusted odds ratio [aOR] 1.72, 95% confidence interval [CI] 1.15–2.57), age (aOR 1.027 per year, 95% CI 1.011–1.043), and p16 positivity (aOR 2.97, 95% CI 1.81–4.89) independently predicted CIN2+, whereas Ki-67 did not (aOR 1.74, 95% CI 0.90–3.35; p = 0.098). Adding p16 to age and genotype increased the AUC from 0.608 to 0.704 (ΔAUC 0.097, bootstrap 95% CI 0.057–0.138); Ki-67 increased it only to 0.707 (ΔAUC 0.003, 95% CI −0.002 to 0.015). Optimism-corrected AUCs were 0.599, 0.696, and 0.697, respectively. The uniform biopsy-reference analysis produced the same pattern. Conclusions: p16 provides reproducible incremental risk information beyond age and HPV genotype in biopsy-confirmed cervical disease, whereas Ki-67 adds little once p16 is known. Neither biomarker should replace histopathology-guided management. Full article

Urban regeneration has become a central focus in global urban studies, increasingly linked to the dual imperatives of sustainability and urban resilience. According to Christopher Alexander’s theories of living structure and pattern language, traditional built environments emerge through progressive adaptation rather than top-down design. Moreover, historic urban fabrics evolve through continuous refinement of spatial solutions that simultaneously respond to environmental, functional, and social needs. Therefore, this study situates urban regeneration within a theoretical framework that recognizes traditional settlements as complex adaptive systems rather than static heritage. Chinese urban villages (Chengzhongcun) and Spanish Suelo Urbano no Consolidado (SUNC, Unconsolidated Urban Land) areas represent two contrasting forms of urban socio-spatial systems engulfed by urban expansion, both characterized by dense, historically rooted morphologies and incomplete infrastructure. As Chinese urban villages shift from a demolition–reconstruction model toward more sustainable regeneration approaches, this study compares Beijing’s Cuigezhuang and Málaga’s El Perchel through spatial analysis and stakeholder surveys. Alexander would argue that the demolition–reconstruction model disrupts the evolutionary processes that generate coherent urban fabrics. The research evaluates how differing planning systems foster or constrain sustainable development and social-spatial resilience in regeneration processes. Urban resilience is explicitly defined here as the capacity of urban communities and spatial structures to adapt to change, withstand pressures, and maintain social cohesion, accessibility, and local identity, while ecological and economic resilience are not measured in this study. Findings demonstrate that Spain’s incremental, participatory approach—anchored in Planes Especiales de Reforma Interior (PERI, special plans for inner urban renewal) and land readjustment (equitable distribution of costs and benefits) mechanisms—significantly outperforms China’s state-led demolition-based model in supporting long-term sustainability, heritage integrity, community cohesion, and spatial continuity. Spain’s legally embedded participation and in situ rehabilitation strategies offer transferable lessons for China’s evolving sustainable and resilience-oriented regeneration paradigm. Full article

Background/Objectives: Preoperative risk stratification in renal cell carcinoma (RCC) remains challenging for tumor aggressiveness and for adherent perinephric fat (APF) relevant to surgical planning. Although intratumoral radiomics are established, the peritumoral and perirenal fat microenvironment is biologically active and may encode imaging biomarkers. This systematic review and meta-analysis evaluated CT-based peritumoral and perirenal fat radiomics for preoperative grading, staging, and APF prediction and examined whether fat-derived features add incremental value beyond intratumoral models. Methods: Following PRISMA 2020 and a registered protocol (PROSPERO CRD420251150155), databases were searched through March 2026, with documented verification searches through August 2026. Eligible studies extracted CT radiomics from peritumoral or perirenal fat in adults with RCC and reported discrimination metrics. Random-effects meta-analyses (restricted maximum likelihood with Hartung–Knapp intervals) were performed; incremental value was estimated from nested within-study AUC differences under predefined rules; and methodological quality was assessed with PROBAST, RQS, METRICS, and TRIPOD, and certainty with an adapted GRADE framework. Results: Twenty-five retrospective studies (10,761 patients) were included. Fat radiomics were most consistent for APF prediction (pooled AUC 0.848, 95% CI 0.738–0.917; I² = 0%). Pooled AUCs were 0.772 (0.599–0.884; I² = 93%; 95% prediction interval 0.298–0.964) for grade and 0.813 (0.681–0.899; I² = 72%) for stage. Combined fat-plus-tumor models were numerically higher than tumor-only models in 12 of 15 studies (exploratory p = 0.022), but the formally estimable nested increment (stage family, five studies) was small (delta-AUC +0.017; governing modified Hartung–Knapp 95% CI −0.008 to +0.042) and statistically compatible with no true difference; fat-only models showed no evidence of differing from tumor-only models. PROBAST rated 72% of studies at high risk of bias, and 88% originated from China. Certainty ranged from VERY LOW (grade prediction; grade-family fat-versus-tumor comparison) to LOW (all remaining outcomes). Conclusions: CT-based peritumoral and perirenal fat radiomics show the most consistent signal for APF prediction, while the measurable increment from adding fat features to tumor models is small and of unestablished clinical utility. Standardized fat segmentation, calibration and decision-curve reporting and prospective multicenter validation are required before clinical translation. Full article

Background/Objectives: The study aimed to assess cardiometabolic effects of two pseudocereals, quinoa and buckwheat, comparing them to the effects of rice and bulgur in adults with overweight or obesity. Methods: This study was conducted on 148 adults with overweight and obesity, aged between 25 and 45 years, consuming 40 g/d quinoa, buckwheat, rice, or bulgur for 4 weeks. Anthropometrical measurements were taken, and dietary intake was assessed; blood pressure and biochemical parameters were examined. Incremental areas under the curve (iAUC) for glucose and insulin were calculated. Subgroup analyses were conducted considering sex. Results: The changes in biochemical and anthropometrical measurements did not differ significantly between groups. However, within-group analysis showed significant changes in many parameters. Among anthropometrical measurements, fat mass declined significantly within quinoa and buckwheat groups (p < 0.05). Blood pressure decreased significantly in the buckwheat group, mainly in women. Fasting glucose decreased significantly only in men in the quinoa group. An increase in iAUC glucose within the bulgur group but a significant decrease in iAUC insulin among men within the buckwheat group was recorded. Total cholesterol (Total-C) significantly decreased in men but increased in women following quinoa consumption. On the other hand, a decrease was reported in high-density lipoprotein cholesterol (HDL-C) in women following quinoa and buckwheat consumption (p < 0.05). Conclusions: Compared with the baseline, the most pronounced changes were observed in blood pressure, lipid profile, and body fat mass, suggesting a potential cardiometabolic benefit of quinoa and buckwheat. However, sex-specific cardiometabolic differences may occur following the consumption of pseudocereal or cereal. Further studies are needed for more robust results. Full article

Background: Skeletal muscle depletion and malnutrition are common in heart failure (HF) and are associated with poor outcomes. Whether imaging-derived skeletal muscle reserve and laboratory-based nutritional indices provide complementary prognostic information remains unclear. We evaluated the prognostic value of total pectoral muscle area (TPMA), Prognostic Nutritional Index (PNI), and Controlling Nutritional Status (CONUT) scores in patients hospitalized with HFmrEF/HFrEF. Methods: In this retrospective single-center study, consecutive patients hospitalized with decompensated HF between 2017 and 2025 who underwent thoracic computed tomography were included. TPMA was measured at the T4 level. Nutritional status was assessed using PNI and CONUT. Receiver operating characteristic analysis, Kaplan–Meier analysis, Spearman correlation, and Cox regression were used to evaluate long-term all-cause mortality. Results: A total of 138 patients (median age 66 years; 35.5% women) were included. During a median follow-up of 34.4 months, 87 patients (63.0%) died. Non-survivors had lower TPMA (2589 vs. 3012 mm², p = 0.002) and PNI (46.0 ± 5.5 vs. 50.2 ± 7.2, p < 0.001). TPMA (AUC 0.661, p = 0.001) and PNI (AUC 0.663, p = 0.001), but not CONUT (AUC 0.561, p = 0.226), predicted mortality. TPMA correlated modestly with PNI (ρ = 0.325, p < 0.001). Low TPMA (<3000 mm²; HR 1.911, p = 0.018), higher BNP (HR 1.024 per 100 pg/mL, p = 0.014), and lower PNI (HR 0.956, p = 0.024) independently predicted mortality. Conclusions: Reduced TPMA and lower PNI were independently associated with long-term mortality in hospitalized patients with HFmrEF/HFrEF. Their modest correlation suggests that they may capture partly distinct aspects of systemic impairment; however, the incremental prognostic value of their combined assessment requires further evaluation. Full article

Background/Objectives: Bereavement care is widely endorsed as a standard of pediatric oncology and palliative care, yet it remains inconsistently implemented across pediatric oncology programs in the United States, and few programs have reported longitudinal delivery metrics. We aim to describe the iterative development and delivery of a multi-component bereavement program within an outpatient pediatric palliative oncology (PPO) program, characterize the population served, and benchmark delivery against national guidelines. Methods: This was a retrospective descriptive analysis of bereavement component delivery for PPO program patients who died between 2017 and 2026, using an iterative quality improvement framework. Program components (calls, condolence cards, packets, books) were tracked prospectively in a registry. Annual completion rates and timeliness were calculated for each family-facing component, and the cohort was characterized by demographic, clinical, and end-of-life variables. Data were reviewed for completeness at extraction; missing values were rare and are noted in the relevant tables. Results: A cohort of 403 deceased patients was included (41% Black, 15% Hispanic/Latino, 50% Medicaid-insured). The program evolved from informal bereavement phone calls (completion 74–81%) during 2017–2019 to a standardized, six-component program by 2020, reaching 93–100% annual delivery for most eligible components during 2022–2025. Early outreach occurred promptly (median 6 days after death for phone calls and condolence cards), and longer-term components were delivered within their intended windows. Conclusions: Comprehensive bereavement was developed over time without a fully formed infrastructure at initiation. This structured program began with one feasible, trackable activity and added components incrementally, achieving highly sustainable delivery that ultimately informed broader institutional practice. Full article

The regeneration of public spaces in historic urban areas increasingly relies on small-scale and incremental interventions. However, how spatial configuration, observed use, and perceived meaning converge or diverge across specific historic public spaces remains insufficiently understood. This exploratory single-case study uses a Perception–Behavior–Space (PBS) evidence-organizing and diagnostic structure to examine three selected public spaces in Guibeicheng, Wuxi. Evidence was drawn from 24 semi-structured interviews, cognitive maps, short-term multi-period behavioral observations at the three sites, and segment-based space syntax analysis at R = n and at metric radii of 400 m and 800 m. The cross-evidence comparison identified three case-specific patterns: a movement–staying mismatch at Sanyang Square Subway Station, a combined configuration–use and memory–use mismatch at Xue Fucheng’s Former Residence, and perception–behavior convergence despite lower configurational values at Chong’an Temple pedestrian street. None of the six configurational measures reproduced the observed pedestrian-flow ordering, indicating that configurational potential was not consistently aligned with mean pedestrian-flow intensity across the three sites. These patterns informed a case-derived interpretive model organized around everyday-use triggering, activity amplification, narrative anchoring, actor coordination, and governance enablement. The PBS evidence structure supports transparent cross-evidence diagnosis and the development of case-informed planning implications for historic public-space regeneration. Full article

Conventional partially hydrolyzed polyacrylamide (HPAM) suffers severe chain coiling, viscosity attenuation and precipitation under high-temperature and high-salinity reservoir brines, restricting its tertiary oil recovery efficiency. Herein, a novel carbon quantum dot hybrid terpolymer (QDHSTP) was synthesized via free-radical copolymerization, where silane-modified nitrogen-doped carbon quantum dots (FNCQDs) were covalently bonded to acrylamide (AM)/2-acrylamido-2-methylpropane sulfonic acid (AMPS)/diallyldimethylammonium chloride (DMDAAC) backbones. FTIR, ¹H NMR and thermogravimetric analysis (TGA) verified successful grafting of FNCQDs, while SEM revealed a continuous three-dimensional entangled network constructed by polymer chains. Steady and oscillatory rheology systematically characterized the solution viscoelasticity: QDHSTP solutions followed the power-law shear-thinning model, with flow behavior index n decreasing from 0.698 to 0.676 and consistency factor k rising from 80.91 to 131.13 mPa·sⁿ as concentration increased from 2000 to 3000 mg/L. All samples behaved as viscosity-dominated viscoelastic fluids, with elastic modulus exhibiting stronger frequency dependence. Benefiting from embedded FNCQDs, QDHSTP retained 79.74% and 76.06% of initial viscosity in 1.0 × 10⁴ mg/L NaCl and CaCl₂ brine, respectively, markedly better than that of the polymer without incorporated FNCQDs respectively, and maintained thickening capacity at 90 °C. Artificial sandstone core flooding demonstrated an incremental oil recovery of 29.8% over baseline waterflooding, attributed to mobility control and elastic residual oil stripping. This covalent nanohybrid strategy provides a facile route to construct thermo-salt tolerant polyacrylamides, offering a promising candidate polymer for harsh oil reservoir chemical flooding. Full article