Search Results (4,203)

Promoting the transition toward green and low-carbon lifestyles is essential for advancing sustainable consumption and environmental sustainability. Based on 6903 valid survey responses from 19 digital household pilot regions in China, this study examines the relationship between household digitalization and green and low-carbon lifestyles. A household digitalization level (HDL) index is constructed using the entropy method across five dimensions: digital network services, digital infrastructure, digital literacy, digital skills, and digital applications. The empirical results show that higher HDL is positively associated with the adoption of green and low-carbon lifestyles, and this association remains robust across a series of sensitivity analyses. Exploratory mechanism analysis indicates that HDL is linked to green and low-carbon lifestyles through improved satisfaction with digital smart technologies and enhanced environmental awareness. Heterogeneity analysis shows that this association is stronger among larger households, urban and suburban households, and households with development-oriented consumption, but weaker among smaller, rural, and subsistence-oriented households. These findings provide micro-level evidence supporting the exploration of the linkage between household digitalization and sustainable household consumption and the coordinated development of digitalization and environmental sustainability. Full article

Accurately evaluating how aero-engine performance supports upper-level capability remains a challenging issue in the digital planning, demonstration, and design of complex equipment systems-of-systems. Existing studies mainly rely on two-level analyses at the subsystem and system-of-systems levels, which are insufficient to characterize the cross-level transmission relationships among the aero-engine, aircraft performance, and overall capability. To address this limitation, this paper proposes a multilayer network-based contribution evaluation method for aero-engines oriented toward digital equipment planning and demonstration. First, a three-layer evaluation index system is constructed, including the overall capability layer, the aircraft performance layer, and the aero-engine performance layer, based on the OODA loop concept and aviation physical constraints. This provides a structured and traceable basis for cross-level requirement decomposition and scheme evaluation. Second, by integrating expert prior judgment with mechanism-based sensitivity analysis, the interrelationships among indicators at different layers are quantified, and a multilayer evaluation index network is established. Third, topological structure analysis is employed to identify key indicators in the aero-engine layer, and a cascading propagation model is introduced to evaluate the supporting roles and contribution rates of both individual indicators and the overall aero-engine layer with respect to the overall capability layer. Simulation results show that the proposed method can effectively reveal the structural characteristics, propagation paths, and dynamic influence patterns of aero-engine-layer indicators within the multilayer network. The proposed method provides methodological support for digital equipment planning, scheme demonstration, design optimization, and capability-oriented decision-making of aero-engines. Full article

Background/Objectives: Chronic kidney disease (CKD) remains underdiagnosed until advanced stages, motivating reliable, clinically deployable screening models that pair high discrimination with an explicit operating threshold and transparent explanations. Methods: In this study, we propose a CKD detection framework that integrates structured preprocessing, class imbalance handling, stratified 10-fold cross-validation with out-of-fold (OOF) prediction, and clinically oriented threshold selection via the Youden index, followed by explainability using SHAP and LIME. Experiments were conducted on two datasets. Across a broad panel of ten machine learning models, gradient boosting methods consistently dominated. Results: LightGBM achieved the best overall clinical composite performance on both datasets. On Dataset 1, LightGBM delivered near-ceiling OOF discrimination (ROC-AUC = 99.98, PR-AUC = 99.98) and an excellent clinically balanced performance at the best Youden threshold (0.41), reaching sensitivity = 99.20, specificity = 99.60, accuracy = 99.40, F1 = 99.40, and MCC = 98.80, with robust cross-validation stability (CV AUC = 99.99 ± 0.04; CV sensitivity = 99.10 ± 1.81; CV specificity = 99.46 ± 1.42; CV MCC = 98.59 ± 2.19), strong calibration (Brier = 0.006), and fast training (0.078 ± 0.019 s/fold). On Dataset 2, LightGBM maintained high generalization (ROC-AUC = 99.72, PR-AUC = 99.64) and clinically deployable balance at the best Youden threshold (0.35), achieving sensitivity = 98.10, specificity = 98.03, accuracy = 98.06, F1 = 98.06, and MCC = 96.13, with consistent fold-wise performance (CV AUC = 99.69 ± 0.25; CV sensitivity = 97.25 ± 1.25; CV specificity = 98.11 ± 1.02; CV MCC = 95.37 ± 1.56), acceptable calibration (Brier = 0.0173), and practical training time (0.742 ± 0.144 s/fold). Conclusions: Finally, SHAP and LIME explanations confirmed that model decisions align with clinically meaningful renal function and symptom/biomarker patterns at both population and patient levels, supporting safer translation of the proposed framework into CKD screening and decision-support workflows. Full article

Background: Metastasis and poor chemotherapy response have stagnated therapeutic progress in osteosarcoma (OS) for the past three decades. Defining the transition from localized to metastatic OS before overt dissemination is fundamental for improving survival. However, effective early diagnostic tools remain scarce, largely due to limited exploitation of the metastasis-associated tumor microenvironment’s own record of prior environmental and stress exposures encoded in cell-intrinsic transcriptional states. Here, we employed a supervised machine learning framework with iterative resampling and multi-stage model selection to identify molecular markers associated with metastasis in osteosarcoma and to develop a computational signature, Auto-RS. Methods: Transcriptomic and clinical data from 139 OS patients with ≥5 years of follow-up were analyzed. A LASSO–Cox framework was applied to derive a gene expression-based risk score, Auto-RS, from which a nomogram integrating age and sex was generated for individualized prognosis. Model interpretability was assessed across six independent single-cell OS patient datasets, and drug sensitivity predictions were inferred by integrating Auto-RS with the Precily algorithm to uncover actionable therapeutic vulnerabilities. Results: Auto-RS, constructed from the expression of four autophagy genes (BNIP3, MYC, PEA15, and SAR1A), served as an independent prognostic factor for overall survival (HR = 1.091; 95% CI, 1.047–1.136; p < 0.001). Time-dependent ROC analysis showed that Auto-RS was the most accurate single predictor (AUC = 0.88), exceeding metastasis (0.83), sex (0.45), and age (0.39). A basic prognostic model (BpM) incorporating metastasis status yielded a C-index of 0.741 (95% CI, 0.679–0.803). The addition of Auto-RS (CpM) improved discrimination (C-index = 0.788; 95% CI, 0.731–0.845), whereas a model without metastasis information (ApM) retained predictive ability (C-index = 0.709; 95% CI, 0.640–0.778). Single-cell analysis confirmed that Auto-RS features aligned with known metastatic trajectories, reflecting the transition from proliferative to invasive tumor states and highlighting coordinated programs among cancer-associated fibroblasts and immune cells. Drug sensitivity integration through Precily identified gemcitabine and cytarabine as FDA-approved agents predicted in silico to show greater sensitivity in the high-risk subgroup. Conclusions: We identified autophagy-mediated transcriptional ‘stress fingerprints’ that are tightly associated with OS metastasis. The Auto-RS signature, composed of BNIP3, MYC, PEA15, and SAR1A, enables early therapeutic stratification of patients independent of overt metastatic status. Moreover, Auto-RS delineates key molecular underpinnings of OS metastasis at single-cell resolution. As a practical laboratory tool, Auto-RS may represent a step toward improved risk stratification, where advances in metastasis prediction and therapeutic guidance converge to improve outcomes in OS. Full article

Rainfall-index-based disaster insurance is an efficient approach to mitigating hydrometeorological losses. However, conventional premium pricing models generally assume memoryless stochastic dynamics that do not fully capture the long-range dependence inherent in rainfall data. This study develops a hydrometeorological disaster insurance model within a fractional Black–Scholes framework to incorporate long-memory effects. The model is formulated using fractional differential equations and solved semi-analytically by integrating the Daftardar–Jafari Method (DJM) with the Kashuri–Fundo (KF) transform, yielding a closed-form solution expressed in terms of the Mittag–Leffler function. The proposed contract is structured as parametric rainfall insurance with a multi-layer payout mechanism based on percentiles corresponding to minor, moderate, and severe housing damage. The results show that variations in the fractional-order parameter significantly affect premium estimation. In particular,  δ = 0.5 recovers the classical model and tends to generate higher premiums than the fractional model with δ = 0.23153, whereas the model with δ = 0.73153 yields lower premiums. These findings indicate that fractional-order parameterization can accommodate diverse risk characteristics and policyholders’ economic capacities, enabling more adaptive, risk-sensitive premium structures. In line with SDG 13 (Climate Action), the proposed framework offers a climate-responsive disaster-mitigation strategy through accessible, actuarially relevant insurance design.  recovers the classical model and tends to generate higher premiums than the fractional model with , whereas the model with  yields lower premiums. These findings indicate that fractional-order parameterization can accommodate diverse risk characteristics and policyholders’ economic capacities, enabling more adaptive, risk-sensitive premium structures. In line with SDG 13 (Climate Action), the proposed framework offers a climate-responsive disaster-mitigation strategy through accessible, actuarially relevant insurance design. Full article

Selecting superior families at the seedling stage is crucial for accelerating genetic gain in sugarcane, yet systematic comparisons of selection methods remain limited. This study evaluated seven selection strategies: phenotypic check-based selection (Pheno), a three-trait combined index (CI3), Best Linear Unbiased Prediction (BLUP), Best Linear Unbiased Estimation (BLUE), tiered family selection (Tiered), logistic regression (LASSO), and the Multi-Trait Family Ideotype Distance Index (MFIDI). The experiment followed an augmented block design with four blocks, two check varieties, and included 125 test families comprising 10,955 seedlings. Using a combined index of standardized cane and sugar yields, families were classified as elite (top 20%), moderate (60%), and weak (bottom 20%). BLUP and BLUE rankings were consistent (Spearman’s ρ > 0.95, TCI = 88%, Jaccard = 0.79). Elite families showed median index values of 0.90 (BLUP) and 0.88 (BLUE) with wide interquartile ranges, whereas weak families had medians of −0.70 with narrow ranges. LASSO achieved excellent predictive performance: AUC = 0.95, accuracy = 0.92, sensitivity = 0.90, specificity = 0.94, identifying cane yield, sugar yield, and millable cane as key drivers. Agreement for inferior families was lower across methods (BCI ≤ 68%). BLUP with a multi-trait index proved most effective for discriminating elite families. Families F31 and F71 consistently ranked top. Combining selection approaches with agreement indices improves early-stage decisions for family selection in sugarcane breeding. Full article

Background: Atrial fibrillation (AF) and heart failure with preserved ejection fraction (HFpEF) usually coexist and are related to increased morbidity and mortality. Cardiovascular benefits have been demonstrated by drugs such as sodium-glucose cotransporter-2 inhibitors (SGLT2i) and GLP-1 receptor agonists including the dual GIP/GLP-1 receptor agonist tirzepatide (collectively, incretin-based therapies); however, their relative effectiveness in patients with concomitant AF and HFpEF remains undefined. Methods: We conducted a retrospective, propensity score-matched cohort study utilizing the TriNetX Global Collaborative Network. Adults with AF or atrial flutter with a diagnosis of HFpEF who initiated incretin-based therapies (GLP-1 receptor agonists or dual GLP-1/GIP receptor agonists) or SGLT2i were included; index medication was required to be initiated within 30 days of a qualifying AF/HFpEF diagnosis. 1:1 matching was performed based on baseline medications, demographics, and comorbidities. Co-primary outcomes were all-cause mortality, inpatient visits, and emergency department (ED) visits at 1 year. Secondary outcomes included myocardial infarction, ischemic stroke, acute kidney injury, transient ischemic attack, major adverse cardiovascular events (MACE; all-cause mortality/MI/stroke composite), and AF-related procedures. Agent-specific subgroup analyses were performed for semaglutide and tirzepatide separately. Sensitivity analyses were conducted at 6 months and 2 years. Results: 7624 patients were included in each cohort after matching (mean age: 70.8 years; 52% women). At 1 year, incretin-based therapy was associated with lower all-cause mortality (5.3% vs. 7.3%, HR 0.721, 95% CI 0.634–0.820; p < 0.001), fewer inpatient visits (30.0% vs. 37.4%, HR 0.743, 95% CI 0.702–0.787; p < 0.001), and no statistically significant difference in ED visits (27.0% vs. 28.0%; HR 0.946, 95% CI 0.888–1.007; p = 0.081) compared with SGLT2i. Incretin-based therapy was also associated with lower risk of MACE (HR 0.709), acute kidney injury (HR 0.751), myocardial infarction (HR 0.583), catheter ablation (HR 0.685), and electrical cardioversion (HR 0.472). No significant differences were observed in ischemic stroke or transient ischemic attack. These findings were broadly consistent at 6-month and 2-year follow-up, and directionally consistent in agent-specific subgroup analyses of semaglutide and tirzepatide. Conclusions: In this large propensity-matched cohort of patients with AF and HFpEF, initiation of incretin-based therapy (GLP-1 receptor agonists or dual GLP-1/GIP receptor agonists) was associated with lower all-cause mortality, fewer inpatient visits, and reduced cardiovascular events compared with SGLT2i. These findings, while subject to observational limitations, suggest potential benefits of incretin-based therapy in this high-risk population and support the need for prospective comparative trials. Full article

Background & Aims: Accurate assessment of liver fibrosis is important for the management of pediatric chronic liver disease (CLD). Transient Elastography (TE) has emerged as a validated non-invasive method for accurately assessing hepatic fibrosis, yet it remains available only in specialized centers and requires specialized equipment. We aimed to develop and internally validate a novel, simple, blood-based scoring system—the pediatric-adapted liver score (PAL score)—to predict advanced fibrosis as defined by liver stiffness, measured using TE across diverse etiologies. Methods: A retrospective study was conducted on 107 pediatric patients with CLD who underwent liver stiffness measurement through TE. Advanced fibrosis was defined as a liver stiffness measurement corresponding to the F3 METAVIR stage or above. Independent predictors of advanced fibrosis were identified using multivariable logistic regression with manual backward elimination. To facilitate bedside utility, the regression model was simplified into a ratio-based index. Performance was assessed via the area under the receiver operating characteristic curve (AUROC) and validated using bootstrap resampling (10,000 iterations). Results: Gamma-glutamyl transferase (GGT), platelets, and albumin were identified as independent predictors of fibrosis. The simplified PAL score demonstrated good discrimination with an AUROC of 0.901 (95% CI: 0.84–0.95). While statistically equivalent to the adult-derived GGT-to-platelet ratio (GPR) and S-Index, the PAL score incorporates parameters of hepatic synthesis and portal hypertension that are absent from other ratios and is easier to calculate at the patient’s bedside. At a clinically practical integer cut-off of 5.0, the score achieved a sensitivity of 95.5% and a negative likelihood ratio of 0.06, effectively ruling out advanced fibrosis. Bootstrap validation confirmed the stability of the model (bootstrap-corrected AUC 0.901). Conclusions: The PAL score is the first simple fibrosis index derived for a diverse pediatric population. Highlighting its primary strength as a highly effective screening tool, the score achieves a sensitivity of 95.5% and a negative likelihood ratio of 0.06 at a user-friendly cut-off of 5. These robust metrics allow clinicians to confidently rule out advanced fibrosis, offering an accessible triage alternative in primary care settings where transient elastography is unavailable. Full article

Background and Objectives: Knee osteoarthritis (KOA) and other degenerative chondropathies are major causes of pain and disability. When core conservative treatments are insufficient, intra-articular hyaluronic acid (HA) and platelet-rich plasma (PRP) are commonly used as adjunctive options, although evidence remains difficult to interpret because of heterogeneity in patients, products, preparation protocols, and treatment schedules. This exploratory retrospective study described short-term clinical outcomes after two standardized intra-articular protocols, hybrid HA and autologous PRP, in a real-world outpatient physiatry setting. Materials and Methods: This monocentric retrospective study included 40 treated knees (19 HA, 21 PRP) from 31 unique patients at the Policlinico di Bari between October 2022 and November 2024. The HA group received two injections of a hybrid high-/low-molecular-weight HA formulation, whereas the PRP group received three injections of autologous PRP. Outcomes were pain intensity, assessed by the Numerical Rating Scale (NRS), and function, assessed by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), from baseline to end-of-cycle follow-up. Results: Both groups showed short-term clinical improvement. Mean NRS scores decreased from 6.26 to 2.26 in the HA group and from 6.76 to 2.29 in the PRP group, with no significant between-group difference in change from baseline (p = 0.509). WOMAC improved by 25.42 ± 20.39 points in the HA group and 20.19 ± 16.18 points in the PRP group (p = 0.372). In the main regression analysis, treatment type was not a significant predictor of outcome; unadjusted and age-/sex-adjusted WOMAC sensitivity models suggested a possible HA advantage that was not retained after full adjustment. Conclusions: In this small exploratory cohort, both protocols were associated with short-term improvements, without definitive fully adjusted evidence of between-group superiority. These findings should not be interpreted as evidence of equivalence or definitive comparative efficacy. Full article

Background/Objectives: The obesity epidemic coexists with the phenomenon of “hidden hunger” (Type B malnutrition)—a micronutrient deficiency amidst a caloric excess. Traditional dietary assessment methods often distort the actual picture by ignoring technological losses during cooking, which necessitates the use of digital tools. Methods: A cross-sectional study (N = 3267) was conducted using the digital platform “NIAP”. The analysis was based on valid 3–7-day dietary records with algorithmic accounting for nutrient retention factors during thermal processing. The nutrient profiles of individuals with a normal body mass index (BMI) and obesity (BMI ≥ 30 kg/m²) were compared. Results: The epidemiology of intake shortfalls was highly prevalent and pronounced: 99.9% of the cohort had ≥1 inadequacy (with a mean negative deviation of −77.3% for vitamin D and −59.2% for Omega-3), and 61.5% exhibited ≥10 simultaneous multiple intake shortfalls. These inadequacy rates remained robust in a sensitivity analysis excluding under-reporters. The obesity group consumed significantly more energy, saturated fatty acids, added sugars, cholesterol, and sodium, but demonstrated a lower relative macronutrient intake (g/kg of body weight). Absolute fiber intake did not differ between the groups, indicating a decrease in its density per 1000 kcal in the diet of individuals with obesity; the intake of Omega-3 polyunsaturated fatty acids (PUFAs) showed a downward trend. The Na:K ratio was significantly higher in the obesity group (1.19 vs. 1.04, p < 0.001). Correlation analysis confirmed an inverse relationship between BMI and the overall nutrient density of the diet. Conclusions: A high-energy diet does not compensate for systemic micronutrient inadequacy among the evaluated cohort. Obesity is associated with a dietary imbalance favoring “empty calories” and pro-inflammatory components against a background of severe multiple dietary inadequacies. The integration of algorithmic dietary assessment that accounts for cooking losses is critical for objective diagnosis and personalized nutritional intervention. Full article

Background: Vitamin D has traditionally been recognized for its role in calcium homeostasis and skeletal health, but vitamin D receptor expression and vitamin D-metabolizing enzymes have also been identified in extra-skeletal tissues, including components of the male reproductive tract. Observational evidence has suggested associations between vitamin D status and androgen-related markers; however, whether vitamin D supplementation has a measurable effect on androgen bioavailability remains uncertain. Objective: This systematic review and meta-analysis evaluated the effects of vitamin D supplementation on total testosterone (TT) and androgen bioavailability markers in adult men, including sex hormone-binding globulin (SHBG), free androgen index (FAI), calculated free testosterone (calculated FT), and bioactive testosterone (BAT) where methodologically compatible. Methods: The review was registered in PROSPERO (CRD420261365005) and conducted according to PRISMA 2020 and Cochrane methodological guidance. Searches were conducted from database inception to April 2026 in PubMed, Web of Science, Scopus, ClinicalTrials.gov, and the WHO ICTRP. Embase was initially planned but was not searched because institutional access was unavailable; this amendment was made before screening, extraction, risk-of-bias assessment, and synthesis. Records were deduplicated in Zotero, screened in a structured matrix, and converted from report-level records into independent comparison-level datasets where appropriate. Meta-analyses used random-effects REML models with Hartung–Knapp adjustment. Results: The official search set comprised 2854 records, of which 703 duplicates were removed, leaving 2151 records for title and abstract screening. The full-text screening file was reconciled to 162 PRISMA-countable reports/records: 135 reports were assessed, 27 reports could not be assessed because the full text was unavailable or had not been obtained for review, and 27 reports/studies were retained for qualitative synthesis. Eighteen reports were considered candidate sources for quantitative synthesis and were operationalized into 21 comparison-level records. The primary TT model included 11 comparisons and showed no clear effect of vitamin D supplementation on final TT (MD 0.47 nmol/L, 95% CI −0.50 to 1.44; I² = 24.1%). No clear effects were observed for SHBG (MD 0.27 nmol/L, 95% CI −2.14 to 2.68), FAI (MD −0.37, 95% CI −4.28 to 3.55), calculated FT sensitivity evidence (MD −0.0096 nmol/L, 95% CI −0.0525 to 0.0332), or BAT exploratory evidence (MD −0.47 nmol/L, 95% CI −1.77 to 0.83). GRADE certainty was low for TT, SHBG, and FAI, and very low for calculated FT and BAT. Conclusions: Current randomized evidence does not demonstrate a statistically clear or reproducible effect of vitamin D supplementation on total testosterone or androgen bioavailability markers in adult men. GRADE certainty was low for total testosterone, SHBG, and FAI, and very low for calculated free testosterone and bioactive testosterone. Because directly measured and calculated free testosterone are not analytically equivalent, free testosterone was not pooled as a primary outcome; method-compatible calculated FT was handled as sensitivity evidence and BAT as exploratory evidence. Full article

Background: Hyperhomocysteinemia (homocysteine [Hcy] ≥15 μmol/L) is frequently observed in patients with impaired kidney function and has been associated with vascular remodeling and increased cardiovascular risk. We aimed to evaluate the relationship between Hcy, arterial stiffness, coronary artery disease (CAD), peripheral arterial disease, and biomarkers of kidney injury in patients undergoing elective coronary angiography. Methods: In this prospective observational study, 133 patients undergoing elective coronary angiography were stratified according to serum Hcy levels (Hcy <15 vs. Hcy ≥15 μmol/L). CAD severity was assessed angiographically. Arterial stiffness was evaluated using carotid–femoral pulse wave velocity (cfPWV), while peripheral arterial disease was assessed using ankle–brachial index (ABI). Kidney function was evaluated using serum creatinine, estimated glomerular filtration rate (eGFR), cystatin C, and urinary albumin-to-creatinine ratio (UACR). Correlation, multivariable regression, logistic regression, and receiver operating characteristic (ROC) analyses were performed. Results: Patients with hyperhomocysteinemia demonstrated significantly worse kidney function, including higher serum creatinine, cystatin C, and UACR levels, and lower eGFR (all p < 0.01). Patients with elevated Hcy levels also exhibited significantly higher cfPWV values (11.4 ± 3.3 vs. 9.7 ± 2.1 m/s, p < 0.001). Hcy correlated positively with cystatin C, creatinine, UACR, and cfPWV, and inversely with eGFR. In multivariable linear regression analysis, Hcy remained independently associated with increased cfPWV after adjustment for age, sex, and eGFR (β = 0.137, 95% CI 0.047–0.226, and p = 0.003). This association remained significant in sensitivity analyses incorporating hypertension, diabetes mellitus, LDL cholesterol, and statin therapy (β = 0.124, 95% CI 0.032–0.216, and p = 0.008). No independent associations were observed between Hcy and angiographic CAD severity or ABI values. ROC analysis demonstrated modest discrimination for elevated arterial stiffness (AUC = 0.66, 95% CI 0.56–0.76) and good discrimination for impaired kidney function (AUC = 0.82, 95% CI 0.69–0.92). Conclusions: Elevated Hcy levels were independently associated with impaired kidney function and increased central arterial stiffness, but not with angiographic CAD severity or peripheral arterial disease. These findings suggest that hyperhomocysteinemia may reflect cardiorenal vascular dysfunction and diffuse vascular remodeling rather than focal obstructive atherosclerotic disease. Further studies are needed to determine its clinical utility and prognostic value. Full article

To address the dilemma of ‘non-grain use of cultivated land’ and support China’s requisition–compensation balance policy, this study developed a multi-dimensional assessment framework integrating the production, ecological, and economic dimensions (3D evaluation model), using Shenyang City as a case study to demonstrate the framework’s operational application and policy relevance. Based on 34,704 Third National Land Survey (TNLS) parcels (27,408.39 ha), we applied the constraint factor assessment method and entropy-weighted composite index model. The results show that non-cultivated agricultural land (NCAL) is generally marginally suitable (citywide average score: 2.50/4), with highly suitable areas accounting for only 4.04% (1106.30 ha). These areas exhibit a triangular spatial pattern distributed across northeastern Faku County, central Sujiatun District, and southern Xinmin City. Sensitivity tests using equal weights and ±20% dimension-weight perturbations confirm that high-suitability area remains limited (3.37–5.63% under entropy-weight scenarios; 8.54% under equal weights). Primary limiting factors include severe organic matter deficiency (average 19 g/kg), shallow soil depth, unfavorable pH, land requiring engineering restoration (94%), and punctiform heavy metal contamination (7.53% of plots, 2065.05 ha as spatially excluded areas). Consequently, we propose a five-tier sequential restoration framework: (1) near-term priority recultivation of highly suitable areas; (2) mid-term topsoil reconstruction for moderately suitable areas; (3) medium-to-long-term topsoil stripping and thickening for low-suitability areas; (4) long-term soil amelioration and slope-to-terrace conversion for marginally suitable areas; and (5) strict prohibition of restoration in unsuitable areas. This study establishes a spatially explicit decision-making system integrating “evaluation–classification–sequencing”, and distinguishes technical suitability from economic, institutional, and policy feasibility, providing a decision-support framework for scientifically implementing the cultivated land requisition–compensation balance policy. Future empirical studies using post-restoration monitoring data are needed to test its predictive accuracy against observed restoration outcomes. 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

Non-invasive methods used for PH detection in clinical practice have several limitations. The combination of high spatiotemporal sensitivity magnetocardiography (MCG) and artificial intelligence algorithms may offer an accurate approach for PH detection. In this study, we develop a convolutional neural network (CNN) model based on the 64-channel MCG time-series data. This exploratory study enrolled patients undergoing 64-channel MCG, including right-heart-catheterization confirmed PH patients and symptomatic controls with low echocardiographic probability of PH. After data preprocessing, a temporal CNN integrating MCG signals with age, sex, and body mass index was developed and compared with conventional machine learning models. The CNN model achieved strong discrimination, with area under the curve (AUC) values of 0.939 (95% confidence interval [CI]: 0.913–0.961) in the development out-of-fold evaluation and 0.974 (95% CI: 0.944–0.994) in the hold-out test set, outperforming conventional machine learning models. Decision curve analysis showed the greatest net benefit at clinically relevant thresholds. Attribution analysis indicated that spatial QRS morphology redistribution contributed substantially to PH classification. The temporal CNN model based on raw 64-channel MCG signals showed promising performance for non-invasive PH detection and outperformed conventional machine learning approaches in this exploratory single-center cohort enriched for PAH and CTEPH. Full article