Search Results (440)

Airport surface scheduling at multi-runway airports is a complex system engineering task that balances efficiency, safety, and sustainability, making it a key research focus in the field of air traffic management. This study proposes a cosine curve-based pushback rate control strategy and a collaborative pushback and taxiing decision-making method for departure aircraft pushback and taxiing. Additionally, the Markov decision process under dynamic pushback control at dual-runway airports is analyzed. An adaptive departure operation optimization model is established. This model considers path conflicts, fuel consumption, taxiway queuing, and runway occupancy during an aircraft departure process, enhancing the operational efficiency in the temporal and spatial dimensions. In the aircraft departure process, a genetic simulated annealing algorithm with nested Markov state transitions is proposed as the optimization algorithm, utilizing a Q-learning algorithm to adaptively adjust crossover and mutation parameters. The effectiveness of the proposed model and algorithm is validated through simulation experiments at Beijing Capital International Airport. Results indicate that this approach can significantly reduce the estimated taxiing fuel-related operating cost by 17.53% in the simulated case, shorten average taxiway waiting time by 56.24%, and decrease average taxi completion time by 20.81%, thereby improving overall airport operational efficiency. Full article

Incidental breast abnormalities may be visible on chest computed tomography (CT), although breast tissue is frequently outside the primary diagnostic focus of these examinations. This proof-of-concept study developed and internally evaluated a bilateral-asymmetry-aware multiple-instance learning framework (BAA-MIL) for case-level discrimination between breast cancer and non-malignant control examinations using preselected breast-containing axial chest CT images. The retrospective single-center case–control dataset included 89 CT examinations from 89 unique patients: 49 histopathologically confirmed breast cancer cases and 40 non-malignant control cases established according to predefined case-level reference criteria. The dataset comprised 304 selected axial CT images, yielding 608 unilateral breast-region crops arranged as 304 bilateral crop pairs. Paired breast crops were processed by a shared convolutional encoder, combined through an explicit side-symmetric asymmetry descriptor, and aggregated across axial images using gated attention-based multiple-instance learning. Performance was assessed using exploratory five-fold stratified patient-level cross-validation and a nested patient-level validation analysis. Under the primary nested patient-level validation protocol, the compact-encoder BAA-MIL implementation achieved an accuracy of 0.528 (95% CI, 0.427–0.629), balanced accuracy of 0.555 (95% CI, 0.465–0.637), sensitivity of 0.286 (95% CI, 0.160–0.415), specificity of 0.825 (95% CI, 0.694–0.930), and ROC AUC of 0.547 (95% CI, 0.420–0.665). The original non-nested analysis yielded higher exploratory estimates, but this analysis used the held-out folds for early stopping and checkpoint selection and is therefore reported only as secondary exploratory analysis. These findings support technical feasibility for a constrained case-level classification task using preselected chest CT images, but do not demonstrate detection of unsuspected incidental breast cancer across complete CT examinations. Performance estimates remain uncertain, and external validation using complete volumetric CT data is required before clinical use. Full article

Background: Evidence on the real-world effectiveness of antiresorptive therapy for hip fracture prevention in very old women remains limited. We aimed to assess the association between antiresorptive use and incident hip fracture among age ≥ 75 older women with osteoporosis. Methods: We conducted a population-based nested case–control study using the Base de Datos para la Investigación Farmacoepidemiológica en Ámbito Público (BIFAP), a Spanish research database. Women aged 75 years or older with osteoporosis and no previous antiresorptive use at cohort entry were followed from 2010 to 2022. Incident hip fracture cases were matched to risk-set controls by age, autonomous region, and calendar year of database registration. Antiresorptive exposure was classified as current, recent, past, or never use. Conditional logistic regression was used to estimate adjusted odds ratios (aORs) and confidence intervals. Results: The study included 2057 incident hip fracture cases and 19,275 matched controls. Compared with never users, current antiresorptive users had lower odds of hip fracture (aOR 0.76; 0.65–0.87), whereas past users had higher odds (aOR 1.91; 1.57–2.33). Ever use was not associated with hip fracture risk compared with never use (aOR 1.01; 0.90–1.13). Conclusions: In this real-world nested case–control study of women aged ≥75 years with osteoporosis, current antiresorptive use was associated with lower odds of hip fracture, whereas past use was associated with higher odds. Because treatment initiation, persistence, and discontinuation are strongly influenced by baseline fracture risk, osteoporosis severity, frailty, and clinical surveillance, these findings should be interpreted as associations rather than causal treatment effects. Full article

Background/Objectives: Large-for-gestational-age (LGA) birth is associated with adverse perinatal outcomes and increased risk of metabolic disease later in life. Despite these risks, epigenetic studies of LGA remain limited, particularly those using umbilical cord blood DNA methylation (DNAm) as the tissue of interest. Methods: We conducted an epigenome-wide association study of cord blood DNAm in a nested case–control sample from the Gestational Regulators of Weight (GROW) cohort. The analysis included 28 term LGA infants and 63 term appropriate-for-gestational-age (AGA) controls. DNAm was measured using the Illumina HumanMethylation450 BeadChip. Epigenome-wide association analyses were performed with adjustment for residual principal components and estimated cord blood cell-type proportions. Results: No CpG sites reached statistical significance after false discovery rate correction. Twenty-four CpGs showed nominal associations with LGA status at p-value < 1.00 × 10⁻⁴, including five CpGs with absolute methylation differences greater than 0.05. Among annotated loci, the strongest interpretable signals included cg06750897 in PBX1 (Δβ = 0.110, p-value = 1.70 × 10⁻⁵) and two nearby CpGs in SMAD3, cg23731272 (Δβ = 0.111, p-value = 4.31 × 10⁻⁵) and cg02486855 (Δβ = 0.109, p-value = 9.45 × 10⁻⁵). These two SMAD3 CpGs showed concordant hypermethylation in LGA infants and formed a candidate regional methylation signal in exploratory targeted regional analysis. Conclusions: In this pilot study, LGA was associated with modest cord blood DNAm differences, although no CpG sites reached genome-wide significance. The strongest interpretable signals involved PBX1 and SMAD3, suggesting candidate loci for further evaluation in larger studies of fetal overgrowth. Full article

Subclinical atherosclerosis (SCA) has been associated with lung function in many populations. Accordingly, those factors involved in respiratory health may contribute to the mechanisms linking pulmonary and cardiovascular disorders. Since the airway microbiome plays a key role in respiratory pathophysiology, microbial abundance and diversity in the upper airway may be associated with SCA risk. This study aimed to assess the association of upper airway microbiome abundance and diversity with SCA risk. A nested case–control study was carried out among adults from the Southern Caribbean. SCA was defined by carotid Doppler ultrasound as a carotid intima-media thickness ≥ 0.8 mm or the presence of carotid plaque. Oropharyngeal mucosal samples were collected under fasting conditions, and the V3-V4 region of the 16SRNA gene was sequenced. Differences in genus-level abundance were assessed using Microbiome Multivariable Association with Linear Models 2 (MaAsLin2). Alpha-diversity indices were compared through Wilcoxon tests. Principal coordinates analysis (PCoA) and Permutational Multivariate Analysis of Variance (PERMANOVA), adjusted for age, body mass index, and smoking status, were performed to assess associations between Bray–Curtis distances and SCA. MaAsLin2 was also applied to determine predicted metabolic pathway enrichment. A total of 40 cases and 40 controls were analyzed. The oropharyngeal microbiomes composition was dominated by three genera: Prevotella (cases: 26.0%; controls: 29.8%), Veillonella (cases: 16.3%; controls: 13.7%) and Fusobacterium (cases: 7.5%; controls: 8.0%). Significant differences in relative abundance were found for Streptococcus, Aureimonas, Mogibaecterium, Candidatus Saccharimonas, Pseudomonas, Segatella, Stomatobaculum, Oribacterium and Lachnoanaerobaculum, with lower abundance in cases for all these genera. Alpha-diversity was lower in cases than in controls, as reflected by the Shannon index (cases: 5.95 IQR [4.87; 6.35] vs. controls: 6.49 IQR [6.29; 6.75], p < 0.001), Simpson index (cases: 0.994, IQR [0.989; 0.996] vs. controls: 0.997 IQR [0.997; 0.998], p < 0.001) and Chao1 richness (cases: 1076.2 IQR [345.2; 1473.4] vs. controls: 1136.1, IQR [841.1; 1635.3], p = 0.04) were compared. In adjusted-PERMANOVA, 8.2% of microbiome variations were associated with SCA (pseudo-F = 7.49, R² = 0.082, p < 0.001), although this finding may have been influenced by intra-group dispersion among cases (PERMDISP: pseudo-F = 5.62, p = 0.018; Tukey’s HSD test: mean difference = −0.071, 95% CI [−0.118, −0.025], p = 0.003) Predicted enrichment of phenylalanine metabolism and indole alkaloid biosynthesis was higher in cases. In conclusion, these exploratory analyses suggest that reduced oropharyngeal microbiome diversity is associated with SCA. Further studies are warranted to clarify the role of the airway microbiome on cardiovascular outcomes. Full article

Background: Early-onset preeclampsia (EO-PE) remains a major cause of maternal and perinatal morbidity and mortality, and early risk stratification is still limited by the lack of simple and widely accessible biomarkers. The neutrophil percentage-to-albumin ratio (NPAR) has emerged as a composite marker reflecting systemic inflammation and endothelial dysfunction. Methods: In this retrospective, nested case–control study (n = 1176), we evaluated the predictive performance of first-trimester NPAR for EO-PE (n = 168) versus frequency-matched normotensive controls (n = 840) and its incremental value beyond established clinical and hemodynamic parameters. Multivariable models were adjusted for gestational age at sampling, and internal validation was performed via bootstrapping. Results: NPAR demonstrated superior discrimination (AUC = 0.848) compared with NLR (AUC = 0.629) and MAP (AUC = 0.614) (p < 0.001 for both). At the optimal cutoff of 16.52, NPAR showed a sensitivity of 81.5% (95% CI: 74.8–87.1%) and a specificity of 76.0% (95% CI: 72.9–78.9%), yielding a prevalence-adjusted positive predictive value (PPV) of 6.5% and a negative predictive value (NPV) of 99.5% based on Bayes’ Theorem. In multivariable analysis, NPAR remained independently associated with EO-PE (aOR 2.25, 95% CI 1.81–2.80; p < 0.001, per 1 SD increase). The addition of NPAR significantly improved model performance, increasing the AUC from 0.612 to 0.830 (DeLong p < 0.001), with robust bootstrap stability. Conclusions: First-trimester NPAR stands out as a potential independent clinical risk vector for early-onset preeclampsia and may offer meaningful additive prognostic utility beyond conventional clinical parameters. Given its low cost and routine availability, it may represent an accessible framework for initial frontline triage in early pregnancy risk stratification, particularly in resource-limited clinical settings where advanced multi-marker screening algorithms are unavailable. Rigorous external validation in prospective, multicenter longitudinal cohorts remains an absolute prerequisite before routine implementation in clinical management pathways. Full article

Binary logistic regression relies on the symmetric logit link, whose fixed inflection point cannot adapt to asymmetric response mechanisms and so may yield miscalibrated probabilities when the true response curve is asymmetric—a problem that can be particularly consequential in rare event or imbalanced applications. This study proposes a flexible, asymmetric link derived from the von Bertalanffy growth equation and tests a single, calibration-oriented hypothesis: estimating an asymmetric link improves the calibration of the predicted probabilities under asymmetric response mechanisms while leaving discrimination unchanged. The single shape parameter ν (the reparameterized von Bertalanffy shape, ν = m − 1; the growth curve baseline parameter is absorbed into the intercept and is not separately identifiable) is estimated jointly with the regression coefficients by L2-penalized maximum likelihood, giving a coherent generalized linear model rather than a post hoc re-thresholding of logistic scores; the logistic link is nested exactly at ν = 1 (m = 2), so the model reduces to ordinary logistic regression whenever the logit is adequate. The link was benchmarked on identical out-of-sample partitions against four competitors—logistic regression at the 0.5 cut-off, threshold-optimized logistic regression, ridge-penalized logistic regression at the same penalty (which separates the link from the regularization it requires), and Stukel’s generalized logistic model—across a correctly specified logistic mechanism and two asymmetric mechanisms (a complementary log–log mechanism and a von Bertalanffy-type best-case reference), three class imbalance ratios (0.10, 0.25, and 0.50) and five sample sizes (100–10,000), for 45,000 iterations in total. Paired differences were summarized by the Hodges–Lehmann median difference, its 95% confidence interval, and the rank-biserial correlation, with Benjamini–Hochberg control of multiplicity. The results supported the hypothesis. At moderate-to-large sample sizes, and increasingly as prevalence approached 0.50, the proposed link achieved lower Brier score and Log–Loss values than the three logistic competitors under both asymmetric mechanisms—for example, a median Log–Loss reduction against the matched-penalty ridge model of about 0.004 at balanced prevalence and the largest sample (95% confidence interval excluding zero; rank-biserial ≈ −1)—an advantage small in absolute size but, at the larger sample sizes, consistent across essentially every replication, and increasing with sample size and prevalence. Discrimination showed no practically important differences at moderate-to-large sample sizes: the area under the ROC curve and overall accuracy were essentially the same across the five methods, so the flexible link improves the quality of the probabilities without degrading class separation. Under the correctly specified logistic mechanism, the method showed no material deterioration, which is consistent with its exact nesting of the logistic model. The contribution is a growth curve-motivated asymmetric link that improves probability calibration under response asymmetry while preserving discrimination and recovering the logistic model when it is adequate. Full article

Tuned viscous mass dampers (TVMDs) are effective devices for wind-induced vibration control in supertall buildings, but their performance depends on a precise resonance condition that can be disturbed by manufacturing tolerances. This study identifies an insufficiently examined asymmetric sensitivity mechanism, termed the “dangerous diagonal effect”, in which opposite-sign errors in TVMD inertance and stiffness amplify tuning-frequency drift and create a worst-case sensitivity space that conventional symmetric uncertainty models may underestimate. To tackle this challenge without requiring prior statistical distributions unavailable at the design stage, an Info-Gap Decision Theory (IGDT) robust optimization framework tailored to TVMDs under stochastic wind excitation is developed. A Kriging-metamodel-assisted Efficient Global Optimization bi-level strategy reduces the computational burden of the nested worst-case search. Applied to a 76-story, 306 m benchmark building under a dual-criterion constraint combining the ISO 10137 comfort limit and a 30% relative degradation bound, the framework certifies comfort compliance for manufacturing errors up to 23.44% along the dangerous-diagonal direction. Under the most severe coupled degradation scenario, which integrates opposite-sign manufacturing detuning, 50-year power-law aging, and Arrhenius thermal drift, the nominal H₂-optimal design collapses to 36.7% vibration reduction efficiency while the IGDT robust design sustains 51.7%, reducing the Monte Carlo failure probability from 3.8% to 1.2% across 500 random realizations. An aeroelastic wind tunnel campaign spanning 620 detuning configurations on a 1:350 scaled model provides physical validation of IGDT design reliability for a TVMD system. The experiments corroborate the dangerous-diagonal sensitivity asymmetry, support the predicted robustness plateau under severe parameter detuning, and show that the IGDT framework maintains comfort compliance where the H₂-optimal design fails. Full article

Existing BIM-based workflows for complex spatial steel bridges often support 3D visualization and documentation, but they still lack a formal requirement-to-function traceability mechanism and a reliable automated link from special-shaped surface modeling to fabrication-oriented data. To address this gap, this study develops and validates a Model-Based Systems Engineering (MBSE)-oriented design–fabrication integration workflow for special-shaped steel bridges. The workflow combines requirement decomposition, functional architecture modeling, ENOVIA-based collaborative data management, skeleton-driven parametric modeling, User-Defined Feature (UDF) templates, Engineering Knowledge Language (EKL) batch instantiation, an IFC-based manufacturing information extension, ProNest nesting, and model-driven NC-code generation. The method was implemented for the Q7 North Pedestrian Bridge, a spatially twisted special-shaped steel landscape bridge. In the case study, the proposed workflow reduced typical repetitive component modeling time by 70.8%, shortened drawing generation time by 80.0%, increased nesting material utilization from 84.6% to 91.8%, and controlled the maximum coordinate-transformation deviation of formwork points within 1.42 mm. Field validation showed a mean fabrication deviation of 1.6 mm and a maximum site assembly closure deviation of 4.5 mm. The results indicate that the proposed MBSE-oriented digital thread improves design consistency, reduces manual data re-entry, and strengthens traceability from requirements to manufacturing and assembly. The study provides a reproducible case-study framework for model-driven steel bridge design–fabrication integration and identifies the limitations of UDF-library construction cost, software-specific learning requirements, and single-project validation. Full article

Aim: To evaluate associations between polymorphisms in CYP3A4 (*1B, *22), CYP3A5 (*3), CYP2J2 (*7, rs11572325), ABCB1 (c.1236C>T, c.2677G>T/A, c.3435C>T, rs4148738) and ABCG2 (c.421C>A) and the occurrence of bleeding or occlusive events in patients receiving rivaroxaban in real-world clinical practice. Methods: A nested case-control study, divided into two substudies (bleeding and thromboembolic events), was conducted within a prospective cohort of 385 adults receiving rivaroxaban at University Hospital Centre Zagreb (September 2021–September 2024). Bleeding events were classified per ISTH criteria, and genotyping was performed using TaqMan real-time PCR. Cases and controls were balanced using entropy balancing, and associations were estimated with Bayesian logistic regression under a skeptical prior N(0, 0.355); LASSO regression was used to identify clinical and genetic predictors of outcomes. Results: In total, 71 patients (18.4%) experienced bleeding events, most frequently gastrointestinal (47.9%), while 314 patients served as controls. No pharmacogenomic variant showed a clear association with bleeding risk (raw and balanced odds ratios 0.80–1.35; 95% credible intervals crossing 1.0). LASSO regression identified age (OR 2.00 per decade), gastrointestinal comorbidity (OR 8.77), and eGFR as the dominant predictors of bleeding. Twenty-one patients experienced occlusive events (15 venous, 6 arterial); however, the low event count precluded meaningful pharmacogenomic analysis. Conclusions: Individual pharmacogenomic variants in CYP3A4, CYP3A5, CYP2J2, ABCB1, and ABCG2 together with pharmacogenetic-based phenotypes were not associated with clinically relevant bleeding in rivaroxaban-treated patients. Traditional clinical risk factors, particularly advanced age and gastrointestinal comorbidity, remain the dominant determinants of adverse outcomes. Routine pharmacogenomic testing to guide rivaroxaban dosing is not currently supported. Full article

Objective: Preeclampsia (PE) is a leading cause of maternal and perinatal morbidity; however, reliable first-trimester biomarkers are limited. Growth arrest-specific protein 6 (Gas6), a vitamin K-dependent ligand for the TAM receptor family (Tyro3, AXL, and MerTK), is crucial for trophoblast invasion and placental remodeling. This study evaluated whether first-trimester serum Gas6 levels differed between women with PE and controls and assessed the predictive utility across phenotypes. Methods: Participants were enrolled prospectively during routine first-trimester screening at 11 + 0 to 13 + 6 weeks, and cases and controls were selected using a nested case–control design after pregnancy outcomes were known. ROC-derived cut-off values for Gas6 were selected retrospectively using the Youden index and were considered exploratory. The PE group was divided into early (n = 15, <34 weeks) and late onset (n = 65, ≥34 weeks) subgroups. ELISA measured serum Gas6. Mann–Whitney U, Kruskal–Wallis, Spearman’s correlation, ROC analysis, and multivariate logistic regression were applied. Results: Gas6 levels were significantly lower in PE than controls (15.73 vs. 38.08 ng/mL, p < 0.001); control reference median (38.08 ng/mL, IQR 27.62 to 49.14), decreasing progressively to late (20.07 ng/mL) and early onset PE (6.45 ng/mL; all p < 0.001). ROC analysis showed the highest exploratory discrimination for early onset preeclampsia (AUC = 0.959, 95% CI: 0.923–0.995; sensitivity 93.3%, specificity 84.1% at a retrospectively selected cut-off of ≤13.82 ng/mL), with more modest discrimination for overall PE (AUC = 0.762) and late onset PE (AUC = 0.708). Lower first-trimester Gas6 levels remained significantly associated with early onset PE after adjustment for maternal age and BMI (OR = 0.555, 95% CI: 0.412–0.748, p < 0.001). Conclusions: Serum Gas6 levels in the first trimester are lower in PE, particularly in cases of early onset disease, highlighting its potential as a candidate biomarker that requires further prospective and external validation before any screening application can be considered. Full article

Background: Abdominal examination (AE) is an important component of clinical assessment in Traditional East Asian Medicine (TEAM), providing information on abdominal shape, tenderness, stiffness, and skin color. However, conventional AE relies largely on subjective judgment and lacks standardized quantitative indicators. This study aimed to quantitatively characterize abdominal physical features associated with the cold pattern (CP) using objective abdominal examination devices and to explore their potential role in supporting standardized pattern-related assessment. Methods: A case–control study was conducted including 63 patients with functional dyspepsia and 60 healthy controls. Participants were classified according to CP status using a validated cold–heat pattern identification questionnaire. Abdominal features were quantified using a digital algometer and a depth-based geometric assessment system, measuring algometric (pressure tolerance, indentation depth, stiffness), geometric (abdominal depth and curvature), and chromatic (CIE L*a*b*) parameters. Group differences were analyzed using generalized linear models adjusted for confounders. A two-stage LASSO logistic regression with nested 10-fold cross-validation was applied. Results: Individuals with CP showed significantly lower pressure tolerance, indentation depth, stiffness, and CIE a* values, along with a flatter abdominal contour. The integrated model achieved a cross-validated ROC–AUC of 0.777 (95% CI, 0.674–0.872), indicating moderate discriminative performance. Conclusions: Quantitative algometric, geometric, and chromatic abdominal features were significantly associated with CP. Objective abdominal measurements may complement conventional AE by providing quantitative physical indicators that support more standardized and clinically relevant pattern-related assessment. These findings highlight the potential clinical utility of quantitative abdominal evaluation in improving diagnostic consistency. Trial registration: KCT0003369. Registered 23 November 2018. Full article

Background/Objectives: This study aimed to examine whether excess body weight is associated with susceptibility to SARS-CoV-2 infection, and to explore its relationship with COVID-19 severity, measured as the risk of hospitalization, in a rural population in Spain. Methods: A case–control observational study was conducted in the Soria Health Area, including 236 confirmed COVID-19 cases and 243 controls without a previous diagnosis of COVID-19. In addition, a nested cohort analysis was performed among the cases to evaluate the association between excess body weight and disease severity, defined by the need for hospitalization. Bivariate and multivariable logistic regression analyses were performed to identify factors independently associated with SARS-CoV-2 infection and hospitalization. Results: Excess body weight was not independently associated with SARS-CoV-2 infection risk after multivariable adjustment. In contrast, increasing body mass index was strongly associated with COVID-19 severity. Among individuals with confirmed infection, hospitalization risk increased nearly fivefold in individuals with overweight (OR = 4.97; 95% CI: 1.75–16.22), and eightfold in those with grade I obesity (OR = 8.35; 95% CI: 2.56–29.83). The highest odds ratio was observed for grade II–III obesity (OR = 72.00; 95% CI: 6.31–820.84), although this estimate was based on a small number of events and should therefore be interpreted with caution. These associations remained significant after multivariable adjustment. Conclusions: In this rural setting, excess body weight was not linked to an increased risk of SARS-CoV-2 infection but remained independently associated with greater COVID-19 severity after adjustment for potential confounding factors. The graded association between BMI and hospitalization risk highlights obesity as a key modifier of adverse outcomes and supports preventive interventions into clinical practice for patients with excess body weight. Full article

Repeated-root constacyclic codes form an important class of algebraic error-correcting codes, combining the cyclic symmetry of constacyclic codes with the additional multiplicity structure produced by repeated roots. These multiplicities are usually a source of technical difficulty in distance analysis; in this paper, we use them instead as controllable design parameters. Let $q=p^m$, let n be prime to p, and let $\lambda \in {\mathbb{F}}_q^{*}$. We study repeated-root $\lambda$-constacyclic codes of length $n{p}^s$ obtained by lifting the half-cyclotomic defining sets. Writing $\lambda ={\lambda }_0^{p^s}$ gives $x^{n{p}^s}-\lambda ={(x^n-{\lambda }_0)}^{p^s}$; hence every code is determined by a multiplicity profile $e:\mathrm{\Gamma }\to 0,1,\dots ,p^s$ on the set $\mathrm{\Gamma }$ of q-cyclotomic coset leaders in $Z_{n,r}$, where $r=ord\left({\lambda }_0\right)$. Equivalently, e determines a nested sequence of simple-root defining sets $T_{p^s-1}\subseteq \cdots \subseteq T_0\subseteq Z_{n,r}$. The main result is a layerwise distance formula: if $C_t$ is the simple-root code defined by $T_t$ and $P_t={\prod }_j(t_j+1)$ for the p-adic expansion $t={\sum }_j{t}_j{p}^j$, then $d_{\mathrm{H}}\left(\mathcal{C}\left(e\right)\right)={min}_{0\le t<p^s}{P}_t{d}_{\mathrm{H}}\left(C_t\right)$. This reduces the repeated-root distance problem to certified distance information for the simple-root layers. Combining the formula with the half-cyclotomic bounds in the two-coset-size case gives explicit certified lower bounds for complete families of repeated-root codes. We also formulate a verified refined layer bound, prove a conditional half-rate family theorem with distance growth at least a constant multiple of $N/{log}_{q}N$ for $N=n{p}^s$, and give a lifting criterion for transferring certified simple-root parameters to the repeated-root setting. The construction is carried out for the length families $n=(q^{\rho }-1)/\left(r\sigma \right)$, $n={\mathrm{\Phi }}_{{\rho }^b}\left(q\right)$, and $n={\mathrm{\Phi }}_{{\rho }_1{\rho }_2}\left(q\right)$. Full article

Background: Systemic inflammation plays a central role in determining postoperative outcomes in patients undergoing isolated coronary artery bypass grafting with cardiopulmonary bypass. Traditional inflammatory indices such as the neutrophil-to-lymphocyte ratio and the platelet-to-lymphocyte ratio have prognostic value; however, their dynamic behavior during cardiopulmonary bypass remains insufficiently characterized. More comprehensive indices, including the systemic immune-inflammation index and the systemic inflammatory response index, may help characterize early intraoperative inflammatory activity; however, their prognostic relevance should be regarded as exploratory and requires prospective validation. Methods: This retrospective nested case–control study included 245 patients who underwent isolated coronary artery bypass grafting, and intraoperative inflammatory indices during cardiopulmonary bypass were evaluated. Because of the nested case–control design, mortality cases were intentionally overrepresented to improve statistical power; therefore, the observed mortality rate does not reflect the true institutional mortality rate. Inflammatory indices (NLR, PLR, SII, and SIRI) were calculated at induction, at the 5th, 45th, and 90th minutes during cardiopulmonary bypass, and in the early postoperative period. Associations between these indices and in-hospital mortality were evaluated using univariate and multivariable logistic regression analyses. Predictive performance was assessed using receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC). Results: The final enriched analytical sample consisted of 51 mortality cases and 194 randomly sampled surviving controls. During cardiopulmonary bypass, inflammatory indices, particularly at the 5th minute, were significantly higher in patients who experienced mortality (p < 0.001 for all major indices). SII demonstrated the strongest predictive performance at the 5th minute (AUC = 0.790), followed by SIRI (AUC = 0.765), PLR (AUC = 0.687), and NLR (AUC = 0.681). In multivariable analysis, SII and SIRI measured at the 5th minute remained independent predictors of mortality. The addition of 5th-minute SII to the limited study-specific clinical model, which included age, ejection fraction, and preoperative creatinine, improved exploratory discrimination for in-hospital mortality (with AUC increasing from 0.698 to 0.797). Conclusions: Early intraoperative assessment of inflammatory indices during cardiopulmonary bypass may provide additional prognostic information in patients undergoing coronary artery bypass grafting. Composite indices, particularly SII and SIRI, showed stronger exploratory discrimination than traditional inflammatory markers in this enriched analytical sample. However, these findings should be considered hypothesis-generating and require prospective external validation before use in perioperative risk stratification or clinical decision-making can be recommended. Full article