Search Results (851)

Background: Ischemic heart disease (IHD) diagnosis is complicated by anatomical-functional dissociation, where morphological stenosis severity fails to reliably predict hemodynamic significance. This diagnostic gap necessitates a shift toward integrated physiological and structural phenotyping, a role increasingly fulfilled by Cardiovascular Magnetic Resonance (CMR). Objective: To systematically evaluate the incremental diagnostic and prognostic value of CMR across the clinical spectrum of IHD, defining its evidence-based integration into multimodal pathways, particularly for diagnostically indeterminate cases. Methods: A systematic review was conducted in accordance with the PRISMA guidelines. A structured literature search of PubMed, Web of Science, and Scopus retrieved peer-reviewed articles published between January 2021 and April 2026. Methodological quality was appraised using the Newcastle–Ottawa Scale and AMSTAR 2, while evidence certainty was evaluated via the GRADE framework. Results: Thirty studies were included in the qualitative synthesis. Current evidence demonstrates that stress perfusion CMR provides superior diagnostic accuracy compared with traditional tests (e.g., SPECT, stress ECG), although it may be outperformed by advanced CT-derived fractional flow reserve in specific post-CCTA cohorts. In indeterminate presentations such as MINOCA, CMR accurately reclassified the underlying etiology in approximately 68% of cases. Furthermore, multiparametric assessment—integrating late gadolinium enhancement (LGE), microvascular obstruction (MVO), and global longitudinal strain (GLS)—refined post-infarction short- and medium-term risk stratification beyond LVEF alone, though the independent prognostic value of MVO attenuates in long-term follow-up (>6 years). Emerging data support the non-inferiority of accelerated stress-only protocols and the utility of artificial intelligence-driven analytics. Conclusions: CMR is a critical modality for resolving anatomical-functional mismatches and providing robust risk stratification. However, evidence does not support its use as a universal first-line test due to operational costs, scan duration, and patient contraindications. Expanding its clinical impact relies strictly on standardizing protocols and adopting AI-assisted, accelerated sequences to mitigate logistical barriers. Full article

Background/Objectives: Neonatal sepsis remains a major cause of morbidity and mortality worldwide, underscoring the critical need for early and accurate diagnostic biomarkers. This study aimed to evaluate the predictive value of the red cell distribution width-to-albumin ratio (RAR) for the diagnosis of neonatal sepsis and to compare its diagnostic performance with the C-reactive protein-to-albumin ratio (CAR) and other hematological parameters. Methods: This retrospective cohort study was conducted in the Neonatology Department of Karadeniz Technical University Faculty of Medicine between January 2015 and June 2025. A total of 874 neonates with a gestational age > 36 weeks were included: 411 with blood culture-confirmed sepsis (108 Gram-negative, 303 Gram-positive) and 463 healthy controls. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis, with optimal cut-off values determined by the Youden index. Results: RAR demonstrated modest diagnostic accuracy for neonatal sepsis, with an area under the curve (AUC) of 0.647 (95% CI: 0.61–0.69), a cut-off value of 5.108, sensitivity of 50.7%, and specificity of 76.7%. RAR was significantly elevated in the Gram-negative group compared with Gram-positive cases and controls (p < 0.001). However, the clinical significance of this subgroup difference requires further investigation. In multivariable logistic regression analysis, RAR remained independently associated with culture-confirmed neonatal sepsis after adjustment for gestational age, birth weight, sex, and mode of delivery (aOR = 2.190, 95% CI: 1.838–2.608, p < 0.001). Among all evaluated markers, CAR achieved the highest diagnostic performance (AUC: 0.981, sensitivity: 88.5%, specificity: 98.7%, PPV: 98.4%, NPV: 90.7%, LR+: 68.47), followed by C-reactive protein (AUC: 0.978), while neutrophil-to-lymphocyte ratio showed the lowest discriminatory ability (AUC: 0.592). Conclusions: RAR showed limited standalone discriminatory performance for culture-confirmed neonatal sepsis, although its association with sepsis remained significant after adjustment for relevant demographic and perinatal factors. CAR demonstrated significantly greater discriminatory performance than RAR. Further studies are needed to determine whether RAR provides incremental value when incorporated into multivariable diagnostic models. Full article

Background/Objectives: Poor oral health, which is often overlooked in nursing homes (NHs), is associated with aspiration pneumonia. This analysis assesses the cost effectiveness of an oral hygiene intervention, “Mouth Care Without a Battle©” (MCWB), which trains NH staff to provide daily mouth care. The first year of a pragmatic cluster randomized effectiveness trial conducted in 14 NHs demonstrated a significant reduction in pneumonia incidence in intervention NHs. Methods: Because the two-year primary outcome was not statistically significant, the first-year analysis is post hoc. The incremental cost-effectiveness ratio (ICER) of costs (staff training, time spent providing mouth care, and pneumonia-related hospitalizations) to effects (reductions in pneumonia cases) over one year was estimated using bootstrapping. Results: Analyses for 1605 residents with clustering by NH show that the likelihood that MCWB is cost-saving ranges from 6.5% to 61.1% depending on whether staff are paid benefits and various levels of estimated hospital costs. Similarly, the likelihood that MCWB results in reduced pneumonia cases but with higher costs ranges from 32.0% to 86.6%. Whether MCWB is cost-effective depends on society’s willingness to pay for reduced pneumonia cases and related unmeasured benefits. These estimates may represent a lower bound of potential cost savings because analyses did not include costs of treating pneumonia if not hospitalized, ambulance transport, or the emotional costs of illness. However, other excluded costs (e.g., dental restorations) and resources required to improve fidelity could reduce the likelihood of cost savings. Conclusions: MCWB and similar interventions that improve oral health care in NHs may yield cost savings or produce benefits from the reduction in pneumonia that justify net increases in costs incurred. It is also important to consider who bears the costs (e.g., the NH) versus who reaps the benefits (e.g., healthier residents and reduced Medicare payments). Full article

Background: Caffeine and sodium bicarbonate (SB) are widely used ergogenic supplements that influence exercise performance through distinct physiological mechanisms and may differentially modulate exercise-related metabolic responses. Whether their co-ingestion provides benefits beyond either supplement alone remains uncertain. This study evaluated the incremental effects of caffeine and SB co-ingestion within trials specifically designed to investigate the combined supplementation strategy. Methods: A systematic review and Bayesian arm-based multilevel network meta-analysis of randomized controlled trials published up to May 2026 was conducted. Eligible studies investigated acute caffeine–SB co-supplementation and, where available, included caffeine-only and SB-only arms, with placebo as the common reference. Exercise performance was the primary outcome; blood lactate, blood pH, blood bicarbonate, and rating of perceived exertion were secondary outcomes. Effects were estimated using Hedges’ g, Bayesian credible intervals, and SUCRA rankings. Results: Thirteen studies involving 181 participants met the eligibility criteria. Within this co-supplementation trial network, caffeine (g = 0.21), SB (g = 0.21), and co-ingestion (g = 0.28) produced small but credible improvements in exercise performance relative to placebo. However, comparisons among active conditions provided no clear evidence that co-ingestion was superior to either supplement alone. SB increased blood pH (g = 0.95) and blood lactate (g = 1.13), whereas caffeine reduced blood bicarbonate (g = −0.89). Co-ingestion elicited the largest increase in blood lactate (g = 1.75), but this response was not accompanied by a proportionally greater improvement in performance. Exploratory analyses suggested possible variation in supplementation responses according to training status. Conclusions: Within trials designed to evaluate caffeine–SB co-supplementation, the caffeine-only, SB-only, and combined conditions showed small improvements in exercise performance relative to placebo. However, co-ingestion elicited more pronounced metabolic responses without a clear performance advantage over either component alone, and the mechanisms underlying this divergence remain uncertain. Full article

A two-level closed-loop calibration framework is proposed to reduce odometry scale errors during motion and pose drift during stationary periods in Mecanum-wheeled mobile robots. At the upper calibration level, the planar displacement between the initial and final poses is calculated using the L2-norm, which reduces the influence of lateral deviation on distance measurements based on a single coordinate axis. Rotational displacement is obtained by accumulating normalized angular increments, thereby avoiding discontinuities when the yaw angle crosses the ±π boundary. A relay controller with a tolerance deadband is also introduced to reduce static-friction-induced stalling and oscillation near the target during low-speed calibration. At the lower odometry interface, the covariance assigned to wheel odometry measurements is adjusted according to the commanded zero-velocity state. During stationary periods, this adjustment increases the contribution of near-zero velocity measurements and limits the effect of residual velocity estimates and sensor noise on the fused pose. The identified longitudinal and rotational compensation factors are then updated online in the dead-reckoning node through an ROS 2 service. Unlike conventional ZUPT implementations, the proposed method does not require an additional zero-velocity pseudo-measurement node. Experiments were conducted on three near-horizontal surfaces: ceramic tile, epoxy resin, and asphalt. Across 720 bidirectional in-place rotation trials, the angular Error Reduction Rate ranged from (59.13%) to (96.58%). In 540 straight-line trials covering nine combinations of surface type and target distance, the overall mean absolute error decreased from 53.22 mm before calibration to 9.69 mm after calibration. Intermittent stop-and-go experiments were further performed using the EKF, UKF, RCKF, and a graph-based SLAM optimization framework implemented by slam_toolbox. For each estimation back-end, the estimated trajectory was evaluated by calculating its deviation from the corresponding synchronized /odom trajectory under the fixed-covariance and proposed ZUPT-based adaptive-covariance configurations; /odom was used as a common comparison baseline rather than as an absolute localization ground truth. The adaptive covariance strategy reduced the positional RMSE by (19.38%–67.44%) across the evaluated filtering back-ends. These results show that the proposed framework can reduce both motion-dependent odometry scale errors and stationary pose drift under the tested surface conditions. Full article

In order to improve maximum power point tracking (MPPT) and energy extraction in grid-connected photovoltaic (PV) systems under various climatic conditions, this research proposes a Secretary Bird Optimization-tuned Super-Twisting Sliding Mode Controller (SBOA–STSMC). The efficacy of traditional MPPT and adaptive control techniques is frequently compromised by nonlinear dynamics, abrupt changes in irradiance, and partial shading. In order to overcome these restrictions, the suggested method uses the Secretary Bird Optimization Algorithm (SBOA) to optimize STSMC parameters, resulting in improved disturbance rejection and transient response. Five increasingly difficult simulation scenarios are used to evaluate the controller. A single-array grid-connected system under stepwise irradiance fluctuations, combined irradiance–temperature disturbances, severe atmospheric dynamics, and low-irradiance operation are examined in Scenarios 1–4. The performance of adaptive controllers tuned using the Harmony Search Algorithm (HSA) and Invasive Weed Optimization (IWO) is compared with the traditional Incremental Conductance approach. In the fifth scenario, which deals with dynamic partial shading in a dual-array arrangement, the suggested approach is contrasted with HSA-based and IWO-based adaptive controllers and the traditional Perturb and Observe (P&O) technique. Furthermore, a sensitivity analysis is carried out for ±50% parameter modifications, demonstrating a small change in the total injected energy. An additional severe-disturbance test under rapid irradiance variations is performed, together with a ±50% sensitivity analysis of the grid-side choke inductance under the same severe profile. Statistical repeatability is further evaluated through 30 independent runs of the SBOA. A separate statistical comparison based on 30 independent runs of SBOA, TLBO, and PSO is also performed using the Wilcoxon rank-sum test, supporting the superior and consistent performance of SBOA. In addition, real-time validation is conducted using a Speedgoat real-time platform to demonstrate the practical implementation capability of the proposed controller. The results confirm improved dynamic response, reduced oscillations, enhanced robustness, and increased energy injected into the grid across all considered operating conditions. Full article

Background: Lifestyle behaviors and psychosocial factors are key determinants of cardiometabolic health across the life course. Beyond traditional risk factors, emerging evidence suggests that chronic stress and burnout may influence metabolic risk through behavioral pathways such as physical inactivity and poor diet. However, their joint contribution to type 2 diabetes risk in working populations remains insufficiently understood. Objectives: Our objectives were to examine the joint contribution of lifestyle habits, sociodemographic factors, and burnout to type 2 diabetes risk, and to explore potential behavioral pathways linking psychosocial stress to metabolic risk in a large adult population. Methods: A cross-sectional study was conducted in 92,480 Spanish workers undergoing routine occupational health assessments between 2021 and 2023. Type 2 diabetes risk was assessed using validated tools (FINDRISC, QDScore, CANRISK). Lifestyle indicators included adherence to the Mediterranean diet and physical activity levels; burnout was assessed using the Burnout Assessment Tool (BAT). Multivariable logistic regression models were used to evaluate associations between determinants and diabetes risk. Mediation analyses were performed to assess the contribution of lifestyle behaviors to the association between burnout and diabetes risk, and predictive performance analyses evaluated the incremental value of burnout. Results: Burnout was independently associated with a higher probability of moderate-to-high diabetes risk across all screening tools. Exploratory cross-sectional mediation analyses indicated that lifestyle behaviors, particularly physical inactivity and low adherence to the Mediterranean diet, statistically accounted for approximately 45% of the observed association. Adding burnout to the models significantly improved discrimination and reclassification of moderate-to-high diabetes-risk classification. In addition, higher diabetes risk was consistently observed among individuals from lower socioeconomic groups and those with unhealthy lifestyle profiles. Conclusions: Lifestyle behaviors and psychosocial stress were associated with estimated diabetes risk across adulthood. Burnout was independently associated with a higher probability of moderate-to-high diabetes-risk classification, with exploratory analyses suggesting that lifestyle behaviors may statistically account for part of this association. These cross-sectional findings highlight the potential relevance of considering both behavioral and psychosocial factors when studying cardiometabolic risk in working populations, while prospective studies are needed to establish temporal and causal relationships. Full article

Continuity and reliability are critical for underwater gravity aided inertial navigation, while variations in gravity field suitability, sensor noise, and environmental disturbances can degrade gravity matching and navigation performance. To address this issue, a data-driven matching error compensation framework is proposed for gravity aided inertial navigation. Within this framework, a Hampel filter identifies unreliable gravity matching outputs based on local temporal consistency, and a CNN–BiLSTM–Attention model predicts compensated position increments for the flagged updates. The model maps INS position increments and measured gravity anomaly sequences to reliable gravity matching increments through local feature extraction, temporal modeling, and attention-based weighting, with offline training and online deployment. Reliable training samples were selected offline using reference trajectories, with synchronized GNSS positions serving only as the reference for sample screening in the marine experiments. Experiments were conducted across five simulated gravity field regions with five gravity matching algorithms and along three measured trajectories acquired using two types of marine gravimeters. In the marine experiments, the proposed method achieved mean APE-O values of 1.60, 1.06, and 1.06 n miles on L6, L7, and L8, respectively. The improvement was most evident on L6 with relatively extended error intervals, while the conventional RBIM method achieved comparable performance on the more regular and localized L8 error interval. Across the evaluated datasets, the proposed framework provided effective compensation for degraded gravity matching updates and improved the continuity of position corrections. Full article

Background/Objectives: Age at alcohol initiation is consistently associated with later alcohol use disorder (AUD), but it remains uncertain whether initiation across distinct developmental stages identifies clinically different adult phenotypes. We examined whether alcohol initiation during early, middle, or late adolescence was associated with graded differences in addictive, psychiatric, and treatment-related complexity among adults with AUD. Methods: This cross-sectional study included 436 treatment-seeking adults with lifetime AUD recruited from addiction programs in Spain. Primary analyses included 409 participants who reported alcohol initiation during early (10–13 years; n = 85), middle (14–16 years; n = 182), or late adolescence (17–21 years; n = 142). Participants underwent structured assessment with the Psychiatric Research Interview for Substance and Mental Disorders (PRISM). Between-group comparisons, ordinal logistic regression, and exploratory latent class analysis (LCA) were performed. Results: Earlier initiation was associated with graded increases in comorbid non-alcohol substance use disorders (67.1%, 64.8%, and 47.2% across early, middle, and late initiation; FDR-adjusted p = 0.003), childhood conduct disorder (21.2%, 9.3%, and 4.2%; FDR-adjusted p < 0.001), and higher rates of lifetime therapeutic community treatment and mutual-support participation. Median age at AUD diagnosis was 19.0, 23.5, and 30.5 years, respectively (p < 0.001). In the model including age at AUD diagnosis, childhood conduct disorder (OR = 3.42, 95%CI 1.50–7.76) and mood disorder (OR = 2.13, 95%CI 1.41–3.21) were associated with earlier initiation. LCA identified a high externalizing/polysubstance complexity class (15.2%) enriched for earlier initiation (p < 0.001). Conclusions: Developmental timing of alcohol initiation was associated with a multidomain adult AUD phenotype. These findings suggest that initiation age could serve as a simple historical prompt for broader assessment; however, its incremental clinical utility was not tested, and it should not be interpreted as evidence of causality or a validated prediction tool. Full article

Waveforms recorded by lightning location networks mix source variability with propagation effects, making terrain-associated distortion difficult to isolate. We developed a path-incremental method in which the additional segment between two stations observing the same stroke carries the propagation signal. From 4466 records of 554 negative cloud-to-ground return strokes, 469 near-collinear pairs were stratified by additional path length and split at the within-stratum median of a digital-elevation-model terrain complexity index. Higher-complexity (rugged) paths showed the clearest near–far increases in rise time and half-peak width, whereas fall time and zero-crossing time showed no stable ordering, indicating that terrain acts mainly on the pulse front and main peak. In the frequency domain, these paths retained lower normalized band-energy fractions at 50–150 and 100–300 kHz, most systematically at 100–300 kHz for subsequent strokes, whereas the 200–500 kHz response was unstable. Separate mixed-effects models linked path elongation, occlusion, and diffraction geometry individually to a 39.7–42.5% lower 100–300 kHz ratio for subsequent strokes. Twelve representative-path axisymmetric finite-difference time-domain simulations under matched source currents reproduced the same ordering in these two bands across three ground conductivities. Rise time, half-peak width, and the normalized 100–300 kHz ratio are the most consistent terrain-associated indicators, supporting terrain-aware waveform interpretation. 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/Objective: The EXTRACT registry cohort of 504 patients undergoing transvenous lead extraction (TLE) has been previously reported in terms of periprocedural safety and short-term outcomes. Data on long-term mortality and its predictors in this population remain limited. The study aimed to identify risk factors for overall mortality at three years following TLE. Methods: This is a secondary, long-term follow-up analysis of the previously published EXTRACT registry cohort of 504 consecutive patients who underwent TLE between 2016 and 2022. We conducted a univariate analysis to predict mortality risk following TLE, followed by Cox regression with cross-validation to identify independent predictors of mortality over a 3-year follow-up period; Brier score assessed prediction accuracy for mortality; and decision curve analysis evaluated the clinical usefulness of the model. Results: Mortality data were completed for 487 patients at three-year follow-up. Long-term outcomes of TLE showed that patients with CIED infection (p = 0.0091), higher NYHA class (p < 0.0001), arterial hypertension (p = 0.0068), previous stroke (p = 0.0092), upgraded to condition pacing post-TLE (p = 0.0092), and higher CHA₂DS₂-VA score (p = 0.0026) had markedly higher mortality at three-year follow-up. Increased mortality was independently associated with estimated glomerular filtration rate (eGFR) and the CHA₂DS₂-VA score. Risk increased incrementally with each 1 mL/min/1.73 m² decrease in eGFR (hazard ratio, 0.99; 95% CI, 0.98–0.99), and each 1-point increase in CHA₂DS₂-VA conferred a 12% higher mortality rate (hazard ratio, 1.12; 95% CI, 1.02–1.23). Conclusions: In this prospective registry, 3-year mortality after TLE was driven predominantly by baseline clinical risk rather than procedural factors. Renal dysfunction and a higher CHA₂DS₂-VA score independently predicted death, supporting the incorporation of kidney function and global vascular risk into pre-extraction assessment and post-extraction management. Full article

Background/Objectives: The lactate/albumin ratio (LAR) integrates tissue hypoperfusion and nutritional reserve into a single dimensionless index. As a late-course measurement (last available value before the primary outcome), it may reflect terminal metabolic deterioration rather than early prognostic signal. We examined the association of the final LAR with in-hospital mortality after adjustment for validated severity scores (APACHE II, SOFA) in critically ill patients receiving CRRT, and evaluated its incremental value beyond lactate alone. Methods: A single-centre retrospective observational study was conducted, including 110 adult patients treated with CRRT/CVVHDF at Konya City Hospital (January 2024–January 2026). Multivariable logistic regression was performed across four hierarchically adjusted models. APACHE II was designated the primary adjustment covariate. ROC analyses compared the final LAR with final lactate and albumin alone. Results: In-hospital mortality was 70.9% (78/110); complete paired final lactate and albumin values were available for 109/110 patients (78 non-survivors, 31 survivors). After APACHE II adjustment, each 0.1-unit increase in the late-course LAR remained significantly associated with in-hospital mortality (OR 1.70; 95% CI 1.16–2.49; p = 0.007), a finding replicated in the ICU-stay sensitivity cohort (n = 100, 73 events; OR 1.63; 95% CI 1.09–2.42; p = 0.016). The LAR trajectory (ΔLAR; AUC 0.725) was significantly greater in non-survivors (+0.104 vs. −0.060; p < 0.001); however, ΔLAR did not significantly outperform the lactate trajectory alone (Δlactate; AUC 0.706; p = 0.212), and lost statistical significance after severity-score adjustment. Furthermore, the association was attenuated and non-significant after SOFA adjustment (OR 1.35; p = 0.077), and the final LAR did not provide statistically significant discriminative advantage over lactate alone (AUC 0.768 vs. 0.761; LRT p = 0.435). Conclusions: The late-course LAR remained significantly associated with mortality after APACHE II adjustment. Three qualifications temper this finding: the association was attenuated after SOFA adjustment, the final LAR did not outperform lactate alone, and the measurement design is susceptible to reverse causality. The LAR trajectory (ΔLAR; AUC 0.725) showed comparable discrimination to the final LAR but did not significantly outperform the lactate trajectory alone (Δlactate; AUC 0.706; p = 0.212) and lost statistical significance after severity-score adjustment, so it should likewise be regarded as hypothesis-generating rather than confirmatory; prospective evaluation with time-stamped serial measurements and landmark analyses in multi-centre CRRT cohorts is warranted. Full article

Asthma is one of the most prevalent chronic respiratory diseases worldwide, and environmental pollutants such as desert dust play a significant role in triggering respiratory sensitization and aggravating asthma symptoms. In this study, a mathematical model is proposed to investigate the dynamics of dust-induced asthma progression. The population is divided into unaware susceptible individuals, aware susceptible individuals, dust-sensitized individuals, and asthmatic individuals, while two additional variables describe dust concentration in the human population and the environment. Fundamental qualitative properties of the model, including positivity, boundedness, existence of equilibria, and stability conditions, are established. It is shown that the asthma-free equilibrium is locally and globally asymptotically stable whenever the dust-induced asthma threshold is below unity, whereas a unique asthma-persistent equilibrium exists when the dust-induced asthma threshold exceeds unity. To reduce the burden of asthma, an optimal control problem is formulated by incorporating three time-dependent interventions: awareness campaigns, medical intervention for dust-sensitized individuals, and environmental dust reduction. Pontryagin’s Maximum Principle is employed to characterize the optimal controls and derive the corresponding adjoint system. Numerical simulations, performed using the forward–backward sweep method, demonstrate that the proposed interventions significantly reduce the number of asthmatic individuals compared with the uncontrolled case. Furthermore, a cost-effectiveness analysis based on the Average Cost-Effectiveness Ratio (ACER) and Incremental Cost-Effectiveness Ratio (ICER) is conducted to compare seven intervention strategies. The results indicate that the medical intervention strategy is the most economically attractive option, while the combined strategy involving all controls achieves the largest reduction in asthma burden. Full article

Space Station Operation Mission Planning (SSOMP) requires coordinated decisions across long-term activity allocation, mid-term logistics optimization, and short-term execution scheduling and is a key component of autonomous mission operations for high-precision space missions. Existing optimization methods have achieved substantial progress at individual planning levels, but their dependence on problem-specific models, limited support for semantic review of decision rationale, and computational cost restrict their adaptability to multi-level planning scenarios. This paper proposes a Large Language Model (LLM)-assisted framework for multi-level SSOMP. The framework combines Staged Fine-Tuning (Staged-FT), Reflective Constraint–Repair Prompting (RCRP), and LLM-Guided Evolutionary Variation (LGEV). Staged-FT uses a Cognitive-Load-Theory-informed curriculum with Low-Rank Adaptation to adapt general-purpose LLMs to SSOMP domain knowledge. RCRP couples a Deterministic Rule Engine with LLM-based semantic repair to improve hard constraint satisfaction. LGEV embeds the fine-tuned LLM into NSGA-III as a fitness-aware variation operator for multi-objective activity allocation. Three case studies are conducted on literature-derived benchmark scenarios of logistics optimization, emergency re-planning, and activity allocation with logistics design, corresponding to Flight Increment Planning, Short-Term Execution Planning, and Overall Operation Planning, respectively. Results show that Staged-FT produces solutions close to traditional algorithms, RCRP achieves full hard constraint satisfaction in the emergency re-planning and logistics planning cases, and LGEV reduces the convergence generations of NSGA-III while improving Pareto-front quality. The framework provides a constraint-aware approach with explicit reasoning traces that can support expert review of AI-assisted planning for autonomous space mission operations. Full article