Search Results (9,594)

The shortest path problem presents formidable challenges in graph optimization, particularly within dense or large-scale networks, where traditional algorithms face serious scalability limitations. This paper puts forth a robust QUBO-based simulated annealing (QUBO-SA) methodology that effectively utilizes a Quadratic Unconstrained Binary Optimization (QUBO) framework to encode path costs and structural constraints simultaneously. Our approach has been rigorously evaluated on synthetic graphs with controlled connectivity, varying from $n=10$ to $n=40$, and on a real-world urban transportation network from Querétaro, Mexico, comprising $n=443$ nodes. We assess performance through rigorous probabilistic reliability indicators, notably the success probability $p_{\mathrm{success}}$, Time-to-Solution, and the relative runtime ratio $R\left(p_{\mathrm{target}}\right)$, benchmarked against Dijkstra’s algorithm. In small synthetic instances ($n=10$), the QUBO-SA method demonstrates outstanding success rates ($p_{\mathrm{success}}\ge 0.97$) with runtimes on par with the deterministic baseline ($R_{0.99}\approx 1$). However, as the problem size increases, success probabilities diminish while computational overhead rises, with $R_{0.99}$ soaring from approximately $1.0$ at $n=10$ to between $4.63$ and $5.83$ at $n=40$. For the urban network, our solver achieves success probabilities between $0.49$ and $0.91$, depending on the specified path length, with $R_{0.99}$ values ranging from $2.17$ to $9.41$. Notably, reducing the target confidence level from $99\%$ to $90\%$ cuts runtime overhead by approximately fifty percent across all configurations. Although the QUBO formulation demonstrates scalability in relation to $n+m$, potentially limiting its use in dense graphs, the sparse structure typical of real-world road networks enables competitive performance in moderately large instances. These findings decisively highlight the trade-off between solution reliability and computational efficiency, pinpointing specific problem regimes where QUBO-based optimization methods are not only viable but advantageous for path-optimization tasks. Full article

This study investigates the enhancement of AA6082/Al₂O₃ aluminum metal matrix nanocomposites (AMMNCs) through powder metallurgy combined with systematic process optimization. Ultrasound-assisted dispersion and Taguchi design L9 orthogonal array were employed to improve nanoparticle distribution and optimize fabrication parameters. The effect of Al₂O₃ content and ultrasonication time (UT) on hardness and compressive strength was analyzed using S/N ratio and ANOVA. Characterization was performed using X-ray Diffraction (XRD) and scanning electron microscopy (SEM). The result shows that Al₂O₃ content had the most significant influence on both hardness (82.25%) and compressive strength (81.08%), followed by UT. The optimal condition produced a maximum hardness of 31.9 HV and compressive strength of 205.53 MPa. Regression models demonstrated strong predictive accuracy (R² > 85%). Overall, the study highlights the effectiveness of parameter optimization in improving nanocomposite performance and provides valuable guidance for advanced material design. Full article

To achieve synergistic, efficient degradation of volatile, harmful gases in asphalt and to scientifically quantify inhibitor dosage, this study proposes a dosage optimization method that integrates nonlinear regression with a multi-response satisfaction function. Focusing on a proprietary composite volatile gas suppressant, we systematically measured the concentration trends of ammonia, nitrogen oxides, sulfur dioxide, and hydrogen sulfide emitted from three asphalt systems: base asphalt, SBS modified asphalt (Styrene-Butadiene-Styrene modified asphalt), and rubber modified asphalt under different suppressant dosages (0%, 0.02%, 0.04%, 0.06%, 0.08%, and 0.10%). First, high-precision prediction models (R² > 0.95) were established using nonlinear regression to relate different inhibitor dosages to corresponding gas concentrations. Based on a satisfaction function, the multi-objective degradation effects were normalized into a comprehensive satisfaction index, and the optimal dosage was then determined. The results indicate: (1) the constructed models can accurately predict the concentrations of volatile harmful gases at various dosages; (2) the predicted optimal blending ratios vary by asphalt type, specifically 0.082% for base asphalt, 0.079% for SBS modified asphalt, and 0.080% for rubber modified asphalt; and (3) at the optimal blending ratios, all four gases achieve high and balanced degradation levels, resulting in the best overall degradation performance. At the same time, road performance tests confirmed that this blending ratio has no significant negative impact on the high-temperature and low-temperature stability or water stability of the asphalt mixture. Compared with traditional single-factor empirical methods, this approach represents a methodological upgrade from qualitative description to quantitative prediction, and from single-objective comparison to multi-objective synergistic optimization, providing data and theoretical support for the precise, efficient, and engineering-applicable use of asphalt volatile gas inhibitors. Full article

Background: In patients with left ventricular hypertrophy, resting structural parameters alone may not explain exertional symptoms. Hence, we investigate whether combined Cardiopulmonary Exercise Testing- Exercise Stress Echocardiography (CPET-ESE) can provide an integrated functional characterisation of hypertrophic phenotypes. Methods: As a preliminary investigation, this prospective single-centre pilot study enrols 43 patients, categorised into: obstructive hypertrophic cardiomyopathy (n = 19), transthyretin cardiac amyloidosis (n = 15), or preserved-ejection-fraction hypertrophic phenotypes (n = 9). Patients undergo symptom-limited semi-supine CPET-ESE on an electronically braked cycle ergometer with an individualised ramp protocol. Peak effort is defined by symptom limitation and respiratory exchange ratio criteria ($RER\ge 1.05$), while peak VO₂ is defined as the highest 30 s averaged value. Results: Exercise responses differ across phenotypes. Patients with obstructive hypertrophic cardiomyopathy have higher peak VO₂ than the other groups, despite their lower chronotropic reserve. The preserved-ejection-fraction hypertrophic group shows lower peripheral oxygen extraction, whereas transthyretin amyloidosis shows a mixed central and peripheral limitation pattern. Right ventricle–pulmonary artery uncoupling is observed in the latter two groups. Conclusions: The use of CPET-ESE may help describe distinct physiological exercise profiles in hypertrophic phenotypes, but these findings should be considered exploratory. The small, heterogeneous and single-centre cohort precludes definitive mechanistic or predictive conclusions and supports the need for larger validation studies. Full article

This study aims to evaluate the potential of Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) based on signal-to-noise ratio (SNR) analysis for monitoring crop structure and moisture. Data were collected using a GNSS antenna placed within an experimental meadow located in NW Italy. GNSS-IR exploits the interference between direct and ground-reflected signals to derive physical parameters such as the vegetation phase center height and soil moisture. In this work, by analyzing and modeling the oscillations in SNR time series, the sensitivity to crop growth dynamics was assessed. Vegetation height and dielectric parameters were compared against corresponding ground-surveyed values collected using a ruler and buried soil moisture sensors. Results suggest that GNSS-IR can detect canopy height with a high degree of consistency (Pearson’s r = 0.89, MAPE = 18%). Results also show that changes in the amplitude and phase of the interference pattern are sensitive to biomass density and dielectric properties of the reflecting surface (r = −0.81 and r = 0.86 respectively). GNSS-IR observables were analyzed across four representative measurement campaigns capturing distinct seasonal stages of meadow development. Despite the limited temporal sampling (n = 4), the selected observations correspond to contrasting vegetation and soil moisture conditions, allowing the identification of systematic variations in crop biophysical properties. These findings open promising perspectives for the development of innovative monitoring strategies in precision agriculture, leveraging existing GNSS infrastructure to obtain key biophysical parameters with minimal additional equipment and operational complexity. Full article

The increasing prevalence of cardiovascular diseases highlights the need to develop vascular grafts that match the mechanics of native vascular tissue and offer functional adaptability. This study reports the development and systematic optimization of a shape-memory polyurethane acrylate (PUA)-based photocurable resin for digital light processing (DLP)-based four-dimensional printing (4DP) applications. Resin formulations were designed by controlling hard/soft segment ratios, reactive diluent content, and crosslink density to position the glass transition temperature (T_g) within the physiological range (25–40 °C). Thermomechanical characterization was performed via dynamic mechanical analysis (DMA) and tensile testing, while a full-factorial Design of Experiments (DoE) approach was applied to optimize DLP process parameters—namely layer thickness, exposure time, and post-curing time. The developed resin formulation yielded a T_g of 38 °C as determined by DMA. Following process optimization, regression models showed high statistical fit (R² > 99%), and experimental validation under optimal conditions (layer thickness: 82.83 µm, exposure time: 11 s, post-curing: 2 min) resulted in an elongation at break of 64.0 ± 3.4%, a Young’s modulus of 10.9 ± 0.1 MPa, and a tensile strength of 6.2 ± 0.3 MPa. The optimized system exhibited thermally triggerable shape memory behavior at near-body temperature, with mechanical properties consistent with natural arterial tissue benchmarks. These findings demonstrate a promising material design strategy for DLP-based 4D-printed vascular structures. Full article

Research into auxetic foams—materials with a negative Poisson’s ratio— is expanding, yet their integration into orthotics for diverse neuropathic conditions remains largely unexplored. This pilot study evaluates the feasibility of fabricating custom auxetic foam insoles and characterizing vertical ground reaction force (vGRF) trends across a heterogeneous cohort. In collaboration with the NASA/Marshall Space Flight Center, six participants, including five representing varied neuropathic etiologies and one healthy control, performed randomized walking trials under three conditions: barefoot, over-the-counter (OTC) insoles, and custom auxetic prototypes. The healthy control was retained in the cohort-level analysis to preserve methodological symmetry across experimental conditions. To maintain physical rigor, vGRF data were mass-normalized (N/kg). A Friedman test (n = 6) evaluated global differences, supplemented by a dual-bootstrap analysis (1000 resamples) to quantify effect magnitudes (r) and numerical uncertainty. Although the Friedman test revealed no statistically significant global differences (Q = 0.333, df = 2, p = 0.846), a descriptively large effect size (r = 0.58) was observed for the auxetic material versus barefoot walking. However, wide 95% bootstrap confidence intervals prevent population-level inference, reinforcing the exploratory nature of these findings. Subject-specific observations showed descriptive differences in vGRF in three participants (0.17 to 1.18 N/kg), while increases in others occurred alongside confounding factors such as self-selected walking velocity. This work demonstrates the mechanical application of auxetic insole prototypes, providing a foundational rationale for future trials utilizing standardized walking velocity to isolate material performance. Full article

The evolution of herbicide resistance can increase, decrease, or have no effect on the growth rate, competitive ability, and fitness of field-selected populations. The growth response of an ACCase-resistant (R) johnsongrass [Sorghum halepense (L.) Pers.] population harboring an Ile1781Leu mutation, and a susceptible (S) population was studied in pot experiments under intraspecific and interspecific competition with corn or sunflower, using a target-neighborhood design. The R population in the intraspecific competition indicated greater fitness-related traits such as height (H), tiller number (TN), aboveground fresh weight (AFW), and rhizome fresh weight (RFW) than the S population. Aggressiveness, competitive ratio, competition intensity index, and relative competition intensity indices confirmed also the superiority of the R population. Similarly, the R population grown in interspecific competition with corn or sunflower produced greater H, TN, and AFW than the S population. In addition, both R and S populations growing in competition with corn produced more H, TN, and AFW than those growing in competition with sunflower. Furthermore, the R population in competition with corn hybrids resulted in a greater reduction in H and AFW in corn plants. These findings strongly support the evidence of fitness advantage in the R population harboring the 1781Leu mutant allele as compared to the S counterpart. Full article

Background/Objectives: Co-processed excipients (CPEs) are designed for direct compression through particle engineering, yet comprehensive powder rheological profiles systematically comparing advanced and traditional characterization methods remain limited. This study characterized fifteen lactose-based excipients using European Pharmacopoeia (Ph. Eur.) methods and the complete Freeman FT4 Powder Rheometer measurement suite, establishing a correlation framework linking particle-level attributes to macroscopic flow behavior. Methods: Fifteen excipients were characterized for bulk and tapped density, compressibility index, flow time (Ph. Eur. 2.9.16), and angle of repose (Ph. Eur. 2.9.36). Particle size and shape were measured by dynamic image analysis. FT4 measurements comprised stability and variable flow rate testing, consolidation, aeration, compressibility, permeability, shear cell, and wall friction at three surface roughness. Pearson correlation matrices were computed across all 53 parameters. Results: Classical flow indices classified most CPE as good-to-satisfactory, failing to discriminate materials with fundamentally different dynamic flow profiles. FT4 testing revealed a fourfold range in Basic Flowability Energy (624–2107 mJ), a ninefold range in flow function coefficient (4.3–35.8), and wide aeration sensitivity differences (Aeration Ratio: 1.9–283.7). Strong correlations were identified between Specific Energy and compressibility index (r = 0.85), cohesion and Flow Rate Index (r = 0.79), and Normalized Aeration Sensitivity and pressure drop (r = 0.86). Within-family comparisons (Tablettose 70/80/100, FlowLac 90/100) revealed that particle size distribution breadth is a more critical flow determinant than median size alone. Conclusions: Combining FT4 rheometry with pharmacopoeial testing provides substantially greater discriminating power than either approach alone, enabling rational excipient selection for direct compression formulation. Full article

Background: Microstructural abnormalities of the corpus callosum (CC) are a consistent finding in schizophrenia, yet conventional diffusion tensor imaging (DTI) metrics provide limited biological specificity. Neurite orientation dispersion and density imaging (NODDI) can disentangle the neurite density index (NDI) and the orientation dispersion index (ODI), providing indirect, model-based markers of white matter microstructure in vivo. Methods: We applied NODDI to diffusion-weighted MRI data in patients with first-episode schizophrenia (FES) and matched healthy controls (HCs). The CC was used as a mask and subdivided into the genu (GCC), body (BCC), and splenium (SCC). Group differences in z-scores of the NDI and ODI were assessed using voxel-wise statistics within the CC and region of interest (ROI) analyses in the GCC, BCC, and SCC, controlling for age and sex. Associations between NODDI metrics and clinical symptoms were examined using the Positive and Negative Syndrome Scale (PANSS). Results: FES patients showed a significantly increased ODI in portions of the GCC, BCC, and SCC, as well as region-specific NDI alterations, with decreased NDI in parts of the SCC and increased NDI in sub-regions of the GCC/BCC (voxel-wise p < 0.05, FWE-corrected). ROI analyses confirmed a significant reduction in NDI z-scores in the SCC in FES patients compared with HCs (p = 0.009), whereas the ODI z-scores in the SCC did not differ significantly between groups (p = 0.124). Despite the absence of group-level ODI differences in the SCC, the SCC ODI was positively correlated with PANSS negative symptom scores in FES patients (r = 0.554, p = 0.002) and was also positively correlated with PANSS total scores in FES (r = 0.457, p = 0.014). This association remained significant in the region of the SCC after regressing out NDI from ODI (residual z_ODI), which was correlated with PANSS negative scores (r = 0.503, p = 0.006) and PANSS total scores (r = 0.474, p = 0.011), and the ODI/NDI ratio in the SCC was also correlated with negative symptom severity (r = 0.457, p = 0.014). Conclusions: Our findings suggest that, in the SCC, negative symptoms in schizophrenia are linked to altered neurite orientation dispersion under conditions of reduced neurite density. The dissociation between group-level NDI and ODI effects and their distinct relationship with psychopathology highlights the value of composite microstructural indices (e.g., residual z_ODI, ODI/NDI) for capturing clinically relevant white matter abnormalities. Full article

Introduction: Robotic gastrectomy is increasingly used in the surgical management of gastric cancer. Indocyanine green (ICG) near-infrared fluorescence imaging has emerged as a technique that enables real-time visualization of lymphatic drainage pathways, potentially facilitating more precise and individualized lymph node dissection. However, the clinical value of ICG-guided fluorescent lymphography during robotic gastrectomy remains incompletely established. Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines. PubMed, Embase, Scopus, and the Cochrane Library were searched from database inception to 31 January 2026 for comparative studies evaluating ICG-guided fluorescent lymphography versus standard robotic gastrectomy for gastric cancer. Statistical analyses were performed using R (version 4.4.2) and the meta package. Results: Six studies, including 406 patients, met the inclusion criteria. Use of ICG was associated with a higher number of retrieved lymph nodes (mean difference [MD] 8.48; 95% CI 4.61–12.36; p = 0.001; I² = 55.5%). Operative time was modestly shorter in the ICG group (MD −10.84 min; 95% CI −21.08 to −0.61; p = 0.038). There were no significant differences in intraoperative blood loss (MD −4.02 mL; p = 0.289), length of hospital stay (MD −0.82 days; p = 0.131), or postoperative complications (odds ratio 0.83; 95% CI 0.46–1.49; p = 0.534). Conclusions: ICG-guided fluorescence imaging during robotic gastrectomy is associated with increased lymph node retrieval and a small reduction in operative time without evidence of increased perioperative morbidity. Larger prospective studies are required to confirm these findings and to evaluate long-term oncologic outcomes. Full article

Background/Objectives: Acute cholecystitis is associated with an increased risk of morbidity and mortality. Thus, early diagnosis and detection of complications are essential. Neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) are inflammatory biomarkers that could predict the diagnosis and complications of acute cholecystitis. Yet, the results of which biomarker has higher accuracy are inconsistent. Objective: To compare the accuracy of NLR and CRP in the diagnosis and prediction of complications in patients with acute cholecystitis. Methods: We searched PubMed, Scopus, and Web of Science in January 2026 for studies that compared both biomarkers (NLR and CRP) for the diagnosis and detection of complications or severity in patients with acute cholecystitis. We assessed the quality of the included studies using the QUADAS 2 tool. A bivariate meta-analysis was performed using R to compare the pooled diagnostic odds ratio (DOR) and the difference in sensitivity and specificity between both biomarkers. We used RevMan software to generate forest plots and summary receiver operating characteristic (SROC) curves using parameters calculated through R. Results: We included 15 studies in the systematic review, and 12 of them were included in the meta-analysis. The pooled data showed that NLR had higher accuracy in the diagnosis of acute cholecystitis compared to CRP, DOR 2.257 (95% CI 1.1, 4.633); however, there was no significant difference in sensitivity or specificity. There was no significant difference between NLR and CRP in detecting complications, including perforation, gangrene, and suppurative cholecystitis, DOR 1.100 (95% CI 0.817, 1.481). Meanwhile, NLR had similar sensitivity but lower specificity −0.050 (95% CI −0.090, −0.010) compared to CRP. NLR had lower overall accuracy in the detection of disease severity grades according to the Tokyo guidelines compared to CRP, DOR 0.170 (95% CI 0.081, 0.359), but higher specificity 0.230 (0.182, 0.279) compared to CRP. Conclusions: This systematic review and meta-analysis showed that NLR had higher diagnostic accuracy than CRP in patients with acute cholecystitis. However, both biomarkers had comparable sensitivity and specificity. Additionally, both biomarkers had comparable accuracy in detecting complications such as perforation, gangrene, or suppurative cholecystitis. CRP had higher overall accuracy in detecting disease severity according to the Tokyo guidelines. Thus, while NLR may be useful in diagnosing acute cholecystitis, CRP could be more effective in assessing disease severity. However, owing to the limited number of included studies, these findings should be interpreted with caution, and further studies are needed to confirm these results. Full article

In this study, we investigated how the formation and properties of Pickering emulsions (PEs) stabilized by zein/tannic acid particles (ZTAPs) are impacted by the method used to generate the particles, before or during emulsification. ZTAPs were obtained through two antisolvent precipitation methods (sequential and co-precipitation) across zein/tannic acid molar ratio (R) range of 1/0 to 1/30. Emulsions were prepared using four methods, either with pre-formed ZTAPs or by mixing zein and tannic acid immediately before or during emulsification. The results indicated that pre-forming the particles prior to emulsification is crucial for controlling droplet size and homogeneity, while the quantity of tannic acid plays a supporting role. Tannic acid is not only critical for emulsion stabilization but also imparts its antioxidant activity to the emulsions. This activity is also controlled by the molar ratio R of the particles and the preparation protocol. ZTAPs are promising plant-based stabilizers for emulsions in the food and pharmaceutical industries. These findings provide a better understanding of the importance of their method of production in controlling the characteristics (droplet size, stability, and antioxidant properties) of the emulsions they stabilize. Full article

Optimizing the recovery of bioactive compounds is critical for the accurate assessment of the quality of freeze-dried vegetables. In this context, Response Surface Methodology (RSM) was performed to optimize the ultrasound-assisted extraction (UAE) of phenolic compounds from freeze-dried broccoli (cv ‘Thassos’) and cauliflower (cv ‘Cercy’) florets. The influence of three process parameters, namely solvent-to-material ratio (20 to 60 mL/g), extraction time (10 to 40 min) and solvent mixture (methanol: water) composition (60 to 100% methanol) was evaluated. Multi-response optimization identified the optimal process conditions for both cultivars (composite desirability = 0.996) as a 60 mL/g ratio, 10 min extraction time and 76% methanol content. The application of the optimized extraction conditions to broccoli ‘Naxos’ and cauliflower ‘Guideline’ cultivars, confirmed the model applicability and revealed significant genotypic heterogeneity (p < 0.05). Pearson’s Correlation Analysis revealed a very high positive (r > 0.9) correlation between TPC and ABTS for both broccoli and cauliflower, high (r = 0.78) correlation between TPC and FRAP for broccoli and moderate (r = 0.63) for cauliflower. These findings confirm that process parameter optimization is crucial for the maximum recovery of phenolic compounds from freeze-dried broccoli and cauliflower, and UAE conditions should be carefully selected to ensure accurate cultivar evaluation. Full article

In modern intensive mutton sheep farming, the high cost and limited supply of conventional feed resources necessitate the exploration of sustainable alternatives. Cotton stalks and sugar beet pulp, abundant agricultural by-products in China, have potential as ruminant feed after proper fermentation treatment, yet their systematic application in sheep production remains underinvestigated. This study evaluated the effects of replacing whole-plant corn microsilage with mixed fermented feed (cotton stalks and sugar beet pulp, 1:1 dry matter ratio) on Suffolk rams (n = 84, 4 months old). Animals were randomly assigned to four groups: control (CK, 0% replacement), MS30 (30% replacement), MS60 (60% replacement), and MS90 (90% replacement). After a 15-day adaptation, the 120-day feeding trial assessed growth performance, slaughter characteristics, meat quality, muscle metabolomics (LC-MS), and jejunal microbiota (16S rRNA sequencing). The MS60 group significantly outperformed the CK group in final body weight, carcass weight, and net weight gain (p < 0.01), slaughter rate (p < 0.05), and meat tenderness (p < 0.05). Fatty acid composition was optimized, with lower SFAs (p < 0.01) and higher MUFAs (p < 0.01). Metabolomic analysis revealed 206 differentially abundant metabolites, with significant enrichment in linoleic acid metabolism, unsaturated fatty acid biosynthesis, and primary bile acid synthesis pathways. The MS60 group exhibited significantly altered jejunal microbiota structure (p < 0.05), including increased Patescibacteria abundance (p < 0.05) and decreased Bifidobacterium (p < 0.001). Replacing 60% of whole-plant corn microsilage with cotton stalk–beet pulp mixed microsilage effectively improved production performance, meat quality, and fatty acid profiles in Suffolk rams, while modulating muscle metabolism and intestinal microbiota structure. These findings provide a practical strategy for sustainable sheep farming utilizing regional agricultural by-products. Full article