Search Results (863)

With the rise of the low-altitude urban traffic system, urban air mobility (UAM) has developed rapidly. As a critical component of the UAM system, the strategic layout of vertiports helps divert ground traffic pressure. To satisfy various demand patterns, different vertiport levels are needed, so we focus on the hierarchical vertiport location problem. Considering the capacity limitation, a median location model is established to minimize vertiport construction cost, passenger commuting cost, and penalty cost. For the nonlinear term in the objective function, the Big-M method is employed. Based on the reformulated model, we improve the branch-and-bound algorithm (LVBB) to solve it, where the Lagrange relaxation method is used to decompose the large-scale problem into parallel subproblems and compute the lower bound, and the variable neighborhood search algorithm is used to obtain the upper bound. Numerical experiments are performed in the 11 administrative districts of Nanjing, China. The results demonstrate that the proposed location scheme effectively balances vertiport construction cost and passenger commuting cost while satisfying capacity limitations. It also significantly reduces commuting time to improve passenger satisfaction. This scheme can offer strategic guidance for infrastructure planning in UAM. Full article

The development of deep coalbed methane (buried depth > 2000 m) in the Yan’an block of Ordos Basin is limited by low permeability, the pore structure of the coal reservoir, and the gas–water occurrence relationship. It is urgent to clarify the key control mechanism of pore structure on gas migration. In this study, based on high-pressure mercury intrusion (pore size > 50 nm), low-temperature N₂/CO₂ adsorption (0.38–50 nm), low-field nuclear magnetic resonance technology, fractal theory and Pearson correlation coefficient analysis, quantitative characterization of multi-scale pore–fluid system was carried out. The results show that the multi-scale pore network in the study area jointly regulates the occurrence and migration process of deep coalbed methane in Yan’an through the ternary hierarchical gas control mechanism of ‘micropore adsorption dominant, mesopore diffusion connection and macroporous seepage bottleneck’. The fractal dimensions of micropores and seepage are between 2.17–2.29 and 2.46–2.58, respectively. The shape of micropores is relatively regular, the complexity of micropore structure is low, and the confined space is mainly slit-like or ink bottle-like. The pore-throat network structure is relatively homogeneous, the difference in pore throat size is reduced, and the seepage pore shape is simple. The bimodal structure of low-field nuclear magnetic resonance shows that the bound fluid is related to the development of micropores, and the fluid mobility mainly depends on the seepage pores. Pearson’s correlation coefficient showed that the specific surface area of micropores was strongly positively correlated with methane adsorption capacity, and the nanoscale pore-size dominated gas occurrence through van der Waals force physical adsorption. The specific surface area of mesopores is significantly positively correlated with the tortuosity. The roughness and branch structure of the inner surface of the channel lead to the extension of the migration path and the inhibition of methane diffusion efficiency. Seepage porosity is linearly correlated with gas permeability, and the scale of connected seepage pores dominates the seepage capacity of reservoirs. This study reveals the pore structure and ternary grading synergistic gas control mechanism of deep coal reservoirs in the Yan’an Block, which provides a theoretical basis for the development of deep coalbed methane. Full article

Emergency material scheduling (EMS) is a core component of post-disaster emergency response, with its efficiency directly impacting rescue effectiveness and the satisfaction of affected populations. However, due to severe road damage, limited availability of resources, and logistical challenges after disasters, current EMS practices often suffer from uneven resource distribution. To address these issues, this paper proposes a priority-based, multi-stage EMS approach with drone coordination. First, we construct a three-level EMS network “storage warehouses–transit centers–disaster areas” by integrating the advantages of large-scale transportation via trains and the flexible delivery capabilities of drones. Second, considering multiple constraints, such as the priority level of disaster areas, drone flight range, transport capacity, and inventory capacities at each node, we formulate a bilevel mixed-integer nonlinear programming model. Third, given the NP-hard nature of the problem, we design a hybrid algorithm—the Tabu Genetic Algorithm combined with Branch and Bound (TGA-BB), which integrates the global search capability of genetic algorithms, the precise solution mechanism of branch and bound, and the local search avoidance features of Tabu search. A stage-adjustment operator is also introduced to better adapt the algorithm to multi-stage scheduling requirements. Finally, we designed eight instances of varying scales to systematically evaluate the performance of the stage-adjustment operator and the Tabu search mechanism within TGA-BB. Comparative experiments were conducted against several traditional heuristic algorithms. The experimental results show that TGA-BB outperformed the other algorithms across all eight test cases, in terms of both average response time and average runtime. Specifically, in Instance 7, TGA-BB reduced the average response time by approximately 52.37% compared to TGA-Particle Swarm Optimization (TGA-PSO), and in Instance 2, it shortened the average runtime by about 97.95% compared to TGA-Simulated Annealing (TGA-SA).These results fully validate the superior solution accuracy and computational efficiency of TGA-BB in drone-coordinated, multi-stage EMS. Full article

Roasted coffee silverskin (RCSS) is a by-product of coffee production characterized by its content of phenolic compounds, both free and bound to macromolecules. In this study, RCSS was fermented to release these compounds and consequently increase its value as a functional food ingredient. Fermentation was carried out using yeast, acetic acid bacteria, and lactic acid bacteria, either as single strains or as a designed microbial consortium. The latter included Saccharomycodes ludwigii, Gluconobacter oxydans, and Levilactobacillus brevis, mimicking a symbiotic culture of bacteria and yeast commonly used in kombucha fermentation (SCOBY). This symbiotic microbial culture consortium demonstrated notable efficacy, significantly enhancing the total phenolic content in RCSS, with values reaching 14.15 mg GAE/g as determined by the Folin–Ciocalteu assay and 7.12 mg GAE/g according to the Fast Blue BB method. Antioxidant capacity improved by approximately 28% (ABTS) and 20% (DPPH). Moreover, the fermented RCSS supported the viability of probiotic strains (Saccharomyces boulardii SB01 and Levilactobacillus brevis ŁOCK 1152) under simulated intestinal conditions. These results suggest that RCSS, particularly after fermentation with a full symbiotic microbial culture consortium, has strong potential as a clean label, zero-waste functional food ingredient. Full article

Strawberry planting requires different amounts of soil water-holding capacity and fertilizer at different growth stages. Determining the stages of strawberry growth has important guiding significance for irrigation, fertilization, and picking. Quick and accurate identification of strawberry plants at different stages can provide important information for automated strawberry planting management. We propose an improved multistage identification model for strawberry based on the YOLOv9 algorithm—the ASHM-YOLOv9 model. The original YOLOv9 showed limitations in detecting strawberries at different growth stages, particularly lower precision in identifying occluded fruits and immature stages. We enhanced the YOLOv9 model by introducing the Alterable Kernel Convolution (AKConv) to improve the recognition efficiency while ensuring precision. The squeeze-and-excitation (SE) network was added to increase the network’s capacity for characteristic derivation and its ability to fuse features. Haar wavelet downsampling (HWD) was applied to optimize the Adaptive Downsampling module (Adown) of the initial model, thereby increasing the precision of object detection. Finally, the CIoU function was replaced by the Minimum Point Distance based IoU (MPDIoU) loss function to effectively solve the problem of low precision in identifying bounding boxes. The experimental results demonstrate that, under identical conditions, the improved model achieves a precision of 97.7%, a recall of 97.2%, mAP50 of 99.1%, and mAP50-95 of 90.7%, which are 0.6%, 3.0%, 0.7%, and 7.4% greater than those of the original model, respectively. The parameters, model size, and floating-point calculations were reduced by 3.7%, 5.6% and 3.8%, respectively, which significantly boosted the performance of the original model and outperformed that of the other models. Experiments revealed that the model could provide technical support for the multistage identification of strawberry planting. Full article

Retrieval-Augmented Generation (RAG) systems have emerged as a critical approach for enhancing large language models with external knowledge, yet the field lacks systematic theoretical analysis for understanding their fundamental characteristics and optimization principles. A novel information-theoretic approach for analyzing and optimizing RAG systems is introduced in this paper by modeling them as cascading information channel systems where each component (query encoding, retrieval, context integration, and generation) functions as a distinct information-theoretic channel with measurable capacity. Following established practices in information theory research, theoretical insights are evaluated through systematic experimentation on controlled synthetic datasets that enable precise manipulation of schema entropy and isolation of information flow dynamics. Through this controlled experimental approach, the following key theoretical insights are supported: (1) RAG performance is bounded by the minimum capacity across constituent channels, (2) the retrieval channel represents the primary information bottleneck, (3) errors propagate through channel-dependent mechanisms with specific interaction patterns, and (4) retrieval capacity is fundamentally limited by the minimum of embedding dimension and schema entropy. Both quantitative metrics for evaluating RAG systems and practical design principles for optimization are provided by the proposed approach. Retrieval improvements yield 58–85% performance gains and generation improvements yield 58–110% gains, substantially higher than context integration improvements (∼9%) and query encoding modifications, as shown by experimental results on controlled synthetic environments, supporting the theoretical approach. A systematic theoretical analysis for understanding RAG system dynamics is provided by this work, with real-world validation and practical implementation refinements representing natural next phases for this research. Full article

Partial Least Squares (PLS) regression has been widely used to model the relationship between predictors and responses. However, PLS may be limited in its capacity to handle complex spectral data contaminated with significant noise and interferences. In this paper, we propose a novel filter learning-based PLS (FPLS) model that integrates an adaptive filter into the PLS framework. The FPLS model is designed to maximize the covariance between the filtered spectral data and the response. This modification enables FPLS to dynamically adapt to the characteristics of the data, thereby enhancing its feature extraction and noise suppression capabilities. We have developed an efficient algorithm to solve the FPLS optimization problem and provided theoretical analyses regarding the convergence of the model, the prediction variance, and the relationships among the objective functions of FPLS, PLS, and the filter length. Furthermore, we have derived bounds for the Root Mean Squared Error of Prediction (RMSEP) and the Cosine Similarity (CS) to evaluate model performance. Experimental results using spectral datasets from Corn, Octane, Mango, and Soil Nitrogen show that the FPLS model outperforms PLS, OSCPLS, VCPLS, PoPLS, LoPLS, DOSC, OPLS, MSC, SNV, SGFilter, and Lasso in terms of prediction accuracy. The theoretical analyses align with the experimental results, emphasizing the effectiveness and robustness of the FPLS model in managing complex spectral data. Full article

Diabetic cardiomyopathy (DCM) in type 2 diabetes (T2D) may lead to heart failure and patient death. Fibroblast growth factor 21 (FGF21) is a therapeutic candidate for treating this disease. However, one impediment to its clinical use is its weak ability to activate downstream signaling pathways. In this study, based on our in-depth understanding of the binding properties of fibroblast growth factor receptor 1c (FGFR1c) with paracrine FGF1 and endocrine FGF21, we engineered a novel FGF21 analog named FGF21^D2D3. This was achieved by substituting the R96–V106 region of FGF21 (the binding site with the D2–D3 domain of FGFR1c) with the corresponding region from FGF1. Structural characterization and binding affinity tests showed that the analog’s capacity to bind FGFR1c was significantly enhanced compared to wild-type FGF21 (FGF21^WT). In a T2D mouse model, we found that FGF21^D2D3 had greater potency than FGF21^WT in improving hyperlipidemia and DCM. Furthermore, mechanistic studies revealed that FGF21^D2D3 more effectively bound FGFR1, activated AMPK, inhibited oxidative stress, and ameliorated DCM. Therefore, our data indicate that FGF21^D2D3 is a better substitute for FGF21^WT in treating DCM by improving dyslipidemia and directly suppressing oxidative stress via FGFR1–AMPK activation in T2D. Full article

This study presents a robust numerical framework for evaluating the upper-bound ultimate bearing capacity of shallow foundations in cohesive and C-phi soils using a self-developed finite element method. The model incorporates multi-segment zero-thickness interface elements to accurately simulate soil discontinuities and progressive failure mechanisms, based on the Mohr–Coulomb failure criterion. In contrast to optimization-based methods such as discontinuity layout optimization (DLO) or traditional finite element limit analysis (FELA), the proposed approach uses predefined failure mechanisms to improve computational transparency and efficiency. A variety of geometric failure mechanisms are analyzed, including configurations with triangular, circular, and logarithmic spiral slip surfaces. Particular focus is given to the transition zone, which is discretized into multiple blocks to enhance accuracy and convergence. The method is developed for two-dimensional problems under the assumption of elastic deformable-plastic behavior and homogeneous isotropic soil, with limitations in automatically detecting failure mechanisms. The proposed approach is validated against classical theoretical solutions, demonstrating excellent agreement. For friction angles ranging from 0° to 40°, the computed bearing capacity factors N_c and N_q show minimal deviation from the analytical results, with errors as low as 0.04–0.19% and 0.12–2.43%, respectively. The findings confirm the method’s effectiveness in capturing complex failure behavior, providing a practical and accurate tool for geotechnical stability assessment and foundation design. Full article

Plasma non-transferrin-bound iron (NTBI) comprises multiple subspecies, classified by their composition, chemical reactivity, and susceptibility to chelation. The redox-active and chelatable fraction of NTBI is referred to as labile plasma iron (LPI). The pathophysiological significance of NTBI and LPI lies in their ability to enter cells via alternative transport pathways that are not regulated by the transferrin receptor system or by cellular iron levels. Several mechanisms have been proposed for their cellular entry, including the hijacking of divalent metal transporters and passive diffusion. This unregulated uptake can lead to iron accumulation in vulnerable tissues such as the liver and the heart. NTBI and LPI bypassing normal cellular control mechanisms can rapidly exceed the cell’s capacity to safely store excess iron, leading to toxicity. Both NTBI and LPI contribute to oxidative stress by participating in free-radical-generating reactions. However, LPI concentration in the bloodstream may be differentially affected by the mode and extent of iron overload, the presence of residual serum iron-binding activity, and the antioxidant capacity of individual sera. In summary, both NTBI and LPI contribute to iron-mediated toxicity but differ in terms of reactivity, availability, and pathogenic potential depending on the pathophysiological conditions that influence the degree of toxicity. Full article

In this paper, a very fast and reliable strategy for load restoration utilizing optimal distribution feeder reconfiguration (DFR) is developed. The automated network configuration switches can improve the resilience of a microgrid (MG) equipped with a centralized and coordinated energy management system (EMS). The EMS has the authority to reconfigure the distribution network to fulfil high priority loads in the entire network, at the lowest cost, while maintaining the voltage at desirable bounds. In the case of islanded operation, the EMS is responsible for serving the high priority loads, including the establishment of new MGs, if necessary. This paper discusses the main functionality of the EMS in both grid-connected and islanded operation modes of MGs. The proposed model is developed based on a mixed-integer quadratically constrained program (MIQCP), including an optimal power flow (OPF) problem to minimize the power losses in normal operation and the load shedding in islanded operation, while keeping voltage and capacity constraints. The proposed framework is implemented on a modified IEEE 33-bus test system and the results show that the model is fast and accurate enough to be utilized in real-life situations without a loss of accuracy. Full article

This paper presents an analytical study of the bit error rate (BER) and signal-to-noise ratio (SNR) performance in simultaneous wireless information and power transfer (SWIPT) amplify-and-forward (AF) relaying systems over Rayleigh fading channels. A power-splitting (PS) protocol is employed at the energy-constrained relay to divide the received signal for concurrent energy harvesting and information processing. Closed-form and asymptotic BER expressions are derived based on exact and bounded moment-generating functions (MGFs), offering insights into how the SNR balance between the source–relay (SR) and relay–destination (RD) links influences system performance. An asymptotic BER expression further reveals that a SWIPT AF relay system can be interpreted as a generalized AF relaying model, sharing the same diversity order as conventional AF systems. Based on this interpretation, an optimization method for the PS factor is proposed, effectively reducing the BER by reinforcing the weaker link. Simulation results confirm the tightness of the derived expressions and the effectiveness of the optimization strategy. Moreover, the analytical framework is extended to multiple SWIPT relaying systems, where multiple relays operate with individually optimized PS ratios. For such configurations, approximations for the system BER, outage probability, and channel capacity are derived and validated. Results demonstrate that increasing the number of relays significantly improves system performance, and the proposed analysis accurately captures these performance gains under varying channel conditions. Full article

Effective monitoring and evaluation (M&E) are essential for ensuring that Maritime Spatial Planning (MSP) contributes to the sustainable development of the blue economy while maintaining alignment with institutional frameworks. The study presented in this paper develops a stakeholder-driven M&E framework for sustainable MSP, emphasizing a participatory methodology to enhance the relevance and applicability of performance assessment. Using a structured mutual learning approach, the research engaged stakeholders in two iterative rounds: the first identified key strategic objectives for a sustainable blue economy through dialogue and a complementary questionnaire survey, while the second refined these into corresponding specific objectives. This process was applied in the context of a case study in Greece, where MSP implementation is shaped by national and EU regulatory frameworks and the socio-economic dynamics of the coastal and maritime sectors. The case study provided a practical testing ground for the proposed methodology, involving stakeholders from government, industry, and civil society to ensure a comprehensive perspective. The insights gained informed the design of a key performance indicator (KPI) framework, integrating qualitative and quantitative metrics tailored to the regional maritime governance landscape. These metrics were selected based on the SMARTIE (Specific, Measurable, Achievable, Relevant, Time-Bound, Inclusive, Equitable) criteria and were clearly aligned with the established objectives. The frequency of measurements, appropriate data collection methods, and indicative data sources were also defined to provide a complete KPIs framework. This stakeholder-driven methodology strengthens the adaptive capacity of MSP by ensuring continuous assessment and revision aligned with sustainability objectives and facilitating ex ante, intermediate, and ex post evaluations. The proposed framework is scalable and transferable, offering a systematic approach to improving policy coherence and decision-making across different geographic, administrative, and sectoral contexts, enabling sustainable governance and maritime governance. Full article

The processing of peaches generates large quantities of by-products, including peels, pomace, and seeds. Despite containing high levels of bioactive compounds with antioxidant properties, these by-products are often discarded as waste, thereby contributing to increased food waste. The present paper aimed to evaluate the total bioactive compound content in peach pomace and biscuits fortified with various concentrations of peach pomace (5%, 10%, and 15%), with a view to utilizing this valuable by-product in functional foods. Compositional analysis revealed that peach pomace is a significant source of polyphenols (1771.64 mg GAE 100 g⁻¹), flavonoids (478.99 mg RE 100 g⁻¹), and anthocyanins (21.18 mg C3GE 100 g⁻¹), and has a radical scavenging capacity of 40.41%. The FTIR analysis confirmed the presence of multiple functional groups in peach pomace that can be associated with polyphenols, polysaccharides, organic acids, esters, monosaccharides, and structurally bound water. Among the individual phenolic compounds, high concentrations of rutin (8.12 mg 100 g⁻¹), chlorogenic acid (3.77 mg 100 g⁻¹), and sinapic acid (2.70 mg 100 g⁻¹) were recorded. Following the replacement of wheat flour with peach pomace, increases in the content of bioactive compounds were observed. At the maximum level of 15% pomace, the biscuits presented the highest concentrations of polyphenols (444.04 mg GAE 100 g⁻¹), flavonoids (211.11 mg RE 100 g⁻¹), anthocyanins (25.43 mg C3GE 100 g⁻¹), sugars (46.48 g GluE 100 g⁻¹), and radical scavenging activity (27.21%). Similar bands were found in the FTIR spectra of the biscuits, indicating the presence of phenolic compounds and glycosides. The 1366 cm⁻¹ band, which is associated with C–O stretching and C–H and N–H deformation in peach pomace, appeared in the enriched biscuit samples at 1340–1374 cm⁻¹ but not in the control sample. These results suggest that peach pomace represents an ingredient with significant potential for use in the food industry, having the ability to improve the nutritional value of biscuits. Full article

High oil content in breaded fried small yellow croaker (BFYC) was reduced using composite batter gels consisting of tapioca starch, wheat flour, and different concentrations of cassia gum (CG; 0%, 0.2%, 0.4%, 0.6%, 0.8%, 1%). The effects of CG on the oil absorption capacity of BFYC and potential mechanisms were investigated. Dynamic rheological analysis revealed that CG addition could enhance the viscoelasticity of the batter by increasing its storage modulus and loss modulus. Furthermore, FTIR and X-ray diffraction results demonstrated that CG interacts with starch through noncovalent interactions, increasing the relative crystallinity from 9.29% to 16.49%, which promoted the formation of a gel layer. This structural improvement effectively inhibited oil absorption. Differential scanning calorimetry analysis showed that within the 0–0.8% CG range, the batter’s denaturation temperature increased from 78.23 °C to 82.08 °C with higher CG concentrations, indicating prolonged gelatinization and enhanced thermal stability that further reduced oil penetration. Low-field nuclear magnetic resonance analysis revealed that CG increased the proportion of tightly bound and weakly bound water in the batter, thereby improving water retention capacity and reducing moisture loss during frying. Microscopic structural observations and Sudan Red-staining tests confirmed that at 0.8% CG concentration, the crust exhibited the lowest porosity with approximately 40% reduction in surface fat content compared to the control group. In conclusion, CG addition significantly improves batter properties and reduces oil content in fried products, providing theoretical support for the development of low-fat fried foods. Full article