
A connected nontrivial graph G is matching covered if every edge of G is contained in some perfect matching of G. A matching covered graph G is minimal if G−e is not matching covered for each edge e of G. A graph is said to be factor-critical if G−v has a perfect matching for every v∈V(G). A factor-critical graph G is said to be minimal factor-critical if G−e is not factor-critical for each edge e∈E(G). In this paper, by employing ear decomposition and edge-exchange techniques, the greatest spectral radii of minimal matching covered bipartite graphs and minimal factor-critical graphs are determined, and the corresponding extremal graphs are characterized.
As the cradle of Chinese civilization, Henan's settlement spatial distribution is of great significance for understanding human-land relations and for cultural heritage protection. This study proposes a novel grid-based prediction approach that integrates multi-source geographic features with machine learning. A 1 km-resolution spatial grid system is constructed to incorporate topographic, hydrological, and spatial association features, forming a three-layer predictive modeling architecture. A spatially aware dual-branch model fuses topographic features with spatial variables such as coordinates and settlement density; a grid-based ensemble model, built on features aggregated at the geographic grid level, combines XGBoost with a dynamic weight optimization algorithm. We systematically incorporate the Topographic Wetness Index (TWI) and hydrological accessibility indicators into the multi-scale framework, employ Focal Loss to address extreme class imbalance, enhance recall via dynamic threshold optimization, and further integrate spatial lag features in conjunction with the initial model for prediction. Experiments show that, in Henan, the proposed method achieves significantly higher predictive accuracy than traditional models. Spatial heatmaps reveal that high-probability settlement zones are concentrated on the loess tablelands and the alluvial plains along the Yellow River, closely matching archaeological findings. The results provide a quantitative spatial decision-making tool for settlement archaeological surveys in the Central Plains.
As an attractive on-demand hydrogen release strategy, ammonia borane (AB, NH3BH3) catalytic hydrolysis still lacks the necessary practicality at present because of the unresolved issues, including the easily prepared, highperformance, and cost-effective catalysts, as well as the according catalytic mechanism. Herein, a novel chitosanbased carbon aerogel (CCA)-encapsulated RuPd bimetallic nanocatalyst is developed through a facile freezedrying and one-step calcination procedure in the absence of any chemical activators and any post-treatment. The abundant N/O-containing functional groups in CS coordinate with the precious metal ions (Ru3+ and Pd2+), thereby facilitating the uniform and tight encapsulation of the resulting metal ultrafine particles. Also, these functional groups favor the introduction of self-doped heteroatoms, further improving the metal dispersion and enhancing the hydrophilicity of the catalysts. Moreover, the ice-crystal templating effect of the aqueous acetic acid solution as well as the chemical activation role of the noble metal chlorides endow the as-prepared catalysts with a hierarchically porous framework, providing adequate surface active sites and favoring mass transfer. In addition, the favorable electronic synergistic effect of the RuPd nanoalloys further promotes AB hydrolysis. Consequently, the optimized bimetallic catalyst (denoted as Ru0.85Pd0.15@CCA) exhibits significantly enhanced catalytic performance compared to the monometallic counterparts. Catalyzed by Ru0.85Pd0.15@CCA, turnover frequency (TOF) and hydrogen generation rate (HGR) are 209.1 min- 1 and 46.0 & times; 103 mL min- 1 g- 1, respectively. Notably, the according apparent activation energy is merely 20.7 kJ mol-1, which is superior to most reported heterogeneous catalysts. Benefiting from the promotion for breaking an O-H bond in a water molecule, adding a certain amount of NaOH (1.5 M) further markedly accelerates hydrogen release (TOF = 546.5 min- 1, HGR = 121.1 & times; 103 mL min- 1 g-1) in the presence of Ru0.85Pd0.15@CCA. This study not only provides a facile and promising strategy for constructing porous carbon-encapsulated metal nanoalloys, but also offers an effective catalyst for boosting AB hydrolysis.
Artificial levees have long played a pivotal role in flood control and river regulation, contributing significantly to the development of perched rivers. However, the coupled effects of varying water-sediment conditions and levee spacing on perched-river evolution remain insufficiently understood. Physical model experiments indicate that water-sediment conditions, compared to levee spacing, are the dominant driver (contributing >74%) of perched river development and transformation, while artificial levees further accelerate this process at least 4 times. The overbank coefficient, defined as the ratio of peak discharge to bankfull discharge, governs the equilibrium state of the interaction between varying water-sediment conditions and levee spacing. A critical indicator (VD2/Q) is proposed to characterize shifts in this coupling effect, and a multiple regression equation (R2 = 0.86) is developed relating the indicator to a set of characteristic coefficients. Convergent cross mapping is used to quantify the causal relationships among the key parameters. The results indicate that the coupling effect of varying water-sediment conditions and levee spacing follows a mechanism: artificial levees compress the space for overbank sedimentation, modify hydraulic conditions in the floodplain and channel, reshaping the spatial pattern of sediment deposition. These changes alter boundary conditions, including floodplain topography and channel morphology, which in turn affect sediment transport capacity and the flow-partitioning ratio between the main channel and the floodplain. The adjusted flow-sediment dynamics then feed back into channel evolution, ultimately driving the development of the perched river. These findings enhance understanding of perched-river formation and evolution and provide a scientific basis for sustainable river management.