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The spatial distribution pattern of rural settlements in the Yellow River Basin is scattered and numerous. It is of great significance to study the discrete distribution of rural settlements for achieving high-quality development and promoting rural revitalization strategy. In this paper, we propose an enhanced evaluation model for assessing the spatial distribution dispersion of rural settlements, incorporating the weight of road grade (the road grade refers to the ranking of traffic capacity and importance of a particular type of road, indicating varying levels of time accessibility). We investigate the dispersion characteristics of rural settlements in the Yellow River Basin in 2020, focusing on both county and city scales. Furthermore, we conduct a comprehensive analysis of the spatial differentiation and scale effects of dispersion evaluation outcomes and their driving forces. Our findings reveal the following insights: (1) The road grade significantly influences the dispersion evaluation. When considering road grade in the dispersion calculation, the results align more closely with the actual situation. (2) The dispersion of rural settlements in the Yellow River Basin exhibits a decreasing trend from west to east. Specifically, the dispersion is higher in the upper reaches compared to the middle and lower reaches. Both city and county scales show spatial autocorrelation in dispersion, with a positive spatial correlation observed. High dispersion values cluster in the west, while low values concentrate in the east. Notably, the agglomeration degree is more pronounced at the county scale than at the city scale, highlighting more localized patterns of agglomeration and dispersion. (3) The multiscale geographically weighted regression model emerges as the optimal model for analyzing the driving forces of dispersion. At the city scale, factors such as river density, road density, and rural economy negatively impact dispersion. However, at the county scale, average elevation and rural economy positively affect dispersion, whereas river density, road density, and rural population density have a negative influence. By incorporating the weight of road grade into our evaluation model, we provide a more nuanced understanding of the spatial distribution dispersion of rural settlements in the Yellow River Basin. Our findings offer valuable insights for policymakers and planners seeking to optimize rural settlement patterns and promote sustainable rural development. [ABSTRACT FROM AUTHOR]

Abstract Background Interest in lycopene metabolism and regulation is growing rapidly because accumulative studies have suggested an important role for lycopene in human health promotion. However, little is known about the molecular processes regulating lycopene accumulation in fruits other than tomato so far. Results On a spontaneous sweet orange bud mutant with abnormal lycopene accumulation in fruits and its wild type, comparative transcripts profiling was performed using Massively Parallel Signature Sequencing (MPSS). A total of 6,877,027 and 6,275,309 reliable signatures were obtained for the wild type (WT) and the mutant (MT), respectively. Interpretation of the MPSS signatures revealed that the total number of transcribed gene in MT is 18,106, larger than that in WT 17,670, suggesting that newly initiated transcription occurs in the MT. Further comparison of the transcripts abundance between MT and WT revealed that 3,738 genes show more than two fold expression difference, and 582 genes are up- or down-regulated at 0.05% significance level by more than three fold difference. Functional assignments of the differentially expressed genes indicated that 26 reliable metabolic pathways are altered in the mutant; the most noticeable ones are carotenoid biosynthesis, photosynthesis, and citrate cycle. These data suggest that enhanced photosynthesis and partial impairment of lycopene downstream flux are critical for the formation of lycopene accumulation trait in the mutant. Conclusion This study provided a global picture of the gene expression changes in a sweet orange red-flesh mutant as compared to the wild type. Interpretation of the differentially expressed genes revealed new insight into the molecular processes regulating lycopene accumulation in the sweet orange red-flesh mutant.

Matching multi-scale road networks in the same area is the first step in merging two road networks or updating one based upon the other. The quality of the merge or update depends greatly on the matching accuracy of the two road networks. We propose an improved probabilistic relaxation method, considering both local and global optimizations for matching multi-scale of road networks. The aim is to achieve local optimization, as well as to address the identification of the M:N matching pattern by means of inserting virtual nodes to achieve global optimization effects. Then, by adding two attribute-related evaluation indicators, we developed four evaluation indicators to evaluate the matching accuracy, considering both geographic and attribute information. This paper also provides instructions on how to identify the proper buffer threshold during matching procedures. Extensive experiments were conducted to compare the proposed method with the traditional approach. The results indicate that: (1) the overall matching accuracy of each evaluation indicator exceeds 90%; (2) the overall matching accuracy increases by 6-12% after an M:N matching pattern is added, and by 4-6% following the addition of topology indicators; and (3) the proper buffer threshold is about twice the average value of the closest distance from all nodes. [ABSTRACT FROM AUTHOR]

The original state-dependent fractional stress-dilatancy (FSD) equation for soils is developed based on the critical state lines (CSLs) with linear form. However, experimental evidences showed that the CSLs of soil in the $p^{\prime}$–$q$ and $e$–$p^{\prime}$ planes could be both nonlinear as well due to significant material degradation. This note aims to propose a unified FSD equation for soils with arbitrary types of CSLs. Detailed derivations are provided. To validate the proposed FSD equation, a series of triaxial test results of ballast and rockfill are simulated.

As a novel optimization technique, chaos has gained much attention and some applications during the past decade. For a given energy or cost function, by following chaotic ergodic orbits, a chaotic dynamic system may eventually reach the global optimum or its good approximation with high probability. To enhance the performance of the local search method (LS), which is based on the generalized reduced gradient algorithm, hybrid local search method is proposed by incorporating chaos. Thus, LS and chaos are hybridized to form a chaotic dynamic local search method (CDLS), which reasonably combines the searching ability of LS and chaotic searching behavior. In this paper, a CDLS method based on the logistic equation is presented to learn Multiple-Valued Logic (MVL) Networks. Simulation results and comparisons with the traditional back propagation algorithm (BP) and the standard LS method show that the CDLS can effectively enhance the searching efficiency and greatly improve the searching quality within reasonable number of iterations. [ABSTRACT FROM AUTHOR]