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Conclusion In this study, we have proposed a new adaptive sliding mode control-based time-varying region tracking controller for multi-robot systems with both uncertain dynamics and unknown input disturbances. A new region tracking potential function is introduced to obtain reduced control input magnitude. Future work includes considering collision avoidance with respect to obstacles in the environment and other control methods handling input saturation.

The spatiotemporal distribution characteristics of cultural heritage reveal the trajectory of human activity changes, and a deep analysis of its natural and cultural factors holds significant reference value for the overall conservation and management of cultural heritages. This study focuses on the cultural heritage at the provincial level and above in Fujian, utilizing GIS spatial analysis to explore the spatiotemporal evolution of cultural heritages and their natural and human influencing factors. The research findings are as follows: (1) The distribution of cultural heritage in Fujian exhibits a clustering pattern, with dense areas transitioning from the upstream regions of the prehistoric and pre-Qin periods to the eastern coastal areas gradually. (2) The Ming and Qing dynasties have the highest number of cultural heritages, with the type of heritage transitioning from ancient sites in the early periods to ancient architecture, and in modern times, mainly important historical sites and representative architectural heritages. (3) The overall centroid coordinates of cultural heritage reveal a shift from the northern part of Fujian to the eastern and southern parts. (4) Natural factors significantly influence the distribution of cultural heritage, with a higher concentration in plain and hilly areas, on slight slopes with gradients between 0.5° and 2.0°, and on the southern and southeastern slopes, especially within a 1-kilometer radius of rivers. (5) The creation of cultural heritage during historical periods is closely linked to the regional history, culture, political, and economic environments. The positive development of these socio-cultural factors has a promotional effect on the quantity of cultural heritage. This study demonstrates the utility and applicability of GIS spatial analysis techniques in cultural heritage research, providing a methodological framework that can be adapted and applied internationally. The findings offer insightful data that can inform targeted conservation and development strategies for cultural heritage, ensuring their effective preservation and sustainable management across different regions.

In multi-resolution remote sensing imagery, roads typically exhibit sparse, elongated, and structurally complex morphological characteristics, posing formidable connectivity modeling challenges for semantic segmentation models. Existing approaches predominantly focus on pixel-level accuracy, often neglecting the topological integrity of road networks, which leads to frequent discontinuities and omissions in predicted results. To address this, this paper proposes an end-to-end road extraction framework equipped with multi-receptive field modeling and structural connectivity preservation capabilities. The model incorporates a multi-receptive-field module to capture road patterns across varying spatial scales, a connectivity-aware decoding mechanism to strengthen structural coherence, and a topology-aware loss that explicitly guides the restoration of continuous road networks during training. On the DeepGlobe-Road dataset, TopoRF-Net achieves OA 98.57%, IoU 69.76%, F1-score 82.18%, Precision 85.50%, and Recall 79.12%; on the Massachusetts dataset, TopoRF-Net similarly achieved outstanding results: OA 96.65%, IoU 59.68%, F1-score 74.75%, Precision 77.98%, and Recall 71.77%. These results conclusively demonstrate that the proposed method significantly outperforms existing approaches in both precision and connectivity metrics, whilst exhibiting favorable parameter efficiency and inference performance.

The development of many modern critical infrastructures calls for the integration of advanced technologies and algorithms to enhance the performance, efficiency, and reliability of network systems [...]

Ground-object classification using remote-sensing images of high resolution is widely used in land planning, ecological monitoring, and resource protection. Traditional image segmentation technology has poor effect on complex scenes in high-resolution remote-sensing images. In the field of deep learning, some deep neural networks are being applied to high-resolution remote-sensing image segmentation. The DeeplabV3+ network is a deep neural network based on encoder-decoder architecture, which is commonly used to segment images with high precision. However, the segmentation accuracy of high-resolution remote-sensing images is poor, the number of network parameters is large, and the cost of training network is high. Therefore, this paper improves the DeeplabV3+ network. Firstly, MobileNetV2 network was used as the backbone feature-extraction network, and an attention-mechanism module was added after the feature-extraction module and the ASPP module to introduce focal loss balance. Our design has the following advantages: it enhances the ability of network to extract image features; it reduces network training costs; and it achieves better semantic segmentation accuracy. Experiments on high-resolution remote-sensing image datasets show that the mIou of the proposed method on WHDLD datasets is 64.76%, 4.24% higher than traditional DeeplabV3+ network mIou, and the mIou on CCF BDCI datasets is 64.58%. This is 5.35% higher than traditional DeeplabV3+ network mIou and outperforms traditional DeeplabV3+, U-NET, PSP-NET and MACU-net networks.

Maize oil is an important food and energy source. Now, Jianbing Yan and colleagues report a genome-wide association study in maize for maize kernel oil composition. They analyzed 368 maize lines with 1.06 million SNPs genome-wide and found 74 loci associated with maize kernel oil concentration and fatty acid composition. Maize kernel oil is a valuable source of nutrition. Here we extensively examine the genetic architecture of maize oil biosynthesis in a genome-wide association study using 1.03 million SNPs characterized in 368 maize inbred lines, including 'high-oil' lines. We identified 74 loci significantly associated with kernel oil concentration and fatty acid composition ( P < 1.8 × 10 −6 ), which we subsequently examined using expression quantitative trait loci (QTL) mapping, linkage mapping and coexpression analysis. More than half of the identified loci localized in mapped QTL intervals, and one-third of the candidate genes were annotated as enzymes in the oil metabolic pathway. The 26 loci associated with oil concentration could explain up to 83% of the phenotypic variation using a simple additive model. Our results provide insights into the genetic basis of oil biosynthesis in maize kernels and may facilitate marker-based breeding for oil quantity and quality.

Understanding the genetic and molecular basis of grain yield is important for maize improvement. Here, we identified 49 consensus quantitative trait loci (cQTL) controlling maize yield-related traits using QTL meta-analysis. Then, we collected yield-related traits associated SNPs detected by association mapping and identified 17 consensus significant loci. Comparing the physical positions of cQTL with those of significant SNPs revealed that 47 significant SNPs were located within 20 cQTL regions. Furthermore, intensive reviews of 31 genes regulating maize yield-related traits found that the functions of many genes were conservative in maize and other plant species. The functional conservation indicated that some of the 575 maize genes (orthologous to 247 genes controlling yield or seed traits in other plant species) might be functionally related to maize yield-related traits, especially the 49 maize orthologous genes in cQTL regions, and 41 orthologous genes close to the physical positions of significant SNPs. In the end, we prospected on the integration of the public sources for exploring the genetic and molecular mechanisms of maize yield-related traits, and on the utilization of genetic and molecular mechanisms for maize improvement.

Early warning on the ship deficiency is crucial for enhancing maritime safety, improving maritime traffic efficiency, reducing ship fuel consumption, etc. Previous studies focused on the ship deficiency exploration by mining the relationships between the ship physical deficiencies and the port state control (PSC) inspection results with statistical models. Less attention was paid to discovering the correlation rules among various parent ship deficiencies and subcategories. To address the issue, we proposed an improved Apriori model to explore the intrinsic mutual correlations among the ship deficiencies from the PSC inspection dataset. Four typical ship property indicators (i.e., ship type, age, deadweight and gross tonnage) were introduced to analyze the correlations for the ship parent deficiency categories and subcategories. The findings of our research can provide basic guidelines for PSC inspections to improve the ship inspection efficiency and maritime safety.

Global warming leads to frequent extreme weather, especially the extreme heat events, which threating the safety of maize production. Here we selected a pair of maize inbred lines, PF5411-1 and LH150, with significant differences in heat tolerance at kernel development stage. The two maize inbred lines were treated with heat stress at kernel development stage. Compared with the control groups, transcriptomic analysis identified 770 common up- and down-regulated genes between PF5411-1 and LH150 under heat stress conditions, and 41 putative TFs were predicted. Based on the interaction term of the two-factorial design, we also identified 6,744 differentially regulated genes between LH150 and PF5411-1, 111 common up-regulated and 141 common down-regulated genes were overlapped with the differentially regulated genes, respectively. Combined with proteins and metabolites data, several key pathways including seven differentially regulated genes were highly correlated with the heat tolerance of maize kernels. The first is the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway ko04141: protein processing in endoplasmic reticulum, four small heat shock protein (sHSP) genes were enriched in this pathway, participating with the process of ER-associated degradation (ERAD). The second one is the myricetin biosynthesis pathway, a differentially regulated protein, flavonoid 3’,5’-hydroxylase [EC:1.14.14.81], catalyzed the synthesis of myricetin. The third one is the raffinose metabolic pathway, one differentially regulated gene encoded the raffinose synthase controlled the synthesis of raffinose, high level of raffinose enhances the heat tolerance of maize kernels. And the last one is the ethylene signaling pathway. Taken together, our work identifies many genes responded to heat stress in maize kernels, and finds out seven genes and four pathways highly correlated with heat tolerance of maize kernels.

Eight Views is a time-honored East Asian cultural-landscape paradigm in which eight emblematic natural—cultural scenes fuse regional character, historical memory, and aesthetic ideals into a coherent narrative. It encodes the collective memory and identity of a city (or garden/region), a premodern ‘mental map’ or proto- ‘city brand’. In China, the historic Urban Eight Views are rooted in local environments and traditions and constitute significant, high-value landscape heritage today. Yet rapid urbanization has inflicted severe physical damage on these ensembles. Coupled with insufficient holistic and systemic understanding among managers and the public, this has led, during development and conservation alike, to spatial insularization, fragmentation, and even disappearance, alongside widening divergences in cultural cognition and biases in value judgment. Taking Longmen Haoyue in Chongqing, one of the historic Urban Eight Views, as a case that manifests these issues, this study develops a holistic–relational approach for the urban, historical Eight Views and explores landscape-based pathways to protect the spatial structure and cultural connotations of the heritage that has been severely damaged and is in a state of disappearance or semi-disappearance amid modernization. Methodologically, we employ decomposition analysis to extract the historical information elements of Longmen Haoyue and its internal relational structure and corroborate its persistence through field surveys. We then apply the FAHP method to grade the conservation value and importance of elements within the Eight Views, quantitatively clarifying protection hierarchies and priorities. In parallel, a multidimensional corpus is constructed to analyze online dissemination and public perception, revealing multiple challenges in the evolution and reconstruction of Longmen Haoyue, including symbolic misreading and cultural decontextualization. In response, we propose an integrated strategy comprising graded element protection and intervention, reconstruction of relational structures, and the building of a coherent cultural-semantic and symbol system. This study provides a systematic theoretical basis and methodological support for the conservation of the urban historic Eight Views cultural landscapes, the place-making of distinctive spatial character, and the enhancement of cultural meanings. It develops an integrated research framework, element extraction, value assessment, perception analysis, and strategic response that is applicable not only to the Eight Views heritage in China but is also transferable to World Heritage properties with similar attributes worldwide, especially composite cultural landscapes composed of multiple natural and cultural elements, sustained by narrative traditions of place identity, and facing risks of symbolic weakening, decontextualization, or public misperception.