Search Results (548)

This study investigates the genomic basis of immune adaptation in the transparent glass catfish (Kv: Kryptopterus vitreolus), focusing on the loss of the Toll-like receptor 21 (TLR21) gene. Comparative genomic analysis with closely related non-transparent North African catfish (Cg: Clarias gariepinus) revealed 11 TLR genes in the latter, while only 8 TLR genes (KvTLR1, 2, 3, 5, 7, 9, 13, and 20) were retained in the glass catfish, with TLR21 specifically absent. Collinearity analysis confirmed that the genomic region containing TLR21 is conserved across eight siluriform species, with loss exclusively in the glass catfish, supporting its lineage-specific absence. Structural expansion was notable in KvTLR5, KvTLR7, and KvTLR20. Molecular docking indicated that binding stability between CpG oligonucleotides and TLR21 varies significantly, with CpG-B 1681 showing the strongest interaction, which highlights sequence-dependent ligand recognition. Interestingly, absence of the TLR1 gene in another transparent teleost, the X-ray tetra (Pristella maxillaris), suggests that transparent fishes may share an evolutionary trend of lineage-specific TLR gene loss. Together, these findings reveal a distinctive evolutionary trajectory in the innate immune receptor family of transparent fishes and provide new molecular insights into their adaptive immune strategies. These insights will benefit the academic community by improving comparative frameworks for fish innate immunity, and they may inform disease prevention and health management strategies in aquaculture and the ornamental fish trade. Full article

Expressway networks represent evolving complex systems whose topological properties significantly impact regional development. This paper presents a decision support framework for addressing the expressway infrastructure sequencing problem using computational intelligence. We develop a novel framework that models expressways as L-space networks and evaluates how construction sequences create path-dependent evolutionary trajectories, introducing network science principles into infrastructure planning decisions. Our decision support framework quantifies project impacts on accessibility, connectivity, and reliability using nine topological metrics and a hybrid weighting mechanism that combines domain expertise with entropy-based uncertainty quantification. The system employs a hybrid TOPSIS algorithm that relies on geometric symmetry to simulate network evolution, capturing emergent properties in which each decision restructures possibilities for subsequent choices—a computational challenge that conventional planning approaches have not addressed. The system was validated with real-world Chongqing expressway planning data, demonstrating its ability to identify sequences that maximize synergistic network effects. Results reveal how topologically equivalent projects produce dramatically different system-wide outcomes depending on implementation order. Analysis shows that network science-informed sequencing substantially enhances system performance by exploiting structural synergies. This research advances decision support frameworks by bridging complex network theory with computational decision-making, creating a novel analytical tool that enables transportation authorities to implement evidence-based infrastructure sequencing strategies beyond the reach of conventional planning methods. Full article

This study addresses the challenges of real-time performance, safety, and trajectory smoothness in robot navigation by proposing an innovative variable-horizon model predictive control (MPC) scheme that utilizes evolutionary algorithms. To effectively adapt to the complex and dynamic conditions during navigation, a constrained multi-objective evolutionary algorithm is used to tune the control parameters precisely. The optimized parameters are then used to dynamically adjust the MPC’s prediction horizon online. To further enhance the system’s real-time performance, warm start and multiple shooting techniques are introduced, significantly improving the computational efficiency of the MPC. Finally, simulation and real-world experiments are conducted to validate the effectiveness of the proposed method. Experimental results demonstrate that the proposed control scheme exhibits excellent navigation performance in differential-drive robot models, offering a novel solution for intelligent mobile robot navigation. Full article

Inland depression irrigation districts in the arid regions of Xinjiang, owing to the absence of natural drainage conditions, exhibit unique groundwater-salt dynamics and face prominent risks of soil salinization, thus necessitating clarification of their water-salt transport mechanisms to ensure sustainable agricultural development. This study takes the Karamay Agricultural Comprehensive Development Zone as the research subject. The study examines the distribution characteristics of soil salinity, groundwater depth, and Total Dissolved Solids (TDS) of groundwater across diverse soil textures, elucidates the correlative relationships between groundwater dynamics and soil salinity, and forecasts the evolutionary trajectory of groundwater levels within the irrigation district. The findings reveal that groundwater depth in silty soil regions (3.24–3.11 m) substantially exceeds that in silty clay regions (2.43–2.61 m), whereas TDS of groundwater demonstrates marginally elevated concentrations in silty clay areas (19.05–16.78 g L⁻¹) compared to silty soil zones (18.18–16.29 g L⁻¹). Soil salinity exhibits pronounced surface accumulation phenomena and considerable inter-annual seasonal variations: manifesting a “spring-peak, summer-trough” pattern in 2023, which inversely transitioned to a “summer-peak, spring-trough” configuration in 2024, with salinity hotspots predominantly concentrated in silty clay distribution zones. A significant sigmoid functional relationship emerges between soil salinity and groundwater depth (R² = 0.73–0.77), establishing critical depth thresholds of 2.44 m for silty soil and 2.72 m for silty clay, beneath which the risk of secondary salinization escalates dramatically. The XGBoost model demonstrates robust predictive capability for groundwater levels (R² = 0.8545, MAE = 0.4428, RMSE = 0.5174), with feature importance analysis identifying agricultural irrigation as the predominant influencing factor. Model projections indicate that mean groundwater depths across the irrigation district will decline to 2.91 m, 2.76 m, 2.62 m, and 2.36 m over the ensuing 1, 3, 5, and 10 years, respectively. Within a decade, 73.33% of silty soil regions and 92.31% of silty clay regions will experience groundwater levels below critical thresholds, subjecting the irrigation district to severe secondary salinization threats. Consequently, comprehensive mitigation strategies encompassing precision irrigation management and enhanced drainage infrastructure are imperative. Full article

Community public sport facilities are core carriers of the national fitness public service system, with their supply–demand alignment directly linked to megacity governance efficiency and residents’ well-being. To address structural issues, such as “human–land imbalance” in facility layout, this study uses the 2010–2024 panel data from Shanghai’s 16 districts, applies supply–demand equilibrium theory, and integrates quantitative methods to analyze spatio-temporal supply–demand coupling and identify key influencing factors. The study yields four key findings: (1) The spatial distribution of facilities and population demonstrates a differentiated evolutionary trajectory marked by “central dispersion and suburban stability”. (2) Supply–demand alignment has continuously improved, as evidenced by the increase in coordinated administrative districts from six to thirteen. Nonetheless, the distance between sports facilities and population centers widened, suggesting that spatial adaptation remains incomplete. (3) Urban population growth exerts a significant positive impact on facility supply. Elasticity coefficients are generally high in suburban areas, while negative elasticity is detected in some central urban areas due to population outflow. (4) Facility construction intensity and residential activity intensity are core driving factors, with economic conditions, transportation infrastructure, and housing prices acting as key supporting factors. This study overcomes traditional aggregate-quantity research limitations, reveals megacity facility supply–demand “spatial mismatch” dynamics, and provides a scientific basis for targeted public sports facility layout and refined governance. Full article

This review addresses the pivotal challenge in distributed-drive electric vehicle (DDEV) dynamics control: how to optimally distribute braking and steering forces during combined maneuvers to simultaneously enhance lateral stability, safety, and energy efficiency. The over-actuated nature of DDEVs presents a unique opportunity for precise torque vectoring but also introduces complex coupled dynamics, making vehicles prone to instability such as rollover during aggressive steering–braking scenarios. Moving beyond a simple catalog of methods, this work provides a structured synthesis and evolutionary analysis of chassis control methodologies. The problem is first deconstructed into two core control objectives: lateral stability and longitudinal braking performance. This is followed by a critical analysis of how integrated control architectures resolve the inherent conflicts between them. The analysis reveals a clear trajectory from independent control loops to intelligent, context-aware coordination. It further identifies a paradigm shift from the conventional goal of merely maintaining stability toward proactively managing stability boundaries to enhance system resilience. Furthermore, this review highlights the growing integration with high-level motion planning in automated driving. By synthesizing the current knowledge and mapping future directions toward deeply integrated, intelligent control systems, it serves as both a reference for researchers and a design guide for engineers aiming to unlock the full potential of the distributed drive paradigm. Full article

With the continuous expansion of high-density urban forms, residents’ opportunities for daily contact with natural environments have been increasingly reduced, making the equity of urban green space allocation a critical challenge for sustainable urban development. Existing studies have largely focused on green space quantity or accessibility at single time points, lacking systematic investigations into the spatiotemporal evolution of green space exposure (GSE) and its equity from the perspective of residents’ actual environmental experiences. GSE refers to the integrated level of residents’ contact with urban green spaces during daily activities across multiple dimensions, including visual exposure, physical accessibility, and spatial distribution, emphasizing the relationship between green space provision and lived environmental experience. Based on this framework, this study takes the central urban area of Hangzhou as the study area and integrates multi-temporal remote sensing imagery with large-scale street view data. A deep learning–based approach is developed to identify green space exposure, combined with spatial statistical methods and equity measurement models to systematically analyze the spatiotemporal patterns and evolution of GSE and its equity from 2013 to 2023. The results show that (1) GSE in Hangzhou increased significantly over the study period, with accessibility exhibiting the most pronounced improvement. However, these improvements were mainly concentrated in peripheral areas, while changes in the urban core remained relatively limited, revealing clear spatial heterogeneity. (2) Although overall GSE equity showed a gradual improvement, pronounced mismatches between low exposure and high demand persisted in densely populated areas, particularly in older urban districts and parts of newly developed residential areas. (3) The spatial patterns and evolutionary trajectories of equity varied significantly across different GSE dimensions. Composite inequity characterized by “low visibility–low accessibility” formed stable clusters within the urban core. This study further explores the mechanisms underlying green space exposure inequity from the perspectives of urban renewal patterns, land-use intensity, and population concentration. By constructing a multi-dimensional and temporally explicit analytical framework for assessing GSE equity, this research provides empirical evidence and decision-making references for refined green space management and inclusive, sustainable urban planning in high-density cities. Full article

Candidozyma auris (formerly Candida auris) is an emerging multidrug-resistant fungal pathogen with confirmed cases in over 30 countries. Although whole-genome sequencing (WGS) analysis defined distinct clades during characterization of underlying genetic mechanism behind multidrug resistance, Clade II remains under-evaluated. In this study, a three-level comparative genomic strategy (Global, Clade, Phenotype) was employed by integration of unbiased genome-wide comparative SNP screening (GATK v4.1.9.0), targeted BLAST profiling (BLAST+ v2.17.0), and in silico protein analysis (ColabFold v1.5.5; DynaMut2 v2.0) for systematic evaluation of mechanisms of antifungal resistance in thirty-nine Clade II C. auris clinical isolates and fourteen reference strains. Global and clade-level analyses confirmed that all the clinical isolates belong to Clade II, according to phylogenetic clustering and mating type locus (MTL) conservation. At the phenotype level, a distinct subclade of fluconazole-resistant mutants was identified to have a heterogenous network of mutations in seven key enzymes associated with cell membrane dynamics and the metabolic stress response. Among these, four core mutations (TAC1B, CAN2, NIC96, PMA1) were confirmed as functional drivers based on strict criteria during multitier in silico protein analysis: cross-species conservation, surface exposure, active site proximity, thermodynamic stability, and protein interface interaction. On the other hand, three high-level fluconazole-resistant clinical isolates (≥128 μg/mL) that lacked these functional drivers were subjected to comprehensive subtractive genomic profiling analysis. The absence of coding mutations in validated resistance drivers, yeast orthologs, and convergent variants suggests that there is an alternative novel non-coding or regulatory mechanism behind fluconazole resistance. These findings highlight Clade II’s evolutionary divergence into two distinct trajectories towards the development of a high level of fluconazole resistance: canonical protein alteration versus regulatory modulation. Full article

With the rapid growth of vessel traffic and the widespread adoption of the Automatic Identification System (AIS) in recent years, analyzing maritime traffic flow characteristics has become an essential component of modern maritime supervision. Clustering analysis is one of the primary data-mining approaches used to extract traffic patterns from AIS data. Addressing the challenge of assigning appropriate weights to the multidimensional features in AIS trajectories, namely latitude and longitude, speed over ground (SOG), and course over ground (COG). This study introduces an adaptive parameter optimization mechanism based on evolutionary algorithms. Specifically, Particle Swarm Optimization (PSO), a representative swarm intelligence algorithm, is employed to automatically search for the optimal feature-distance weights and the core parameters of Density-Based Spatial Clustering of Applications with Noise (DBSCAN), enabling dynamic adjustment of clustering thresholds and global optimization of model performance. By designing a comprehensive clustering evaluation index as the objective function, the proposed method achieves optimal parameter allocation in a multidimensional similarity space, thereby uncovering maritime traffic clusters that may be overlooked when relying on single-dimensional features. The method is validated using AIS trajectory data from the Xiamen Port area, where 15 traffic clusters were successfully identified. Comparative experiments with two other clustering algorithms demonstrate the superior performance of the proposed approach in trajectory pattern analysis, providing valuable reference for maritime regulatory and traffic management applications. Full article

The basic/helix-loop-helix (bHLH) transcription factors are crucial regulators of plant development and stress responses. In this study, we conducted a genome-wide analysis of the bHLH family in Rosa roxburghii, an economically important fruit crop. A total of 89 non-redundant RrbHLHs were identified and unevenly distributed across the seven chromosomes. Phylogenetic analysis classified them into 23 subfamilies and 7 Arabidopsis subfamilies were absent, indicating lineage-specific evolutionary trajectories. Conserved motif and gene structure analyses showed that members within the same subfamily generally shared similar architectures, yet subfamily-specific variations were evident, suggesting potential functional diversification. Notably, key residues involved in DNA-binding and dimerization were highly conserved within the bHLH domain. Promoter analysis identified multiple cis-acting elements related to hormone response, stress adaptation, and tissue-specific regulation, hinting at broad regulatory roles. Expression profiling across fruit developmental stages and in response to GA₃ treatment revealed dynamic expression patterns. Furthermore, 21 duplicated gene pairs (17 segmental and 4 tandem duplicated pairs) were identified, with most evolving under purifying selection. Detailed analysis of these pairs revealed that segmental duplication, coupled with structural variations such as exon indels, dissolution/joining, and exonization/pseudoexonization, substantially contributed to their functional divergence during evolution. Our results provide a basis for understanding the evolution and potential functions of the RrbHLHs. Full article

Insect pollination, a critical ecological process, pre-dates the emergence of angiosperms by nearly 200 million years, with fossil evidence indicating pollination interactions between insects and non-angiosperm seed plants during the Late Paleozoic. This review examines the symbiotic relationships between insects and gymnosperms in pre-angiosperm ecosystems, highlighting the complexity of these interactions. Fossil records suggest that the mutualistic relationships between insects and gymnosperms, which facilitated plant reproduction, were as intricate and diverse as the modern interactions between angiosperms and their pollinators, particularly bees. These early pollination systems likely involved specialized behaviors and plant adaptations, reflecting a sophisticated evolutionary dynamic long before the advent of flowering plants. The Anthropocene presents a dichotomy: while climate change and anthropogenic pressures threaten insect biodiversity and risk disrupting angiosperm reproduction, such upheaval may simultaneously generate opportunities for novel plant–insect interactions as ecological niches are vacated. Understanding the deep evolutionary history of pollination offers critical insight into the mechanisms underlying the resilience and adaptability of these mutualisms. The evolutionary trajectory of bees—originating from predatory wasps, diversifying alongside angiosperms, and reorganizing after mass extinctions—exemplifies this dynamic, demonstrating how pollination networks persist and reorganize under environmental stress and underscoring the enduring health, resilience, and adaptability of these essential ecological systems. Full article

In this study, we investigate the Suvarṇabhūmi area, corresponding to central–southern Mainland Southeast Asia. We test the hypothesis that this region, located to the south of the Himalayan foothills, can be characterised as a convergence zone in which diverse entities involving humans, animals, and artefacts have significantly diverged from their related counterparts outside the area. We argue that this process of convergence was facilitated by the Maritime Silk Road trade networks, which were particularly active between the 3rd century BCE and the 9th century CE. Comparative data are derived from multiple scientific disciplines, including linguistic typology, onomastics, epigraphy, archaeology, and evolutionary biology. This includes typological features of language, toponyms, inscriptions, glass bead chemistry and related material culture, and phylogenetic data from patterns of endemism to illustrate parallel convergence scenarios observed for each data type. The results reveal recurring patterns of convergence. Linguistic, technological, and biological entities tend to diverge from their original forms and realign with predominant regional types when entering the Suvarṇabhūmi area. The spread of Indic and Sinitic linguistic and cultural elements, the adaptation and development of Brāhmī scripts into distinct local forms, the secondary manufacturing of glass beads, and unique genetic lineages in mammals, amphibians, reptiles, fish, and plants all point to the region’s role as a dynamic interaction sphere. We argue that Suvarṇabhūmi functions as an ecological system, in which trajectories of convergence are notable across a number of individual aspects of cultural and biological diversity. Altogether, these components have contributed to shaping the region’s distinctive natural and cultural history. Full article

China’s traditional courtyard drainage systems have evolved over millennia, embodying distinctive wisdom in sustainable rainwater management. This study aims to clarify the evolutionary logic of these systems, which shifted from relying on surface runoff to adopting more systematic drainage approaches. This addresses a gap in existing research on the systemic evolution of micro-scale units. From a sustainability perspective, the study also explores the relevance of traditional drainage practices to contemporary sponge city development. This research examines traditional courtyard drainage systems through a comprehensive methodology that integrates literature reviews, historical evidence analyses, and comparative historical research. The results reveal an evolutionary trajectory from localized and passive interventions to more holistic and systematic regulation. This process was driven by three interrelated factors: the natural environment, socio-technical conditions, and ritual–cultural systems. Based on this analysis, the study elucidates the logical connections between historical experiences and contemporary practice across three dimensions of sustainability: environmental, technological, and sociocultural. The findings offer both theoretical and practical insights for improving modern urban stormwater management. Full article

Urban forests and green spaces are increasingly promoted as Nature-Based Solutions (NbS) to mitigate climate risks, enhance human well-being, and support resilient and sustainable cities. Focusing on the theme of optimizing urban green space ecosystem services to foster resilient and sustainable cities, this study systematically analyzes 861 relevant publications indexed in the Web of Science Core Collection from 2005 to 2025. Using bibliometric analysis and scientific knowledge mapping methods, the research examines publication characteristics, spatial distribution patterns, collaboration networks, knowledge bases, research hotspots, and thematic evolution trajectories. The results reveal a rapid upward trend in this field over the past two decades, with the gradual formation of a multidisciplinary knowledge system centered on environmental science and urban research. China, the United States, and several European countries have emerged as key nodes in global knowledge production and collaboration networks. Keyword co-occurrence and cluster analyses indicate that research themes are mainly concentrated in four clusters: (1) ecological foundations and green process orientation, (2) nature-based solutions and blue–green infrastructure configuration, (3) social needs and environmental justice, and (4) macro-level policies and the sustainable development agenda. Overall, the field has evolved from a focus on ecological processes and individual service functions toward a comprehensive transition emphasizing climate resilience, human well-being, and multi-actor governance. Based on these findings, this study constructs a knowledge ecosystem framework encompassing knowledge base, knowledge structure, research hotspots, frontier trends, and future pathways. It further identifies prospective research directions, including climate change adaptation, integrated planning of blue–green infrastructure, refined monitoring driven by remote sensing and spatial big data, and the embedding of urban green space ecosystem services into the Sustainable Development Goals and multi-level governance systems. These insights provide data support and decision-making references for deepening theoretical understanding of Urban Green Space Ecosystem Services (UGSES), improving urban green infrastructure planning, and enhancing urban resilience governance capacity. Full article

Plant disease specimens are invaluable resources for investigating the origin and spread mechanisms of plant pathogenic microorganisms. Citrus canker, caused by Xanthomonas citri pv. citri (Xcc), is one of the most devastating bacterial diseases in citrus production. Here, we report the complete genome sequence of Xcc strain GD82, isolated from Guangdong Province during the early outbreak stage in the 1980s. Comparative analysis with modern genomes revealed key differences in structural variations, functional single-nucleotide polymorphisms (SNPs), and phage-related fragments, suggesting potential associations between insertions/deletions (InDels) and pathogenicity or environmental adaptation. This study provides critical insights into the evolutionary trajectory of Xcc and the epidemiological dynamics of citrus canker in China. Full article