Evolution Of Clusters Research Articles

Art Pattern Design Based on Visual Semantic Segmentation and Evolutionary Algorithm Optimization

This paper aims to address the issue of traditional art patterns not fully leveraging contextual information in image semantic segmentation. It proposes a multi-level feature aggregation method for image semantic segmentation based on visual Transformer and coordinate attention adjustment (CA Adjustment). Initially, the input image is segmented into slices for linear projection, incorporating learnable positional embeddings to derive an encoded input sequence. Subsequently, employing a visual Transformer-based encoder, the image is transformed into patches to capture global context across the network. CA Adjustment is then introduced to adaptively merge fusion features and visual backbone features using weighted adjustments. Lastly, a multi-objective grasshopper optimization algorithm is designed based on a clustering evolution mechanism to further enhance algorithm performance. Extensive experimental results demonstrate that our proposed algorithm effectively models global contextual information for image feature extraction. Compared to existing advanced algorithms, our method achieves high segmentation accuracy in semantic segmentation tasks, consistently exceeding 95%. Ablation experiments further validate the efficacy of our approach, underscoring its broad applicability in high-precision image semantic segmentation.

Characterization of droplet clusters in a turbulent multiphase gas cloud using a model cough simulator

This study aims to investigate the transport of droplets ejected from an artificial cough simulator, which releases a turbulent puff of droplets into the surrounding air, closely resembling the human coughing process. The focus is on understanding droplet clustering within the multiphase gas cloud across various operating conditions that emulate the wide variation in the spray characteristics in actual human subjects owing to infection severity, age, and gender. Time-resolved particle image velocimetry (PIV) technique was employed to measure the velocity of both droplet and gas phases. It also facilitates the identification and characterization of droplet clusters through Voronoi analysis of the PIV images. The area and length scale of individual droplet clusters were measured, and the degree of droplet clustering was quantified using the clustering index and relative droplet number density within the clusters. Additionally, the interferometric laser imaging for droplet sizing technique was utilized for planar measurement of individual droplet sizes. The range of Stokes number indicated partial to poor response of the droplets to the turbulent eddies. The results reported, for the first time, the presence of droplet clusters in the simulated coughing process. The wide spectrum of cluster size and self-similar evolution of droplet clusters unveil a multi-scale clustering phenomenon, shedding light on the intricate dynamics of the respiratory droplet dispersion process. The study comprehensively investigates the role of injection pressure on droplet clustering and the spatial development of the clusters, revealing some interesting findings, which are discussed.

A 3D view of multiple populations’ kinematics in Galactic globular clusters

We present the first 3D kinematic analysis of multiple stellar populations (MPs) in a representative sample of 16 Galactic globular clusters (GCs). For each GC in the sample, we studied the MP line-of-sight, plane-of-the-sky and 3D rotation, and velocity distribution anisotropy. The differences between first-population (FP) and second-population (SP) kinematic patterns were constrained by means of parameters specifically defined to provide a global measure of the relevant physical quantities and to enable a meaningful comparison among different clusters. Our analysis provides the first observational description of the MP kinematic properties and of the path they follow during their long-term dynamical evolution. In particular, we find evidence of differences between the rotation of MPs along all velocity components with the SP preferentially rotating faster than the FP. The difference between the rotation strength of MPs is anticorrelated with the cluster dynamical age. We also observe that FPs are characterized by isotropic velocity distributions at any dynamical age probed by our sample. On the contrary, the velocity distribution of SP stars is found to be radially anisotropic in dynamically young clusters and isotropic at later evolutionary stages. The comparison with a set of numerical simulations shows that these observational results are consistent with the long-term evolution of clusters forming with an initially more centrally concentrated and more rapidly rotating SP subsystem. We discuss the possible implications these findings have on our understanding of MP formation and early evolution.

A Systematic Analysis of Star Cluster Disruption by Tidal Shocks. II. Predicting Star Cluster Dissolution Rates from a Time-series Analysis of Their Tidal Histories

Most of the dynamical mass loss from star clusters is thought to be caused by the time variability of the tidal field (“tidal shocks”). Systematic studies of tidal shocks have been hampered by the fact that each tidal history is unique, implying both a reproducibility and a generalization problem. Here we address these issues by investigating how star cluster evolution depends on the statistical properties of its tidal history. We run a large suite of direct N-body simulations of clusters with tidal histories generated from power spectra of a given slope and with different normalizations, which determine the timescales and amplitudes of the shocks, respectively. At fixed normalization (i.e., the same median tidal field strength), the dissolution timescale is nearly independent of the power spectrum slope. However, the dispersion in dissolution timescales, obtained by repeating simulations for different realizations of statistically identical tidal histories, increases with the power spectrum slope. This result means that clusters experiencing high-frequency shocks have more similar mass-loss histories than clusters experiencing low-frequency shocks. The density–mass relationship of the simulated clusters follows a power law with slope between 1.08 and 1.45, except for the lowest normalizations (for which clusters effectively evolve in a static tidal field). Our findings suggest that star cluster evolution can be described statistically from a time-series analysis of its tidal history, which is an important simplification for describing the evolution of the star cluster population during galaxy formation and evolution.

Revisiting Socransky’s Complexes: A Review Suggesting Updated New Bacterial Clusters (GF-MoR Complexes) for Periodontal and Peri-Implant Diseases and Conditions

This review aimed to identify newly discovered bacteria from individuals with periodontal/peri-implant diseases and organize them into new clusters (GF-MoR complexes) to update Socransky’s complexes (1998). For methodological development, the PCC (Population, Concept, Context) strategy was used for the focus question construction: “In patients with periodontal and/or peri-implant disease, what bacteria (microorganisms) were detected through laboratory assays?” The search strategy was applied to PubMed/MEDLINE, PubMed Central, and Embase. The search key terms, combined with Boolean markers, were (1) bacteria, (2) microbiome, (3) microorganisms, (4) biofilm, (5) niche, (6) native bacteria, (7) gingivitis), (8) periodontitis, (9) peri-implant mucositis, and (10) peri-implantitis. The search was restricted to the period 1998–2024 and the English language. The bacteria groups in the oral cavity obtained/found were retrieved and included in the GF-MoR complexes, which were based on the disease/condition, presenting six groups: (1) health, (2) gingivitis, (3) peri-implant mucositis, (4) periodontitis, (5) peri-implantitis, and (6) necrotizing and molar–incisor (M-O) pattern periodontitis. The percentual found per group refers to the number of times a specific bacterium was found to be associated with a particular disease. A total of 381 articles were found: 162 articles were eligible for full-text reading (k = 0.92). Of these articles, nine were excluded with justification, and 153 were included in this review (k = 0.98). Most of the studies reported results for the health condition, periodontitis, and peri-implantitis (3 out of 6 GF-MoR clusters), limiting the number of bacteria found in the other groups. Therefore, it became essential to understand that bacterial colonization is a dynamic process, and the bacteria present in one group could also be present in others, such as those observed with the bacteria found in all groups (Porphyromonas gingivalis, Tannarela forsythia, Treponema denticola, and Aggregatibacter actinomycetemcomitans) (GF-MoR’s red triangle). The second most observed bacteria were grouped in GF-MoR’s blue triangle: Porphyromonas spp., Prevotela spp., and Treponema spp., which were present in five of the six groups. The third most detected bacteria were clustered in the grey polygon (GF-MoR’s grey polygon): Fusobacterium nucleatum, Prevotella intermedia, Campylobacter rectus, and Eikenella corrodens. These three geometric shapes had the most relevant bacteria to periodontal and peri-implant diseases. Specifically, per group, GF-MoR’s health group had 58 species; GF-MoR’s gingivitis group presented 16 bacteria; GF-MoR’s peri-implant mucositis included 17 bacteria; GF-MoR’s periodontitis group had 101 different bacteria; GF-MoR’s peri-implantitis presented 61 bacteria; and the last group was a combination of necrotizing diseases and molar–incisor (M-I) pattern periodontitis, with seven bacteria. After observing the top seven bacteria of all groups, all of them were found to be gram-negative. Groups 4 and 5 (periodontitis and peri-implantitis) presented the same top seven bacteria. For the first time in the literature, GF-MoR’s complexes were presented, gathering bacteria data according to the condition found and including more bacteria than in Socransky’s complexes. Based on this understanding, this study could drive future research into treatment options for periodontal and peri-implant diseases, guiding future studies and collaborations to prevent and worsen systemic conditions. Moreover, it permits the debate about the evolution of bacterial clusters.

Twins in diversity: understanding circumstellar disc evolution in the twin clusters of W5 complex

ABSTRACT Young star-forming regions in massive environments are ideal test beds to study the influence of surroundings on the evolution of discs around low-mass stars. We explore two distant young clusters, IC 1848-East and West located in the massive W5 complex. These clusters are unique due to their similar (distance, age and extinction) yet distinct (stellar density and far-ultraviolet radiation fields) physical properties. We use deep multiband photometry in optical, near-infrared and mid-infrared wavelengths complete down to the substellar limit in at least five bands. We trace the spectral energy distribution of the sources to identify the young pre-main sequence members in the region and derive their physical parameters. The disc fraction for the East and West clusters down to 0.1 M$_\odot$ was found to be $\sim 27\,\pm$ 2 per cent (N$_\mathrm{disc}$ = 184, N$_\mathrm{discless}$ = 492) and $\sim 17\,\pm$ 1 per cent (N$_\mathrm{disc}$ = 173, N$_\mathrm{discless}$ = 814), respectively. While no spatial variation in the disc fraction is observed, these values are lower than those in other nearby young clusters. Investigating the cause of this decrease, we find a correlation with the intense feedback from massive stars throughout the cluster area. We also identified the disc sources undergoing accretion and observed the mass accretion rates to exhibit a positive linear relationship with the stellar host mass and an inverse relationship with stellar age. Our findings suggest that the environment significantly influences the dissipation of discs in both clusters. These distant clusters, characterized by their unique attributes, can serve as templates for future studies in outer galaxy regions, offering insights into the influence of feedback mechanisms on star and planetary formation.

Acquisition and evolution of the neurotoxin domoic acid biosynthesis gene cluster in Pseudo-nitzschia species

Of the hitherto over 60 taxonomically identified species in the genus of Pseudo-nitzschia, 26 have been confirmed to be toxigenic. Nevertheless, the acquisition and evolution of the toxin biosynthesis (dab) genes by this extensive group of Pseudo-nitzschia species remains unclear. Through constructing chromosome-level genomes of three Pseudo-nitzschia species and draft genomes of ten additional Pseudo-nitzschia species, putative genomic integration sites for the dab genes in Pseudo-nitzschia species were explored. A putative breakpoint was observed in syntenic regions in the dab gene cluster-lacking Pseudo-nitzschia species, suggesting potential independent losses of dab genes. The breakpoints between this pair of conserved genes were also identified in some dab genes-possessing Pseudo-nitzschia species, suggesting that the dab gene clusters transposed to other loci after the initial integration. A “single acquisition, multiple independent losses (SAMIL)” model is proposed to explain the acquisition and evolution of the dab gene cluster in Pseudo-nitzschia species.

High‐Performance Na‐Storage and Sodiation Behavior Identification in Cellulose‐Derived Hard Carbon by High‐Resolution Element Mapping Microscopy

Nowadays, hard carbon is one of the most promising anode materials for sodium‐ion batteries. However, the Na‐storage performance of hard carbon varies for different precursors and synthetic processes due to disparities in the dopant content, dimensions, and categories of defects, graphitic domains, which lead to controversial explanations for the energy storage mechanism. Herein, self‐freestanding membrane of cellulose‐derived carbon fibers is presented, delivering a reversible Na‐storage capacity of 330 mAh g−1 at 50 mA g−1 due to abundant ordered graphitic zones with enlarged interlayer spacings around 0.39 ± 0.03 nm. Benefiting from a robust solid electrolyte interphase layer rich in NaF nanocrystals, the membrane also holds a superior rate capability of 100 mAh g−1 at 2 A g−1 and long‐term cycling stability with capacity retention of 82.6% at 1.5 A g−1 for 4000 cycles. A clear sodiation behavior of Na+ intercalation into enlarged carbon graphitic layers at the slope step above 0.10 V and Na cluster evolution in the micropores at the plateau step around 0.01–0.10 V is disclosed by high‐resolution element mapping microscopy, different from the accepted mechanism of Na+ intercalation into graphitic layers at the plateau step.

Spatial and temporal evolution patterns and driving mechanisms of rural settlements: a case study of Xunwu County, Jiangxi Province, China

Urbanization and industrialization have driven rapid socio-economic development, leading to a significant population shift from rural areas to cities. This demographic transition has resulted in substantial changes in rural settlements, presenting considerable challenges for rural revitalization. Given the spatial differentiation, it is crucial to analyze the spatiotemporal evolution patterns and driving mechanisms of rural settlements under various development scenarios and at multiple scales within a county. Such analysis is essential for rational planning and sustainable development. This study analyzes the spatial and temporal evolution patterns and driving mechanisms of rural settlements in Xunwu County, Jiangxi Province, China, using land use dynamics, hot and cold spot analysis, and center of gravity migration models. The Multiscale Geographically Weighted Regression Model (MGWR) is employed to explore their transformation driving mechanisms. The results show that during 2010–2020 in the study area, the total change rate of rural settlements was 39.82%, with a dynamic degree of 2.87%. The average centroid of the settlements is located in Wenfeng Township, gradually migrating southeastward by 3.7 km. Cold spots are shrinking northward, while hotspots are gathering in Chengjiang Town. Socio-economic conditions dominate the evolution of rural clusters in this region, showing obvious spatial heterogeneity. This is followed by locational conditions that are weakening in influence, while the impact of natural geographical conditions exists in the northeast region. The research findings offer a scientifically rigorous and well-founded analysis of the evolution and driving mechanisms of rural settlements. This analysis provides a solid theoretical basis for policy planning in urban-rural integrated development and supports the sustainable growth of rural communities.

Temperature-induced evolution of CuOx clusters in CuOx/TiO2 catalyst for boosting auto-exhaust oxidation

Developing non-noble metal oxides, replacing platinum group catalysts for auto-exhaust purification, where their usage amount exceeds 40 % of global demand, remains a challenge. Herein, we presented a combined approach on the synthesis and application of robust CuOx/TiO2 catalysts with ultra-fine CuOx clusters (ca. 1 nm). The strong interaction between CuOx and TiOx induces favorable interfacial charge accumulation, facilitating the extraction of the interfacial oxygen atoms in Cu2-x-O-Ti4-y chains and the surface lattice oxygen on CuOx clusters. Isotope 18O2 experiments and DFT calculations jointly confirmed that these oxygen atoms preferentially participate in the oxidation through the Mars-van Krevelen mechanism below 250 °C. The resulted oxygen vacancies facilitate the adsorption and activation of O2 molecules, which will participate the oxidation above 250 °C through Eley-Rideal mechanism. The increase in the temperature also drives the synergy of active oxygen species in the interfacial Cu2-x-O-Ti4-y bond chains and on CuOx clusters, cooperatively promoting the conversion of NO to NO2. As a result, the CuOx/TiO2 catalyst exhibits exceptional catalytic performance in soot oxidation, with a four-fold higher reaction rate (4.17 μmol g−1 min−1) than that of single-atom Cu₁-TiO2 catalyst. Such findings provide a novel strategy for the advancement of Cu-based cluster catalysts in environmental applications.

The formation and evolution of dark star clusters – II. The impact of primordial mass segregation

ABSTRACT We investigate the impact of primordial mass segregation on the formation and evolution of dark star clusters (DSCs). Considering a wide range of initial conditions, we conducted N-body simulations of globular clusters (GCs) around the Milky Way. In particular, we assume a canonical initial mass function for all GCs without natal kicks for supernova remnants, namely neutron stars or black holes. Our results demonstrate that clusters with larger degrees of primordial mass segregation reach their DSC phase earlier and spend a larger fraction of their dissolution time in such a phase, compared to clusters without mass segregation. In primordially segregated clusters, the maximum Galactocentric distance that the clusters can have to enter the DSC phase is almost twice that of the clusters without primordial mass segregation. Primordially segregated clusters evolve with a higher number of stellar mass black holes, accelerating energy creation in their central regions and consequently increasing evaporation rates and cluster sizes during dark phases. The simulations reveal that aggregating heavy components at the centre doubles the time spent in the dark phase. Additionally, the study identifies potential links between simulated dark clusters and initial conditions of Milky Way GCs, suggesting some may transition to dark phases before dissolution. Higher primordial mass segregation coefficients amplify the average binary black hole formation rate by 2.5 times, raising higher expectations for gravitational-wave emissions.

Evolution of Star Clusters within Galaxies Using Self-consistent Hybrid Hydro/N-body Simulations

We introduce a GPU-accelerated hybrid hydro/N-body code (Enzo-N) designed to address the challenges of concurrently simulating star clusters and their parent galaxies. This task has been exceedingly challenging, primarily due to the considerable computational time required, which stems from the substantial scale difference between galaxies (∼0.1 Mpc) and star clusters (∼parsecs). Yet, this significant scale separation means that particles within star clusters perceive those outside the star cluster in a semistationary state. By leveraging this aspect, we integrate a direct N-body code (Nbody6++GPU) into a cosmological (magneto)hydrodynamic code (Enzo) through utilization of the semistationary background acceleration approximation. We solve the dynamics of particles within star clusters using a direct N-body solver with regularization for few-body interactions, while evolving particles outside—dark matter, gas, and stars—using a particle-mesh gravity solver and hydrodynamic methods. We demonstrate that Enzo-N successfully simulates the coevolution of star clusters and their parent galaxies, capturing phenomena such as core collapse of the star cluster and tidal stripping due to galactic tides. This comprehensive framework opens up new possibilities for studying the evolution of star clusters within galaxies, offering insights that were previously inaccessible.

Sn and Cu influence on Mg:Si ratios evolution in clusters based on DFT and its impact on precipitation hardening of pre-aged Al-1.0Mg-0.6Si alloys

Using atom probe tomography (APT), transmission electron microscopy (TEM), and hardness tests, the effect of Sn and Cu on the evolution of Mg:Si ratios in clusters and subsequent precipitation hardening behavior of pre-aged Al-1.0Mg-0.6Si alloys are investigated, and the underlying mechanism is revealed by density functional theory (DFT) calculation of interaction energy. It is shown that, the doping of Sn and/or Cu increases the average Mg:Si ratio in clusters. This increase is attributed to the strong interaction of Sn/Cu with Mg solutes, which enhances the binding of Mg to Si-rich clusters and results in a higher proportion of clusters with Mg:Si ratios near 1 (0.75 ∼ 1.25). Consequently, the enhanced precipitation of β" precipitates during artificial aging is observed in Sn and/or Cu doped alloys, due to the ease of clusters with Mg:Si ratios near 1 transform into β" precipitates, leading to an improved hardening response. Notably, the combined doping of Sn and Cu exhibits the strongest aggregation tendency towards Mg solutes, yielding the most pronounced strengthening effects on precipitation and hardening response during artificial aging. Furthermore, a schematic model detailing the evolution of Mg:Si ratios in clusters is proposed, based on the APT results and DFT calculation of interaction energy.

Heterogeneous oxidation involving different atomic clusters in sintering-free amorphous SiBCN ceramic with MA@PDC-SiBCN structure

Amorphous SiBCN monoliths featuring a structure of three-dimensional PDC-SiBCN network encapsulating MA-SiBCN nanoparticles (MA@PDC-SiBCN), were prepared without the need for sintering densification (>1800°C), enabling preparation of dense ceramics at a much lower temperature (1100°C). The continuous PDC-SiBCN network effectively inhibits oxygen diffusion, reducing the mass loss from B-C-N cluster oxidation and mass gain from silicon-containing clusters by 51.5% and 86.9%, respectively. Besides, the phase-separation coupled heterogeneous oxidation behaviors and kinetics of different atomic clusters in MA@PDC-SiBCN ceramic during non-isothermal oxidation up to 1500°C were investigated. Finally, the evolution of the different atomic clusters within the oxide layer during the heterogeneous oxidation process was analyzed to elucidate the micro-mechanisms behind the enhanced oxidation resistance.

Supermassive black hole formation via collisions in black hole clusters

More than 300 supermassive black holes have been detected at redshifts larger than six, and they are abundant in the centers of local galaxies. Their formation mechanisms, however, are still rather unconstrained. A possible origin of these supermassive black holes could be mergers in dense black hole clusters, forming as a result of mass segregation within nuclear star clusters at the center of galaxies. In this study, we present the first systematic investigation of the evolution of such black hole clusters in which the effect of an external potential is taken into account. Such a potential could be the result of gas inflows into the central region; for example, as a result of galaxy mergers. We show here that the efficiency of the formation of a massive central object is mostly regulated by the ratio of cluster velocity dispersion divided by the speed of light, potentially reaching efficiencies of 0.05–0.08 in realistic systems. Our results show that this scenario is potentially feasible and may provide black hole seeds of at least 103 M⊙. We conclude that the formation of seed black holes via this channel should be taken into account in statistical assessments of the black hole population.

Characteristics Analysis and Modeling of Integrated Sensing and Communication Channel for Unmanned Aerial Vehicle Communications

As an important part of 6th generation (6G) communication, integrated sensing and communication (ISAC) for unmanned aerial vehicle (UAV) communication has attracted more and more attention. The UAV ISAC channel model considering the space-time evolution of joint and shared clusters is the basis of UAV ISAC system design and network evaluation. This paper introduces the UAV ISAC channel characteristics analysis and modeling method. In the UAV ISAC network, the channel consists of a communication channel and a sensing channel. A joint channel parameter is a combination of all (communication and sensing) multiple path component (MPC) parameter sets, while a shared path is the intersection of the communication path and sensing path that have some of the same MPC parameters. Based on the data collected from a ray-tracing (RT) UAV-to-ground scenario, the joint paths and shared paths of ISAC channels are clustered. Then, by introducing the occurrence and disappearance of clusters based on the birth–death (B–D) process, the space-time evolution of different clusters is described, and the influence of the addition of sensing clusters and the change in flight altitude on the B–D process is explored. Finally, the effects of the sensing cluster and flight altitude on the UAV ISAC channel characteristics, including the angle, time–varying characteristics, and sharing degree (SD), are analyzed. The related UAV ISAC channel characteristics analysis can provide reference for the future development of UAV ISAC systems.

FRACTAL DIMENSION OF STAR CLUSTERS

Quantitative analysis of the structure of star clusters is crucial for understanding their formation and evolution. In this article, we explore the application of fractal dimension analysis to study the evolution of star clusters, also fractal dimension, a concept from fractal geometry, provides a quantitative measure of the complexity and self-similarity of geometric objects. By considering star clusters as complex networks, we employ the box covering method to calculate their fractal dimension. Our methodology combines the well-established Minimum Spanning Tree (MST) and Box-Covering (BC) methods and using these methods, the fractal structure of the clusters was determined. It was revealed that star clusters disintegrate at a fractal dimension of 1.3 and obey a power law. It should be noted that the obtained result was compared with the results of the McLuster.

A framework for spatial-temporal cluster evolution representation and analysis based on graphs

Analysis on spatial-temporal data has several benefits that range from an improved traffic network in a city to increased earnings for drivers and ridesharing companies. A common analysis technique is clustering. However, most clustering techniques consider a constrained representation of clusters that is limited to a single timestamp. Evolving clusters exist through several timestamps and interact with other spatial-temporal objects or clusters, having cluster relationships. When many evolving clusters exist for analysis, a graph can be used to represent cluster evolution. In this article, we propose a framework for graph-based cluster evolution representation and analysis. The framework represents cluster structure and relationships as well as provides a graph representation of cluster evolution for analysis. Evaluation is done in three case studies with spatial-temporal data about taxis that can identify important phenomena or trends in movements in a city for traffic improvement.

Lifecycle of Pd Clusters: Following the Formation and Evolution of Active Pd Clusters on Ceria During CO Oxidation by In Situ/Operando Characterization Techniques

Lifecycle of Pd Clusters: Following the Formation and Evolution of Active Pd Clusters on Ceria During CO Oxidation by In Situ/Operando Characterization Techniques

Evolution and Domestication of a Novel Biosynthetic Gene Cluster Contributing to the Flavonoid Metabolism and High-Altitude Adaptability of Plants in the Fagopyrum Genus.

The diversity of secondary metabolites is an important means for plants to cope with the complex and ever-changing terrestrial environment. Plant biosynthetic gene clusters (BGCs) are crucial for the biosynthesis of secondary metabolites. The domestication and evolution of BGCs and how they affect plant secondary metabolites biosynthesis and environmental adaptation are still not fully understood. Buckwheat exhibits strong resistance and abundant secondary metabolites, especially flavonoids, allowing it to thrive in harsh environments. A non-canonical BGC named UFGT3 cluster is identified, which comprises a phosphorylase kinase (PAK), two transcription factors (MADS1/2), and a glycosyltransferase (UFGT3), forming a complete molecular regulatory module involved in flavonoid biosynthesis. This cluster is selected during Tartary buckwheat domestication and is widely present in species of the Fagopyrum genus. In wild relatives of cultivated buckwheat, a gene encoding anthocyanin glycosyltransferase (AGT), which glycosylates pelargonidin into pelargonidin-3-O-glucoside, is found inserted into this cluster. The pelargonidin-3-O-glucoside can help plants resist UV stress, endowing wild relatives with stronger high-altitude adaptability. This study provides a new research paradigm for the evolutionary dynamics of plant BGCs, and offers new perspectives for exploring the mechanism of plant ecological adaptability driven by environmental stress through the synthesis of secondary metabolites.