Nest Structure Research Articles

Highly birefringent and low loss anti-resonant hollow-core fiber with stadium-shaped nested structure

Abstract We propose a stadium-shaped nested anti-resonant hollow-core fiber (SSAF), designed to enable high birefringence and low loss in the near-infrared bands. A numerical investigation and simulation for variations in the parameters of the stadium-shaped nested structure were conducted, and the confinement loss (CL) was reduced by parameter optimization, while a birefringence of 10-4 was maintained. With optimized SSAF structure, the birefringence and CL are improved to 1.39 ×10−4 and 26.5 dB/km at 1.38 µm, 1.28 ×10−4 and 2.64 dB/km at
1.55 µm, respectively. Meanwhile, it exhibits favorable single-mode characteristics and achieves a high-order mode extinction ratio (HOMER) of up to 103, and the superior bending resistance characteristics were validated. Our work offers valuable guidance for designing and optimizing highly birefringent anti-resonant hollow-core fiber (ARF), and the proposed
SSAF has great application potential in polarization-dependent transmission and interferometric fiber gyroscopes.

Back to geometry: Efficient indoor space segmentation from point clouds by 2D–3D geometry constrains

This paper addresses the challenge of indoor space segmentation from 3D point clouds, which is essential for understanding interior layouts, reconstructing 3D structures, and developing indoor navigation maps. While current deep learning-based methods rely on projecting 3D point clouds into 2D for instance extraction, they often fail to capture the local and global 3D features necessary for effectively segmenting complex indoor spaces, such as multi-ring nested structures. These methods also struggle with generalization across different scenes. In response, this paper proposes an efficient indoor space segmentation method that integrates both 2D and 3D geometric constraints. By leveraging the distribution characteristics of point clouds in 2D and the local and global features in 3D, the method achieves reliable extraction of vertical structural information in complex indoor environments. To address under-segmentation in small spaces due to varying scales, the paper introduces an adaptive extraction method for space partition anchors, guided by local features. During instance-level space segmentation, a hierarchical contour tree structure is employed to precisely partition complex indoor spaces, effectively handling circular and composite structures. The proposed approach was tested on 96 RGB-D scans from the Beike dataset and 6 large-scale indoor scenes from the S3DIS dataset, covering a range of complexities, sizes, and structures. The experimental section includes ablation studies and thorough comparisons with existing state-of-the-art spatial partitioning algorithms based on morphology and deep learning. Results demonstrate that the proposed method significantly outperforms existing approaches in terms of accuracy, robustness, and generalization ability, providing a solid foundation for indoor space modeling and robotic navigation. The source code and datasets will be made publicly available via the “EISPGeo” link.

Research on Self-supporting Structure in Bird Nests

The mystery behind the bird nest’s construction is not well understood. Our study focuses on the stability of a self-supporting nest-like structure. Firstly, we derived a stable/unstable phase boundary for the structure at the fixed coefficient of friction with varying geometrical parameters through force analysis. Structures with a lower height and greater friction coeffi- cient between rods are more stable. The theoretical phase boundary matched the experiment results well. Then we investigate the nest structure’s stability under applied weight. Static structures with lower height and more rods (five>four>three) are more stable. Our theory also predicts a transition from plastic phase to elastic phase. These theoretical predictions are all confirmed by experiment. In the experiment, we also find that wet rod structures are more stable than dry ones. The structures can support up to 100 times of it’s weight.

SceneKG: A Geo‐Scene Based Spatiotemporal Knowledge Representation Framework Considering Geo‐Processes

ABSTRACTCurrent geographic knowledge graph research mainly focuses on static knowledge coupling through analysis of web text and maps, but its knowledge expression model fails to incorporate knowledge mechanisms such as process evolution and interactions. The geo‐scene is a synthesis of various geographic elements which prescribes spatial, temporal, semantic, attribute, and interrelationships. It has demonstrated its utility in facilitating geocomputation, spatiotemporal simulation and reasoning related to geo‐process. Therefore, developing a geo‐scene‐based knowledge graph is significant to improve the ability of spatiotemporal knowledge representation and service. In this study, we first analyze the basic characteristics of geo‐scenes and try to emphasize the evolution of geo‐scenes through redefining the ontologies ‘event’, ‘process’ and ‘state’. To describe the dynamic nested structure of geo‐scenes, we propose a geo‐scene knowledge representation framework, and illustrate the representation of a geo‐scene and its inner relationships. Moreover, to keep the integrity, interaction and dynamic of geo‐scenes, we develop a event‐process centered geo‐scene knowledge organization method. Furthermore, we have tested the utility of our proposed representation by the Beijing 731 heavy rainstorm. The case study represents heavy rainstorm to demonstrate the complicated structure of the disaster scene, and the support for precipitation process simulation, early warning information organization, and disaster situation information query. The proposed representation provides an idea for the construction of geo‐dynamic knowledge graphs, encodes both static and dynamic geographic knowledge, makes explicit the evolution and interaction knowledge in geo‐scenes, and expands the application service of geo‐scene knowledge graph in the era of GeoAI.

On the structure of species-function participation in multilayer ecological networks

Understanding how biotic interactions shape ecosystems and impact their functioning, resilience and biodiversity has been a sustained research priority in ecology. Yet, traditional assessments of ecological complexity typically focus on species-species interactions that mediate a particular function (e.g., pollination), overlooking both the synergistic effect that multiple functions might develop as well as the resulting species-function participation patterns that emerge in ecosystems that harbor multiple ecological functions. Here we propose a mathematical framework that integrates various types of biotic interactions observed between different species. Its application to recently collected data of an islet ecosystem—reporting 1537 interactions between 691 plants, animals and fungi across six different functions (pollination, herbivory, seed dispersal, decomposition, nutrient uptake, and fungal pathogenicity)—unveils a non-random, nested structure in the way plant species participate across different functions. The framework further allows us to identify a ranking of species and functions, where woody shrubs and fungal decomposition emerge as keystone actors whose removal have a larger-than-random effect on secondary extinctions. The dual insight—from species and functional perspectives—offered by the framework opens the door to a richer quantification of ecosystem complexity and to better calibrate the influence of multifunctionality on ecosystem functioning and biodiversity.

A sustainable and robust Janus film Inspired by the bird’s nest structure for efficient year-round outdoor thermal management

Janus structures combining radiative cooling and heating have attracted considerable interest for providing thermal comfort in dynamic environments. However, most of the strategies ignore the weak interfacial bonding due to the differences in material properties of the cooling and heating sides, which ultimately results in a lack of durability. Herein, inspired by the bird’s nest structure, we demonstrated a dual-mode Janus film with bonded interfaces through a simple vacuum-assisted filtration and PDMS modification. The unique structure of the film ensures efficient thermal management including a sub-ambient temperature drop of ∼6.7 °C and a rise of ∼19.8 °C under direct sunlight irradiance. The cooling performance is activated by the synergistic enhancement with BaSO4 and BC porous networks, which exhibits high solar reflectivity (∼95.6 %) and MIR emissivity (∼95.2 %). The heating performance is derived from solar heating (∼71.6 °C at one sun irradiation) and Joule heating (∼88.6 °C at a low voltage of 2.5 V) as a complement, benefiting from the photothermal and electrothermal conversion of MXene. The cooling and heating can be easily obtained by flipping. In addition, the film maintains efficient cooling and heating even after being immersed in water and exposed to sunlight, thereby ensuring outdoor thermal management. Overall, this dual-mode Janus film shows great potential for regulating outdoor thermal comfort and alleviating the energy crisis.

Centromere Landscapes Resolved from Hundreds of Human Genomes.

High-fidelity (HiFi) sequencing has facilitated the assembly and analysis of the most repetitive region of the genome, the centromere. Nevertheless, our current understanding of human centromeres is based on a relatively small number of telomere-to-telomere assemblies, which has not yet captured its full diversity. In this study, we investigated the genomic diversity of human centromere higher order repeats (HORs) via both HiFi reads and haplotype-resolved assemblies from hundreds of samples drawn from ongoing pangenome-sequencing projects and reprocessed them via a novel HOR annotation pipeline, HiCAT-human. We used this wealth of data to provide a global survey of the centromeric HOR landscape; in particular, we found that 23 HORs presented significant copy number variability between populations. We detected three centromere genotypes with unbalanced population frequencies on chromosomes 5, 8, and 17. An inter-assembly comparison of HOR loci further revealed that while HOR array structures are diverse, they nevertheless tend to form a number of specific landscapes, each exhibiting different levels of HOR subunit expansion and possibly reflecting a cyclical evolutionary transition from homogeneous to nested structures and back.

3D-printed modular platform for path-customizable liquids transport

Spontaneous liquid transport is increasingly being applied in various fields such as microfluidics, fuel cells, phase change heat transfer, water harvesting, etc. However, long-distance spontaneous liquid transport with path-customizable motion trajectories is still challenging. Drawing multi-inspirations from the wedge-shaped structures of iris petals, the continuous structures of bamboo joints, and the microgroove structures of Nepenthes mouth edge, we fabricate a modular, pump-free biomimetic liquid transport platform by 3D printing and surface modification. The platform is composed of sequential wedge notches, and a crescent-shaped groove is designed at the joint of every two connected wedge structures. The platform is characterized by path-customizable liquid transport trajectories and can be used to achieve long-distance liquid transport without the need of external energy fields, and the multi-level nested structures along the depth significantly facilitates the liquid transport. Experimental study and theoretical force analysis show that the crescent-shaped grooves enable the liquid to overcome joint barriers by converting potential energy accumulated at joints into kinetic energy, achieving a maximum velocity of 18 mm/s. Taking advantage of the flexibility of 3D printing and long-distance transport capability, the modular structure of the platform enables customization of the transport distance and trajectory. By assembling 14 bamboo-like wedge-shaped units in series, we realized a transport distance up to 350 mm, which could be further increased by connecting more units. Furthermore, we develop various modular and multifunctional liquid transport platforms for anti-gravity transport, liquid diversion, and customized transport trajectories, which demonstrate that our design strategy could be an available solution for path-customizable liquids transport in fields like bio-sensing, fuel cells, etc.

An Oriented Diffusion Strategy to Configure All-Region Ultrahigh-Density Metal Single Atoms for High-Capacity Sodium Storage.

Single-atom metals (SAMs), despite being promising for high-utilization catalysis, biomedicine, and energy storage, usually suffer from limited catalytic performance caused by low metal loading. Herein, via an oriented diffusion strategy, all-region ultrahigh-loading (18.9wt.%) Sn-SAMs over carbon nanorings matrix (Sn-SAMs@CNR) are initially achieved based on the transformation of a g-C3N4@SnO2@polydopamine ring-like nested structure. The formation process of Sn-SAMs involves a critical conversion from oxygen-coordination (SnO2) to nitrogen-coordination (Sn-N4) and simultaneous anti-Osterwalder ripening promoted under spatial confinement. Notably, the g-C3N4-derived N-containing gaseous intermediates dynamically drive the oriented diffusion (inside-out diffusion) of Sn-SAMs across the carbon nanorings, realizing an all-region ultrahigh loading of SAMs throughout the carbon matrix. This strategy is also applied to other metal materials (Fe, Co, Ni, Cu, and Sb), and features excellent universality. When applied as the anode for sodium-ion batteries, experimental analyses and theoretical calculations demonstrate that high-loading Sn-N4 active sites significantly optimize electron density distribution and improve reaction kinetics. Consequently, Sn-SAMs@CNR exhibits outstanding durability of 364mAhg-1 even after 5000 cycles with an impressively low (0.00068%) capacity decay per cycle. This work opens up a universally new avenue for all-region ultrahigh loading of SAMs to carbon matrix for high-performance energy storage.

Three-layered functionally specialized nest structures enhance strength and water retention in mounds of Globitermes sulphureus (Blattodea: Termitidae).

Termite mounds are a ubiquitous feature of savanna ecosystems, yet the mechanisms by which termites (Blattodea: Termitoidae) mitigate the challenges posed by seasonal drought and flooding through mound construction remain insufficiently explored. This study investigates the material properties, water retention capabilities, and resistance to raindrop penetration across three distinct layers of Globitermes sulphureus (Haviland, 1898) (Blattodea: Termitidae) nests. Our findings reveal a pronounced diversification and specialization of materials and functions across these layers. Specifically, the outer layer has decreased moisture permeability, the middle layer has enhanced resistance to water penetration, and the innermost layer has a high capacity for water retention. The integration of these functionally specialized layers provides a compelling evidence for explaining how these termites are able to adapt to the fluctuating environmental conditions characteristic of savanna ecosystems. Furthermore, this highlights the nest's buffering capability against environmental stressors. The complexity of this construction, marked by a level of self-organization rarely observed in the animal kingdom, underscores a significant instance of architectural ingenuity among non-human builders.

MS-UNet: Multi-Scale Nested UNet for Medical Image Segmentation with Few Training Data Based on an ELoss and Adaptive Denoising Method

Traditional U-shape segmentation models can achieve excellent performance with an elegant structure. However, the single-layer decoder structure of U-Net or SwinUnet is too “thin” to exploit enough information, resulting in large semantic differences between the encoder and decoder parts. Things get worse in the field of medical image processing, where annotated data are more difficult to obtain than other tasks. Based on this observation, we propose a U-like model named MS-UNet with a plug-and-play adaptive denoising module and ELoss for the medical image segmentation task in this study. Instead of the single-layer U-Net decoder structure used in Swin-UNet and TransUNet, we specifically designed a multi-scale nested decoder based on the Swin Transformer for U-Net. The proposed multi-scale nested decoder structure allows for the feature mapping between the decoder and encoder to be semantically closer, thus enabling the network to learn more detailed features. In addition, ELoss could improve the attention of the model to the segmentation edges, and the plug-and-play adaptive denoising module could prevent the model from learning the wrong features without losing detailed information. The experimental results show that MS-UNet could effectively improve network performance with more efficient feature learning capability and exhibit more advanced performance, especially in the extreme case with a small amount of training data. Furthermore, the proposed ELoss and denoising module not only significantly enhance the segmentation performance of MS-UNet but can also be applied individually to other models.

Factors influencing risk of predation by subsidized predators on juvenile Mojave desert tortoises (Gopherus agassizii)

A persistent lack of juvenile recruitment in populations of the imperiled Mojave desert tortoise (Gopherus agassizii) has been attributed to artificially inflated populations of coyotes (Canis latrans) and common ravens (Corvus corax) in some areas. Subsidized by resources in the form of road-killed prey, movement corridors, or nesting perches provided by ever-expanding road and powerline networks, these “subsidized predators” threaten tortoises and other species thanks to subsidies that help support their populations in areas where they might otherwise have been less abundant. Here, we quantified the risk of predation from these subsidized predators on juvenile Mojave desert tortoises by quantifying attack rates on 3D-printed replicas. We evaluated predation risk as a function of replica size, distance from powerlines, and season—variables that can inform release strategies of head-started and translocated tortoises. We found significantly greater risk of predation from ravens in the spring than in the fall. Replica size did not significantly influence predation risk from ravens or coyotes. Replica distance from a powerline or road also did not significantly influence predation risk, supporting previous studies that have found the risk of predation can persist for up to 1.6 km from raven nesting structures. Our results support recommendations for releasing juvenile head-started and translocated tortoises in the fall and away from areas close to raven nesting structures. Our study provides insight into the interactions of prey and subsidized predators and helps guide management on potential mitigation strategies for minimizing the impacts of subsidized predators on species like the imperiled Mojave desert tortoise.

Highly resilient aerogel/sponge nested structures assisted multimodal tactile sensory system for robotic embodied perception

Large language models (LLMs) exhibit outstanding reasoning abilities when robots perform tasks, but are limited to the passively receiving information and lack multi-feature perception of realistic objects. Humans obtain complementary and coupled information from interactions with objects through the skin. Here, a multimodal tactile sensory system is reported to assist the LLM-equipped robots in actively perceiving and understanding multiple features of objects including material, compliance and thermal insulation. A multi-parametric tactile sensing array, where each sensor in the array comprises of a triboelectric unit, a decoupling pressure-temperature dual-mode sensing unit and a heating unit, is constructed to acquire the multiparametric tactile signals. The pressure-temperature sensing unit is fabricated from the developed aerogel/sponge nested composite structures, which exhibit stable compression resilience under the compression strain of over 90 %, impressive fatigue resistance with stable responses after 10,000 compression cycles, and linear thermoelectric responses over wide temperature gradients. The multi-parametric tactile signals are analyzed using Mamba time series network model, resulting in the high-precision clustering of multiple features (up to 98.3 %). Supported by a multimodal interactive perception framework, the LLM realizes multi-feature understanding of objects. With large-scale sample datasets and multi-task training, the LLM-equipped robots powered by the multimodal tactile sensory system are expected to realize embodied intelligence.

Clinical decision support improves autoimmune/paraneoplastic antibody panel utilization.

Selection of autoimmune/paraneoplastic antibody panels remains challenging because health-care professionals often lack familiarity with panel contents, recommended specimen types, and antibody combinations for a given patient. Inappropriate use adds cost, prompts unnecessary additional workup, and delays the identification of the true cause of patient symptoms. In this study, we assessed whether order-entry clinical decision support can improve autoimmune/paraneoplastic antibody panel utilization. An order-entry clinical decision support tool was embedded in the electronic health record system. Using a nested panel structure, the decision support tool prompted clinicians to identify their patient's clinical presentation and guided selection of the appropriate tests. In addition, the tool featured a duplicate checking function to alert clinicians when placing multiple orders with substantially similar antibody content within a 3-month period. Panel ordering practices were assessed during the 12 months before implementation and compared with the 6 months immediately following implementation. Clinical decision support significantly reduced the monthly test volume of all orderables from 75.8 per month before implementation to 54.5 per month after implementation (incident rate ratio [IRR], 0.72; 95% CI, 0.63-0.81; P < .001). Placement of multiple orders for panels with substantially overlapping antibody content also decreased significantly, from 7.0 per month to 1.2 per month (IRR, 0.17; 95% CI, 0.07-0.33; P < .001). The number of neural-specific antibodies detected remained unchanged, but the reduction in total test volume increased the neural-specific antibody positivity rate from 4.2% to 6.8% (IRR, 1.61; 95% CI, 0.94-2.70; P = .075). Order-entry clinical decision support offers an efficient and effective approach to improve the utilization of autoimmune/paraneoplastic antibody panels.

Recovering nested structures in networks: an evaluation of hierarchical clustering techniques

Abstract In this article, we present various algorithms to partition the nodes of a network into groups that show the property of nestedness. Since perfect nestedness is a rare phenomenon, we consider the task from a data mining perspective, and we search for groups having high-level of nestedness. We utilize both agglomerative and divisive hierarchical clustering procedures and compare them on several benchmark and real-life networks. Furthermore, we propose different metrics derived from the results of our algorithms. We show that average-linkage and complete-linkage clustering can recover the largest fully nested clusters, and that the cluster size-weighted mean nestedness was a more stable metric for measuring clustering performance. Our proposed algorithms allow us to create multiple resolution views of nestedness-based clustering of networks, extending the field of graph-based data mining.

Heterologous Biosynthesis of New Lanthipeptides Nocardiopeptins with an Unprecedented Bridging Pattern of Lanthionine and Labionin.

The class III lanthipeptide synthetase (LanKC) installs unusual amino acids, such as lanthionine and labionin, in lanthipeptides. Through genome mining, we discovered a new class III lanthipeptide synthetase coding gene (nptKC) and precursor peptide coding genes (nptA1, nptA2, and nptA3) in the genome of the actinobacterium Nocardiopsis alba. Coexpression experiments of the biosynthetic genes in Escherichia coli resulted in the production of new lanthipeptides named nocardiopeptins A1-A3. Analysis of two-dimensional NMR spectra after enzymatic degradation and partial basic hydrolysis of nocardiopeptin A2 revealed that labionin was located in lanthionine with opposite orientations, forming a nesting structure in nocardiopeptin A2. To the best of our knowledge, this bridging pattern in the lanthipeptides was unprecedented, indicating a novel reaction characteristic of the class III lanthipeptide synthetase NptKC.

Differential use of nest materials and niche space among avian species within a single ecological community.

Differential use of resources among bird species has been examined extensively in diet and nesting sites, but few studies have assessed this regarding avian nest materials. We assessed the structure and composition of nests in a group of co-existing passerine shrubland birds at a site in Massachusetts, USA. We found, measured, collected, and dissected nests, and then weighed nest materials in morphological groups (e.g., bark, twigs, feathers) to determine if our seven focal species were using different nest materials. Among species, we compared proportional material masses in complete nests, and also separately in the exterior, structural part of the nest and the interior, cup lining. We found that the proportional masses of all 17 material types that we examined in nests differed among species. The compositions of nests among all seven bird species were distinct in multivariate ordination space and only a few pairs of species had substantial niche overlap. Proportional masses of materials within discrete sections (exterior and interior) also varied among species. Although some differences in nest composition could be partially explained by bird species size, nest materials differed even within the three larger bodied species and within four smaller bodied species. Our study builds upon previous studies that have shown species-specificity in avian nest composition and supports the notion that birds using the same environment have distinct niches in relation to the materials placed in their nests. Niche partitioning due to interspecific competition could partially explain our findings, as certain materials are limited as resources, and searching for suitable nest materials is energetically costly. Additionally, other factors, such as partitioned nest sites, may have led to differential nest material use. We recommend further research to help elucidate underlying mechanisms of nest composition partitioning in birds and potentially other nest-building taxa.

The Breeding colonies, population growth and breeding success of the Dalmatian pelican Pelecanus crispus in Greece: a country-wide perspective, 1967-2021

Greece holds the third larger breeding population of Dalmatian Pelican in the world. We present data about the establishment and growth, breeding performance and conservation status for all six colonies of the species in Greece for 40 years. Main features of wetlands and colonies are described. We discuss the local, regional and global natural and anthropogenic factors that may have affected colony growth. After 1982 colony surveys were carried out with various methods, adapted to the particularities of each wetland and availability of resources, and targeted estimating number of nests and number of near-fledged young via direct counting either during on-site visits or from vantage points, and recently, counts on photos taken by drones flown one or more times during breeding. Number of nests in Lake Mikri Prespa rose from ca. 100 to 1200-1500 and levelled-off. DPs from Prespa started breeding successfully in Kerkini in 2004 after placement of artificial nesting rafts. The Karla Reservoir was colonised in 2011, just two years after it started filling with water. The DP colony on Lake Chimaditis, an important stop over and feeding site, probably initiated around 2016 and continues growing. The two colonies at the western coastline have limited exchanges with those in the eastern part of the country. Amvrakikos increased and levelled off recently as conservation and management measures restricted disturbance, whilst emigrants re-established the old colony at Messolonghi in 2011 which continues to grow. The overall breeding population in Greece grew from ca 100 to over 2000 br pairs showing an annual growth rate of 7.9%. Younger colonies show high annual growth rates clearly attributed to immigration, while older colonies have growth rates less than 10%. Interacting natural and anthropogenic factors are assumed to have contributed to pelican increase in Greece the last 40 years: better legal protection status, increasingly effective protection, patrolling and conservation measures; public awareness campaigns; provision of artificial nesting structures; increased winter survival due to higher temperatures owed to climate change; less disturbance and persecution due to decline of fisheries; increasing abundance and availability of fish due to eutrophication and climate change; increasing numbers of sympatric great cormorants rendering pelican fishing more efficient; appearance of new wetlands and change of wetlands due to human intervention works.

Study on the Aging Precipitation Behavior and Kinetics of Al-10.0Zn-3.0Mg-2.8Cu Alloy by Pre-Deformation Treatment.

In this paper, the effect of thermomechanical treatment process on the hardening behavior, grain microstructure, precipitated phase, and tensile mechanical properties of the new high-strength and high-ductility Al-10.0Zn-3.0Mg-2.8Cu alloy was studied, and the optimal thermomechanical treatment process was established. The strengthening and toughening mechanisms were revealed, which provided technical and theoretical guidance for the engineering application of this kind of high strength-ductility aluminum alloy. Al-10.0Zn-3.0Mg-2.8Cu alloy cylindrical parts with external longitudinal reinforcement were prepared by a composite extrusion deformation process (reciprocal upsetting + counter-extrusion) with a true strain up to 2.56, and the organizational evolution of the alloys during the extrusion deformation process and the influence of pre-stretching treatments on the subsequent aging precipitation behaviors and mechanical properties were investigated. The results show that firstly, the large plastic deformation promotes the fragmentation of coarse insoluble phases and the occurrence of dynamic recrystallization, which results in the elongation of the grains along the extrusion direction, and the volume fraction of recrystallization reaches 42.4%. Secondly, the kinetic study showed that the decrease in the activation energy of precipitation increased the nucleation sites, which further promoted the diffuse distribution of the second phase in the alloy and a higher number of nucleation sites, while limiting the coarsening of the precipitated phase. When the amount of pre-deformation was increased from 0% to 2%, the size of the matrix precipitated phase decreased from 5.11 μm to 4.1 μm, and when the amount of pre-deformation was increased from 2% to 7%, the coarsening of the matrix precipitated phase took place, and the size of the phase increased from 4.1 μm to 7.24 μm. The finalized heat treatment process for the deformation of the aluminum alloy tailframe was as follows: solution (475 °C/3 h) + 2% pre-stretching + aging (120 °C/24 h), at which the comprehensive performance of the alloy was optimized, with a tensile strength of 634.2 MPa, a yield strength of 571.0 MPa, and an elongation of 15.2%. The alloy was strengthened by both precipitation strengthening and dislocation strengthening. After 2% pre-stretching, the fracture surface starts to be dominated by dense tough nest structure, and most of them are small tough nests, and small and dense tough nests are the main reason for the increase in alloy toughness after 2% pre-stretching deformation.

Ant and termite collective behavior: Group‐level similarity arising from individual‐level diversity

AbstractAnimal collective behavior produces group‐level patterns that emerge from individual‐level interactions among members. Such sophisticated behavioral coordination can be observed across various taxa, indicating evolutionary convergence. Among the most striking examples are two social insect lineages: ants and termites. Ants and termites evolved socially independently, inhabit terrestrial and subterranean environments, and face a similar collective task of maintaining their colonies with many individuals. This results in the convergent evolution of collective phenomena, such as constructing complex nest structures or movement coordination based on chemical and tactile cues. However, although the striking similarity attracts the most attention, little research has focused on how ants and termites differ in collective behaviors at individual and group levels. Here, we review the similarities and distinctions of collective behaviors in ants and termites. Even with similarities in group‐level patterns, rich diversity exists in mechanisms of behavioral coordination and the functions of collective patterns. Comparative analysis of collective behavior is challenging, but recent advances in automatic movement tracking methodologies have greatly expanded the potential for generating further insights. Finally, we conclude that comparative collective behavioral analysis can enhance our ability to understand biodiversity and provide alternative solutions for collective problem‐solving in many fields.