Evolutionary Process Research Articles

Numerical characterization on fracture evolution behavior of pre-flawed sandstone under monotonic and multilevel cyclic loading

This study employed an improved stress corrosion model within a three-dimensional particle flow program to investigate the mechanical and cracking behavior of fractured sandstone samples with varying rock bridge angles under both monotonic loading and multilevel cyclic loading. Firstly, using the experimental results from intact sandstone under uniaxial compression, we calibrated the microscopic mechanical parameters of the parallel bond model. Then, the model was validated using the experimental results of fractured sandstone under monotonic and cyclic loading. Finally, the initiation, propagation, and coalescence behavior of cracks in fractured sandstone samples under the above two loading paths, as well as the evolution process of the stress field, displacement field, and force chain distribution, were discussed in detail. The results show that the stress–strain curves, strength, deformation parameters, and macroscopic failure modes obtained from numerical simulations are consistent with those from laboratory mechanical tests. The mechanical behavior of fractured sandstone is influenced by both the rock bridge angle and the loading path. As the rock bridge angle decreases, the mechanical parameters of the sample show an increasing trend, and the influence of rock bridge angle on the failure mode is reduced. Cracks in the samples all initiate at the tips of pre-existing flaws, and the rock bridge angle affects the crack propagation and coalescence process: for sandstones with smaller rock bridge angles, cracks gradually extend to the sample’s ends; for sandstones with larger rock bridge angles, direct coalescence of cracks at the rock bridge is observed, then extending to the sample’s ends. Compared with monotonic loading, the damage degree of sandstone samples under multilevel cyclic loading is more severe, and even obvious block spalling is observed. The experimental and numerical simulation results are expected to improve the understanding of the mechanical behavior and fracture behavior of fractured rocks under monotonic and multilevel cyclic loading.

Spatio-temporal evolution law of anisotropic shear damage on rock mass joint surface affected by joint morphology

The spatial–temporal evolution law of shear damage on the joint surface is closely related to its morphological characteristics. Understanding the heterogeneous failure behavior of the joint surface is essential for revealing the controlling role of the joint morphology. The diorite from the Guanshan Tunnel is investigated through anisotropic direct shear tests in this study. Based on shear damage quantification and acoustic emission (AE) localization techniques, the heterogeneous damage evolution law of joint surfaces under different joint compression strength (JCS), normal stress (σn), and morphology parameter (M) is studied. The results indicate that the joint surface morphology, shear damage, and AE parameters exhibit similar anisotropic characteristics in different shear directions. An increase in the morphology parameter leads to an increase in shear failure, with shear fracture energy and the number of fracture events showing an increasing trend. Meanwhile, the occurrence of a large number of fracture points shifts from the pre-peak nonlinear period to the post-peak period. However, the evolution process of fracture events exhibits certain similarities, though the morphology parameters are different in two opposite shear directions. Additionally, shear damage volume and fracture energy demonstrate consistency in spatial distribution and quantitative characteristics, while the linear scale factor between cumulative shear fracture energy and damage volume decreases with increasing joint surface strength. These findings assist in a better understanding of the anti-sliding property of joint surfaces and provide crucial clues for further exploration of joint surface failure mechanisms.

Unlocking a Fast Track for Magnesium Migration in Cu1.8S1-xSex via Anion-Tuning Chemistry.

Rechargeable magnesium batteries (rMBs) are promising candidates for next-generation batteries in which sulfides are widely used as cathode materials. The slow kinetics, low redox reversibility, and poor magnesium storage stability induced by the large Coulombic resistance and ionic polarization of Mg2+ ions have obstructed the development of high-performance rMBs. Herein, a Cu1.8S1-xSex cathode material with a two-dimensional sheet structure has been prepared by an anion-tuning strategy, achieving improved magnesium storage capacity and cycling stability. Element-specific synchrotron radiation analysis is evidence that selenium incorporation has indeed changed the chemical state of Cu species. Density functional theory calculations combined with kinetics analysis reveal that the anionic substitution endows the Cu1.8S1-xSex electrode with favorable charge-transfer kinetics and low ion diffusion barrier. The principal magnesium storage mechanisms and structural evolution process have been revealed in details based on a series of ex situ investigations. Our findings provide an effective heteroatom-tuning tactic of optimizing electrode structure toward advanced energy storage devices.

Causes and Consequences of Varying Transposable Element Activity: An Evolutionary Perspective.

Transposable elements (TEs) are genomic parasites found in nearly all eukaryotes, including humans. This evolutionary success of TEs is due to their replicative activity, involving insertion into new genomic locations. TE activity varies at multiple levels, from between taxa to within individuals. The rapidly accumulating evidence of the influence of TE activity on human health, as well as the rapid growth of new tools to study it, motivated an evaluation of what we know about TE activity thus far. Here, we discuss why TE activity varies, and the consequences of this variation, from an evolutionary perspective. By studying TE activity in nonhuman organisms in the context of evolutionary theories, we can shed light on the factors that affect TE activity. While the consequences of TE activity are usually deleterious, some have lasting evolutionary impacts by conferring benefits on the host or affecting other evolutionary processes.

Series arc-induced internal short circuit leading to thermal runaway in lithium-ion battery

With the widespread implementation of battery energy storage systems (BESSs), significant attention has been focused on issues involving electrical safety. The series arc hazard caused by loose connectors between batteries has become a serious problem. However, research findings for the evolution process of the series arc and the related hazard principle are still unclear. Therefore, in this study we focus on the series arc at the negative terminal of a 20 Ah prismatic lithium-ion battery, establish an experimental platform for the arc, and conduct research on the hazards process. Our results indicate that the arc can induce the thermal failure of the battery when the power supply voltage is 300 V and the circuit current is 15 A. Through a battery voltage analysis, computed tomography scans, and jellyroll disassembly, we uncover the evolution process and hazard laws of series arcs and clarify the failure pathways of arc-induced battery faults. The hotspots formed by arc melt the casing and cause electrolyte leakage. In addition, the heat transfer from the battery terminal to the jellyroll induces separator melting and internal short circuits in batteries. These cause an internal short circuit between the anode and the cathode, as well as combustion of the leaked electrolyte, which give rise to distinct thermal runaway behavior under different states of charge. By comparing runaway behavior with failures triggered by external heating, we clarify that the series arc is a novel risk factor that induces failure. This study addresses the gap in research related to arc effects on battery safety. This is crucial to the development of safe battery systems that do not present arc hazards.

Single-cell and spatial transcriptome assays reveal heterogeneity in gliomas through stress responses and pathway alterations.

Glioma is a highly heterogeneous malignancy of the central nervous system. This heterogeneity is driven by various molecular processes, including neoplastic transformation, cell cycle dysregulation, and angiogenesis. Among these biomolecular events, inflammation and stress pathways in the development and driving factors of glioma heterogeneity have been reported. However, the mechanisms of glioma heterogeneity under stress response remain unclear, especially from a spatial aspect. This study employed single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to explore the impact of oxidative stress response genes in oligodendrocyte precursor cells (OPCs). Our analysis identified distinct pathways activated by oxidative stress in two different types of gliomas: high- and low- grade (HG and LG) gliomas. In HG gliomas, oxidative stress induced a metabolic shift from oxidative phosphorylation to glycolysis, promoting cell survival by preventing apoptosis. This metabolic reprogramming was accompanied by epithelial-to-mesenchymal transition (EMT) and an upregulation of stress response genes. Furthermore, SCENIC (Single-Cell rEgulatory Network Inference and Clustering) analysis revealed that oxidative stress activated the AP1 transcription factor in HG gliomas, thereby enhancing tumor cell survival and proliferation. Our findings provide a novel perspective on the mechanisms of oxidative stress responses across various grades of gliomas. This insight enhances our comprehension of the evolutionary processes and heterogeneity within gliomas, potentially guiding future research and therapeutic strategies.

Ionospheric TEC Prediction in China during Storm Periods Based on Deep Learning: Mixed CNN-BiLSTM Method

Applying deep learning to high-precision ionospheric parameter prediction is a significant and growing field within the realm of space weather research. This paper proposes an improved model, Mixed Convolutional Neural Network (CNN)—Bidirectional Long Short-Term Memory (BiLSTM), for predicting the Total Electron Content (TEC) in China. This model was trained using the longest available Global Ionospheric Maps (GIM)-TEC from 1998 to 2023 in China, and underwent an interpretability analysis and accuracy evaluation. The results indicate that historical TEC maps play the most critical role, followed by Kp, ap, AE, F10.7, and time factor. The contributions of Dst and Disturbance Index (DI) to improving accuracy are relatively small but still essential. In long-term predictions, the contributions of the geomagnetic index, solar activity index, and time factor are higher. In addition, the model performs well in short-term predictions, accurately capturing the occurrence, evolution, and classification of ionospheric storms. However, as the predicted length increases, the accuracy gradually decreases, and some erroneous predictions may occur. The northeast region exhibits lower accuracy but a higher F1 score, which may be attributed to the frequency of ionospheric storm occurrences in different locations. Overall, the model effectively predicts the trends and evolution processes of ionospheric storms.

THE EVOLUTION AND REVOLUTION OF MARKETING MIX FROM 4P TO 4C TO 4E TO E-MARKETING MIX: A LITERATURE OVERVIEW

Marketing mix is an important concept in the world of marketing that was first introduced by an academic named Jerome McCarthy in the 1960s. The marketing mix was created in the early days of the marketing concept when physical products, physical distribution and mass communication were dominant. The marketing mix paradigm, in its famous version of the 4 Ps, went all the way through the evolution of marketing theory being object of discussion both in academic literature as well as in managerial practice. In today’s era of revolutionary change, the digital business represents the more recent of the business contexts and the one with the greater need for a differentiation and upgradation of the mix. Throughout this evolutionary process, researchers have given their views who think the 4 Ps paradigms is able to adapt to the environmental changes by including new elements inside each “P”, and some affirmed that the 4 Ps paradigm is obsolete and propose new paradigms. This paper aims to clarify these two different approaches to marketing mix evolution through a review of the main literature regarding e-marketing mix and its constituents which provides an up gradation to the existing elements of marketing mix as well as focusing on the development of marketing mix theory for the digital context. . In the context of the wars between the upstart internet retailers and the existing brick and mortar retailers, this study would pave the way to consider E-marketing as an innovated way to customer delight. The evolution of 'Product,' 'Price,' 'Place,' and 'Promotion' in the digital era requires a holistic understanding of consumer behavior, technological advancements, and the interconnected nature of the online world.

Uncovering structural variants in Creole cattle from Guadeloupe and their impact on environmental adaptation through whole genome sequencing.

Structural variants play an important role in evolutionary processes. Besides, they constitute a large source of inter individual genetic variation that might represent a major factor in the aetiology of complex, multifactorial traits. Their importance in adaptation is becoming increasingly evident in literature. Yet, the characterization of the genomic landscape of structural variants in local breeds remains scarce to date. Herein, we investigate patterns and gene annotation of structural variants in the Creole cattle from Guadeloupe breed using whole genome sequences from 23 bulls representative of the population. In total, we detected 32821 ascertained SV defining 15258 regions, representing ~ 17% of the Creole cattle genome. Among these, 6639 regions have not been previously reported in the Database of Genomic Variants archive. Average number of structural variants detected per individual in the studied population is in the same order of magnitude of that observed in indicine populations and higher than that reported in taurine breeds. We observe an important within-individual variability where approximately half of the detected structural variants have low frequency (MAF < 0.25). Most of the detected structural variants (55%) occurred in intergenic regions. Genic structural variants overlapped with 7793 genes and the predicted effect of most of them is ranked as "modifier". Among the structural variants that were predicted to have a high functional impact on the protein, a 5.5 Kb in length, highly frequent deletion on chromosome 2, affects ALPI, a gene associated with the interaction between gut microbiota and host immune system. The 6639 newly identified structural variants regions include three deletions and three duplications shared by more than 80% of individuals that are significantly enriched for genes related to tRNA threonylcarbamoyladenosine metabolic process, important for temperature adaptation in thermophilic organisms, therefore suggesting a potential role in the thermotolerance of Creole cattle from Guadeloupe cattle to tropical climate. Overall, highly frequent structural variants that are specific to the Creole cattle population encompass olfactory receptor and immunity genes as well as genes involved in muscle tone, muscle development and contraction. Beyond mapping and characterizing structural variants in the Creole cattle from Guadeloupe breed, this study provides valuable information for a better understanding of the potential role of chromosomal rearrangements in adaptive traits in cattle.

Hydrogeochemical Characteristics and Formation Processes of Ordovician Limestone Groundwater in Zhuozishan Coalfield, Northwest China

A comprehensive understanding of the characteristics and formation mechanisms of groundwater in mining areas is essential for the effective prevention of coal mine water and the rational management of groundwater resources. The objective of this study was to examine the hydrogeochemical characteristics and evolution of Ordovician groundwater in the Zhuozishan coal mine, located in the northwest region of China. A total of 34 groundwater samples were collected for hydrogeochemical analyses and the investigation of their evolution processes, with the aid of a piper trilinear diagram, a Gibbs diagram, and an ion ratio diagram. The results indicate that the concentration of sodium (Na+), potassium (K+), bicarbonate (HCO3−), chloride (Cl−), sulphate (SO42−), total dissolved solids (TDS), and pH increases from the recharge area to the discharge area, whereas the concentration of calcium (Ca2+) and magnesium (Mg2+) decreases. The hydrogeochemical characteristics of the runoff from Zhuozishan to Gongdeer coalfield and further southward display a notable north–south directional change. The groundwater process is primarily controlled by rock weathering action and cation exchange, with Na+ and K+ deriving primarily from cation exchange and only to a minor extent from halite dissolution. In conclusion, the northern part of the coalfield is characterised by a geological structure that creates a retention area with groundwater, resulting in an unordered runoff process with a complex formation mechanism. The middle region is devoid of geological constraints that would alter the flow direction, thus simplifying the process of groundwater formation. In contrast, the southern area experiences an increase in strata depth and fault blocking, which creates a retention zone, thereby rendering the groundwater formation process more complex. This research contributes to the effective management of groundwater resources in this coalfield and other mining sites.

Multi-UAV Path Planning Based on Cooperative Co-Evolutionary Algorithms with Adaptive Decision Variable Selection

When dealing with UAV path planning problems, evolutionary algorithms demonstrate strong flexibility and global search capabilities. However, as the number of UAVs increases, the scale of the path planning problem grows exponentially, leading to a significant rise in computational complexity. The Cooperative Co-Evolutionary Algorithm (CCEA) effectively addresses this issue through its divide-and-conquer strategy. Nonetheless, the CCEA needs to find a balance between computational efficiency and algorithmic performance while also resolving convergence difficulties arising from the increased number of decision variables. Moreover, the complex interrelationships between the decision variables of each UAV add to the challenge of selecting appropriate decision variables. To tackle this problem, we propose a novel collaborative algorithm called CCEA-ADVS. This algorithm reduces the difficulty of the problem by decomposing high-dimensional variables into sub-variables for collaborative optimization. To improve the efficiency of decision variable selection in the collaborative algorithm and to accelerate the convergence speed, an adaptive decision variable selection strategy is introduced. This strategy selects decision variables according to the order of solving single-UAV constraints and multi-UAV constraints, reducing the cost of the optimization objective. Furthermore, to improve computational efficiency, a two-stage evolutionary optimization process from coarse to fine is adopted.Specifically, the Adaptive Differential Evolution with Optional External Archive algorithm (JADE) is first used to optimize the waypoints of the UAVs to generate a basic path, and then, the Dubins algorithm is combined to optimize the trajectory, yielding the final flight path. The experimental results show that in four different scenarios involving 40 UAVs, the CCEA-ADVS algorithm significantly outperforms the Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and JADE algorithms in terms of path performance, running time, computational efficiency, and convergence speed. In addition, in large-scale experiments involving 500 UAVs, the algorithm also demonstrates good adaptability, stability, and scalability.

Authentication Methods Selection in Information Security through Hybrid AHP and EGT

The information security leader frequently encounters the challenge of choosing the appropriate defence strategy. Effective multi-criteria decision-making (MCDM) is essential in the field of information security for determining the optimal strategies that involve more than one party. To address this challenge, we propose a hybrid model that combines the strengths of the Analytic Hierarchy Process (AHP) with Evolutionary Game Theory (EGT). The hybrid model helps the information security leader assess the criteria for security controls and make the optimal decisions to protect the organization's data. Initially, the AHP is utilized to assess the criteria of information security control. Subsequently, the priority of the alternatives is established through evaluating these criteria. Furthermore, we will construct a defence-attack circumstance using the EGT framework, which involves formulating strategies and determining payoffs for both the information security leaders and attackers involved. We utilize the replicator dynamic to examine the process of evolution in the game, resulting in the determination of the optimal strategy. A case study is conducted to determine the optimal strategy for information security leaders and attackers. The result indicates that the best defence strategy is password protection, followed by token-based and biometric-based protections. On the other hand, the optimal strategy for attackers is no attack, followed by attack and moderate attack. This study contributes to the multi-criteria decision-making (MCDM) problem’s solving by considering the dynamic aspect between both defender and attacker in the context of information security.

Mantle dynamics of the stagnating slab: A case study of Shandong Peninsula and adjacent areas

The Shandong Peninsula is located in the eastern part of the North China Craton (NCC). Influenced by the collision between the North and South China blocks and the subduction of the Pacific Plate, the tectonic evolution process is highly complex. Previous studies have proposed that the thick cratonic root beneath the eastern NCC has been destructed. To better understand the relationship between the craton reactivation and the deep subduction, more constraints on the topography variations of the mantle transition zone (MTZ) discontinuities are required. In this study, we stacked 9073 P‐to‐S receiver functions calculated from 129 broadband seismic stations to image the depth variations of the MTZ discontinuities beneath the Shandong Peninsula and its adjacent area. To decrease the influence of velocity anomaly above the MTZ discontinuities, we converted the apparent depths into corrected depth using regional and global 3D velocity models. The apparent depth of the 410‐km discontinuity exhibits a depression of approximately 6 km, which normalizes after velocity correction. This implies the existence of the low‐velocity anomaly in the upper mantle, possibly caused by slab dehydration and water infiltration into the upper mantle. The significant depression of the 660‐km discontinuity indicated the presence of the cold Pacific slab stagnating at the base of the MTZ. The gradual westward depression of the 660‐km discontinuity by 50 km could provide evidence for the sinking of the western margin of the flat‐lying subducting Pacific slab in the MTZ beneath the Shandong Peninsula.

Measurement and Spatial-Temporal Evolution of Industrial Carbon Emission Efficiency in Western China

As it is an important industrial base in China, it is of great significance to improve the industrial carbon emission efficiency in the western region to promote the low-carbon sustainable development of the region. This paper selects the input–output panel data of 11 provinces in western China from 2010 to 2021, and adopts the three-stage DEA model to measure the industrial carbon emission efficiency in western China under a non-traditional geographic division at the overall and regional levels and analyze its influencing factors. The Dagum Gini coefficient, its decomposition method, and the kernel density estimation method are used to analyze the regional differences and dynamic evolution process of industrial carbon emission efficiency in the western region. The results of the study show that (1) after removing environmental and random factors, the industrial carbon emission efficiency in western China has been improved, but there are inter-regional differences, characterized by “the third region &gt; the second region &gt; the first region”; (2) the levels of green development, shared development, innovative development, and coordinated development have a positive impact on the improvement of industrial carbon emission efficiency in western China, while the level of industrialization has a relatively smaller influence, and economic development, government support, open development level, and energy consumption structure have not yet played a significant role; (3) the spatial differences in the efficiency of industrial carbon emissions in western China have generally increased during the sample period, with inter-regional differences being the main source; and (4) the industrial carbon emission efficiency in western China is characterized by overall improvements in time and space but with stage differences and multi-polarization of regional differences. This study has a certain reference value for improving industrial carbon emission efficiency in western China.

Pulsar Population Synthesis with Magnetorotational Evolution: Constraining the Decay of the Magnetic Field

We present a population synthesis model for normal radio pulsars in the Galaxy incorporating the latest developments in the field and the magnetorotational evolution processes. Our model considers spin-down with a force-free magnetosphere and the decay of the magnetic field strength and its inclination angle. The simulated pulsar population is fit to a large observation sample that covers the majority of radio surveys using the Markov Chain Monte Carlo technique. We compare the distributions of four major observables—spin period (P), spin-down rate ( Ṗ ), dispersion measure, and radio flux density—using accurate high-dimensional Kolmogorov–Smirnov statistics. We test two B-field decay scenarios, an exponential model motivated by ohmic dissipation and a power-law model motivated by the Hall effect. The former clearly provides a better fit, and it can successfully reproduce the observed pulsar distributions with a decay timescale of 8.3−3.0+3.9 Myr. The result suggests that significant B-field decay in aged pulsars and ohmic dissipation could be the dominant process.

Cryogenic damage behavior of carbon fiber reinforced polymer composite laminates via fiber-optic acoustic emission

Cryogenic temperatures cause significant changes in the mechanical response and microscopic failure mechanisms of carbon fiber reinforced polymer (CFRP) composites. However, the mechanisms by which cryogenic temperatures affect composites are not yet fully understood due to a lack of adequate in-situ characterization techniques. Herein, the cryogenic damage evolution process of CFRP composites was investigated by constructed fiber-optic acoustic emission (AE) detection system. Tensile damage behavior of woven CFRP composites at 300 K, 153 K and 77 K was evaluated by AE characteristic response and cluster analysis combined with scanning electron microscopy. According to the results, increased damage activity within the composites at cryogenic condition promoted the release of mechanical energy, as well as an increase in the contribution of fiber damage to overall damage, which are the dominant micro-strengthening mechanisms of composite laminates under cryogenic conditions. This study provides a novel explanation for understanding the cryogenic damage behavior of composites.

Formation and evolution of nanobubbles in CH4-H2O-Alcohol system: Insight into the effect of alcohol chain length from molecular dynamics simulations

Nanobubbles (NBs) which are gas filled cavities of nanometre dimensions present in liquids attracted increasing attention in the recent years due to their application in various fields such as chemistry, biology, medicine etc. An important aspect of NB research is the study of effect of additives on formation and evolution of these bubbles. The present study examined by applying molecular dynamics simulations, the formation and evolution of methane NBs in the CH4-H2O-Alcohol system, which is known to form during alcohol induced dissociation of CH4 hydrates in the natural gas extraction process. The effect of alcohol type and concentration on NB formation and evolution was examined through simulations of CH4-H2O-CH3OH, CH4-H2O-C2H5OH and CH4-H2O-nC3H7OH systems. The study revealed that increase in both concentration and the alkyl chain length of alcohols promoted NB formation. Alcohol molecules are found to enhance NB nucleation through accumulation near the NB-liquid interface resulting in a decrease in the surface tension (γ) at the interface. These effects become more pronounced as the alkyl chain length increases which explains the enhanced NB formation in systems containing nC3H7OH and C2H5OH compared to those containing CH3OH. The mechanism of formation and evolution of NBs is found to significantly depend on the type of alcohol present. NBs are found to nucleate at multiple locations in the systems containing nC3H7OH and C2H5OH which eventually coalesce to form a single large stable NB. In the presence of NBs which vary significantly in size, bubble growth was also found to occur through Ostwald ripening which involves transfer of CH4 from smaller NB to the larger one. In contrast, in the CH4-H2O-CH3OH system, primarily a single NB nucleated which grew in size through absorption of CH4 molecules dissolved in the liquid, rather than through coalescence or Ostwald ripening. The observed influence of alcohol type on the process of NB evolution is explained by examining the influence of alkyl chain length on γ and diffusivity of CH4 molecules. Due to the role of NBs on methane hydrate regeneration from the hydrate melt, we examined the influence of NB in the CH4-H2O-Alcohol system on the organization of water molecules (HSWs) present in the hydration shell of dissolved CH4. The value of F4 order parameter of HSWs and the number of hydrogen bonded water rings in the hydration shell of CH4 were analysed. The value of F4 order parameter indicate that the hydrophobic alkyl chain of alcohol induced hydrate like arrangement of HSWs, which is more pronounced in the case of alcohol with longer alkyl chain. However, alcohol molecules are also found to dislodge HSWs around CH4 resulting in a decrease in the number of water rings around dissolved CH4 which is not conducive to hydrate formation. These observations are consistent with the reported dual effect of alcohol on hydrate formation with alcohol promoting hydrate formation at low concentrations and inhibiting at high concentrations.

Optimization model for urban ecological network connectivity considering geospatial constraints

ABSTRACT Connectivity enhancement of ecological networks is an efficient and advantageous spatial planning strategy, and it is a hot research topic to analyze ecological networks based on complex systems theory and perform model optimization. As a typical geographic network, the evolution process of ecological network, such as node and edge growth, will be subject to geospatial constraints, and the current research lacks optimization models that take the geospatial constraints into account. This study focused on urban ecological network connectivity and the distribution of nodes as well as structural fractures where the connectivity of the ecological network was hindered were analyzed. Then it introduced a local world network model to optimize network connectivity and designed a network growth mechanism with limited added nodes and optimal connections. An ecological network optimization model considering geospatial constraints was constructed, and the network closeness index was used to fit the objective function curve to select optimization schemes. This study used Shenzhen, China as a case study, and the results indicated that the initial ecological network was significantly fractured by urban construction. In the optimization scenario, the network evolution reached its optimal state at the simulation step size of t = 26. At this point, the closeness index of the optimized network was increased by 15%. The optimization model constructed in this paper emphasizes the importance of functional restoration of existing network nodes, and the results of the study can provide support for ecospatial layout optimization and management.

Evolution of the Cytomegalovirus RL11 Gene Family in Old World monkeys and Great Apes

Abstract Cytomegalovirus is a genus of herpesviruses, members of which share a long history of co-evolution with their primate hosts including Great Apes, Old and New World monkeys. These viruses are ubiquitous within their host populations and establish lifelong infection in most individuals. Although asymptomatic in healthy individuals, infection poses a significant risk to individuals with a weakened or underdeveloped immune system. The genome of human cytomegalovirus is the largest among human-infecting viruses, and comprises at least fifteen separate gene families, which may have arisen by gene duplication. Within human cytomegalovirus, the RL11 gene family is the largest. RL11 genes are non-essential in vitro but have immune evasion roles that are likely critical to persistence in vivo. These genes demonstrate an extreme level of inter-species and intra-strain sequence diversity, that makes it challenging to deduce the evolutionary relationships within this gene family. Understanding the evolutionary relationships of these genes, especially accurate ortholog identification, is essential for reconstructing ancestral genomes, deciphering gene repertoire and order, and enabling reliable functional analyses across the Cytomegalovirus species, thereby offering insights into evolutionary processes, genetic diversity, and the functional significance of genes. In this work, we combined in silico genome screening with sequence-based and structure-guided phylogenetic analysis to reconstruct the evolutionary history of the RL11 gene family. We confirmed that RL11 genes are unique to cytomegaloviruses of Old World monkeys and Great Apes, showing that this gene family was formed by multiple early duplication events and later lineage-specific losses. We identified four main clades of RL11 genes and showed that their expansions were mainly lineage-specific and happened independently in cytomegaloviruses of Great Apes, African Old World monkeys and Asian Old World monkeys. We also identified groups of orthologous genes across the Cytomegalovirus tree showing that some human cytomegalovirus-specific RL11 genes emerged before the divergence of human and chimpanzee cytomegaloviruses but were subsequently lost in the latter. The extensive and dynamic species-specific evolution of this gene family suggests their functions target elements of host immunity that have similarly co-evolved during speciation.

Evolutionary origin and distribution of leucine-rich repeat-containing G protein-coupled receptors in insects

Leucine-rich repeat-containing G protein-coupled receptors (LGRs) are crucial for animal growth and development. They were categorized into four types (A, B, C1, and C2) based on their sequence and domain structures. Despite the widespread distribution of LGRs across bilaterians, a thorough investigation of their distribution and evolutionary history remains elusive. Recent studies insect LGRs, especially the emergence of type C2 LGRs in various hemimetabolous insects, had prompted our study to address these problems. Initially, we traced the origins of LGRs by exploiting data from 99 species spanning 11 metazoan phyla, and discovered that type A and B LGRs originated from sponges, while type C LGRs originated from cnidarians. Subsequently, through comprehensive genomic and transcriptomic analyses across 565 species across 25 orders of insects, we found that both type A and C1 LGRs divided into two gene clusters. These clusters can be traced back to basal Insecta and an early ancestor of the Arthropoda, respectively. Furthermore, the absence of type B LGRs in wingless insects suggests a role in wing development, while the absence of type C2 LGRs in holometabolous insects hints at novel functions unrelated to insect metamorphosis. According to the origin of LGRs and the investigation of LGRs in insects, we speculated that type A and B LGRs appeared first among four types of LGRs, type A evolved into type C LGRs later, and type A and C1 LGRs independently duplicated during the evolutionary process. This study provides a more comprehensive view of the evolution of LGR genes than previously available, and sheds light on the evolutionary history and significance of LGRs in insect biology.