Hasil untuk "Evolution"

H. Ellegren

Jianan He, Joshua D. Butson, Ruijia Gu et al.

Abstract MXenes, a novel member of the 2D material family, shows promising potential in stabilizing isolated atoms and maximizing the atom utilization efficiency for catalytic applications. This review focuses on the role of MXenes as support for single‐atom catalysts (SACs) for various electrochemical reactions, namely the hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), carbon dioxide reduction reaction (CO2RR), and nitrogen reduction reaction (NRR). First, state‐of‐the‐art characterization and synthesis methods of MXenes and MXene‐supported SACs are discussed, highlighting how the unique structure and tunable functional groups enhance the catalytic performance of pristine MXenes and contribute to stabilizing SAs. Then, recent studies of MXene‐supported SACs in different electrocatalytic areas are examined, including experimental and theoretical studies. Finally, this review discusses the challenges and outlook of the utilization of MXene‐supported SACs in the field of electrocatalysis.

Yongyun Chen, Qiusheng Gu, Junhui Fan et al.

Accretion supermassive black holes in the center of active galaxies usually produce “jet”-collimated bipolar outflows of relativistic particles. Magnetic fields near the black hole event horizon may play a crucial role in the formation of jets/outflows. Both theory and observation indicate that jets/outflows driven by centrally active supermassive black holes have a feedback effect on the overall properties of the host galaxies. Therefore, the magnetic field is a key ingredient for the formation and evolution of galaxies. Here, we report a clear correlation between the magnetic field of jets and star formation rate for a large sample of 96 galaxies hosting supermassive black holes, which suggests that the star formation of active galactic nuclei host galaxies may be powered by the jets.

Li Jia, Zhuojun Liu, Yisen Li

Abstract This study analyzes the spatiotemporal dynamics of rural settlement evolution in Guangdong Province, China, examining their transformation amid rapid urbanization and industrialization over the past 20 years. Rural settlements serve as primary spatial carriers for production and living activities, embodying multiple functions including production, living, ecological, and cultural aspects. Using GIS-based analytical tools, including landscape pattern indices, average nearest neighbor index, kernel density estimation, and geographical detector methods, we examined settlement evolution patterns and their driving factors. Results show a continuous decline in settlement numbers, while patch areas exhibited a U-shaped trend of decreasing then increasing. Settlement patterns shifted from “reduction” to “integration”, with intensifying spatial agglomeration over time. The Pearl River Delta and Eastern Guangdong regions followed similar trajectories, reflecting the impact of urbanization and industrialization on rural development. Multiple factors, including natural conditions, socioeconomic variables, and locational accessibility, drove these changes. The spatial distribution of rural settlements demonstrates an overall trend of agglomeration, which has gradually intensified over time, leading to significant variations in settlement density across different regions. The findings reveal significant regional disparities and temporal changes in settlement patterns, highlighting the complex interplay between rural transformation and urban development. This research contributes to understanding rural transformation processes in developing countries and emphasizes the need for differentiated approaches in spatial planning and rural revitalization strategies to address the challenges of disordered land expansion and population hollowing while promoting sustainable rural development.

Xinyu Xu, Yousry A. El-Kassaby, Sijia Liu et al.

Cycads, renowned as “living fossils”, are among the most ancient extant seed plants, playing a crucial role in understanding plant evolution and sex differentiation. Despite their importance, research on their genetics and sex differentiation remains scarce. This study investigates three species, represented by six samples, collected from various regions in Fujian Province, China, using whole-genome resequencing on the Illumina platform. The sequence data underwent rigorous quality control, alignment, and variant detection, focusing on SNP and InDel distribution and annotation. Among the studied species, <i>Cycas revoluta</i> exhibited the highest number of SNPs and the greatest heterozygosity values. Based on SNP data, phylogenetic trees and principal component analysis revealed distinct clusters, with the three <i>C. revoluta</i> samples forming one cluster, while the two <i>C. szechuanensis</i> samples and the <i>C. taiwaniana</i> sample were grouped separately. Gene function using COG and GO annotations, and KEGG enrichment analysis, all highlighted differences in genomic structure and functional gene distribution between male and female <i>cycads</i>. Notably, genes associated with sex differentiation, such as MADS-box and auxin-responsive protein genes, were shown, while other transcription factors showed distinct annotations and enrichment patterns based on sex. This study improves our understanding of genetic variation, evolutionary relationships, and gene enrichment in <i>cycads</i>, providing a foundation for conservation, cultivation, and insights into sex differentiation mechanisms in these ancient plants.

Duc Kieu, Tung Kieu, Peng Han et al.

Due to the global trend towards urbanization, people increasingly move to and live in cities that then continue to grow. Traffic forecasting plays an important role in the intelligent transportation systems of cities as well as in spatio-temporal data mining. State-of-the-art forecasting is achieved by deep-learning approaches due to their ability to contend with complex spatio-temporal dynamics. However, existing methods assume the input is fixed-topology road networks and static traffic time series. These assumptions fail to align with urbanization, where time series are collected continuously and road networks evolve over time. In such settings, deep-learning models require frequent re-initialization and re-training, imposing high computational costs. To enable much more efficient training without jeopardizing model accuracy, we propose the Topological Evolution-aware Framework (TEAM) for traffic forecasting that incorporates convolution and attention. This combination of mechanisms enables better adaptation to newly collected time series, while being able to maintain learned knowledge from old time series. TEAM features a continual learning module based on the Wasserstein metric that acts as a buffer that can identify the most stable and the most changing network nodes. Then, only data related to stable nodes is employed for re-training when consolidating a model. Further, only data of new nodes and their adjacent nodes as well as data pertaining to changing nodes are used to re-train the model. Empirical studies with two real-world traffic datasets offer evidence that TEAM is capable of much lower re-training costs than existing methods are, without jeopardizing forecasting accuracy.

Yang Cao, Jingzheng Luan

Differential Evolution (DE) is widely recognized as a highly effective evolutionary algorithm for global optimization. It has proven its efficacy in tackling diverse problems across various fields and real-world applications. DE boasts several advantages, such as ease of implementation, reliability, speed, and adaptability. However, DE does have certain limitations, such as suboptimal solution exploitation and challenging parameter tuning. To address these challenges, this research paper introduces a novel algorithm called Enhanced Binary JADE (EBJADE), which combines differential evolution with multi-population and elites regeneration. The primary innovation of this paper lies in the introduction of strategy with enhanced exploitation capabilities. This strategy is based on utilizing the sorting of three vectors from the current generation to perturb the target vector. By introducing directional differences, guiding the search towards improved solutions. Additionally, this study adopts a multi-population method with a rewarding subpopulation to dynamically adjust the allocation of two different mutation strategies. Finally, the paper incorporates the sampling concept of elite individuals from the Estimation of Distribution Algorithm (EDA) to regenerate new solutions through the selection process in DE. Experimental results, using the CEC2014 benchmark tests, demonstrate the strong competitiveness and superior performance of the proposed algorithm.

Junpeng Zheng, Ruhao Zhao, Cong Zhang et al.

Generalized two-dimensional (2D) Airy beam is a kind of self-accelerating beam with variable initial angle between its two wings, manifested itself as an initial angle determined parabolic trajectory during the free-space propagation. However, the independent and flexible manipulation of both the transverse optical field and longitudinal trajectory of the generalized 2D Airy beam has not been achieved yet which limits its application in the various fields. Herein, we report on tailoring of the propagation properties of the generalized 2D Airy beam based on the catastrophe theory, where analytical expression of its propagation trajectory is derived. In order to clarify the relationship between the transverse optical field distribution and the longitudinal trajectory, we analytically put forward a generation vector, facilitating the tailoring of both longitudinal trajectory and transverse distribution of optical field simultaneously. Consequently, we can effectively generate the generalized 2D Airy beam and precisely manipulate the evolution of its peak intensity. Once the initial and terminal points of trajectory are determined in advance, we can flexibly tailor the trajectory of 2D Airy beam, with the help of corresponding generation vector. Meanwhile, when the longitudinal trajectory is fixed, we can flexibly rotate the transverse optical field distribution of the generalized 2D Airy beam and manipulate its initial angle. Experimental verifications of the manipulation capabilities for the longitudinal trajectory, initial angle, and the rotation of transverse optical field are provided to validate our theoretical results.

Diogo L. Pires, Igor Erovenko, Mark Broom

Evolutionary models are used to study the self-organisation of collective action, often incorporating population structure due to its ubiquitous presence and long-known impact on emerging phenomena. We investigate the evolution of multiplayer cooperation in mobile structured populations, where individuals move strategically on networks and interact with those they meet in groups of variable size. We find that the evolution of multiplayer cooperation primarily depends on the network topology and movement cost while using different stochastic update rules seldom influences evolutionary outcomes. Cooperation robustly co-evolves with movement on complete networks and structure has a partially detrimental effect on it. These findings contrast an established wisdom in evolutionary graph theory that cooperation can only emerge under some update rules and if the average degree is low. We find that group-dependent movement erases the locality of interactions, suppresses the impact of evolutionary structural viscosity on the fitness of individuals, and leads to assortative behaviour that is much more powerful than viscosity in promoting cooperation. We analyse the differences remaining between update rules through a comparison of evolutionary outcomes and fixation probabilities.

Yue Zhang

Developmental bias plays a major role in phenotypic evolution. Some researchers have argued that phenotypes, regulated by development, can only evolve along restricted trajectory under certain scenarios, such as the case for mammalian molar size ratios. However, this view has been challenged. Broadly speaking, sources for phenotypic variation remain largely unknown. The study here presents a generalized Inhibitory Cascade Model and explains that the original model described only means of phenotypes resulting from selection when viewed under a higher taxonomic scope. Consequently, I propose the combined property of development: certainty, when the prior intersegmental inhibition is strong, and uncertainty, when the opposite holds. This property potentially not only explains counterintuitively high levels of developmental instability, but also plays an essential role in generating phenotypic variation.

A. Haddad, C. Chiarabba, M. Lazar et al.

Abstract The Dead Sea Fault (DSF) is a crustal‐scale continental transform fault separating the African and the Arabian plates. Neogene to Quaternary volcanic activity is well‐spread in Northern Israel. Yet, the origin of the magmas that fed the eruptions is still unpinned. Our local earthquake tomography depicts velocity distributions typical of rifting settings. At 9 km depth, a prominent high Vp/Vs anomaly marks the presence of cooling melts. We propose that protracted transtension along the DSF caused crustal thinning promoting the emplacement of magmatic bodies. Crustal emplacements of magmas in Northern Israel reconcile multiple observations, including the high geothermal gradient, the prominent magnetic anomalies and the traces of mantle‐derived fluids in the springs across the Sea of Galilee. We provide a compelling evidence for rifting in segments of the DSF and identify the potential source of magmatism that fed part of the volcanic activity of the area.

Yaya Wu, Yan Wen, Anan Guo et al.

This work used electroshocking treatment (EST) plus external loading to regulate the microstructure of titanium matrix composites (TMCs). The external loading was 0.3 MPa. After EST plus external loading with 0.3 MPa, the α was reduced to 2.53 μm in size. The percentage of high angle grain boundaries (HAGBs) in α increased first and then decreased. The percent of HAGBs in TiB decreased, mainly due to the introduction of abundant dislocations in the TiB/matrix interface after EST. After EST, the maximum texture strength of TiB decreased from 13.09 to 12.97, and that of α decreased from 3.11 to 1.58. After EST under external loading with 0.3 MPa, the maximum texture strength of TiB decreased to 8.10. The orientation of TiB experienced significant variation. TEM results showed that TiB and α formed a distorted interface after EST under external loading with 0.3 MPa. The interplanar spacing of TiB and α was varied. All results show that the texture of TMCs can be relieved by EST plus external loading with 0.3 MPa. It is mainly attributed to the thermal and athermal effects and the imposed external loads with EST. EST plus external loading provides a new method for manipulating the microstructure of TMCs.

SOCHICHIU, GRETA-CORNELIA , SAVIŢKAIA-BARAGHIN, IARÎNA

In the twentieth century, in the field of textile art there were exhibition events that caused major changes in the attitude of artists and the public towards the two-dimensional or three-dimensional textile art object. Throughout its evolution, the textile art has undergone transformations and turning points, in line with the dominant artistic trends and styles of the time. From the first manifestations in consecrated form, that of a two-dimensional decorative object made of textile fibers in specific weaving techniques, and until now it has oscillated one after the other between the status of first-rate art and applied art, being closely linked to the craft of weaving that preceded it.

Grégoire Clarté, Robin J. Ryder

We propose a model of the evolution of a matrix along a phylogenetic tree, in which transformations affect either entire rows or columns of the matrix. This represents the change of both lexical and phonological aspects of linguistic data, by allowing for new words to appear and for systematic phonological changes to affect the entire vocabulary. We implement a Sequential Monte Carlo method to sample from the posterior distribution, and infer jointly the phylogeny, model parameters, and latent variables representing cognate births and phonological transformations. We successfully apply this method to synthetic and real data of moderate size.

Louise G. Køhler, Bastian Huwer, José Martín Pujolar et al.

This data article includes a qualitative and quantitative description of the gelatinous macrozooplankton community of the North Sea during January-February 2021. Sampling was conducted during the 1st quarter International Bottom Trawl Survey (IBTS) on board the Danish R/V DANA (DTU Aqua Denmark) and the Swedish R/V Svea (SLU Sweden), as part of the ichthyoplankton investigation during night-time. A total of 147 stations were investigated in the western, central and eastern North Sea as well as the Skagerrak and Kattegat. Sampling was conducted with a 13 m long Midwater Ring Net (MIK net, Ø 2 m, mesh size 1.6 mm, cod end with smaller mesh size of 500 µm), equipped with a flow meter. The MIK net was deployed in double oblique hauls from the surface to c. 5 m above the sea floor [1,2]. Samples were visually analysed unpreserved on a light table and/or with a stereomicroscope or magnifying lamp within 2 hours after catch. A total of 13,510 individuals were counted/sized. Twelve gelatinous macrozooplankton species or genera were encountered, namely the hydrozoan Aequorea vitrina, Aglantha digitale, Clytia spp., Leuckartiara octona, Tima bairdii, Muggiaea atlantica; the scyphozoans Cyanea capillata and Cyanea lamarckii and the ctenophores Beroe spp., Bolinopsis infundibulum, Mnemiopsis leidyi, Pleurobrachia pileus. Abundance data are presented on a volume specific (m−3) and area specific (m−2) basis. Size data have been used to estimate wet weights based on published length-weight regressions (see Table 1). For the groups i) hydrozoan jellyfish, ii) scyphozoan jellyfish, iii) ctenophores, as well as iv) grouped gelatinous macrozooplankton, spatial weight specific distribution patterns are presented. This unpublished dataset contributes baseline information about the gelatinous macrozooplankton diversity and its specific distribution patterns in the extended North Sea area during winter (January-February) 2021. These data can be an important contribution to address global change impacts on marine systems, especially considering gelatinous macrozooplankton abundance changes in relation to anthropogenic stressors.

Xiuhui Zhai, Xinle Pang, Xiang Wang et al.

A facile one-pot hydrothermal method has been demonstrated for the fabrication of an innovative hydrangea-like NiSe/FeSe2 nanocatalyst for boosting oxygen evolution reaction (OER). Benefitting from the advantages of the porous architecture, high specific surface area, facilitated electron transfer rate, an ultralow overpotential of merely 210 mV is required for the optimized NiSe/FeSe2(1:1.5) to drive the electrocatalytic water oxidation to reach to 10 mA cm−2. Moreover, by equipping NiSe/FeSe2(1:1.5) with Pt/C for electrochemical water splitting, a cell potential of merely 1.60 V is demanded to attain 10 mA cm−2, even outperforming the IrO2 ‖ Pt/C couple. More importantly, the structure and morphology of NiSe/FeSe2(1:1.5) are still well maintained after a long-term chronopotentiometry test. This work opens a new avenue for constructing effective and durable non-precious electrocatalysts for OER.

Evan K. Irving-Pease, Rasa Muktupavela, Michael Dannemann et al.

Genetic association data from national biobanks and large-scale association studies have provided new prospects for understanding the genetic evolution of complex traits and diseases in humans. In turn, genomes from ancient human archaeological remains are now easier than ever to obtain, and provide a direct window into changes in frequencies of trait-associated alleles in the past. This has generated a new wave of studies aiming to analyse the genetic component of traits in historic and prehistoric times using ancient DNA, and to determine whether any such traits were subject to natural selection. In humans, however, issues about the portability and robustness of complex trait inference across different populations are particularly concerning when predictions are extended to individuals that died thousands of years ago, and for which little, if any, phenotypic validation is possible. In this review, we discuss the advantages of incorporating ancient genomes into studies of trait-associated variants, the need for models that can better accommodate ancient genomes into quantitative genetic frameworks, and the existing limits to inferences about complex trait evolution, particularly with respect to past populations.

Juan Santos, José Carcione, Gabriela Savioli et al.

A pandemic caused by a new coronavirus (COVID-19) has spread worldwide, inducing an epidemic still active in Argentina. In this chapter, we present a case study using an SEIR (Susceptible-Exposed-Infected-Recovered) diffusion model of fractional order in time to analyze the evolution of the epidemic in Buenos Aires and neighboring areas (Región Metropolitana de Buenos Aires, (RMBA)) comprising about 15 million inhabitants. In the SEIR model, individuals are divided into four classes, namely, susceptible (S), exposed (E), infected (I) and recovered (R). The SEIR model of fractional order allows for the incorporation of memory, with hereditary properties of the system, being a generalization of the classic SEIR first-order system, where such effects are ignored. Furthermore, the fractional model provides one additional parameter to obtain a better fit of the data. The parameters of the model are calibrated by using as data the number of casualties officially reported. Since infinite solutions honour the data, we show a set of cases with different values of the lockdown parameters, fatality rate, and incubation and infectious periods. The different reproduction ratios R0 and infection fatality rates (IFR) so obtained indicate the results may differ from recent reported values, constituting possible alternative solutions. A comparison with results obtained with the classic SEIR model is also included. The analysis allows us to study how isolation and social distancing measures affect the time evolution of the epidemic.

Julie Rowlett, Carl-Joar Karlsson

In numerous contexts, individuals may decide whether they take actions to mitigate the spread of disease, or not. Mitigating the spread of disease requires an individual to change their routine behaviours to benefit others, resulting in a 'disease dilemma' similar to the seminal prisoner's dilemma. In the classical prisoner's dilemma, evolutionary game dynamics predict that all individuals evolve to 'defect.' We have discovered that when the rate of cooperation within a population is directly linked to the rate of spread of the disease, cooperation evolves under certain conditions. For diseases which do not confer immunity to recovered individuals, if the time scale at which individuals receive information is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges. Moreover, in the limit as mitigation measures become increasingly effective, the disease can be controlled, and the rate of infections tends to zero. Our model is based on theoretical mathematics and therefore unconstrained to any single context. For example, the disease spreading model considered here could also be used to describe social and group dynamics. In this sense, we may have discovered a fundamental and novel mechanism for the evolution of cooperation in a broad sense.

Rui Wang, Yuta Hozumi, Yong-Hui Zheng et al.

The transmission and evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are of paramount importance to the controlling and combating of coronavirus disease 2019 (COVID-19) pandemic. Currently, near 15,000 SARS-CoV-2 single mutations have been recorded, having a great ramification to the development of diagnostics, vaccines, antibody therapies, and drugs. However, little is known about SARS-CoV-2 evolutionary characteristics and general trend. In this work, we present a comprehensive genotyping analysis of existing SARS-CoV-2 mutations. We reveal that host immune response via APOBEC and ADAR gene editing gives rise to near 65\% of recorded mutations. Additionally, we show that children under age five and the elderly may be at high risk from COVID-19 because of their overreacting to the viral infection. Moreover, we uncover that populations of Oceania and Africa react significantly more intensively to SARS-CoV-2 infection than those of Europe and Asia, which may explain why African Americans were shown to be at increased risk of dying from COVID-19, in addition to their high risk of getting sick from COVID-19 caused by systemic health and social inequities. Finally, our study indicates that for two viral genome sequences of the same origin, their evolution order may be determined from the ratio of mutation type C$>$T over T$>$C.