Hasil untuk "Evolution"

M. Perc, A. Szolnoki

Prevalence of cooperation within groups of selfish individuals is puzzling in that it contradicts with the basic premise of natural selection. Favoring players with higher fitness, the latter is key for understanding the challenges faced by cooperators when competing with defectors. Evolutionary game theory provides a competent theoretical framework for addressing the subtleties of cooperation in such situations, which are known as social dilemmas. Recent advances point towards the fact that the evolution of strategies alone may be insufficient to fully exploit the benefits offered by cooperative behavior. Indeed, while spatial structure and heterogeneity, for example, have been recognized as potent promoters of cooperation, coevolutionary rules can extend the potentials of such entities further, and even more importantly, lead to the understanding of their emergence. The introduction of coevolutionary rules to evolutionary games implies, that besides the evolution of strategies, another property may simultaneously be subject to evolution as well. Coevolutionary rules may affect the interaction network, the reproduction capability of players, their reputation, mobility or age. Here we review recent works on evolutionary games incorporating coevolutionary rules, as well as give a didactic description of potential pitfalls and misconceptions associated with the subject. In addition, we briefly outline directions for future research that we feel are promising, thereby particularly focusing on dynamical effects of coevolutionary rules on the evolution of cooperation, which are still widely open to research and thus hold promise of exciting new discoveries.

Á. Rivas, S. Huelga

J. Losos

Convergent evolution of similar phenotypic features in similar environmental contexts has long been taken as evidence of adaptation. Nonetheless, recent conceptual and empirical developments in many fields have led to a proliferation of ideas about the relationship between convergence and adaptation. Despite criticism from some systematically minded biologists, I reaffirm that convergence in taxa occupying similar selective environments often is the result of natural selection. However, convergent evolution of a trait in a particular environment can occur for reasons other than selection on that trait in that environment, and species can respond to similar selective pressures by evolving nonconvergent adaptations. For these reasons, studies of convergence should be coupled with other methods—such as direct measurements of selection or investigations of the functional correlates of trait evolution—to test hypotheses of adaptation. The independent acquisition of similar phenotypes by the same genetic or developmental pathway has been suggested as evidence of constraints on adaptation, a view widely repeated as genomic studies have documented phenotypic convergence resulting from change in the same genes, sometimes even by the same mutation. Contrary to some claims, convergence by changes in the same genes is not necessarily evidence of constraint, but rather suggests hypotheses that can test the relative roles of constraint and selection in directing phenotypic evolution.

A. Einstein, L. Infeld

Boyan Liu, Boyan Liu, Xufeng Liu et al.

BackgroundA growing body of research indicates that mechanobiology plays a pivotal role in cancer pathogenesis and holds considerable therapeutic potential. However, a comprehensive bibliometric analysis of this interdisciplinary field is lacking, partly due to challenges in cross-database data integration. In this study, we aim to construct a systematic knowledge map of cancer mechanobiology to delineate its research progress, core structure, and emerging trends.MethodsIn this study, we integrated 1,947 publications from the Web of Science (WoS) Core Collection and Scopus (1976–2025). To address cross-database heterogeneity, we developed a novel, customized, multi-stage data-standardization workflow combining a bespoke Python parsing engine with fuzzy string matching algorithms and manual verification. The unified dataset was analyzed using CiteSpace, VOSviewer, and Bibliometrix.ResultsThe United States and China are the most prolific countries, while the University of California system is the most productive institution. Valerie M. Weaver is the most published author, while Matthew J. Paszek is the most co-cited, indicating foundational influence. Cell is the most influential journal based on co-citation frequency. Keyword analysis reveals a thematic evolution from “extracellular matrix stiffness” and “mechanotransduction” to frontier areas such as “cancer immunotherapy” and “YAP signaling protein.”ConclusionIn this study, we construct a comprehensive bibliometric map of cancer mechanobiology. Our findings elucidate the developmental trajectory and research hotspots of the field, providing a data-driven reference for future investigations, international collaborations, and clinical translation of physical oncology.

Mohsen Ahmed Abdelmohsen, Mahmoud Mohamed Ali Rezk, Ayda A youssef et al.

Abstract Background Tuberous sclerosis complex (TSC) is a multisystem genetic disorder characterized by the development of benign tumors across multiple organ systems. While supratentorial cerebral manifestations are well documented, infratentorial involvement, particularly cerebellar tubers, remains less explored. This study aimed to evaluate the prevalence, imaging characteristics, and longitudinal changes of cerebellar tubers in patients with TSC. Methods A retrospective analysis was conducted on 61 pediatric and young adult patients diagnosed with TSC who underwent brain MRI between 2005 and 2023. MR imaging included standard sequences such as T1WI, T2WI, FLAIR, DWI, ADC mapping, SWI, and post-contrast T1WI. All scans were independently reviewed by three experienced neuroradiologists (each one with 15 years of experience); they were blinded to clinical data. Results Cerebellar tubers were identified in 29 out of 61 patients (47.5%), totaling 50 lesions. The most common morphology was wedge-shaped (96%). Signal intensity varied across sequences: T1 hypointense (92%), T2 hyperintense (86%), and FLAIR mixed patterns (variable). Enhancement after contrast administration was observed in 6% of tubers (striated pattern), and calcifications were present in 14%. Retraction deformities adjacent to tubers were noted in 48% of cases. Patients with cerebellar tubers had significantly more cerebral tubers than those without (mean: 29 vs 22; p < 0.001). Follow-up MRI in 13 patients (mean follow-up: 5.3 years) showed stability in 84.6%, slight regression in 7.7%, and progression in 7.7%. Conclusions Cerebellar tubers are relatively common in TSC and exhibit distinct morphological and signal characteristics. These lesions demonstrate dynamic behavior over time, correlating with supratentorial abnormalities and potentially influencing neurobehavioral outcomes. Awareness of these features can aid in early diagnosis and long-term monitoring.

Alexander Kaier, Maria Ntefidou

Membrane contact sites (MCSs) between the endoplasmic reticulum and the plasma membrane enable the transport of lipids without membrane fusion. Extended Synaptotagmins (ESYTs) act at MCSs, functioning as tethers between two membrane compartments. In plants, ESYTs have been mainly investigated in <i>A. thaliana</i> and shown to maintain the integrity of the plasma membrane, especially during stress responses like cold acclimatization, mechanical trauma, and salt stress. ESYTs are present at the MCSs of plasmodesmata, where they regulate defense responses by modulating cell-to-cell transfer of pathogens. Here, the analysis of ESYTs was expanded to the bryophyte <i>Physcomitrium patens</i>, an extant representative of the earliest land plant lineages. <i>P. patens</i> was found to contain a large number of ESYTs, distributed over all previously established classes and an additional class not present in <i>A. thaliana</i>. Motif discovery identified regions in the Synaptotagmin-like mitochondrial (SMP) domain that may explain phylogenetic relationships as well as protein function. The adaptation mechanisms of <i>P. patens</i> necessary to conquer land and its simple tissue structure make it highly suitable as a model organism to study ESYT functions in tip growth, stress responses, and plasmodesmata-mediated transport, and open new directions of research regarding the function of MCSs in cellular processes and plant evolution.

Thomas P. Huff, Emily R. Russ, Todd M. Swannack

Anthropogenic activity leads to changes in sediment dynamics, creating imbalances in sediment distributions across the landscape. These imbalances can be variable within a littoral system, with adjacent areas experiencing sediment starvation and excess sediment. Historically, sediments were viewed as an inconvenient biproduct destined for disposal; however, beneficial use of dredge material (BUDM) is a practice that has grown as a preferred methodology for utilizing sediment as a resource to help alleviate the sediment imbalances within a system. BUDM enables organizations to adopt a more innovative and sustainable sediment management approach that also provides ecological, economic, and social co-benefits. Although location data are available on BUDM sites, especially in the US, there is limited understanding on how these sites evolve within the larger landscape, which is necessary for quantifying the co-benefits. To move towards BUDM more broadly, new tools need to be developed to allow researchers and managers to understand the effects and benefits of this practice. The National Exposed Sediment Search and Inventory (NESSI) was built to show the capability of using machine learning techniques to identify dredged sediments. A combination of satellite imagery data obtained and processed using Google Earth Engine and machine learning algorithms were applied at known dredged material placement sites to develop a time series of dredged material placement events and subsequent site recovery. These disturbance-to-recovery time series are then used in a landscape analysis application to better understand site evolution within the context of the surrounding areas.

Zheng Yuan, Daming Zhang, Xu Dong

Abstract In order to investigate the mechanical properties and energy evolution patterns of composite rock masses with structural planes of different inclinations, this study selected composite rock samples made from coal and sandstone, with structural plane inclinations of 0°, 30°, 45°, 60°, and 90°. Uniaxial compression tests were conducted, and energy theory was applied to analyze the energy transformation characteristics during the deformation and failure process. The results show that the structural plane inclination significantly influences the compressive strength, peak strain, and elastic modulus of the composite rock masses. The compressive strength exhibits a “U-shaped” trend, first decreasing and then increasing, with the minimum at 45° and the maximum at 90°. The peak strain decreases monotonically as the angle increases, while the elastic modulus increases exponentially. The energy evolution process can be divided into four stages: compaction, elastic deformation, plastic deformation, and failure. The total peak strain energy and elastic energy percentages exhibit a pattern of first decreasing and then increasing with changes in the inclination angle. A piecewise damage constitutive model considering the compaction stage was established based on the experimental results. The model curve aligns well with the experimental data and can accurately characterize the stress-strain evolution characteristics of composite rock masses with structural planes of different inclinations. The findings of this study provide theoretical insights for disaster prevention and control in deep mines, as well as the stability analysis of composite rock masses.

Tianqi Huang, Peter J. Morin, Sara Ruane

In response to the surge of urbanization in the modern era, many organisms have undergone various changes, such as the shift of their morphological traits to face the challenges brought by this drastic environmental transformation. Rapid adaptive evolution in the morphology of urban-dwelling organisms has been documented in a broad array of taxa, such as lizards and birds, by comparing urban populations with their nonurban counterparts. However, relevant studies concerning more elusive and secretive organisms that also occur in both natural and urbanized habitats (e.g., snakes), are still lacking. Snakes lack appendages, which are often the trait of interest in other morphological studies, but factors such as head shape play a critical role in snakes, as it determines the prey size of these gape-limited predators. In this study, we apply both linear and geometric morphometric analyses to examine interpopulation morphological differences and sexual dimorphism in a small, semi-fossorial snake, Dekay’s brownsnake (Storeria dekayi). We focus on head shape in six different populations across the rural-urban gradient in New Jersey and New York, USA. We find evidence of increased morphological divergence and decreased sexual dimorphism in populations inhabiting more urbanized areas. Our study suggests the occurrence of an adaptive morphological shift in this common species in the urban environments, and lays the path for further investigation of urban adaptation in snakes and similar secretive species.

Katharine Sarikakis, Angeliki Chatziefraimidou

Protecting children’s privacy continues to challenge policymakers and citizens alike in the media age and debates often point to the need for data protection literacy. The latter constitutes only one limited aspect of privacy, yet, it dominates actions by global platforms as they seek to monetise on personal data. The integration of artificial intelligence (AI) into the various platforms that children daily use, further complicates the effort to counter violations of privacy globally. Importantly, children’s views on these matters need to be further integrated in the global debates on privacy. This study contributes to knowledge about children’s experiences and perceptions of privacy while online, by examining children’s media literacy through a qualitative meta-synthesis of research data from work with children in Vienna, Austria. Children’s media literacy skills are presented along with children’s digital privacy literacy skills and their development is traced through the different age groups. Furthermore, the study examines the intersection between privacy literacy and AI literacy. Through a systematic synthesis of qualitative findings, this study aims to develop a map that describes the essential skills needed for personal data protection at different developmental stages in AI-driven media. The findings highlight the evolution of skills across the nine-16 age range, such as critical evaluation and privacy management. Although younger children may struggle with abstract AI concepts, they are able to understand basic privacy settings. Older children may begin to grasp the implications of data used in AI but still lack the critical skills to evaluate AI-driven disinformation.

C. M. Bogert

Desanka Lazic, Cornelia Geßner, Katharina J. Liepe et al.

Abstract Local adaptation is key for ecotypic differentiation and species evolution. Understanding underlying genomic patterns can allow the prediction of future maladaptation and ecosystem stability. Here, we report the whole-genome resequencing of 874 individuals from 100 range-wide populations of European beech (Fagus sylvatica L.), an important forest tree species in Europe. We show that genetic variation closely mirrors geography with a clear pattern of isolation-by-distance. Genome-wide analyses for genotype-environment associations (GEAs) identify relatively few potentially adaptive variants after correcting for an overwhelming signal of statistically significant but non-causal GEAs. We characterize the single high confidence genomic region and pinpoint a candidate gene possibly involved in winter temperature adaptation via modulation of spring phenology. Surprisingly, allelic variation at this locus does not result in any apparent fitness differences in a common garden. More generally, reciprocal transplant experiments across large climate distances suggest extensive phenotypic plasticity. Nevertheless, we find indications of polygenic adaptation which may be essential in natural ecosystems. This polygenic signal exhibits broad- and fine-scale variation across the landscape, highlighting the relevance of spatial resolution. In summary, our results emphasize the importance, but also exemplify the complexity, of employing natural genetic variation for forest conservation under climate change.

Simegnew Yihunie Alaba, Ali C. Gurbuz, John E. Ball

The pursuit of autonomous driving relies on developing perception systems capable of making accurate, robust, and rapid decisions to interpret the driving environment effectively. Object detection is crucial for understanding the environment at these systems’ core. While 2D object detection and classification have advanced significantly with the advent of deep learning (DL) in computer vision (CV) applications, they fall short in providing essential depth information, a key element in comprehending driving environments. Consequently, 3D object detection becomes a cornerstone for autonomous driving and robotics, offering precise estimations of object locations and enhancing environmental comprehension. The CV community’s growing interest in 3D object detection is fueled by the evolution of DL models, including Convolutional Neural Networks (CNNs) and Transformer networks. Despite these advancements, challenges such as varying object scales, limited 3D sensor data, and occlusions persist in 3D object detection. To address these challenges, researchers are exploring multimodal techniques that combine information from multiple sensors, such as cameras, radar, and LiDAR, to enhance the performance of perception systems. This survey provides an exhaustive review of multimodal fusion-based 3D object detection methods, focusing on CNN and Transformer-based models. It underscores the necessity of equipping fully autonomous vehicles with diverse sensors to ensure robust and reliable operation. The survey explores the advantages and drawbacks of cameras, LiDAR, and radar sensors. Additionally, it summarizes autonomy datasets and examines the latest advancements in multimodal fusion-based methods. The survey concludes by highlighting the ongoing challenges, open issues, and potential directions for future research.

Kameel Khabaz, Karen Yuan, Joseph Pugar et al.

Clinical imaging modalities are a mainstay of modern disease management, but the full utilization of imaging-based data remains elusive. Aortic disease is defined by anatomic scalars quantifying aortic size, even though aortic disease progression initiates complex shape changes. We present an imaging-based geometric descriptor, inspired by fundamental ideas from topology and soft-matter physics that captures dynamic shape evolution. The aorta is reduced to a two-dimensional mathematical surface in space whose geometry is fully characterized by the local principal curvatures. Disease causes deviation from the smooth bent cylindrical shape of normal aortas, leading to a family of highly heterogeneous surfaces of varying shapes and sizes. To deconvolute changes in shape from size, the shape is characterized using integrated Gaussian curvature or total curvature. The fluctuation in total curvature (δK) across aortic surfaces captures heterogeneous morphologic evolution by characterizing local shape changes. We discover that aortic morphology evolves with a power-law defined behavior with rapidly increasing δK forming the hallmark of aortic disease. Divergent δK is seen for highly diseased aortas indicative of impending topologic catastrophe or aortic rupture. We also show that aortic size (surface area or enclosed aortic volume) scales as a generalized cylinder for all shapes. Classification accuracy for predicting aortic disease state (normal, diseased with successful surgery, and diseased with failed surgical outcomes) is 92.8±1.7%. The analysis of δK can be applied on any three-dimensional geometric structure and thus may be extended to other clinical problems of characterizing disease through captured anatomic changes.

Xiawei Yang, Mingxuan Yao, Yu Su et al.

In this paper, T-joints of Ti-6Al-3Nb-2Zr-1Mo titanium alloy were joined with friction stir welding, and microstructure evolution and forming mechanism were studied. The effect of using tungsten inert gas welding to heat additionally the FSW was investigated. Results show a strong effection microstructure of stir zone (SZ) due to the temperature gradient and fast cooling rate. The top and middle sections of SZ have a basketweave microstructure, while there is duplex microstructure at the bottom. When welding at 750 rpm-50 mm/min, the maximum tensile strength of the joint is similar to that of the base metal (BM). As the heat input increases, grain coarsening occurs, which reduces the joint tensile strength and the ability to plastically deform. The fracture mode changes from mixed fracture to ductile one. When TIG-assisted heat source is 20 mm in front of the tool and the power input is in 600 W, the temperature field produced is relatively uniform, which has a positive effect on the weld.

R. Goldschmidt

W. M. Mokofe

Objective: South Africa is a country with great potential for intensive development due to the active growth and adoption of digital technologies. The rapidly emerging digital landscape is transforming the legal framework, which in turn influences the digital environment. This transformative relationship determined the focus of the research, which is to identify the legal system adaptability under dynamic changes, as well as the legal landscape evolution under digitalization and technological progress.Methods: the study of the changing legal landscape required an interdisciplinary approach that combines legal analysis with ideas from sociology, economics, etc. In doing so, the formal-legal method was used to examine the key legal instruments shaping South Africa's digital environment and providing the opportunities and challenges of the interaction between digital technologies and South African law.Results: the paper provides insights into how the South African legal system is addressing digital challenges; assesses the integration of digital innovations into the legal system; highlights the transformative impact of digital technologies on traditional legal processes, including collecting evidence, dispute resolution and access to justice. Finally, it evaluates the role of digital technologies in making legal processes more efficient.Scientific novelty: the study contributes to the ongoing debate on the complex relationship between digital technologies and South African law. It shows how South African law is coping with digital complexities and substantiates new insights into the transformation of the traditional legal paradigm as a result of digitalization, as well as its implications for legal proceedings and access to justice. By delving into the adaptations, challenges and innovations arising at the intersection of law, technologies and digitalization, insights are gained into how South African law navigates the dynamic digital landscape.Practical significance: adapting the legal landscape to digitalization and technological advances is critical to ensure rapid technological progress. It also requires collaboration between government agencies, civil society, experts in law and technology. The study provides valuable recommendations and suggestions for policymakers, legal practitioners and stakeholders shaping South Africa's legal ecosystem. The author addresses the challenges of ensuring personal data privacy, enhancing electronic interactions, and countering cybercrime. The importance of introducing technological achievements while maintaining robust legal safeguards is emphasized.

M. Bitterman

J. Harlan, J. M. Wet, E. Price