Hasil untuk "Human evolution"

R. Miikkulainen, J. Liang, Elliot Meyerson et al.

Abstract The success of deep learning depends on finding an architecture to fit the task. As deep learning has scaled up to more challenging tasks, the architectures have become difficult to design by hand. This paper proposes an automated method, CoDeepNEAT, for optimizing deep learning architectures through evolution. By extending existing neuroevolution methods to topology, components, and hyperparameters, this method achieves results comparable to best human designs in standard benchmarks in object recognition and language modeling. It also supports building a real-world application of automated image captioning on a magazine website. Given the anticipated increases in available computing power, evolution of deep networks is promising approach to constructing deep learning applications in the future.

J. Isidro, V. Borges, M. Pinto et al.

The largest monkeypox virus (MPXV) outbreak described so far in non-endemic countries was identified in May 2022 (refs. 1–6). In this study, shotgun metagenomics allowed the rapid reconstruction and phylogenomic characterization of the first MPXV outbreak genome sequences, showing that this MPXV belongs to clade 3 and that the outbreak most likely has a single origin. Although 2022 MPXV (lineage B.1) clustered with 2018–2019 cases linked to an endemic country, it segregates in a divergent phylogenetic branch, likely reflecting continuous accelerated evolution. An in-depth mutational analysis suggests the action of host APOBEC3 in viral evolution as well as signs of potential MPXV human adaptation in ongoing microevolution. Our findings also indicate that genome sequencing may provide resolution to track the spread and transmission of this presumably slow-evolving double-stranded DNA virus. Analysis of the first sequences from the 2022 multi-country outbreak of monkeypox virus shows relatedness and substantial divergence from a 2018–2019 outbreak, suggesting rapid virus evolution with possible implications for human-to-human transmission.

L. Hooper, A. Macpherson

J. Martínez

M. Slatkin

W. Bean

A. Zihlman, R. Boyd, P. Richerson

D. Parkin, F. Bray

D. Lytle, N. Poff

Robin I. M. Dunbar

C. Billings

C. Boesch, H. Boesch-Achermann

C. Bustamante, A. Fledel-Alon, S. Williamson et al.

S. Okasha

Brian Boyd

Christopher Boehm

MARINA POPA

Since the beginning of time, the world's economies have been interconnected. These connections have ranged from simple partnerships to complex exchanges of resources. Throughout human history, no country has ever possessed all the resources it needed, making international connections essential. People, trade, capital, and information have always been the key flows driving global interaction, although their evolution varies depending on the global context. In an ever-changing international system shaped by economic, political, and social factors, these flows shift in scale and direction but consistently remain the forces that keep states connected. Economic flows are reflected in the export and import of goods and services, migration (i.e., the movement of people), technology transfer, information exchange, innovation, foreign direct investment, and the operations of transnational corporations. Without these components, the global economy cannot function effectively, increasing the risk of widening gaps between countries or even their isolation. Therefore, international economic flows are essential for global growth, the development of partnerships, diversification of supply sources, market expansion, and job creation. They are the engine of growth and development. This article aims to identify the defining features of each type of flow and to demonstrate the importance of the global economic circuit they create. By analysing trade, migration, capital, and technology flows, the paper will justify their critical role in the economies of all countries, regardless of their level of development.

Shanshan Wang, Gangtian Liu, Jun Ma et al.

In recent years, environmental behavior has emerged as a crucial research direction for achieving sustainable development. Promoting environmental awareness and related practices can effectively reduce pollution, protect ecosystems, and enhance human well-being. A systematic understanding of research hotspots and evolutionary trends in this field holds significant theoretical and practical value. This study employed bibliometric methods and utilized ScientoPy and VOSviewer analysis tools to conduct a systematic and multi-dimensional analysis of 6,524 articles on environmental behavior published in the Web of Science and Scopus databases from 1974 to 2024. The findings show that the volume of literature on environmental behavior has grown rapidly, confirming its interdisciplinary and global nature. Diachronic clustering analysis identified three distinct evolutionary stages. China ranked first and the United States second in terms of the total number of publications. Current emerging hotspots with the fastest growth include “green human resource management” and “environmental awareness.” Meanwhile, “pro-environmental behavior,” “sustainability,” “climate change,” and “place attachment” remain consistently high-potential research themes. This study comprehensively reveals the historical evolution and shifting hotspots in environmental behavior research over the past 50 years. The findings provide strong evidence and clear directions for scholars, policymakers, and practitioners.

Christos Tsakalidis, George E. Konidaris, Evangelia Tsoukala et al.

Dental wear analyses of extinct animals offer key insights into their dietary preferences and in turn contribute substantially to palaeoenvironmental reconstructions, leading to more accurate interpretations about past ecosystems. This study employs dental mesowear analysis on Pliocene and Pleistocene elephants and mammoths from several localities in Northern Greece (Ptolemais Basin, Mygdonia Basin, Drama Basin, and the Neapolis-Grevena Basin), aiming to classify them into three main dietary categories (browsers, mixed-feeders, grazers) and investigate potential niche partitioning. The method relies on documenting the wear pattern of molar surfaces through angle measurements on the enamel ridges, which reflect the average annual diet of the examined taxon and in turn the annual ecological conditions of the studied area. Prior to the palaeodietary study and in order to ensure the taxonomic attribution of the examined specimens, a taxonomic review was conducted which confirmed the presence of the mammoths <i>Mammuthus rumanus</i>, <i>Mammuthus meridionalis</i> (southern mammoth), and <i>Mammuthus trogontherii</i> (steppe mammoth), and the European straight-tusked elephant <i>Palaeoloxodon antiquus</i>. Dental mesowear results indicate a grazing diet for <i>M.</i> (cf.) <i>rumanus</i>, a mainly browsing diet for <i>M. meridionalis</i> but mixed-feeding to grazing for the subspecies <i>Mammuthus meridionalis vestinus</i>, a grazing one for <i>M. trogontherii</i>, and a wide diet spectrum for <i>P. antiquus</i>, including browsing, mixed-feeding and grazing, depending on the locality. This study expands our knowledge on the palaeoecology of Greek proboscideans and further highlights the importance of mesowear analysis on proboscidean teeth for palaeodietary and palaeoenviromental inferences.

Debangshu Paul, Zachariah Arwood, Pierre-Yves Mulon et al.

While predicting mechanical responses under various stress scenarios is of significant interest in the field of orthopedic research, finite element (FE) modeling studies specifically focusing on the tibia remain notably limited. Given that mechanical properties and structural form of goat tibiae closely mimic those of human tibiae, they can serve as excellent models for comparative orthopedic research. While existing literature on goat bone research offers rich in vivo models, it lacks a validated FE model of the tibia subjected to thorough spatial error assessment. The purpose of this study is to develop a novel FE modeling framework for goat tibia with prediction of failure load and crack location using a phase field fracture method. In particular, this study applies established model forms for the spatial density dependence of elastic moduli and fracture toughness from human long bones to the modeling of goat tibia for the first time and assesses the accuracy of simulated versus measured behavior. The framework involves constructing a mesh of the bone geometry from a 3D quantitative computed tomography (QCT) scan of the goat tibia. To make the process accessible and extensible, open-source software was utilized throughout the entire modeling process for the first time. To validate this FE model, we conducted a uniaxial compression test by applying the load along the shaft axis. A Digital Image Correlation (DIC) system provided high-resolution strain measurements across the surface of the tibia, with the results found to align well with FE simulation outcomes. Subsequently, a high-performance computing (HPC) environment was used to couple the elastic model with a phase field fracture model – resulting in fracture initiation and evolution predictions that closely mirror experimental observations. This QCT-based approach offers a framework for personalized modeling of goat tibia and, in the future, human tibiae, thereby enabling patient-specific analysis relating to fracture risk, implant effectiveness, and optimal treatment strategies.