Hasil untuk "Human evolution"

David G. Rand, M. Nowak

P. Stankiewicz, J. Lupski

Yong-shu He, Wen Zhang, Zhao-Qing Yang

C. Elsik, R. Tellam, K. Worley

A survey of genetic diversity of cattle suggests two domestication events in Asia and selection by husbandry. Not Just Dinner on Legs Several thousand years ago, human beings realized the virtues of domesticating wild animals as easy meat. Soon other possibilities became apparent, and as revealed in a series of papers in this issue, early pastoralists became selective about breeding for wool, leather, milk, and muscle power. In two papers, Gibbs et al. report on the bovine genome sequence (p. 522; see the cover, the Perspective by Lewin, and the Policy Forum by Roberts) and trace the diversity and genetic history of cattle (p. 528), while Chessa et al. (p. 532) survey the occurrence of endogenous retroviruses in sheep and map their distribution to historical waves of human selection and dispersal across Europe. Finally, Ludwig et al. (p. 485) note the origins of variation in the coat-color of horses and suggest that it is most likely to have been selected for by humans in need of good-looking transport. To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.

S. Tishkoff, F. A. Reed, A. Ranciaro et al.

W. Enard, M. Przeworski, S. Fisher et al.

Á. Pascual-Leone, A. Amedi, F. Fregni et al.

S. Schwartz, W. Kent, A. Smit et al.

The Mouse Genome Analysis Consortium aligned the human and mouse genome sequences for a variety of purposes, using alignment programs that suited the various needs. For investigating issues regarding genome evolution, a particularly sensitive method was needed to permit alignment of a large proportion of the neutrally evolving regions. We selected a program called BLASTZ, an independent implementation of the Gapped BLAST algorithm specifically designed for aligning two long genomic sequences. BLASTZ was subsequently modified, both to attain efficiency adequate for aligning entire mammalian genomes and to increase its sensitivity. This work describes BLASTZ, its modifications, the hardware environment on which we run it, and several empirical studies to validate its results.

S. Mi, X. Lee, Xiangping Li et al.

A. Efstratiadis, J. Posakony, T. Maniatis et al.

D. Bachtrog

D. Buss

M. Lengnick-Hall, C. Lengnick-Hall, Leticia S. Andrade et al.

Zhuoqun Jiang, ShunYi Yeo, Dorien Herremans et al.

While reciprocal self-disclosure drives intimacy, digital tools seldom scaffold autonomy, competence, and relatedness -- the motivational underpinnings defined by Self-Determination Theory (SDT) that enable deep exchange. We introduce a chatbot employing dual-layer scaffolding to satisfy these needs: first providing enabling affordances (instrumental support) for vulnerability, then mediating affordances (relational support) for responsiveness. In a randomized study (N = 72; 36 couples) comparing Partner Support (PS: both layers), Direct Support (DS: enabling only), and Basic Prompt (BP: questions only), results reveal a critical distinction. While enabling affordances (PS, DS) were sufficient to deepen disclosure, only mediating affordances (PS) reliably elicited partner-provided need support and increased perceived closeness. Furthermore, controlled motivation decreased across conditions, and scaffolding buffered vitality, which remained stagnant in BP. We contribute empirical evidence that SDT-guided mediation fosters connection, offering a practical framework for designing AI-mediated conversations that support, rather than replace, human intimacy.

Nathan Gabriel, Adrian V. Bell, Paul E. Smaldino

Individual social identities indicate group affiliations and are typically associated with group-typical preferences, signals that indicate group membership, and the propensity to condition actions on the social signals of others, resulting in group-differentiated interaction norms. Past work modeling identity signaling and coordination has typically assumed that individuals belong to one of a discrete set of groups. Yet individuals can simultaneously belong to multiple groups, which may be nested within larger groupings. Here, we introduce the generalized Bach or Stravinsky game, a coordination game with ordered preferences, which allows us to construct a model that captures the overlapping and hierarchical nature of social identity. Our model unifies several prior results into a single framework, including results related to coordination, minority disadvantage, and cross-cultural competence. Our model also allows agents to express complex social identities through multidimensional signaling, which we use to explore a variety of complex group structures. Our consideration of intersectional identities exposes flaws in naive measures of group structure, illustrating how empirical studies may overlook some social identities if they do not consider the behaviors that those identities function to afford.

Michael Batty

Abstract Artificial Intelligence (AI) is entirely coincident with the emergence of the digital computer. It was assumed from the start, some 75 years ago, that the computer had more than the required power to simulate human intelligence. This led to the speculation that ultimately computers would take over many of our own tasks which we once considered could never be modelled using machines. Here, we sketch the history and evolution of AI, note the different phases in this history, define distinctions between strong and weak AI, and emphasise the difference between generative and discriminative processes. There are many possible applications in city planning with the most suggestive and possibly the most disruptive being those related to the development of new methods for generating sustainable plans and designs. We make a key distinction between inductive and deductive AI, demonstrating these differences with methods of machine learning (ML), showing how early network methods based on the perceptron, can be linked to deductive procedures that enable us to build new models for city design. Our key illustration links urban simulation models to land cover built around geospatial data infused with ML. The aim of this paper is to chart the progress in AI and its applicability to city science and city planning from its first applications and speculate on future developments.

Yibowen Zhao, Yiming Cao, Zhiqi Shen et al.

Intensive Care Units (ICUs) are critical environments characterized by high-stakes monitoring and complex data management. However, current practices often rely on manual data transcription and fragmented information systems, introducing potential risks to patient safety and operational efficiency. To address these issues, we propose a human-AI synergy system based on a cloud-edge-end architecture, which integrates visual-aware data extraction and semantic interaction mechanisms. Specifically, a visual-aware edge module non-invasively captures real-time physiological data from bedside monitors, reducing manual entry errors. To improve accessibility to fragmented data sources, a semantic interaction module, powered by a Large Language Model (LLM), enables physicians to perform efficient and intuitive voice-based queries over structured patient data. The hierarchical cloud-edge-end deployment ensures low-latency communication and scalable system performance. Our system reduces the cognitive burden on ICU nurses and physicians and demonstrates promising potential for broader applications in intelligent healthcare systems.

Kunal Bhosikar, Siddharth Katageri, Vivek Madhavaram et al.

Generating realistic full-body motion interacting with objects is critical for applications in robotics, virtual reality, and human-computer interaction. While existing methods can generate full-body motion within 3D scenes, they often lack the fidelity for fine-grained tasks like object grasping. Conversely, methods that generate precise grasping motions typically ignore the surrounding 3D scene. This gap, generating full-body grasping motions that are physically plausible within a 3D scene, remains a significant challenge. To address this, we introduce MOGRAS (Human MOtion with GRAsping in 3D Scenes), a large-scale dataset that bridges this gap. MOGRAS provides pre-grasping full-body walking motions and final grasping poses within richly annotated 3D indoor scenes. We leverage MOGRAS to benchmark existing full-body grasping methods and demonstrate their limitations in scene-aware generation. Furthermore, we propose a simple yet effective method to adapt existing approaches to work seamlessly within 3D scenes. Through extensive quantitative and qualitative experiments, we validate the effectiveness of our dataset and highlight the significant improvements our proposed method achieves, paving the way for more realistic human-scene interactions.

Ruiying Gao, Gaoming Ding, Ying Zhang et al.

Solar-driven interfacial evaporation desalination technology offers a feasible solution to the global shortage of freshwater resources. However, previous interfacial evaporation technologies have often only focused on the production of freshwater resources, without fully utilizing the high-energy photons in sunlight and the salinity gradient generated after seawater evaporation. In this work, a solar-driven water–hydrogen–electricity (SWHE) co-production system integrated by solar-driven interfacial evaporation (SIE), interface photocatalytic hydrogen evolution (IPHE), and reverse electrodialysis (RE) was proposed. The aim is to enhance the efficiency of solar energy utilization and achieve simultaneous production of freshwater, hydrogen, and electricity. Under 2-sun irradiation, the SWHE device achieved a water generation rate of 0.77 kg m⁻² h⁻¹, a hydrogen generation rate of 8.57 mmol m⁻² h⁻¹, and a highest power density of 2.9 mW m⁻². Outdoor tests demonstrate that the cumulative water production reached 1.6 kg m⁻² over 6 h, with a total hydrogen yield of 12.22 mmol m⁻² and a highest power density of 0.095 mW m⁻², which validated the environmental adaptability of SWHE system. This novel design strategy is expected to provide a novel form of freshwater resources and energy supply for human society.

Houjiang Liu, Jacek Gwizdka, Matthew Lease

Given the volume of potentially false claims online, claim prioritization is essential in allocating limited human resources available for fact-checking. In this study, we perceive claim prioritization as an information retrieval (IR) task: just as multidimensional IR relevance, with many factors influencing which search results a user deems relevant, checkworthiness is also multi-faceted, subjective, and even personal, with many factors influencing how fact-checkers triage and select which claims to check. Our study investigates both the multidimensional nature of checkworthiness and effective tool support to assist fact-checkers in claim prioritization. Methodologically, we pursue Research through Design combined with mixed-method evaluation. Specifically, we develop an AI-assisted claim prioritization prototype as a probe to explore how fact-checkers use multidimensional checkworthy factors to prioritize claims, simultaneously probing fact-checker needs and exploring the design space to meet those needs. With 16 professional fact-checkers participating in our study, we uncover a hierarchical prioritization strategy fact-checkers implicitly use, revealing an underexplored aspect of their workflow, with actionable design recommendations for improving claim triage across multidimensional checkworthiness and tailoring this process with LLM integration.