Hasil untuk "Fossil man. Human paleontology"

Adam C. Pritchard, Jacob A. Mccartney, Georgios L. Georgalis et al.

We report on the oldest vertebra of a terrestrial snake from the Paleogene of eastern North America. The nearly complete trunk vertebra was recovered from the Eocene Nanjemoy Formation of Virginia and is referred to Constrictores, the clade including booids and pythonoids, as it bears a relatively broad centrum, high neural spine, and a relatively massive zygosphene compared to most other snake taxa. Although a combination of features of the specimen, including a dorsoventrally tall and transversely narrow neural canal and a relatively high neural spine mostly developed in the posterior half of the neural arch, are distinct from most other described Paleogene Constrictores, we refrain from naming a new taxon based on a single element. The discovery of this early Eocene snake in the north of the Paleogene Atlantic coast strengthens similarities with contemporaneous vertebrate assemblages in western North America, the Paleogene Gulf Coast of North America, and western Europe. It also extends the broad biogeographic range of the rich Paleogene radiation of Constrictores to the Atlantic coast of North America. The specimen also exhibits interesting taphonomic signatures (e.g., eroded outer layers of cortical and articular bone, specific damages of the zygantrum) indicating that it may have been digested prior to fossilization.

Saverio Bartolini-Lucenti, Marie Meyer, Samuele Frosali et al.

We describe a new fossil raccoon dog from the Late Pliocene site of Jradzor, Armenia, a key site to understand biogeographic connections and dispersal between Asia, Europe, and Africa. The specimens analysed here for the first time exhibit a mosaic of primitive and derived cranial and dental traits, distinguishing them from known taxa such as Nyctereutes tingi (e.g. elongated cranium, reduced subangular lobe), N. sinensis (e.g. molar proportions, sulcal pattern), and N. megamastoides (e.g. absence of squared M1 morphology). Virtual reconstruction of the endocranium reveals a unique sulcal and gyral pattern, including a parenthesis-shaped gyrus sigmoideus and a deeply developed sulcus pseudosylvius, placing it morphologically closer to Canini than extant Vulpini. Considering these features, we propose to ascribe it to a new Nyctereutes species. Morphometric and geometric morphometric analyses support its taxonomic distinctiveness and suggest ecological and behavioural affinities with jackal-like canids. Notably, the relative development of the rostral portion of the cerebrum implies a social structure more complex than that of extant Nyctereutes, suggesting the possibility of seasonal pack formation. Additionally, we reassess several neuroanatomical traits previously considered diagnostic, such as the cerebellar vermis and sulcus endomarginalis, revealing greater variability within Nyctereutes and challenging previous phylogenetic assumptions. These findings underscore the Pliocene diversification of the genus and highlight the Caucasus as a pivotal region in canid evolution. The erection of a new Nyctereutes species enriches our understanding of canid paleobiology and provides new perspectives on the evolutionary trajectories of hypocarnivorous canids.

Antoine Pictet, Luc Georges Bulot

Abstract The Hauterivian type region and more widely the Jura mountains were investigated for their ammonites of the family Neocomitidae. Three rare lower Hauterivian genera are described here: (i) a more detailed description of Haroella charcensis Bulot, Pictet, Frau & Bryers, 2024 is given, which was identified in historical collections of ammonites from the Jura mountains, originating from a phosphatic conglomerate dating from the local Leopoldia buxtorfi Horizon and making it the oldest representative of the genus; (ii) Lyticoceras subhystricoides (Kilian & Reboul, 1915) from the Eclépens quarry is currently being revised as Theodorites cf. theodori Baraboshkin and Mikhailova, 2006; (iii) the new genus Jurienella is introduced for “Breistrofferella” peyroulensis Atrops, Autran & Reboulet 1996, previously known only to a few Provençal sections, in SE France. The stratigraphic position of the Jura specimens raises questions about the age of this taxon, as well as the phyletic link between the genera Bresitrofferella Thieuloy, 1971 and Acanthodiscus Uhlig, 1905. The Haroella-Theodorites lineage is presently considered to be separate from the Lyticoceras-Cruasiceras lineage. The Haroella-Theodorites lineage seems to originate from, or to be closely allied to the late Valanginian species Distoloceras hystrix (Phillips, 1829) sensu Neumayr & Uhlig, genotype of Distoloceras.

Comité Organizador de la RCAPA 2024

Libro de Resúmenes de la Reunión de Comunicaciones de la Asociación Paleontológica Argentina. La misma tuvo lugar en la ciudad de San Rafael (Mendoza, Argentina) durante los días 22-24 de Noviembre del 2024.

Richard A. Fariña, Elspeth Hayes, Luis A. Lemoine et al.

Abstract Several sites in the Americas are proposed to have evidence of human occupation before the Last Glacial Maximum (LGM). The timing of human colonisation of the Americas is a matter of debate due to its intrinsic interest, but also because of the implications of that arrival for the extinction of the megafauna. Here, we study a notable indentation in the right calcaneus of a giant extinct ground sloth Lestodon armatus from the Arroyo del Vizcaíno site, Uruguay, dated to ~ 33 cal kyBP. We use a combination of 3D CT-scan modelling, high-resolution silicone casting, and microscopic wear and residue analysis to describe the morphology of the lesion, its associated residues, and the possible mechanisms behind its formation. Considering the indentation’s features, including its shape, depth, and the presence of organic residues, we argue that it could have been created by a penetrating object with a rounded tip, possibly a bone, ivory or hardened wood tip attached to a shaft. This evidence contributes to discussions on the dates of human arrival in South America and the potential interactions with the megafauna.

Richard Jiarui Tong

This paper offers a concise, 60-year synthesis of human-AI collaboration, from Licklider's ``man-computer symbiosis" (AI as colleague) and Engelbart's ``augmenting human intellect" (AI as tool) to contemporary poles: Human-Centered AI's ``supertool" and Symbiotic Intelligence's mutual-adaptation model. We formalize the mechanism for effective teaming as a causal chain: Explainable AI (XAI) -> co-adaptation -> shared mental models (SMMs). A meta-analytic ``performance paradox" is then examined: human-AI teams tend to show negative synergy in judgment/decision tasks (underperforming AI alone) but positive synergy in content creation and problem formulation. We trace failures to the algorithm-in-the-loop dynamic, aversion/bias asymmetries, and cumulative cognitive deskilling. We conclude with a unifying framework--combining extended-self and dual-process theories--arguing that durable gains arise when AI functions as an internalized cognitive component, yielding a unitary human-XAI symbiotic agency. This resolves the paradox and delineates a forward agenda for research and practice.

Jason T. Isa, Lillian J. Ratliff, Samuel A. Burden

When humans interact with learning-based control systems, a common goal is to minimize a cost function known only to the human. For instance, an exoskeleton may adapt its assistance in an effort to minimize the human's metabolic cost-of-transport. Conventional approaches to synthesizing the learning algorithm solve an inverse problem to infer the human's cost. However, these problems can be ill-posed, hard to solve, or sensitive to problem data. Here we show a game-theoretic learning algorithm that works solely by observing human actions to find the cost minimum, avoiding the need to solve an inverse problem. We evaluate the performance of our algorithm in an extensive set of human subjects experiments, demonstrating consistent convergence to the minimum of a prescribed human cost function in scalar and multidimensional instantiations of the game. We conclude by outlining future directions for theoretical and empirical extensions of our results.

Dmytro Kuzmenko, Nadiya Shvai

Robots must balance compliance with safety and social expectations as blind obedience can cause harm, while over-refusal erodes trust. Existing safe reinforcement learning (RL) benchmarks emphasize physical hazards, while human-robot interaction trust studies are small-scale and hard to reproduce. We present the Empathic Ethical Disobedience (EED) Gym, a standardized testbed that jointly evaluates refusal safety and social acceptability. Agents weigh risk, affect, and trust when choosing to comply, refuse (with or without explanation), clarify, or propose safer alternatives. EED Gym provides different scenarios, multiple persona profiles, and metrics for safety, calibration, and refusals, with trust and blame models grounded in a vignette study. Using EED Gym, we find that action masking eliminates unsafe compliance, while explanatory refusals help sustain trust. Constructive styles are rated most trustworthy, empathic styles -- most empathic, and safe RL methods improve robustness but also make agents more prone to overly cautious behavior. We release code, configurations, and reference policies to enable reproducible evaluation and systematic human-robot interaction research on refusal and trust. At submission time, we include an anonymized reproducibility package with code and configs, and we commit to open-sourcing the full repository after the paper is accepted.

Xingyu Xiao, Hongxu Zhu, Jingang Liang et al.

Human error remains a dominant risk driver in safety-critical sectors such as nuclear power, aviation, and healthcare, where seemingly minor mistakes can cascade into catastrophic outcomes. Although decades of research have produced a rich repertoire of mitigation techniques, persistent limitations: scarce high-quality data, algorithmic opacity, and residual reliance on expert judgment, continue to constrain progress. This review synthesizes recent advances at the intersection of risk-informed decision making, human reliability assessment (HRA), artificial intelligence (AI), and cognitive science to clarify how their convergence can curb human-error risk. We first categorize the principal forms of human error observed in complex sociotechnical environments and outline their quantitative impact on system reliability. Next, we examine risk-informed frameworks that embed HRA within probabilistic and data-driven methodologies, highlighting successes and gaps. We then survey cognitive and human-performance models, detailing how mechanistic accounts of perception, memory, and decision-making enrich error prediction and complement HRA metrics. Building on these foundations, we critically assess AI-enabled techniques for real-time error detection, operator-state estimation, and AI-augmented HRA workflows. Across these strands, a recurring insight emerges: integrating cognitive models with AI-based analytics inside risk-informed HRA pipelines markedly enhances predictive fidelity, yet doing so demands richer datasets, transparent algorithms, and rigorous validation. Finally, we identify promising research directions, coupling resilience engineering concepts with grounded theory, operationalizing the iceberg model of incident causation, and establishing cross-domain data consortia, to foster a multidisciplinary paradigm that elevates human reliability in high-stakes systems.

Peter Lindes, Kaoutar Skiker

We have a vision of a day when autonomous robots can collaborate with humans as assistants in performing complex tasks in the physical world. This vision includes that the robots will have the ability to communicate with their human collaborators using language that is natural to the humans. Traditional Interactive Task Learning (ITL) systems have some of this ability, but the language they can understand is very limited. The advent of large language models (LLMs) provides an opportunity to greatly improve the language understanding of robots, yet integrating the language abilities of LLMs with robots that operate in the real physical world is a challenging problem. In this chapter we first review briefly a few commercial robot products that work closely with humans, and discuss how they could be much better collaborators with robust language abilities. We then explore how an AI system with a cognitive agent that controls a physical robot at its core, interacts with both a human and an LLM, and accumulates situational knowledge through its experiences, can be a possible approach to reach that vision. We focus on three specific challenges of having the robot understand natural language, and present a simple proof-of-concept experiment using ChatGPT for each. Finally, we discuss what it will take to turn these simple experiments into an operational system where LLM-assisted language understanding is a part of an integrated robotic assistant that uses language to collaborate with humans.

Aung Pyae

Human-AI collaboration is evolving from a tool-based perspective to a partnership model where AI systems complement and enhance human capabilities. Traditional approaches often limit AI to a supportive role, missing the potential for reciprocal relationships where both human and AI inputs contribute to shared goals. Although Human-Centered AI (HcAI) frameworks emphasize transparency, ethics, and user experience, they often lack mechanisms for genuine, dynamic collaboration. The "Human-AI Handshake Model" addresses this gap by introducing a bi-directional, adaptive framework with five key attributes: information exchange, mutual learning, validation, feedback, and mutual capability augmentation. These attributes foster balanced interaction, enabling AI to act as a responsive partner, evolving with users over time. Human enablers like user experience and trust, alongside AI enablers such as explainability and responsibility, facilitate this collaboration, while shared values of ethics and co-evolution ensure sustainable growth. Distinct from existing frameworks, this model is reflected in tools like GitHub Copilot and ChatGPT, which support bi-directional learning and transparency. Challenges remain, including maintaining ethical standards and ensuring effective user oversight. Future research will explore these challenges, aiming to create a truly collaborative human-AI partnership that leverages the strengths of both to achieve outcomes beyond what either could accomplish alone.

James K Ruffle, Samia Mohinta, Guilherme Pombo et al.

The benefits of artificial intelligence (AI) human partnerships-evaluating how AI agents enhance expert human performance-are increasingly studied. Though rarely evaluated in healthcare, an inverse approach is possible: AI benefiting from the support of an expert human agent. Here, we investigate both human-AI clinical partnership paradigms in the magnetic resonance imaging-guided characterisation of patients with brain tumours. We reveal that human-AI partnerships improve accuracy and metacognitive ability not only for radiologists supported by AI, but also for AI agents supported by radiologists. Moreover, the greatest patient benefit was evident with an AI agent supported by a human one. Synergistic improvements in agent accuracy, metacognitive performance, and inter-rater agreement suggest that AI can create more capable, confident, and consistent clinical agents, whether human or model-based. Our work suggests that the maximal value of AI in healthcare could emerge not from replacing human intelligence, but from AI agents that routinely leverage and amplify it.

Edwin-Alberto Cadena, Byron Benítez, Francisco Emmanuel Apen et al.

Bothremydidae was one of the most diverse and widespread group of side-necked turtles (pleurodirans) during the Cretaceous and part of the Paleogene. In South America, the Paleogene record of bothremydids is restricted to Puentemys mushaisaensis from the middle–late Paleocene Cerrejón Formation of Colombia, Inaechelys pernambucensis from the Paleocene of Brazil, and Motelomama olssoni from the early Eocene of Perú. Here, we describe two shells of P. mushaisaensis and several other isolated bones conferred to this taxon from the upper Paleocene and lower Eocene Arcillolitas de Socha Formation found in the Socha Region, Boyacá Department of Colombia. U-Pb dating of detrital zircon from two levels from this formation indicates maximum depositional ages of 56.83±0.04 Ma and 57.2±0.5 Ma for the areniscas guía interval of the formation. The new occurrence of P. mushaisaensis in the Socha region, at least 500 km south from Cerrejón, indicates a wider biogeographical distribution of northern South America Paleocene herpetofauna, possibly helped by low topography and ecosystems connectivity via a faunistic corridor.

Qiao Feng, Yuanwang Yang, Yebin Liu et al.

We introduce FOF-X for real-time reconstruction of detailed human geometry from a single image. Balancing real-time speed against high-quality results is a persistent challenge, mainly due to the high computational demands of existing 3D representations. To address this, we propose Fourier Occupancy Field (FOF), an efficient 3D representation by learning the Fourier series. The core of FOF is to factorize a 3D occupancy field into a 2D vector field, retaining topology and spatial relationships within the 3D domain while facilitating compatibility with 2D convolutional neural networks. Such a representation bridges the gap between 3D and 2D domains, enabling the integration of human parametric models as priors and enhancing the reconstruction robustness. Based on FOF, we design a new reconstruction framework, FOF-X, to avoid the performance degradation caused by texture and lighting. This enables our real-time reconstruction system to better handle the domain gap between training images and real images. Additionally, in FOF-X, we enhance the inter-conversion algorithms between FOF and mesh representations with a Laplacian constraint and an automaton-based discontinuity matcher, improving both quality and robustness. We validate the strengths of our approach on different datasets and real-captured data, where FOF-X achieves new state-of-the-art results. The code has already been released for research purposes at https://cic.tju.edu.cn/faculty/likun/projects/FOFX/index.html.

Shaoyang Xu, Weilong Dong, Zishan Guo et al.

Prior research has revealed that certain abstract concepts are linearly represented as directions in the representation space of LLMs, predominantly centered around English. In this paper, we extend this investigation to a multilingual context, with a specific focus on human values-related concepts (i.e., value concepts) due to their significance for AI safety. Through our comprehensive exploration covering 7 types of human values, 16 languages and 3 LLM series with distinct multilinguality (e.g., monolingual, bilingual and multilingual), we first empirically confirm the presence of value concepts within LLMs in a multilingual format. Further analysis on the cross-lingual characteristics of these concepts reveals 3 traits arising from language resource disparities: cross-lingual inconsistency, distorted linguistic relationships, and unidirectional cross-lingual transfer between high- and low-resource languages, all in terms of value concepts. Moreover, we validate the feasibility of cross-lingual control over value alignment capabilities of LLMs, leveraging the dominant language as a source language. Ultimately, recognizing the significant impact of LLMs' multilinguality on our results, we consolidate our findings and provide prudent suggestions on the composition of multilingual data for LLMs pre-training.

Ayan Banerjee, Aranyak Maity, Imane Lamrani et al.

Control affine assumptions, human inputs are external disturbances, in certified safe controller synthesis approaches are frequently violated in operational deployment under causal human actions. This paper takes a human-in-the-loop human-in-the-plant (HIL-HIP) approach towards ensuring operational safety of safety critical autonomous systems: human and real world controller (RWC) are modeled as a unified system. A three-way interaction is considered: a) through personalized inputs and biological feedback processes between HIP and HIL, b) through sensors and actuators between RWC and HIP, and c) through personalized configuration changes and data feedback between HIL and RWC. We extend control Lyapunov theory by generating barrier function (CLBF) under human action plans, model the HIL as a combination of Markov Chain for spontaneous events and Fuzzy inference system for event responses, the RWC as a black box, and integrate the HIL-HIP model with neural architectures that can learn CLBF certificates. We show that synthesized HIL-HIP controller for automated insulin delivery in Type 1 Diabetes is the only controller to meet safety requirements for human action inputs.

Matheus Valentim, Jeanette Falk, Nanna Inie

The recent leaps in complexity and fluency of Large Language Models (LLMs) mean that, for the first time in human history, people can interact with computers using natural language alone. This creates monumental possibilities of automation and accessibility of computing, but also raises severe security and safety threats: When everyone can interact with LLMs, everyone can potentially break into the systems running LLMs. All it takes is creative use of language. This paper presents Hacc-Man, a game which challenges its players to "jailbreak" an LLM: subvert the LLM to output something that it is not intended to. Jailbreaking is at the intersection between creative problem solving and LLM security. The purpose of the game is threefold: 1. To heighten awareness of the risks of deploying fragile LLMs in everyday systems, 2. To heighten people's self-efficacy in interacting with LLMs, and 3. To discover the creative problem solving strategies, people deploy in this novel context.

Comité Organizador de las 35 JAPV

Las Jornadas Argentinas de Paleontología de Vertebrados (JAPV) se realizan anualmente en nuestro país desde la década de 1980. El objetivo general es presentar, promover, difundir y discutir los últimos avances y resultados originales de los estudios sobre los vertebrados fósiles de Argentina. Aunque originalmente la reunión se planteó desde la necesidad de interacción entre la comunidad de paleontólogos de vertebrados de Argentina, durante las últimas décadas ha alcanzado un nivel internacional que convoca a especialistas del mundo especializados en diferentes temáticas tales como: taxonomía, anatomía, paleobiología, filogenia, paleobiogeografía, diversidad, evolución. Con la misma motivación, las 35º JAPV 2022 se realizaron por tercera vez con sede en el Museo Paleontológico Egidio Feruglio (MEF), Trelew, Chubut. Esta institución (Unidad Asociada a CONICET) presenta investigadores/as y becarios/as de CONICET que trabajan en diversas líneas de investigación en vertebrados fósiles (paleoherpetología y paleomastozoología), abarcando Mesozoico y Cenozoico hasta la actualidad.

NICHOLAS J. CZAPLEWSKI, CHARLES G. BAKER

We surveyed molar surface morphology of bats of 281 extant and extinct species in 5 archaic and 19 extant families using scanning microscopy. We note the occurrence of structural features on talonid crests, the cristid obliqua, postcristid, and entocristid, and their absence in upper molars, even of the same species having them on lowers. We term the structures “carnassiform notches” (CN) for their resemblance to similar features on the carnassial teeth of carnivorans. A CN consists of a small cleft in the edge of a talonid shearing crest accompanied by an adjacent “accessory trough” on the basinward side of the notch. The CN occur in bats with tribosphenic molar morphology and insectivorous or insectivorous–omnivorous dietary habits. Of 19 extant families examined, eight include members that possess lower molars with a CN in at least the cristid obliqua: Megadermatidae, Nycteridae, Mystacinidae, Furipteridae, Thyropteridae, Phyllostomidae, Natalidae, and Vespertilionidae (Murininae and Kerivoulinae only). An extinct genus of Hipposideridae, Vaylatsia, shows CN although extant hipposiderids do not. In extinct families for which lower molar fossils are available, notches were not recognized on the talonids, indicating the condition is not plesiomorphic for bats and probably evolved convergently in different lineages. Where present, the CN or troughs are morphologically consistent within a family, and might serve in some cases as characters supporting phylogenetic analyses and clade diagnoses. CN and accessory troughs probably increase the functional efficiency at sectioning chitin by increasing the effective length of a crest while maintaining the same cusp-to-cusp distance and precise occlusal relationships, and by improving the food-capture area of the shearing blade during occlusion. The accessory troughs provide an immediately adjacent fragment-clearance area. The increased sophistication of this food-processing system might be particularly important in species that must quickly acquire, chew, and swallow their food and resume echolocating in flight. The common ancestor of bats probably did not have CN in its molars, and the presence of CN does not signal carnivory in bats.

LARISA A. DOGUZHAEVA