Hasil untuk "Fossil man. Human paleontology"

C. Bae, K. Douka, M. Petraglia

Andreea Tulbure, Carmen Scheidemann, Elias Steiner et al.

Task-oriented handovers (TOH) are fundamental to effective human-robot collaboration, requiring robots to present objects in a way that supports the human's intended post-handover use. Existing approaches are typically based on object- or task-specific affordances, but their ability to generalize to novel scenarios is limited. To address this gap, we present AFT-Handover, a framework that integrates large language model (LLM)-driven affordance reasoning with efficient texture-based affordance transfer to achieve zero-shot, generalizable TOH. Given a novel object-task pair, the method retrieves a proxy exemplar from a database, establishes part-level correspondences via LLM reasoning, and texturizes affordances for feature-based point cloud transfer. We evaluate AFT-Handover across diverse task-object pairs, showing improved handover success rates and stronger generalization compared to baselines. In a comparative user study, our framework is significantly preferred over the current state-of-the-art, effectively reducing human regrasping before tool use. Finally, we demonstrate TOH on legged manipulators, highlighting the potential of our framework for real-world robot-human handovers.

Gaole He, Brian Y. Lim

Large Language Models (LLMs) are increasingly used to power autonomous agents for complex, multi-step tasks. However, human-agent interaction remains pointwise and reactive: users approve or correct individual actions to mitigate immediate risks, without visibility into subsequent consequences. This forces users to mentally simulate long-term effects, a cognitively demanding and often inaccurate process. Users have control over individual steps but lack the foresight to make informed decisions. We argue that effective collaboration requires foresight, not just control. We propose simulation-in-the-loop, an interaction paradigm that enables users and agents to explore simulated future trajectories before committing to decisions. Simulation transforms intervention from reactive guesswork into informed exploration, while helping users discover latent constraints and preferences along the way. This perspective paper characterizes the limitations of current paradigms, introduces a conceptual framework for simulation-based collaboration, and illustrates its potential through concrete human-agent collaboration scenarios.

Antoine Pictet, Serge Ferry, Lara Pietra

This study presents a high-resolution biostratigraphic analysis of a nearly 30 km long platform-to-slope transect on the southern margin of the Vercors Urgonian platform, based on detailed ammonite data. The primary objective is to refine the chronostratigraphic framework of the upper Barremian Urgonian series and to reassess the timing and significance of marlstone intercalations within the carbonate succession. For this purpose, more than 100 ammonite specimens were collected along the transect at various stratigraphic levels. All standard ammonite biozones and most subzones of the upper Barremian have been confidently identified, allowing precise dating of key sedimentary and stratigraphic events. A central issue concerns the platform-to-basin correlation of Paquier’s so-called “Heteroceras marlstone”, which conflates two distinct marly intercalations of different ages under a single term. We distinguish two major marlstone complexes – (1) Ambel / Font Froide – La Béguère and (2) Pas de la Couronne / La Révolte / Lower Orbitolina Beds – that have been variously attributed to, or confused with, the Heteroceras marlstone by Paquier, his followers, and his detractors. Based on ammonite biostratigraphy, only the second complex can be confidently correlated with the Heteroceras marlstone. Together with the Upper Orbitolina Beds, these intervals are interpreted as recording three successive ingressions, the final one marking the ultimate demise of the Urgonian platform near the Barremian–Aptian boundary. This revised biostratigraphic framework clarifies long-standing stratigraphic ambiguities, strengthens regional correlations, and provides new insights into the timing and mechanisms of Lower Cretaceous carbonate platform evolution in the western Tethys.

Comité Organizador de las XXXVIII JAPV

Libro de resúmenes de las XXXVIII Jornadas Argentinas de Paleontología de Vertebrados, que tuvieron lugar en la Ciudad de San Luis (San Luis, Argentina) del 21 al 23 de mayo de 2025.

Siyan Zhao, Jiachun Li, Gilles Cuny et al.

A taxonomic study of four tooth genera of euselachian sharks from the Ladinian–Carnian interval of the Guizhou and Yunnan Provinces, South China is presented. They include one euselachian shark of uncertain affinity, two indeterminate neoselachian sharks and one potential hexanchid shark. These four taxa display non-durophagous feeding behaviour, including grasping-swallowing, grasping, tearing and cutting strategies. High-resolution micro-CT scans and 3D reconstructions reveal that Euselachii gen. et sp. indet. and Neoselachii gen. et sp. indet. 1 possess orthodont teeth. Euselachii gen. et sp. indet. exhibits a prominent longitudinal vascular canal, but lacks an ascending pulp cavity, while Neoselachii gen. et sp. indet. 1 features two longitudinal vascular canals and a vascular cavity that ascends into the main cusp. To our knowledge, this study provides the first three-dimensional documentation of dental vascularisation in Triassic chondrichthyans.

B. Mecozzi, Ivana Fiore, B. Giaccio et al.

The site of Casal Lumbroso is located in the north-west sector of Rome (central Italy). Stratigraphic and geochemical data presented here evidence that the archaeological and paleontological horizon lies at the top of the Tiber River aggradational succession related to the MIS 11c sea level highstand (dated at ca. 404 ka), and that the paleohabitat was characterised by wooded environments and humid climatic conditions. Paleontological analysis allows attributing most of the remains to an adult individual of straight-tusked elephant, Palaeoloxodon antiquus, with sporadic elements referred to Stephanorhinus sp., Bovinae, Cervinae, Cervus elaphus, Dama sp., Canis sp., Oryctolagus sp., Talpa sp., Testudines, and Amphibia. Two bird remains are referred to Anatidae and Strigiformes. A rich lithic assemblage, mainly made of flint, was also found associated with the fossil remains. Taphonomic, technological and functional analyses indicate that the P. antiquus carcass was probably exploited by humans not only as a food source, but also as a source of raw material, as documented by the presence of several intentionally fractured elephant bone fragments, some of them also with flake removals, with localized use wear traces. The findings at Casal Lumbroso highlight once again the importance of the territory around the city of Rome for Middle Pleistocene studies. The northwestern sector of the city, where other important sites such as Castel di Guido and La Polledrara di Cecanibbio have also been discovered, is therefore crucial for understanding human strategies for exploiting elephant carcasses.

D. Alba

Debora Firmino de Souza, Sonia Sousa, Kadri Kristjuhan-Ling et al.

The Industry 5.0 transition highlights EU efforts to design intelligent devices that can work alongside humans to enhance human capabilities, and such vision aligns with user preferences and needs to feel safe while collaborating with such systems take priority. This demands a human-centric research vision and requires a societal and educational shift in how we perceive technological advancements. To better understand this perspective, we conducted a systematic literature review focusing on understanding how trust and trustworthiness can be key aspects of supporting this move towards Industry 5.0. This review aims to overview the most common methodologies and measurements and collect insights about barriers and facilitators for fostering trustworthy HRI. After a rigorous quality assessment following the Systematic Reviews and Meta-Analyses guidelines, using rigorous inclusion criteria and screening by at least two reviewers, 34 articles were included in the review. The findings underscores the significance of trust and safety as foundational elements for promoting secure and trustworthy human-machine cooperation. Confirm that almost 30% of the revised articles do not present a definition of trust, which can be problematic as this lack of conceptual clarity can undermine research efforts in addressing this problem from a central perspective. It highlights that the choice of domain and area of application should influence the choice of methods and approaches to fostering trust in HRI, as those choices can significantly affect user preferences and their perceptions and assessment of robot capabilities. Additionally, this lack of conceptual clarity can be a potential barrier to fostering trust in HRI and explains the sometimes contradictory findings or choice of methods and instruments used to investigate trust in robots and other autonomous systems in the literature.

Tauhid Tanjim, Jonathan St. George, Kevin Ching et al.

The human-robot interaction (HRI) field has recognized the importance of enabling robots to interact with teams. Human teams rely on effective communication for successful collaboration in time-sensitive environments. Robots can play a role in enhancing team coordination through real-time assistance. Despite significant progress in human-robot teaming research, there remains an essential gap in how robots can effectively communicate with action teams using multimodal interaction cues in time-sensitive environments. This study addresses this knowledge gap in an experimental in-lab study to investigate how multimodal robot communication in action teams affects workload and human perception of robots. We explore team collaboration in a medical training scenario where a robotic crash cart (RCC) provides verbal and non-verbal cues to help users remember to perform iterative tasks and search for supplies. Our findings show that verbal cues for object search tasks and visual cues for task reminders reduce team workload and increase perceived ease of use and perceived usefulness more effectively than a robot with no feedback. Our work contributes to multimodal interaction research in the HRI field, highlighting the need for more human-robot teaming research to understand best practices for integrating collaborative robots in time-sensitive environments such as in hospitals, search and rescue, and manufacturing applications.

Sasha Mitts

In the rapidly evolving field of artificial intelligence (AI), traditional benchmarks can fall short in attempting to capture the nuanced capabilities of AI models. We focus on the case of physical world modeling and propose a novel approach to augment existing benchmarks with human-derived evaluation criteria, aiming to enhance the interpretability and applicability of model behaviors. Grounding our study in the Perception Test and OpenEQA benchmarks, we conducted in-depth interviews and large-scale surveys to identify key cognitive skills, such as Prioritization, Memorizing, Discerning, and Contextualizing, that are critical for both AI and human reasoning. Our findings reveal that participants perceive AI as lacking in interpretive and empathetic skills yet hold high expectations for AI performance. By integrating insights from our findings into benchmark design, we offer a framework for developing more human-aligned means of defining and measuring progress. This work underscores the importance of user-centered evaluation in AI development, providing actionable guidelines for researchers and practitioners aiming to align AI capabilities with human cognitive processes. Our approach both enhances current benchmarking practices and sets the stage for future advancements in AI model evaluation.

David Stammer, Hannah Strauss, Peter Knees

The rapid rise of AI-generated art has sparked debate about potential biases in how audiences perceive and evaluate such works. This study investigates how composer information and listener characteristics shape the perception of AI-generated music, adopting a mixed-method approach. Using a diverse set of stimuli across various genres from two AI music models, we examine effects of perceived authorship on liking and emotional responses, and explore how attitudes toward AI, personality traits, and music-related variables influence evaluations. We further assess the influence of perceived humanness and analyze open-ended responses to uncover listener criteria for judging AI-generated music. Attitudes toward AI proved to be the best predictor of both liking and emotional intensity of AI-generated music. This quantitative finding was complemented by qualitative themes from our thematic analysis, which identified ethical, cultural, and contextual considerations as important criteria in listeners' evaluations of AI-generated music. Our results offer a nuanced view of how people experience music created by AI tools and point to key factors and methodological considerations for future research on music perception in human-AI interaction.

Janik Kaden, Maximilian Hilger, Tim Schreiter et al.

With robots increasingly integrating into human environments, understanding and predicting human motion is essential for safe and efficient interactions. Modern human motion and activity prediction approaches require high quality and quantity of data for training and evaluation, usually collected from motion capture systems, onboard or stationary sensors. Setting up these systems is challenging due to the intricate setup of hardware components, extensive calibration procedures, occlusions, and substantial costs. These constraints make deploying such systems in new and large environments difficult and limit their usability for in-the-wild measurements. In this paper we investigate the possibility to apply the novel Ultra-Wideband (UWB) localization technology as a scalable alternative for human motion capture in crowded and occlusion-prone environments. We include additional sensing modalities such as eye-tracking, onboard robot LiDAR and radar sensors, and record motion capture data as ground truth for evaluation and comparison. The environment imitates a museum setup, with up to four active participants navigating toward random goals in a natural way, and offers more than 130 minutes of multi-modal data. Our investigation provides a step toward scalable and accurate motion data collection beyond vision-based systems, laying a foundation for evaluating sensing modalities like UWB in larger and complex environments like warehouses, airports, or convention centers.

DENG Tao

Prof. Qiu Zhanxiang’s academic life presents a cross regional scientific research landscape: born in Qingdao City on the coast of the Yellow Sea, he devoted his life to exploring the mysteries of terrestrial mammalian evolution. In his early years, he received systematic training at the Geological Department of Moscow University and graduated in 1960, which laid a solid disciplinary foundation for him. After returning to China, he took root in the Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, starting a scientific research journey that lasted for more than half a century. As a paleontologist, his career has distinct international characteristics: from 1982 to 1984, he was awarded the Humboldt Scholarship from the Federal Republic of Germany and completed his doctoral thesis at the Gutenberg University of Mainz, and from 1982 to 1999, he conducted a series of international cooperation projects. His academic leadership was particularly prominent in his career, as he led multiple strategic scientific research projects during his tenure at the institute from 1991 to 1995. His scientific research footprint spans from the Nei Mongol Gobi to the Tibetan Plateau, and from the Yushe Basin in Shanxi Province to the Linxia Basin in Gansu Province. The National Climbing Plan of “Research on the origin of early human beings and environmental background” presided over by him has created a new paradigm of interdisciplinary research. In terms of disciplinary achievements, Prof. Qiu has achieved three landmark accomplishments: deciphering the evolutionary code of the Paleocene red bed mammalian fauna of South China, clarifying the lineage of giant rhino fossils, and establishing a biochronological scale for the Neogene terrestrial strata in China and conducting in-depth research on the carnivore and perissodactyl fossils contained therein. These achievements have provided a key evidence chain for analyzing the evolutionary mechanism of mammals’ adaptation to environmental changes over 66 million years, which not only won him the title of CAS Academician in 2005, but also left China’s mark in the field of international Cenozoic paleontology and stratigraphy.

LI Chun-Xiao, TANG Jian-Rong, WANG Shi-Qi, WANG Lin-Chang, ZHENG Ying-Kai, DENG Ke, LIN Min, CHEN Run-Sheng, ZHOU Guo-Wu, CHEN Zhong-Yang

Stegolophodon is an age-informative genus of mammals that had a widespread distribution during the Neogene. This paper reports the discovery of Stegolophodon fossils from the Middle Miocene lower Fotan Formation at the Zhangpu locality, Fujian Province, China. This discovery represents the first evidence of Neogene proboscidean fossils in southeastern China. The newly found molar materials have low tooth crowns, very straight lophs/lophids, and an indistinct median sulcus. The mesoconelets and posterior cingulum are well-developed, while the second posterior pretrite central conule is significantly reduced. These specimens closely resemble Stegolophodon pseudolatidens in cheek tooth morphology, and can thus be attributed to the same species. This discovery fills a gap in the fossil record of large mammals in this region during the Neogene and provides valuable insights into the evolution of proboscideans and paleoenvironments.

B. Mecozzi, Alessio Iannucci, Marco Carpentieri et al.

Here we revise all the paleontological sample of Notarchirico, including historical collections and new findings collected during 2016–2023 excavations. Notarchirico is one of the most significant sites for the study of human evolution and terrestrial ecosystem dynamics during the Early-Middle Pleistocene Transition, preserving nearly 100.000 years of environmental and climatic changes constrained between 695 ± 6 ka and 614 ± 12 ka. The deposit yielded the oldest human fossil of the Italian Peninsula, and one of the oldest European evidence of Homo heidelbergensis, as well as one of the earliest evidence of bifacial tools in western Europe, commonly associated with the Acheulean techno-complex. Our paleontological results revealed the presence of three different mammal complexes, documenting faunal dynamics in response of climatic driven-changes recognized during the early Middle Pleistocene. The lower complex (levels I2-G) indicates the dominance of wooded spaces, sparse steppes, and the existence of water bodies (lakes or ponds), indicating a deterioration of the fully interglacial conditions recorded during the end of MIS 17; the middle complex (levels G-C) with a low number of mammal remains can be attributed to the glacial conditions of MIS 16; the upper complex (levels B-above α) indicates an improvement in climate, transitioning towards the full interglacial conditions of the of MIS 15. The faunal sample of Notarchirico, based on its firm chronological setting, offers important data for the Biochronological Scheme of European Land Mammals, including one of the oldest records of Palaeoloxodon antiquus and Cervus elaphus in Europe, Panthera spelaea in southwestern Europe, Dama cf. roberti in Italian Peninsula, and one of the latest occurrences of Bison schoetensacki in Europe.

Enrico Martini, Harshil Parekh, Shaoting Peng et al.

Pursuing natural and marker-less human-robot interaction (HRI) has been a long-standing robotics research focus, driven by the vision of seamless collaboration without physical markers. Marker-less approaches promise an improved user experience, but state-of-the-art struggles with the challenges posed by intrinsic errors in human pose estimation (HPE) and depth cameras. These errors can lead to issues such as robot jittering, which can significantly impact the trust users have in collaborative systems. We propose a filtering pipeline that refines incomplete 3D human poses from an HPE backbone and a single RGB-D camera to address these challenges, solving for occlusions that can degrade the interaction. Experimental results show that using the proposed filter leads to more consistent and noise-free motion representation, reducing unexpected robot movements and enabling smoother interaction.

Zhibin Liu, Haoye Dong, Aviral Chharia et al.

Generating lifelike 3D humans from a single RGB image remains a challenging task in computer vision, as it requires accurate modeling of geometry, high-quality texture, and plausible unseen parts. Existing methods typically use multi-view diffusion models for 3D generation, but they often face inconsistent view issues, which hinder high-quality 3D human generation. To address this, we propose Human-VDM, a novel method for generating 3D human from a single RGB image using Video Diffusion Models. Human-VDM provides temporally consistent views for 3D human generation using Gaussian Splatting. It consists of three modules: a view-consistent human video diffusion module, a video augmentation module, and a Gaussian Splatting module. First, a single image is fed into a human video diffusion module to generate a coherent human video. Next, the video augmentation module applies super-resolution and video interpolation to enhance the textures and geometric smoothness of the generated video. Finally, the 3D Human Gaussian Splatting module learns lifelike humans under the guidance of these high-resolution and view-consistent images. Experiments demonstrate that Human-VDM achieves high-quality 3D human from a single image, outperforming state-of-the-art methods in both generation quality and quantity. Project page: https://human-vdm.github.io/Human-VDM/

Morten Roed Frederiksen, Katrin Fischer, Maja Matarić

This paper describes a between-subjects Amazon Mechanical Turk study (n = 220) that investigated how a robot's affective narrative influences its ability to elicit empathy in human observers. We first conducted a pilot study to develop and validate the robot's affective narratives. Then, in the full study, the robot used one of three different affective narrative strategies (funny, sad, neutral) while becoming less functional at its shopping task over the course of the interaction. As the functionality of the robot degraded, participants were repeatedly asked if they were willing to help the robot. The results showed that conveying a sad narrative significantly influenced the participants' willingness to help the robot throughout the interaction and determined whether participants felt empathetic toward the robot throughout the interaction. Furthermore, a higher amount of past experience with robots also increased the participants' willingness to help the robot. This work suggests that affective narratives can be useful in short-term interactions that benefit from emotional connections between humans and robots.

Martin Wolfgang Lauer-Schmaltz, Philip Cash, John Paulin Hansen et al.

Human Digital Twins (HDTs) are a fast-emerging technology with significant potential in fields ranging from healthcare to sports. HDTs extend the traditional understanding of Digital Twins by representing humans as the underlying physical entity. This has introduced several significant challenges, including ambiguity in the definition of HDTs and a lack of guidance for their design. This survey brings together the recent advances in the field of HDTs to guide future developers by proposing a first cross-domain definition of HDTs based on their characteristics, as well as eleven key design considerations that emerge from the associated challenges.