Hasil untuk "Fossil man. Human paleontology"

Adam Hepworth, Zena Assaad, Austin Wyatt et al.

Military human robot interaction (MHRI) presents a novel opportunity to blend the capabilities of autonomous and Artificial Intelligence (AI)-enabled systems with the skills and expertise of humans. The concept promises military advantages and greater operational effectiveness and efficiencies. However, the associated human-AI dynamics create challenges when attempting to design, implement, and operationalise the increasingly symbiotic relationship between humans and machines. Meaningful human control (MHC) is a popularised conceptualisation of what is deemed a responsible interaction among human and artificial agents; however, this notion falls short in military contexts and hinders the realisation of military advantages that could be achieved by advancing the adoption of responsible AI. This paper presents meaningful human command (MHC1) as a more operationally effective concept for advanced military command and control systems that embed AI-enabled autonomous systems. We introduce, explore, and unpack meaningful human command in the context of military human-robot interaction, presenting a vignette that offers a technologically feasible concept of an AI-enabled system within military operations. The vignette is used to guide, contextualise, and add realism to the narrative describing the concept and highlights associated MHRI challenges.

TSUKASA OKOSHI, RYUJI TAKASAKI, KENTARO CHIBA et al.

Numerous exquisitely preserved mammal fossils unearthed from Upper Cretaceous strata in the Gobi Desert of Mongolia have played a key role in understanding Mesozoic mammalian evolution. These splendid mammal fossils have been recovered mainly from the Baruungoyot and Djadokhta formations, but only two fragmentary remains of mammals have been collected from the underlying Bayanshiree Formation. Here we report a new species of Zhelestidae, Ravjaa ishiii gen. et sp. nov., based on a new mammal specimen recently discovered from the Bayanshiree Formation at the Bayan Shiree locality. The new specimen is represented by a well-preserved partial right dentary with the distal portion of an ultimate premolar and the first to the third molars. The gross observation and the phylogenetic analyses demonstrate zhelestid affinities: the subequally tall protoconid and metaconid, closely approximated hypoconulid and entoconid. Zhelestidae was widely distributed from Eurasia to North America in the Late Cretaceous but has not previously been recovered in the abundant Late Cretaceous mammalian fauna of Mongolia. This species represents the first zhelestid from the Mongolian Upper Cretaceous strata and contributes to further understanding of their paleobiogeographic and ecological insights.

Birger Moell

This study investigates the development and assessment of an artificial human designed as a conversational AI chatbot, focusing on its role as a clinical psychologist. The project involved creating a specialized chatbot using the Character.ai platform. The chatbot was designed to engage users in psychological discussions, providing advice and support with a human-like touch. The study involved participants (N=27) from diverse backgrounds, including psychologists, AI researchers, and the general public, who interacted with the chatbot and provided feedback on its human-likeness, empathy, and engagement levels. Results indicate that while many users found the chatbot engaging and somewhat human-like, limitations were noted in areas such as empathy and nuanced understanding. The findings suggest that although conversational AI has made strides, it remains far from achieving the true human-like interaction necessary for Artificial General Intelligence (AGI). The study highlights the challenges and potential of AI in human-computer interactions, suggesting directions for future research and development to bridge the gap between current capabilities and AGI. The project was completed in November of 2022 before the release of chatGPT.

Jingshu Li, Zicheng Zhu, Renwen Zhang et al.

Chatbots are increasingly integrated into people's lives and are widely used to help people. Recently, there has also been growing interest in the reverse direction-humans help chatbots-due to a wide range of benefits including better chatbot performance, human well-being, and collaborative outcomes. However, little research has explored the factors that motivate people to help chatbots. To address this gap, we draw on the Computers Are Social Actors (CASA) framework to examine how chatbot anthropomorphism-including human-like identity, emotional expression, and non-verbal expression-influences human empathy toward chatbots and their subsequent prosocial behaviors and intentions. We also explore people's own interpretations of their prosocial behaviors toward chatbots. We conducted an online experiment (N = 244) in which chatbots made mistakes in a collaborative image labeling task and explained the reasons to participants. We then measured participants' prosocial behaviors and intentions toward the chatbots. Our findings revealed that human identity and emotional expression of chatbots increased participants' prosocial behavior and intention toward chatbots, with empathy mediating these effects. Qualitative analysis further identified two motivations for participants' prosocial behaviors: empathy for the chatbot and perceiving the chatbot as human-like. We discuss the implications of these results for understanding and promoting human prosocial behaviors toward chatbots.

Bohan Huang, Qianyun Bao, Haoyuan Ma

Medical image segmentation faces significant challenges in preserving fine-grained details and precise boundaries due to complex anatomical structures and pathological regions. These challenges primarily stem from two key limitations of conventional U-Net architectures: (1) their simple skip connections ignore the encoder-decoder semantic gap between various features, and (2) they lack the capability for multi-scale feature extraction in deep layers. To address these challenges, we propose the U-Net with Multi-scale Adaptive KAN (U-MAN), a novel architecture that enhances the emerging Kolmogorov-Arnold Network (KAN) with two specialized modules: Progressive Attention-Guided Feature Fusion (PAGF) and the Multi-scale Adaptive KAN (MAN). Our PAGF module replaces the simple skip connection, using attention to fuse features from the encoder and decoder. The MAN module enables the network to adaptively process features at multiple scales, improving its ability to segment objects of various sizes. Experiments on three public datasets (BUSI, GLAS, and CVC) show that U-MAN outperforms state-of-the-art methods, particularly in defining accurate boundaries and preserving fine details.

Yaomin Jiang, Levin Brinkmann, Anne-Marie Nussberger et al.

Partner selection is crucial for cooperation and hinges on communication. As artificial agents, especially those powered by large language models (LLMs), become more autonomous, intelligent, and persuasive, they compete with humans for partnerships. Yet little is known about how humans select between human and AI partners and adapt under AI-induced competition pressure. We constructed a communication-based partner selection game and examined the dynamics in hybrid mini-societies of humans and bots powered by a state-of-the-art LLM. Through three experiments (N = 975), we found that bots, though more prosocial than humans and linguistically distinguishable, were not selected preferentially when their identity was hidden. Instead, humans misattributed bots' behaviour to humans and vice versa. Disclosing bots' identity induced a dual effect: it reduced bots' initial chances of being selected but allowed them to gradually outcompete humans by facilitating human learning about the behaviour of each partner type. These findings show how AI can reshape social interaction in mixed societies and inform the design of more effective and cooperative hybrid systems.

FERNANDO E. LOPEZ, OSVALDO A. CONDE, ALEJANDRO R. BRAECKMAN et al.

Graptolites represent one of the most important index fossils for the lower to middle Paleozoic biostratigraphy worldwide. Compared to other regions, graptolite faunas exhibited a marked decrease in diversity in Argentina during the Silurian, what resulted in reduced and low-varied registers and denied biostratigraphic works in its territory. This study introduces new Silurian graptolite faunas from the Los Espejos Formation, Poblete Norte section, Central Precordillera of Argentina. A total of thirteen graptolitic levels were identified, containing Bohemograptus bohemicus, Lobograptus sp., Saetograptus argentinus argentinus, Saetograptus cf. S. varians, Uncinatograptus uncinatus notouncinatus, Uncinatograptus elsae sp. nov., and Uncinatograptus lisandroi sp. nov. The occurrence of Uncinatograptus spp. in association with B. bohemicus could indicate the presence of the lower Gorstian Neodiversograptus nilssoni Biozone. A few meters above, the finding of S. a. argentinus in association with S. cf. S. varians, U. u. notouncinatus, and Lobograptus sp. suggest the presence of the lower Gorstian Lobograptus progenitor Biozone. The upper graptolitic beds yield specimens of S. a. argentinus and B. bohemicus, suggesting late Gorstian to early Ludfordian ages. These new graptolite faunas allow to correlate more precisely with local (Precordillera and Famatina), regional (North Western Argentina and Bolivia) and global equivalent sections. This discovery introduces new graptolite faunas, first-time recorded in South America, proposes for the first time a graptolite biostratigraphy for the Ludlow of Precordillera, and complements so far insufficient knowledge on Ludlovian graptolitic faunas of the continent in a critical time in the history of this fossil group.

Niroop Sugunaraj

This paper examines the complex nature of cyber attacks through an analysis of the LastPass breach. It argues for the integration of human-centric considerations into cybersecurity measures, focusing on mitigating factors such as goal-directed behavior, cognitive overload, human biases (e.g., optimism, anchoring), and risky behaviors. Findings from an analysis of this breach offers support to the perspective that addressing both the human and technical dimensions of cyber defense can significantly enhance the resilience of cyber systems against complex threats. This means maintaining a balanced approach while simultaneously simplifying user interactions, making users aware of biases, and discouraging risky practices are essential for preventing cyber incidents.

R. Folk

The late eighteenth and early nineteenth centuries have long been considered as a formative period for modern Irish political traditions such as nationalism, republicanism and unionism. For Europe it was the time of a turnover in science moving from observation to experiment and from speculation to fact. Richard Kirwan was a well known natural philosopher in Europe and a respected man of science in his time. Throughout all the wars, he was connected with his colleagues in a network reaching across Europe and even to America. Using a few examples, this article is intended to provide an insight how the network worked in a time that was marked by political conflicts and revolutionary events in both science and social life.

Marcelo R. Sánchez-Villagra, Mariano Bond, Marcelo Reguero et al.

Abstract Roth’s explorations, the resulting collections many now allocated in La Plata, Zurich, Geneva and Copenhagen, and his significant contributions in geological—especially stratigraphic—and paleontological topics, are a paradigmatic case for the global history of paleontology and for the Swiss migration history in Latin America. His work included the discovery of a diverse megafauna from the Pampean region, of sites and strata in Patagonia of paleontological significance, and the recognition of a group of endemic ungulate mammals, Notoungulata. Roth’s discovery of a human skeleton associated with a glyptodont carapace is one of the first reports of the coexistence of humans with the extinct fauna of the South American Quaternary. Roth became a renowned scholar at the Museo de La Plata, which was a leading scientific institution in the nation-making of Argentina, particularly in the expansion of the Patagonian frontier. He also kept strong ties with his native Switzerland, where late in his adult life he obtained some formal training and tried to attract other Swiss nationals to work in natural sciences in Argentina. His biography sheds light about the circumstances of his scientific collection and career in the interstices between amateur and professional science, modernity and imperialism at the turn of the twentieth century.

László Kocsis, Márton Rabi, Alex Ulianov et al.

Abstract The fossil vertebrate fauna of Máriahalom contains remains from a wide range of ecologies including terrestrial and aquatic mammals, crocodiles, sharks, and rays among others. All these were found mixed in mollusc-rich, shallow water, coastal deposits. The aim of the study is to trace the origin of the fossils using their rare earth element (REE) content and their respective ecology with stable oxygen isotopic compositions. In addition, marine vertebrates and calcareous marine fossils were analysed for their Sr isotope composition to provide a new age estimate for the locality. The REE content and their distribution in the fossils indicate similar early diagenetic environments and possible contemporaneous fossilization for the entire vertebrate assemblage. Reworked fossils of significantly different age can be excluded. The enamel/enameloid-derived phosphate oxygen isotope composition of selected fossil taxa fit well with previously inferred habitats that include marine, brackish, and terrestrial environments. Notably, the stem-pinniped Potamotherium valletoni is best interpreted as freshwater dweller instead of marine, consistent with the sedimentology of other occurrences. Our novel 87Sr/86Sr data suggest an Aquitanian age (21.4 ± 0.5 Ma) for the Máriahalom site that is younger than the previously proposed Late Oligocene age based on biostratigraphy (MP28–30 European Mammal Paleogene Reference Levels). An Aquitanian age raises the possibility that the index fossil taxon, the anthracothere mammal Microbunodon minimum, may have vanished earlier in Western Europe than in the Central Paratethys region.

Jialun Cai, Hong Liu, Runwei Ding et al.

3D human pose estimation errors would propagate along the human body topology and accumulate at the end joints of limbs. Inspired by the backtracking mechanism in automatic control systems, we design an Intra-Part Constraint module that utilizes the parent nodes as the reference to build topological constraints for end joints at the part level. Further considering the hierarchy of the human topology, joint-level and body-level dependencies are captured via graph convolutional networks and self-attentions, respectively. Based on these designs, we propose a novel Human Topology aware Network (HTNet), which adopts a channel-split progressive strategy to sequentially learn the structural priors of the human topology from multiple semantic levels: joint, part, and body. Extensive experiments show that the proposed method improves the estimation accuracy by 18.7% on the end joints of limbs and achieves state-of-the-art results on Human3.6M and MPI-INF-3DHP datasets. Code is available at https://github.com/vefalun/HTNet.

FANGYUAN MAO, CUNYU LIU, JIN MENG

A new specimen of Lactodens sheni, the only known spalacolestine from the Early Cretaceous Jehol Biota, is reported from the Jiufotang Formation, Liaoning, China. The description focuses on the dental and mandibular morphologies from both the new specimen and the holotype, particularly those that were unknown or poorly known from the holotype when the taxon was established. As revealed primarily by high-resolution computed tomography, morphologies and size gradient of the lower molars and detailed features of the mandibles, such as the masseteric foramen, can be unequivocally described. The dental and mandibular morphologies of Lactodens are compared with those of Origolestes lii, also from the Jehol Biota; these two taxa represent by far the best specimens in Spalacotheriidae and Zhangheotheriidae, respectively, and could be used as the representatives of their own groups in future higher-level phylogenetic analysis of mammals. The two taxa display considerable differences in dental and mandibular features, probably indicating a deeper split of spalacotheriids and zhangheotheriids than previously thought. Absence of the Meckelian groove in Lactodens, contrasting to the distinct one that holds a sizable Meckel’s cartilage in adult Origolestes, suggests an independent evolution of the definitive mammalian middle ear within “symmetrodontans”. The morphological gradient in the tooth row and association of the upper and lower dentitions from the same individual animal are also instructive for interpreting molar variations and evolution in “symmetrodontans” and mammals.

Taewoon Kim, Michael Cochez, Vincent Francois-Lavet et al.

Inspired by the cognitive science theory, we explicitly model an agent with both semantic and episodic memory systems, and show that it is better than having just one of the two memory systems. In order to show this, we have designed and released our own challenging environment, "the Room", compatible with OpenAI Gym, where an agent has to properly learn how to encode, store, and retrieve memories to maximize its rewards. The Room environment allows for a hybrid intelligence setup where machines and humans can collaborate. We show that two agents collaborating with each other results in better performance than one agent acting alone.

Di Fu, Fares Abawi, Erik Strahl et al.

Human eye gaze plays an important role in delivering information, communicating intent, and understanding others' mental states. Previous research shows that a robot's gaze can also affect humans' decision-making and strategy during an interaction. However, limited studies have trained humanoid robots on gaze-based data in human-robot interaction scenarios. Considering gaze impacts the naturalness of social exchanges and alters the decision process of an observer, it should be regarded as a crucial component in human-robot interaction. To investigate the impact of robot gaze on humans, we propose an embodied neural model for performing human-like gaze shifts. This is achieved by extending a social attention model and training it on eye-tracking data, collected by watching humans playing a game. We will compare human behavioral performances in the presence of a robot adopting different gaze strategies in a human-human cooperation game.

Takahiro Tsumura, Seiji Yamada

The social acceptance of AI agents, including intelligent virtual agents and physical robots, is becoming more important for the integration of AI into human society. Although the agents used in human society share various tasks with humans, their cooperation may frequently reduce the task performance. One way to improve the relationship between humans and AI agents is to have humans empathize with the agents. By empathizing, humans feel positively and kindly toward agents, which makes it easier to accept them. In this study, we focus on tasks in which humans and agents have various interactions together, and we investigate the properties of agents that significantly influence human empathy toward the agents. To investigate the effects of task content, difficulty, task completion, and an agent's expression on human empathy, two experiments were conducted. The results of the two experiments showed that human empathy toward the agent was difficult to maintain with only task factors, and that the agent's expression was able to maintain human empathy. In addition, a higher task difficulty reduced the decrease in human empathy, regardless of task content. These results demonstrate that an AI agent's properties play an important role in helping humans accept them.

Tim Schreiter, Tiago Rodrigues de Almeida, Yufei Zhu et al.

Rapid development of social robots stimulates active research in human motion modeling, interpretation and prediction, proactive collision avoidance, human-robot interaction and co-habitation in shared spaces. Modern approaches to this end require high quality datasets for training and evaluation. However, the majority of available datasets suffers from either inaccurate tracking data or unnatural, scripted behavior of the tracked people. This paper attempts to fill this gap by providing high quality tracking information from motion capture, eye-gaze trackers and on-board robot sensors in a semantically-rich environment. To induce natural behavior of the recorded participants, we utilise loosely scripted task assignment, which induces the participants navigate through the dynamic laboratory environment in a natural and purposeful way. The motion dataset, presented in this paper, sets a high quality standard, as the realistic and accurate data is enhanced with semantic information, enabling development of new algorithms which rely not only on the tracking information but also on contextual cues of the moving agents, static and dynamic environment.

Lucas Nicolás Lerzo, José Luis Carballido, Pablo Ariel Gallina

An isolated vertebra from the Late Cretaceous of Uzbekistan (Asia), previously interpreted as a titanosaur anterior caudal, was recently assigned as the holotype and unique specimen of a new rebbachisaurid taxon, Dzharatitanis kingi. This record would drastically impact both biogeographical and chronological aspects of the group. As some of the characters identified for such systematic assignment seem to have been incorrectly scored and/or have a more widespread distribution amongst Neosauropoda, we revised and discussed them in depth to verify the putative rebbachisaurid affinities of this taxon. The phylogenetic analyses carried out recovered Dzharatitanis as a titanosaur sauropod, most probably related to Lognkosauria. The extra steps needed to force Dzharatitanis within Rebbachisauridae confirms that its titanosaur affinity is not solely the most parsimonious hypothesis but also is well supported when the incompleteness of the material is considered. Given this new phylogenetic position, a new modified diagnosis is provided here. Although more complete evidence is needed, the reinterpretation of Dzharatitanis as a titanosaur with lognkosaurian affinities suggests a wider biogeographic distribution of this group of colossosaurs during the Cretaceous. At present, there is no reliable evidence to assume that rebbachisaurid sauropods have inhabited Asia.

DANIEL MADZIA, SVEN SACHS, MARK T. YOUNG et al.

Shijun Cai, Seok-Hee Hong, Jialiang Shen et al.

Understanding what graph layout human prefer and why they prefer is significant and challenging due to the highly complex visual perception and cognition system in human brain. In this paper, we present the first machine learning approach for predicting human preference for graph layouts. In general, the data sets with human preference labels are limited and insufficient for training deep networks. To address this, we train our deep learning model by employing the transfer learning method, e.g., exploiting the quality metrics, such as shape-based metrics, edge crossing and stress, which are shown to be correlated to human preference on graph layouts. Experimental results using the ground truth human preference data sets show that our model can successfully predict human preference for graph layouts. To our best knowledge, this is the first approach for predicting qualitative evaluation of graph layouts using human preference experiment data.