Hasil untuk "Fossil man. Human paleontology"

S. Gould, N. Eldredge

Daniela Soledad Monti

This paper provides a list of all named species in the family Olenidae, along with their geographic and stratigraphic records. It also discusses each of the valid genera in the family and describes the composition of the entire group and its subfamilies in terms of species and generic richness across different periods and geographical areas. The family encompasses 64 genera and 394 species, primarily concentrated in the subfamilies Oleninae and Pelturinae (65.63% of the genera and 58.12% of the species). The Olenidae was first documented during the Guzhangian in Baltica, and subsequently, its range expanded globally to Eastern Gondwana (Australia), South China, and Siberia. The Furongian saw a peak in species diversity (61.88% of the total) and widespread distribution. During the Tremadocian, the number of species declined, yet the geographic range persisted, and this decrease continued for the rest of the Ordovician. Although the family is cosmopolitan, Baltica and Avalonia host almost half of the records (46.71%). Challenges in olenid systematics include species lacking proper illustrations and/or lost type materials, poorly diagnosed genera, and potential polyphyletic larger families. The study emphasizes the importance of precise species and genus delimitation. The dataset presented serves as an initial step in achieving a clearer phylogenetic classification of the family Olenidae.

Kaitlynn Taylor Pineda, Ethan Brown, Chien-Ming Huang

Small talk can foster rapport building in human-human teamwork; yet how non-anthropomorphic robots, such as collaborative manipulators commonly used in industry, may capitalize on these social communications remains unclear. This work investigates how robot-initiated small talk influences task performance, rapport, and interaction dynamics in human-robot collaboration. We developed an autonomous robot system that assists a human in an assembly task while initiating and engaging in small talk. A user study ($N = 58$) was conducted in which participants worked with either a functional robot, which engaged in only task-oriented speech, or a social robot, which also initiated small talk. Our study found that participants in the social condition reported significantly higher levels of rapport with the robot. Moreover, all participants in the social condition responded to the robot's small talk attempts; 59% initiated questions to the robot, and 73% engaged in lingering conversations after requesting the final task item. Although active working times were similar across conditions, participants in the social condition recorded longer task durations than those in the functional condition. We discuss the design and implications of robot small talk in shaping human-robot collaboration.

Bongsu Kang, Jundong Kim, Tae-Rim Yun et al.

This study quantitively examines which features of AI-generated text lead humans to perceive subjective consciousness in large language model (LLM)-based AI systems. Drawing on 99 passages from conversations with Claude 3 Opus and focusing on eight features -- metacognitive self-reflection, logical reasoning, empathy, emotionality, knowledge, fluency, unexpectedness, and subjective expressiveness -- we conducted a survey with 123 participants. Using regression and clustering analyses, we investigated how these features influence participants' perceptions of AI consciousness. The results reveal that metacognitive self-reflection and the AI's expression of its own emotions significantly increased perceived consciousness, while a heavy emphasis on knowledge reduced it. Participants clustered into seven subgroups, each showing distinct feature-weighting patterns. Additionally, higher prior knowledge of LLMs and more frequent usage of LLM-based chatbots were associated with greater overall likelihood assessments of AI consciousness. This study underscores the multidimensional and individualized nature of perceived AI consciousness and provides a foundation for better understanding the psychosocial implications of human-AI interaction.

Petra Lukeneder, Dirk Fuchs, Alexander Lukeneder

Abstract Coleoid cephalopods are widespread from the Mesozoic till today. The extinct group of the Phragmoteuthida is thought to represent either stem-neocoleoids, stem-decabrachians, or stem-octobrachians. The well-known, almost complete specimens of Phragmoteuthis bisinuata from the Carnian Polzberg Konservat-Lagerstätte near Lunz am See (Lower Austria, Northern Calcareous Alps) and Cave del Predil (Northern Italy, Julian Alps) come from historical collections. These specimens do not reflect the entire coleoid assemblage within this environment. In order to obtain a more complete picture of the Carnian coleoid fauna, 430 coleoid specimens from the Polzberg locality and 60 specimens from contemporaneous localities around Cave del Predil were studied in detail. All available elements (phragmocones, proostraca, cartilages, hooks, beaks, ink sacs) attributed to the coleoid fauna were recorded, measured and evaluated taxonomically and taphonomically. Reviews of historical collection material permitted comparisons with recently collected material. The notation of co-occurrences of other faunal elements yielded insights into the palaeoecological context of this Upper Triassic environment within the Polzberg Basin. The new material from Polzberg does not support the previous assumption of a monospecific composition of the Polzberg coleoid fauna. Instead, we report the occurrence of the new phragmoteuthid Phragmoteuthis polzbergensis nov. sp. and a newly excavated specimen of Phragmoteuthis indicates the presence of ten arms within the group of the Phragmoteuthida for the first time. Phragmocones with small opening angles combined with cylindrical (roundly closed) body chambers, and arm hook types which are unusual for phragmoteuthids indicate the presence of the basal coleoid group comprising the rostrum-less genus Mojsisovicsteuthis. ZooBank LSID: urn:lsid:zoobank.org:pub:7EE7425C-6B0C-4800-925A-52D9108C13C7.

Di Fu, Fares Abawi, Philipp Allgeuer et al.

Mirroring non-verbal social cues such as affect or movement can enhance human-human and human-robot interactions in the real world. The robotic platforms and control methods also impact people's perception of human-robot interaction. However, limited studies have compared robot imitation across different platforms and control methods. Our research addresses this gap by conducting two experiments comparing people's perception of affective mirroring between the iCub and Pepper robots and movement mirroring between vision-based iCub control and Inertial Measurement Unit (IMU)-based iCub control. We discovered that the iCub robot was perceived as more humanlike than the Pepper robot when mirroring affect. A vision-based controlled iCub outperformed the IMU-based controlled one in the movement mirroring task. Our findings suggest that different robotic platforms impact people's perception of robots' mirroring during HRI. The control method also contributes to the robot's mirroring performance. Our work sheds light on the design and application of different humanoid robots in the real world.

Kevin Leahy, Ho Chit Siu

Conveying human goals to autonomous systems (AS) occurs both when the system is being designed and when it is being operated. The design-step conveyance is typically mediated by robotics and AI engineers, who must appropriately capture end-user requirements and concepts of operations, while the operation-step conveyance is mediated by the design, interfaces, and behavior of the AI. However, communication can be difficult during both these periods because of mismatches in the expectations and expertise of the end-user and the roboticist, necessitating more design cycles to resolve. We examine some of the barriers in communicating system design requirements, and develop an augmentation for applied cognitive task analysis (ACTA) methods, that we call robot task analysis (RTA), pertaining specifically to the development of autonomous systems. Further, we introduce a top-down view of an underexplored area of friction between requirements communication -- implied human expectations -- utilizing a collection of work primarily from experimental psychology and social sciences. We show how such expectations can be used in conjunction with task-specific expectations and the system design process for AS to improve design team communication, alleviate barriers to user rejection, and reduce the number of design cycles.

Mahnaz Roshanaei, Rezvaneh Rezapour, Magy Seif El-Nasr

Social interactions promote well-being, yet barriers like geographic distance, time limitations, and mental health conditions can limit face-to-face interactions. Emotionally responsive AI systems, such as chatbots, offer new opportunities for social and emotional support, but raise critical questions about how empathy is perceived and experienced in human-AI interactions. This study examines how empathy is evaluated in AI-generated versus human responses. Using personal narratives, we explored how persona attributes (e.g., gender, empathic traits, shared experiences) and story qualities affect empathy ratings. We compared responses from standard and fine-tuned AI models with human judgments. Results show that while humans are highly sensitive to emotional vividness and shared experience, AI-responses are less influenced by these cues, often lack nuance in empathic expression. These findings highlight challenges in designing emotionally intelligent systems that respond meaningfully across diverse users and contexts, and informs the design of ethically aware tools to support social connection and well-being.

Miguel A. Blanco-Rios, Milton O. Candela-Leal, Cecilia Orozco-Romo et al.

Within the field of Humanities, there is a recognized need for educational innovation, as there are currently no reported tools available that enable individuals to interact with their environment to create an enhanced learning experience in the humanities (e.g., immersive spaces). This project proposes a solution to address this gap by integrating technology and promoting the development of teaching methodologies in the humanities, specifically by incorporating emotional monitoring during the learning process of humanistic context inside an immersive space. In order to achieve this goal, a real-time emotion detection EEG-based system was developed to interpret and classify specific emotions. These emotions aligned with the early proposal by Descartes (Passions), including admiration, love, hate, desire, joy, and sadness. This system aims to integrate emotional data into the Neurohumanities Lab interactive platform, creating a comprehensive and immersive learning environment. This work developed a ML, real-time emotion detection model that provided Valence, Arousal, and Dominance (VAD) estimations every 5 seconds. Using PCA, PSD, RF, and Extra-Trees, the best 8 channels and their respective best band powers were extracted; furthermore, multiple models were evaluated using shift-based data division and cross-validations. After assessing their performance, Extra-Trees achieved a general accuracy of 96%, higher than the reported in the literature (88% accuracy). The proposed model provided real-time predictions of VAD variables and was adapted to classify Descartes' six main passions. However, with the VAD values obtained, more than 15 emotions can be classified (reported in the VAD emotion mapping) and extend the range of this application.

Tinghe Ding

Agents centered around Large Language Models (LLMs) are now capable of automating mobile device operations for users. After fine-tuning to learn a user's mobile operations, these agents can adhere to high-level user instructions online. They execute tasks such as goal decomposition, sequencing of sub-goals, and interactive environmental exploration, until the final objective is achieved. However, privacy concerns related to personalized user data arise during mobile operations, requiring user confirmation. Moreover, users' real-world operations are exploratory, with action data being complex and redundant, posing challenges for agent learning. To address these issues, in our practical application, we have designed interactive tasks between agents and humans to identify sensitive information and align with personalized user needs. Additionally, we integrated Standard Operating Procedure (SOP) information within the model's in-context learning to enhance the agent's comprehension of complex task execution. Our approach is evaluated on the new device control benchmark AitW, which encompasses 30K unique instructions across multi-step tasks, including application operation, web searching, and web shopping. Experimental results show that the SOP-based agent achieves state-of-the-art performance in LLMs without incurring additional inference costs, boasting an overall action success rate of 66.92\%. The code and data examples are available at https://github.com/alipay/mobile-agent.

Vaibhav Balloli, Sara Beery, Elizabeth Bondi-Kelly

Image retrieval plays a pivotal role in applications from wildlife conservation to healthcare, for finding individual animals or relevant images to aid diagnosis. Although deep learning techniques for image retrieval have advanced significantly, their imperfect real-world performance often necessitates including human expertise. Human-in-the-loop approaches typically rely on humans completing the task independently and then combining their opinions with an AI model in various ways, as these models offer very little interpretability or \textit{correctability}. To allow humans to intervene in the AI model instead, thereby saving human time and effort, we adapt the Concept Bottleneck Model (CBM) and propose \texttt{CHAIR}. \texttt{CHAIR} (a) enables humans to correct intermediate concepts, which helps \textit{improve} embeddings generated, and (b) allows for flexible levels of intervention that accommodate varying levels of human expertise for better retrieval. To show the efficacy of \texttt{CHAIR}, we demonstrate that our method performs better than similar models on image retrieval metrics without any external intervention. Furthermore, we also showcase how human intervention helps further improve retrieval performance, thereby achieving human-AI complementarity.

OLGA WILK

Sarcopterygian remains are relatively common in the so-called “Placoderm Sandstone” (storm-origin bone-bearing breccia) from the Emsian (Lower Devonian) of Podłazie in the Holy Cross Mountains (Poland). Previous studies have mainly referenced the presence of dipnomorphs, chiefly portrayed by porolepiforms and occurrences of dipnoans. Porolepiforms are represented by Porolepis ex gr. P. posnaniensis, based on scales, skull and shoulder-girdle elements, whereas other remains have been attributed to Heimenia sp. The aim of this paper is to present the most detailed description of the porolepiforms and other sarcopterygian fishes from the “Placoderm Sandstone” from the Holy Cross Mountains since 1960s. Here, I present a new study based on more than 200 specimens, using both microtomographic (CT-scan) and silicon casts analyses, which indicate that not two, but at least three different taxa of sarcopterygians occur in the “Placoderm Sandstone” from Podłazie. The new data presented herein depict a more diversified assemblage of sarcopterygians in the marginal-marine environment of the Lower Devonian of the Holy Cross Mountains than previously thought, and shed a new light on sarcopterygian diversity along the shores of the Old-Red continent.

NINON ALLAIRE, SAMUEL GINOT, KENNETH DE BAETS et al.

Fossils of Devonian ammonoids are abundant and well-preserved in the Anti-Atlas of Morocco; as such they provide an invaluable record of regional morphological disparity changes (diversity of shapes) that characterise the first steps of ammonoid evolution. However, they were rarely analysed quantitatively with respect to their morphological spectrum. Here, we investigated the morphological disparity of the Early–Middle Devonian ammonoids of the Moroccan Anti- Atlas by analysing the shape of their whorl profile. A geometric morphometric approach based on the acquisition of outline semilandmark coordinates was used to analyse the whorl profiles. For comparison, morphometric ratios based on classical conch measurements were also analysed to investigate the overall conch geometry. Several standard disparity estimators were computed to measure different aspects of morphological disparity fluctuations through time. It appears that a major increase in disparity occurred throughout the Early Devonian, followed by fluctuating disparity during the Middle Devonian constituting a general decreasing trend. Only the end-Eifelian Kačák Event shows a significant decrease in disparity. Thus, the ammonoids explored the range of possible shapes fairly quickly during their initial radiation; however, we found no evidence for an early burst of shape diversity (i.e., the rise does not exceed the expectations given diversity). Nevertheless, correlation tests between diversity and disparity time series support that they are partially decoupled. The highly resolved biozone record highlights that the increase in disparity began earlier than the increase in diversity that characterises the late Emsian.

Elke Schneebeli-Hermann, Evelyn Kustatscher

Abstract Well-preserved Carnian (Late Triassic) palynomorphs are rare in Switzerland, despite sediments include one of the important plant fossil localities, Neue Welt near Basel. Modern detailed palynological studies on Triassic palynomorphs in general and especially in the Carnian are scarce, most palynological studies were carried out more than 50 years ago. Nevertheless (Late) Triassic sediments still yield surprises for palynological research. Here, we present the results of the re-study of the famous Belchentunnel samples that were studied and published by Bernhard Scheuring in 1970. The less cheerful result concerns the preservation of slides: more than 60% of the slides are degraded. On the other hand, the restudy of the well-preserved slides showed an unexpected number of algae, acritarchs, and spore taxa not described so far. Especially the spores facilitate the correlation with the well-known biostratigraphic schemes established for the Germanic Basin. The distribution of Porcellispora longdonensis throughout the Belchentunnel succession is especially striking. The acme just below the Schilfsandstein might suggest the presence of ephemeral ponds.

ANGUS D. CROUDACE, CAIZHI SHEN, JUNCHANG LÜ et al.

Colour reconstructions have provided new insights into the lives of dinosaurs and other extinct animals, by predicting colouration patterns from fossilised pigment-bearing organelles called melanosomes. Although these methods have become increasingly popular, only a small number of dinosaurs have been studied using these techniques, which require exceptional preservation of fossil feathers, leaving open key questions such as whether dinosaurs changed their plumage patterns during ontogeny. Here we reconstruct the feather colouration of an approximately one-year-old individual of the Early Cretaceous dromaeosaurid theropod Wulong bohaiensis, which to our knowledge is the first unequivocal juvenile paravian for which aspects of the original colour has been predicted. Using quadratic discriminant analysis (QDA) and multinomial logistic regression (MLR) on the most comprehensive available datasets, we find strong evidence for iridescent plumage of the forelimb and hindlimb remiges and grey plumage on other portions of the body. This suggests that some juvenile paravians used shiny iridescent feathers for signalling purposes, possibly even before reaching somatic or sexual maturity, and thus we can conclude that this paravian used iridescent signalling for intraspecific communication other than sexual signalling. Finally, our results show that when analysing fossil datasets that are entirely comprised of solid and cylindrical melanosomes QDA consistently outperforms MLR, providing more accurate and higher classification probability colour predictions.

Sebastián Ariel Frezzia, Alejandro Fabián Zucol

La continua evolución de herramientas aplicadas en digitalización y modelado 3D, en el último tiempo, ha permitido su utilidad en diferentes campos científicos, uno de ellos la paleontología, dando beneficios en relación al estudio y la exposición de materiales fósiles. En el presente trabajo se exponen dos metodologías para digitalización de morfotipos fitolíticos como modelos tridimensionales a partir de imágenes en dos dimensiones utilizando software de libre acceso, denominados modelo de burbujas y modo esculpir. Ambas metodologías se consideran complementarias a la hora de generar un modelo de fitolito tridimensional. Esta propuesta resulta eficaz para lograr modelados 3D, generando no sólo una forma amigable para visualizar dichos morfotipos, sino también una manera efectiva para el conocimiento y entendimiento de la variedad de morfologías que pueden caracterizar a los silicofitolitos.

Stephanie M. Lukin, Kimberly A. Pollard, Claire Bonial et al.

Human-guided robotic exploration is a useful approach to gathering information at remote locations, especially those that might be too risky, inhospitable, or inaccessible for humans. Maintaining common ground between the remotely-located partners is a challenge, one that can be facilitated by multi-modal communication. In this paper, we explore how participants utilized multiple modalities to investigate a remote location with the help of a robotic partner. Participants issued spoken natural language instructions and received from the robot: text-based feedback, continuous 2D LIDAR mapping, and upon-request static photographs. We noticed that different strategies were adopted in terms of use of the modalities, and hypothesize that these differences may be correlated with success at several exploration sub-tasks. We found that requesting photos may have improved the identification and counting of some key entities (doorways in particular) and that this strategy did not hinder the amount of overall area exploration. Future work with larger samples may reveal the effects of more nuanced photo and dialogue strategies, which can inform the training of robotic agents. Additionally, we announce the release of our unique multi-modal corpus of human-robot communication in an exploration context: SCOUT, the Situated Corpus on Understanding Transactions.

Jakob Ambsdorf, Alina Munir, Yiyao Wei et al.

Recent developments in explainable artificial intelligence promise the potential to transform human-robot interaction: Explanations of robot decisions could affect user perceptions, justify their reliability, and increase trust. However, the effects on human perceptions of robots that explain their decisions have not been studied thoroughly. To analyze the effect of explainable robots, we conduct a study in which two simulated robots play a competitive board game. While one robot explains its moves, the other robot only announces them. Providing explanations for its actions was not sufficient to change the perceived competence, intelligence, likeability or safety ratings of the robot. However, the results show that the robot that explains its moves is perceived as more lively and human-like. This study demonstrates the need for and potential of explainable human-robot interaction and the wider assessment of its effects as a novel research direction.

Jitendra Maan, Harsh Maan

Cancer is one of the most common and fatal diseases in the world. Breast cancer affects one in every eight women and one in every eight hundred men. Hence, our prime target should be early detection of cancer because the early detection of cancer can be helpful to cure cancer effectively. Therefore, we propose a saliency detection system with the help of advanced deep learning techniques, such that the machine will be taught to emulate actions of pathologists for localization of diagnostically pertinent regions. We study identification of five diagnostic categories of breast cancer by training a CNN (VGG16, ResNet architecture). We have used BreakHis dataset to train our model. We focus on both detection and classification of cancerous regions in histopathology images. The diagnostically relevant regions are salient. The detection system will be available as an open source web application which can be used by pathologists and medical institutions.

F. Grine