Hasil untuk "Fossil man. Human paleontology"

Qi Li, Alexander Bi, Qian Li

Asian ctenodactyloids were highly diverse in the Paleogene. As early rodents, they provide important insights into the earliest evolution of the rodent brain. Here, we describe the first virtual endocasts of the early Eocene Exmus mini and the Oligocene Bounomys ulantatalensis and compare them with extant taxa (Ctenodactylus sp. and Pectinator spekei). From the Eocene to the present, the endocasts of ctenodactyloids reveal a reduction in olfactory bulb size, increased neocorticalization, expansion of the temporal lobes, a decrease in petrosal lobule size, and an overall increase in encephalization. Specifically, the cerebrum changes from an ovoid to a teardrop shape due to lateral expansion of the temporal lobes, and the petrosal lobule becomes much smaller in extant taxa. A reduction in the olfactory bulbs and petrosal lobules, and an increase in body mass not proportional to brain size, were observed from the early Eocene E. mini to the early Oligocene B. ulantatalensis, a change that may reflect ecological shifts during the Eocene–Oligocene transition.

SangYeop Jeong, Yeongseo Na, Seung Gyu Jeong et al.

In VR interactions with embodied conversational agents, users' emotional intent is often conveyed more by how something is said than by what is said. However, most VR agent pipelines rely on speech-to-text processing, discarding prosodic cues and often producing emotionally incongruent responses despite correct semantics. We propose an emotion-context-aware VR interaction pipeline that treats vocal emotion as explicit dialogue context in an LLM-based conversational agent. A real-time speech emotion recognition model infers users' emotional states from prosody, and the resulting emotion labels are injected into the agent's dialogue context to shape response tone and style. Results from a within-subjects VR study (N=30) show significant improvements in dialogue quality, naturalness, engagement, rapport, and human-likeness, with 93.3% of participants preferring the emotion-aware agent.

ZHU Xu-Feng, CHANG Fei, LI Yu, ZHANG Xu-Huang, GAO Dian-Song, WANG Qiang, QIU Rui, WANG Xiao-Lin, LIU Di, JIA Song-Hai, JIA Guang-Hui, ZHANG Jian-Hua, XU Li

The Upper Cretaceous of Tantou Basin in western Henan has yielded many vertebrate fossils, which are featured by several non-avian dinosaurs. Meanwhile, studies on their eggs were yet inadequate though many eggshells have been reported. The newly discovered material 41HⅤ0199 was excavated from the Upper Cretaceous Qiupa Formation in 2021. The block preserves eight complete eggs arranged in two partial rings that form a partial clutch, and there are some scattered eggshells preserved closely with the block, showing a concave-up to concave-down ratio of 54.5 : 45.5, which indicates that the scattered eggshells come from the clutch and the clutch had been partially broken before it was buried. Based on morphological and microstructural characteristics, the eggs and eggshells can be assigned to Macroolithus yaotunensis (Elongatoolithidae), an oospecies known to be related to oviraptorids, which leads Yulong mini to be its probable producer. Besides, some eggshells show microstructural signs indicating egg retention, which marks the second example of egg retention in the oofamily Elongatoolithidae.

Jan Batzner, Volker Stocker, Stefan Schmid et al.

Sycophantic response patterns in Large Language Models (LLMs) have been increasingly claimed in the literature. We review methodological challenges in measuring LLM sycophancy and identify five core operationalizations. Despite sycophancy being inherently human-centric, current research does not evaluate human perception. Our analysis highlights the difficulties in distinguishing sycophantic responses from related concepts in AI alignment and offers actionable recommendations for future research.

Md Mofijul Islam, Alexi Gladstone, Sujan Sarker et al.

As robots enter human workspaces, there is a crucial need for them to comprehend embodied human instructions, enabling intuitive and fluent human-robot interaction (HRI). However, accurate comprehension is challenging due to a lack of large-scale datasets that capture natural embodied interactions in diverse HRI settings. Existing datasets suffer from perspective bias, single-view collection, inadequate coverage of nonverbal gestures, and a predominant focus on indoor environments. To address these issues, we present the Refer360 dataset, a large-scale dataset of embodied verbal and nonverbal interactions collected across diverse viewpoints in both indoor and outdoor settings. Additionally, we introduce MuRes, a multimodal guided residual module designed to improve embodied referring expression comprehension. MuRes acts as an information bottleneck, extracting salient modality-specific signals and reinforcing them into pre-trained representations to form complementary features for downstream tasks. We conduct extensive experiments on four HRI datasets, including the Refer360 dataset, and demonstrate that current multimodal models fail to capture embodied interactions comprehensively; however, augmenting them with MuRes consistently improves performance. These findings establish Refer360 as a valuable benchmark and exhibit the potential of guided residual learning to advance embodied referring expression comprehension in robots operating within human environments.

Noora Sassali, Roel Pieters

Pointing gestures are a common interaction method used in Human-Robot Collaboration for various tasks, ranging from selecting targets to guiding industrial processes. This study introduces a method for localizing pointed targets within a planar workspace. The approach employs pose estimation, and a simple geometric model based on shoulder-wrist extension to extract gesturing data from an RGB-D stream. The study proposes a rigorous methodology and comprehensive analysis for evaluating pointing gestures and target selection in typical robotic tasks. In addition to evaluating tool accuracy, the tool is integrated into a proof-of-concept robotic system, which includes object detection, speech transcription, and speech synthesis to demonstrate the integration of multiple modalities in a collaborative application. Finally, a discussion over tool limitations and performance is provided to understand its role in multimodal robotic systems. All developments are available at: https://github.com/NMKsas/gesture_pointer.git.

Nicole Klein, Torsten M. Scheyer

Bone histology and microanatomy of neck and dorsal vertebrae, a dorsal rib, and osteoderms from different body regions of Eusaurosphargis aff. dalsassoi from Winterswijk, The Netherlands, are studied by petrographic thin sections and micro-computed tomographic (μCT) data. Osteohistology in the axial elements differs from that of marine reptiles and corroborates a terrestrial or semiaquatic life style for Eusaurosphargis aff. dalsassoi. Not only the outer shape and overall microanatomy of the osteoderms, but also the association and attachment of the osteoderms to the underlying endoskeletal element (i.e., cervical vertebra, rib, appendicular element) vary depending on body region. Furthermore, chondroid bone is identified in the osteoderms of Eusaurosphargis aff. dalsassoi, which is the oldest evidence of this tissue in osteoderms of an extinct tetrapod. For comparison, μCT data of two neural arches tentatively identifiable as pertaining to the enigmatic Middle Triassic Saurosphargis voltzi (the holotype and only specimen of this taxon is considered lost) could be included. They share with Eusaurosphargis aff. dalsassoi the elongated transverse processes and a general similar microstructure, but also present an anteroposteriorly broadened bony sheath of the transverse process in ventral view, which is absent in Eusaurosphargis aff. dalsassoi.

Mengyuan Liu, Chen Chen, Songtao Wu et al.

Recognizing interactive actions, including hand-to-hand interaction and human-to-human interaction, has attracted increasing attention for various applications in the field of video analysis and human-robot interaction. Considering the success of graph convolution in modeling topology-aware features from skeleton data, recent methods commonly operate graph convolution on separate entities and use late fusion for interactive action recognition, which can barely model the mutual semantic relationships between pairwise entities. To this end, we propose a mutual excitation graph convolutional network (me-GCN) by stacking mutual excitation graph convolution (me-GC) layers. Specifically, me-GC uses a mutual topology excitation module to firstly extract adjacency matrices from individual entities and then adaptively model the mutual constraints between them. Moreover, me-GC extends the above idea and further uses a mutual feature excitation module to extract and merge deep features from pairwise entities. Compared with graph convolution, our proposed me-GC gradually learns mutual information in each layer and each stage of graph convolution operations. Extensive experiments on a challenging hand-to-hand interaction dataset, i.e., the Assembely101 dataset, and two large-scale human-to-human interaction datasets, i.e., NTU60-Interaction and NTU120-Interaction consistently verify the superiority of our proposed method, which outperforms the state-of-the-art GCN-based and Transformer-based methods.

Benedetta Matcovich, Cristina Gena, Fabiana Vernero

In recent years, robotics has evolved, placing robots in social contexts, and giving rise to Human-Robot Interaction (HRI). HRI aims to improve user satisfaction by designing autonomous social robots with user modeling functionalities and user-adapted interactions, storing data on people to achieve personalized interactions. Personality, a vital factor in human interactions, influences temperament, social preferences, and cognitive abilities. Despite much research on personality traits influencing human-robot interactions, little attention has been paid to the influence of the robot's personality on the user model. Personality can influence not only temperament and how people interact with each other but also what they remember about an interaction or the person they interact with. A robot's personality traits could therefore influence what it remembers about the user and thus modify the user model and the consequent interactions. However, no studies investigating such conditioning have been found. This paper addresses this gap by proposing distinct user models that reflect unique robotic personalities, exploring the interplay between individual traits, memory, and social interactions to replicate human-like processes, providing users with more engaging and natural experiences

Margarito Mora-Núñez, Claudia Aurora Uribe Mú, Yalma Luisa Vargas Rodríguez et al.

En el estado de Jalisco, localizado en el oeste de México, se encuentran yacimientos fósiles que abarcan desde el Cretácico inferior al Cuaternario. En este trabajo se presenta una lista sistemática del registro fósil de Jalisco, México, y se analiza la composición de su riqueza. Fue revisada la literatura global sobre el tema y consultadas las colecciones que poseen material fósil de la región. Se obtuvieron un total de 293 especies organizadas en tres reinos, seis phyla, 12 clases, 49 órdenes, 87 familias y 184 géneros. Un total de 67 especies (22,9%) son microfósiles y 226 (77,1%) son macrofósiles. Los microfósiles incluyen dos especies de foraminíferos (3%) y 65 de diatomeas (97%). Entre los macrofósiles, el grupo mayormente representado a nivel de clase es Mammalia con 110 especies (48,7%), seguido por Gastropoda con 37 (16,4%), Sauropsida con 35 (15,5%) y Teleostei con 30 (13,3%); las clases con menor representación son Isopoda, Scaphopoda, Amphibia y Magnoliopsida con un registro cada una. El periodo mejor representado es el Cuaternario, con 199 especies (67,9%), seguido por el Neógeno con 49 especies (16,7%) y, finalmente, el Cretácico con 45 (15,4%). Por localidad, la más rica es Chapala y Zacoalco para el Cuaternario, Tecolotlán para el Neógeno y Tamazula para el Cretácico. Las especies incluidas fueron registradas desde 1875 hasta el 2022.

Zhenzhi Wang, Jingbo Wang, Yixuan Li et al.

Text-conditioned motion synthesis has made remarkable progress with the emergence of diffusion models. However, the majority of these motion diffusion models are primarily designed for a single character and overlook multi-human interactions. In our approach, we strive to explore this problem by synthesizing human motion with interactions for a group of characters of any size in a zero-shot manner. The key aspect of our approach is the adaptation of human-wise interactions as pairs of human joints that can be either in contact or separated by a desired distance. In contrast to existing methods that necessitate training motion generation models on multi-human motion datasets with a fixed number of characters, our approach inherently possesses the flexibility to model human interactions involving an arbitrary number of individuals, thereby transcending the limitations imposed by the training data. We introduce a novel controllable motion generation method, InterControl, to encourage the synthesized motions maintaining the desired distance between joint pairs. It consists of a motion controller and an inverse kinematics guidance module that realistically and accurately aligns the joints of synthesized characters to the desired location. Furthermore, we demonstrate that the distance between joint pairs for human-wise interactions can be generated using an off-the-shelf Large Language Model (LLM). Experimental results highlight the capability of our framework to generate interactions with multiple human characters and its potential to work with off-the-shelf physics-based character simulators. Code is available at https://github.com/zhenzhiwang/intercontrol

Galina Weinstein

In this paper, I review the book: Gary S. Berger, Michael DiRuggiero. "Einstein: The Man and His Mind." Bologna: Damiani, 2022. Illustrations. 209 pp. $70.00, cloth, ISBN 978-88-6208-784-1.

JENNIFER E. BAUER, SARAH L. SHEFFIELD, JOHNNY A. WATERS et al.

Understanding the phylogenetic relationship among derived blastozoans has been a goal of researchers since phylogenetic methodologies were first applied to Paleozoic echinoderms. Paul (2021) proposed a new “pan-dichoporites” group to circumscribe early Paleozoic blastozoans. Unfortunately, this work includes many inaccuracies, non-reproducible analyses, and nonstandard method choices that confuse rather than advance the understanding of echinoderm paleobiology. Herein, we focus on key aspects of philosophy, methodology, and data reproducibility the publication of Paul (2021) raises that need to be addressed and considered by echinoderm researchers as they assess the concept of pan-dichoporite echinoderms.

CHRISTOPHER R.C. PAUL

Cladistic analyses will be inaccurate if based on inaccurate data. Most blastozoan taxa were defined before cladistics was proposed. Redescription of precladistic taxa should be a priority. Cladistics recognizes similarities between taxa, not differences. Differences always exist, so the two approaches are asymmetrical. Any suggested similarity or homology needs testing, including output of computer-based analyses. New interpretations of plate homology between glyptocystitoid and hemicosmitoid rhombiferans had already rendered input data obsolete before the pan-dichoporite paper was published. Universal Elemental Homology (UEH) is not a scientific hypothesis. It makes no testable predictions; no system of naming plates can.

Nicole Klein, Heinz Furrer, Iris Ehrbar et al.

Abstract The Alpine Prosanto Formation (Middle Triassic) cropping out in the Ducan region in eastern Switzerland has yielded a rich fish and reptile fauna. Here, we present new pachypleurosaur remains from the upper part of the formation (Early Ladinian), similar to the previously known pachypleurosaurs from the Middle Triassic UNESCO World Heritage Site of Monte San Giorgio in southern Switzerland/northern Italy. From these remains, a new pachypleurosaur species, Prosantosaurus scheffoldi nov. gen. et spec., is described on the basis of six fairly complete skeletons, one disarticulated specimen and an isolated skull. As is typical for pachypleurosaurs and most other Triassic marine reptiles, the new taxon is based to a large degree on a combination of characters (e.g., nasals articulating broadly with the anterior margins of the prefrontals and lacking posterior processes; postorbitals with rounded anterior processes that articulate with the postfrontals anterolaterally) rather than on many unambiguous autapomorphies, although a few of the latter were found including (1) a premaxilla which is excluded from entering both the external and internal nares and (2) a parietal, which is distinctly longer than wide and carrying distinct anterolaterally angled processes. Phylogenetic relationships of the new taxon are tested within European Pachypleurosauria, revealing that the new species is the sister taxon to a clade including Serpianosaurus, Proneusticosaurus, and the monophyletic Neusticosaurus spp. Mapping of palaeogeographic and stratigraphical distribution of valid European pachypleurosaurs shows that a formerly proposed scenario of migration of pachypleurosaurs from the eastern Palaeotethys during the Olenekian into the Germanic Basin and a subsequent diversification and invasion during the Anisian into the intraplatform basins of the South Alpine realm must be re-assessed. The exceptional preservation and preparation of the Ducan fossils further allow the description of tooth replacement patterns for the first time in a European pachypleurosaur species. The “alveolarization” of replacement teeth, the horizontal replacement pattern, and the subsequent remodelling of the functional alveoli during tooth replacement supports the monophyly of Sauropterygia as discussed before.

CAROLINE J. BUTTLER, LESLEY CHERNS, LUCY M.E. MCCOBB

Silurian turreted gastropods from the Upper Leintwardine Formation, Ludlow Series, collected in Delbury Quarry, Shropshire, UK, are all encrusted by the trepostome bryozoan Homotrypa cochlea sp. nov. Bryozoans were not found to encrust any other component of the shelly fauna and thus seemed preferentially to choose the gastropod shells. The relationship between these two organisms was examined to consider whether the bryozoans were using the dead, empty mollusc shells as a substrate, if they were living symbiotically with live gastropods, or if the shells were inhabited by a non-gastropod host. There is evidence that the bryozoans encrusted the shells of living gastropods but continued growing after the death of the mollusc, potentially with the shell then occupied by a conchicole. Bryozoans encased the gastropod shells and, after death of the mollusc, the internal cavity became a “closed” microenvironment where the shell form and sometimes the recrystallised shell became preserved. The aragonitic shells of these gastropods were prone to dissolution early in diagenesis, and no gastropods are found without encrusting bryozoans. Bryoimmuration resulted in a local taphonomic window for the molluscs, which are notably sparse in most early Palaeozoic shelly faunas—the so-called “missing molluscs” phenomenon.

Richard G. Freedman, Joseph B. Mueller, Jack Ladwig et al.

Robots that interact with humans in a physical space or application need to think about the person's posture, which typically comes from visual sensors like cameras and infra-red. Artificial intelligence and machine learning algorithms use information from these sensors either directly or after some level of symbolic abstraction, and the latter usually partitions the range of observed values to discretize the continuous signal data. Although these representations have been effective in a variety of algorithms with respect to accuracy and task completion, the underlying models are rarely interpretable, which also makes their outputs more difficult to explain to people who request them. Instead of focusing on the possible sensor values that are familiar to a machine, we introduce a qualitative spatial reasoning approach that describes the human posture in terms that are more familiar to people. This paper explores the derivation of our symbolic representation at two levels of detail and its preliminary use as features for interpretable activity recognition.

Z. Yüce, H. Efe, Özge Uysal Yoca

INTRODUCTION Ancient DNA (aDNA) research has been an active field in molecular biology for over 30 years. Developing techniques has led to detailed studies that shed light on our past, future and interactions with the world we live in. Secrets of our ancient ancestors are revealed by working with archeological/paleontological samples, answering questions on our shared life on our planet. The recovery of DNA sequences from skeletal remains such as bones and teeth, reveal the genetic and evolutionary history of man; while also shedding light on the migration routes and demographic processes populations have undergone. In addition, aDNA studies have revealed environmental crises affecting population bottlenecks and demographic dynamics of several megafauna species up until their extinction. Data from ancient DNA is also a very important tool to draw conclusions about the mode and pace of evolutionary processes for reconstructing the phenotypic properties of prehistoric groups, and to consider the relative effects of selection and demography in changing allele frequencies within human populations (1). In addition to human studies, investigations on animals and plants are also extensively performed in aDNA research. These studies contribute to our knowledge on evolutionary processes occurring in animals and plants, extinct species, changes in genetic diversity in populations, the interaction of changes in the population with geographic location and determination of phylogenetic relationships (2). ABSTRACT

Felix Gradstein, Anna Waskowska

Abstract Globuligerina glinskikhae nov. sp. Gradstein & Waskowska and Globuligerina waskowskae nov. sp. Gradstein are new species of Jurassic planktonic foraminifera from the Middle Jurassic of Dagestan and Poland. G. glinskikhae nov. sp. with its remarkable ‘protoglobigerine’ test may be an early evolutionary offshoot of Globuligerina oxfordiana (Grigelis). It may be an index taxon for upper Bajocian through Bathonian strata in Eastern Europe and Southwest Asia, and might be recognizable also in thin sections. We consider G. waskowskae nov. sp. to be a possible forerunner of Conoglobigerina helvetojurassica (Haeusler), the first planktonic foraminiferal species with a reticulate wall texture. Currently, is only known from Poland. In some localities, specimens of G. oxfordiana and of G. glinskikhae nov. sp. posses an additional apertural opening, often lacking a rim; its function is enigmatic. The postulated lineage from Jurassic Globuligerina balakhmatovae (Morozova) to Cretaceous Clavihedbergella eocretacea Neagu is refined with the description of Petaloglobigerina simmonsi nov. gen., nov. sp. Gradstein from the Kimmeridgian of Portugal. The evolutionary transition from G. balakhmatovae to P. simmonsi occurs by means of the ontogenic development of a petaloid test, with a pronounced flattening of the whorl with ovate chambers, the last ones often offset and twisted. Jurassic planktonic foraminifera, now known to consist of three genera and 12+ species underwent long periods of stasis, interrupted by late Bajocian, mid-Oxfordian and early Kimmeridgian evolution. The three ‘stasis and root’ taxa G. oxfordiana, G. bathoniana and G. balakhmatovae are geographically widespread in lower to mid palaeo-latitudes, and stratigraphically long ranging within the Middle and Late Jurassic. Modern digital microscopes, with co-axial and side LED lighting and excellent image stacking software are important tools in the study of Jurassic planktonic foraminifera, and fast and cost-effective communication tools in modern micropalaeontology. ZooBank LSID: urn:lsid:zoobank.org:pub:A2927FFD-8C2B-4712-A06F-EE9D45ACA481.

Krishnananda Prabhu Sivananda, Francesco Verdoja, Ville Kyrki

While 2D occupancy maps commonly used in mobile robotics enable safe navigation in indoor environments, in order for robots to understand and interact with their environment and its inhabitants representing 3D geometry and semantic environment information is required. Semantic information is crucial in effective interpretation of the meanings humans attribute to different parts of a space, while 3D geometry is important for safety and high-level understanding. We propose a pipeline that can generate a multi-layer representation of indoor environments for robotic applications. The proposed representation includes 3D metric-semantic layers, a 2D occupancy layer, and an object instance layer where known objects are replaced with an approximate model obtained through a novel model-matching approach. The metric-semantic layer and the object instance layer are combined to form an augmented representation of the environment. Experiments show that the proposed shape matching method outperforms a state-of-the-art deep learning method when tasked to complete unseen parts of objects in the scene. The pipeline performance translates well from simulation to real world as shown by F1-score analysis, with semantic segmentation accuracy using Mask R-CNN acting as the major bottleneck. Finally, we also demonstrate on a real robotic platform how the multi-layer map can be used to improve navigation safety.