Representation Of World Research Articles

Hippocampal coding of identity, sex, hierarchy, and affiliation in a social group of wild fruit bats.

Social animals live in groups and interact volitionally in complex ways. However, little is known about neural responses under such natural conditions. Here, we investigated hippocampal CA1 neurons in a mixed-sex group of five to 10 freely behaving wild Egyptian fruit bats that lived continuously in a laboratory-based cave and formed a stable social network. In-flight, most hippocampal place cells were socially modulated and represented the identity and sex of conspecifics. Upon social interactions, neurons represented specific interaction types. During active observation, neurons encoded the bat's own position and head direction, together with the position, direction, and identity of multiple conspecifics. Identity-coding neurons encoded the same bat across contexts. The strength of identity coding was modulated by sex, hierarchy, and social affiliation. Thus, hippocampal neurons form a multidimensional sociospatial representation of the natural world.

Hierarchical surprise signals in naturalistic violation of expectations

Abstract Surprise responses signal both high-level cognitive alerts that information is missing, and increasingly specific back-propagating error signals that allow updates in processing nodes. Studying surprise is, hence, central for cognitive neuroscience to understand internal world representations and learning. Yet, only few prior studies used naturalistic stimuli targeting our high-level understanding of the world. Here, we use magic tricks in an fMRI experiment to investigate neural responses to violations of core assumptions held by humans about the world. We showed participants naturalistic videos of three types of magic tricks, involving objects appearing, changing color, or disappearing, along with control videos without any violation of expectation. Importantly, the same videos were presented with and without prior knowledge about the tricks’ explanation. Results revealed generic responses in frontal and parietal areas, together with responses specific to each of the three trick types in posterior sensory areas. A subset of these regions, the midline areas of the default mode network (DMN), showed surprise activity that depended on prior knowledge. Equally, sensory regions showed sensitivity to prior knowledge, reflected in differing decoding accuracies. These results suggest a hierarchy of surprise signals involving generic processing of violation of expectations in frontal and parietal areas with concurrent surprise signals in sensory regions that are specific to the processed features.

Behind the lenses: Biases in the contribution of wildlife photography to biodiversity representation

Abstract Nature‐related visual media has a significant impact on today's society by engaging the public in conservation problems and promoting pro‐environmental behaviours. Although major attention has been paid to how some types of visual media (e.g. documentaries) offer unrealistic portrayals of the natural world, biases on representation by wildlife photography remain unexplored. In the present study, we assessed biases in wildlife photography at spatial, temporal, taxonomic, conservation status and selection criteria scales, and modelled the factors influencing the probability of portrayed organisms winning a wildlife photography contest by using data on 1333 pictures featured in the Wildlife Photographer of the Year, one of the most popular wildlife photography competitions worldwide. The representation of biomes mostly coincides with their extension on the planet. However, we detected an overrepresentation of temperate (broadleaf and conifer), Mediterranean and tropical forests. We detected a positive change over time in representing historically neglected taxa, such as insects. We also detected an increase in representation of Mangroves, Marine Ecosystems, Tundra and temperate forests and grasslands. Mammals and birds were overrepresented in photographs while insects and plants were underrepresented, and so were species listed as ‘Least Concern’ and ‘Data Deficiency’. The top 10 ranking species included charismatic carnivore species. Our results showed that the jury's choice offered a more diverse representation of biodiversity than the people's choice, and the winning photographs showcased fewer taxonomic groups than the non‐winning pictures. Realm, domain and colourfulness influenced the probability of an organism's picture being winner, but the variability explained by our model reflects that there are a large number of unexplored determinants (e.g. socio‐economical, technical or emotional). Our research detected a trend towards a more balanced representation of the natural world in wildlife photography, although biases are yet large, which may influence people's perception of the current status of species and habitats they encompass. Our results highlight a need to evenly represent species and ecosystems to increase public awareness, which requires providing data on species identity and conservation status to increase public knowledge. Finally, we underscore the need to report compliance with ethical guidelines when photographing wildlife. Read the free Plain Language Summary for this article on the Journal blog.

AN ANALYSIS OF AN ENGLISH AS A FOREIGN LANGUAGE TEXTBOOK UNDER THE CRITICAL DISCOURSE ANALYSIS PERSPECTIVE: The representation of the anglophonic world

Critical Discourse Analysis (CDA) is concerned with the investigation and study of different means of power that are perpetrated through the discourse practice. Furthermore, the reproduction and the combat to these hegemonic discourses are concerns to the CDA. In this sense, the present research aimed to analyze a textbook, which is academically used in an English Language Course to form English teachers at a university, under the CDA theoretical framework. The inquisitive look of the research is directed to the representations of the anglophonic communities in the analyzed material. From this idea, the general objective of the research was to analyze, from the CDA perspective, the representations of the anglophonic world in the textbook. It was also aimed to investigate the ideology and hegemony that encompass the discourse of the textbook. The Textbook used in this study was The New Framework 2. In order to pursuit the objectives, the Theoretical Framework was based on different CDA theoreticians, such as Fairclough (2001), and Van Dijk (2012). The research was also based on theoreticians from the cultural studies, sociology, history and education (teaching/learning of Foreign Languages), such as Lacoste (2005) and Thompson (2011). The study showed that the Textbook utilized in the research transmits a certain ideology that will be passed on in classrooms; meaning that there is a hegemonic discourse that finds its way to be perpetuated.

Stimulus-invariant aspects of the retinal code drive discriminability of natural scenes

Everything that the brain sees must first be encoded by the retina, which maintains a reliable representation of the visual world in many different, complex natural scenes while also adapting to stimulus changes. This study quantifies whether and how the brain selectively encodes stimulus features about scene identity in complex naturalistic environments. While a wealth of previous work has dug into the static and dynamic features of the population code in retinal ganglion cells (RGCs), less is known about how populations form both flexible and reliable encoding in natural moving scenes. We record from the larval salamander retina responding to five different natural movies, over many repeats, and use these data to characterize the population code in terms of single-cell fluctuations in rate and pairwise couplings between cells. Decomposing the population code into independent and cell-cell interactions reveals how broad scene structure is encoded in the retinal output. while the single-cell activity adapts to different stimuli, the population structure captured in the sparse, strong couplings is consistent across natural movies as well as synthetic stimuli. We show that these interactions contribute to encoding scene identity. We also demonstrate that this structure likely arises in part from shared bipolar cell input as well as from gap junctions between RGCs and amacrine cells.

Monte Carlo tree search with spectral expansion for planning with dynamical systems.

The ability of a robot to plan complex behaviors with real-time computation, rather than adhering to predesigned or offline-learned routines, alleviates the need for specialized algorithms or training for each problem instance. Monte Carlo tree search is a powerful planning algorithm that strategically explores simulated future possibilities, but it requires a discrete problem representation that is irreconcilable with the continuous dynamics of the physical world. We present Spectral Expansion Tree Search (SETS), a real-time, tree-based planner that uses the spectrum of the locally linearized system to construct a low-complexity and approximately equivalent discrete representation of the continuous world. We prove that SETS converges to a bound of the globally optimal solution for continuous, deterministic, and differentiable Markov decision processes, a broad class of problems that includes underactuated nonlinear dynamics, nonconvex reward functions, and unstructured environments. We experimentally validated SETS on drone, spacecraft, and ground vehicle robots and one numerical experiment, each of which is not directly solvable with existing methods. We successfully show that SETS automatically discovers a diverse set of optimal behaviors and motion trajectories in real time.

Detection of RPL-based Routing Attacks Using Machine Learning Algorithms

This study analyzes various machine learning techniques for detecting attacks against Routing Protocol for Low-Power and Lossy Networks (RPL), a routing protocol commonly used in Internet of Things (IoT) applications. RPL is often employed in IPv6-based IoT applications that require low power consumption and limited bandwidth. The research reviews recent literature examining attacks on RPL-based networks and utilizes the ROUT-4-2023 dataset for detecting routing attacks. This dataset, created using the Cooja simulator, encompasses four types of routing attacks: Blackhole Attack, Flooding Attack, DODAG Version Number Attack, and Decreased Rank Attack. The attack types are detected using machine learning techniques like AdaBoost, KNN, Random Forest, Decision Tree, and Bagging. In the combined dataset, the Decision Tree and Bagging algorithm exhibited the highest performance with a 99.99% accuracy. To create a more accurate representation of the real world, we incorporate a 10% level of noise into the dataset. On the noisy dataset, Random Forest algorithm performed the best with about 84.80% accuracy. The high accuracy show that the employed methods can be effectively used as an Intrusion Detection System (IDS) to protect IoT networks. As a result, this study demonstrates that machine learning techniques offer a promising approach for detecting routing attacks in the RPL protocol. The findings provide useful information for researchers and practitioners in the field of IoT security. This study contributes to the potential of machine learning-based algorithms to enhance the security of IoT networks and contributes to future research in this area.

Accuracy Assessment of an Image-Based Cloud-Based Indoor Mapping Platform as an Alternative for Desktop Applications

Abstract. The generation of 3D spatial datasets, especially in indoor space, has continually been a challenge in developing spatial applications that are aimed for the realistic representation of the real world. Despite their potential, the creation of 3D spatial data remains a challenge, particularly in terms of cost and complexity associated with traditional methods. While this method proves to be a reliable and accurate method of creating such data, this approach entails challenges in economic, computational, and human resource aspects. Alternatively, omnidirectional images have emerged as cost-effective alternatives for representing 3D spaces, offering a comprehensive field of view and facilitating the generation of structure and appearance representations through mesh-based 3D maps. This study evaluates the geometric accuracy of a cloud-based image-based mapping platform for generating 3D representations of indoor spaces, aiming to assess its suitability as an alternative to desktop-based platforms. We obtained 30 sample lines and compare respective measurements from each of the generated meshes to a ground truth value. Results show that while there are no significant differences in the mean errors, the mesh generated from a cloud-based platform produced minimal errors. This demonstrates the potential of this platform for generating 3D representations of indoor space, acceptable in both geometric accuracy and visualization capabilities.

A Fast Cross‐Chain Protocol Based on Trusted Notary Group for Metaverse

ABSTRACTThe metaverse is a virtual environment that combines the real and digital worlds through technological and social structures. It heralds a novel paradigm in internet applications and societal engagement by weaving together diverse cutting‐edge technologies to facilitate a virtual representation of the tangible world. Within the metaverse, the facets of economy, culture, and other dimensions are fully documentable, trackable, and quantifiable, largely owing to the capabilities of blockchain technology. Nonetheless, the transactional volume within the metaverse is typically substantial, posing challenges for a singular blockchain platform in terms of efficiency and support capacity. Consequently, a multi‐blockchain infrastructure becomes essential to underpin the economic fabric of the metaverse. Enabling the collaborative operation of multiple blockchain platforms, specifically achieving the seamless transfer of value across different blockchain ecosystems, has emerged as a critical challenge. To address this challenge, this paper introduces a cross‐chain protocol predicated on a multi‐role notary system designed to facilitate inter‐blockchain value transfers. The protocol specifies the functions of different entities within the notary framework, allocating specific duties to notaries, committees, and a leader. It also promotes mutual oversight among notaries to sustain a dynamic and equitable group structure. Furthermore, an incentive mechanism is proposed to motivate committee members toward prompt and judicious decision‐making regarding votes. Based on experiments conducted on the Ethereum platform, our proposed solution exhibits a 75% reduction in transaction time compared to Ethereum's transaction confirmation time.

Perception, Evolution, and the Explanatory Scope of Scientific Theories

According to the interface theory of perception, our perceptual systems have evolved to provide a species-specific interface to guide adaptive behaviour, and not to provide veridical representations of an observer-independent world. Results of simulations of evolutionary resource games, genetic algorithms, and multiple mathematical theorems have supported and fleshed out this claim in various ways. They indicate that the probability is zero that any perceptual system has been shaped by natural selection to represent the true structure of an observer-independent world. Bagwell (2023) thinks that this argument is self-defeating because it implies that organisms, resources, genes, etc. that are essential constituents of Darwin's theory do not provide an insight into the nature of observerindependent reality. Bagwell's argument relies on a false premise, however — namely, that the mathematical formulation of a scientific theory cannot dethrone its fundamental concepts. More broadly, his argument involves a fundamental misunderstanding of the nature of scientific theories — of their explanatory scope and their necessary limits.

Deconstructing Radiant Inventory: Christopher Dewdney's Representations of the Natural World in Radiant Inventory

This article presents an analysis of Christopher Dewdney’s “Radiant Inventory” using the literary theory of deconstruction. The purpose is to try and understand the poem through Jacques Derrida’s deconstruction. The article will further examine how the deconstruction of the poem can bring the traditional notion of reading a text into application and how the perception of reality can be challenged to show multiple perspectives using language and imagery. The analysis sheds light on the poem’s questioning of the relationship between object and identity and the role of language in shaping our understanding of reality. It will strictly adhere to Jacques Derrida’s deconstruction. The purpose is to demonstrate how the deconstructive approach can offer a deeper understanding of the complexities and nuances present in the poem.

Traces of Our Past: The Social Representation of the Physical World

How do humans build and navigate their complex social world? Standard theoretical frameworks often attribute this success to a foundational capacity to analyze other people’s appearance and behavior to make inferences about their unobservable mental states. Here we argue that this picture is incomplete. Human behavior leaves traces in our physical environment that reveal our presence, our goals, and even our beliefs and knowledge. A new body of research shows that, from early in life, humans easily detect these traces—sometimes spontaneously—and readily extract social information from the physical world. From the features and placement of inanimate objects, people make inferences about past events and how people have shaped the physical world. This capacity develops early and helps explain how people have such a rich understanding of others: by drawing not only on how others act but also on the environments they have shaped. Overall, social cognition is crucial not only to our reasoning about people and actions but also to our everyday reasoning about the inanimate world.

Digital Twins in 3D Printing Processes Using Artificial Intelligence

Digital twins (DTs) provide accurate, data-driven, real-time modeling to create a digital representation of the physical world. The integration of new technologies, such as virtual/mixed reality, artificial intelligence, and DTs, enables modeling and research into ways to achieve better sustainability, greater efficiency, and improved safety in Industry 4.0/5.0 technologies. This paper discusses concepts, limitations, future trends, and potential research directions to provide the infrastructure and underlying intelligence for large-scale semi-automated DT building environments. Grouping these technologies along these lines allows for a better consideration of their individual risk factors and use of available data, resulting in an approach to generate holistic virtual representations (DTs) to facilitate predictive analyses in industrial practices. Artificial intelligence-based DTs are becoming a new tool for monitoring, simulating, and optimizing systems, and the widespread implementation and mastery of this technology will lead to significant improvements in performance, reliability, and profitability. Despite advances, the aforementioned technology still requires research, improvement, and investment. This article’s contribution is a concept that, if adopted instead of the traditional approach, can become standard practice rather than an advanced operation and can accelerate this development.

Performing Discourse in Pursuit of Credibility: A Quantitative Content Analysis of Dutch Live Blogs

ABSTRACT Live blogs are a popular format for covering crises, breaking news, politics, or sports events. Despite their popularity among journalists and the public, the format has also been subject to scholarly debate regarding the conflict between immediacy versus credibility, resulting in a high degree of uncertainty for producers and consumers. Journalists cope with this paradox by performing discourse: imposing valid and persuasive representations of the social world. One way to do so is by the use and representation of sources. In this paper, we uncover the performative discourse of live blogs through possible patterns of sourcing and discursive strategies among a range of live blogs and the way journalists cope with the mix of speed and uncertainty. Based on a quantitative content analysis of nine Dutch live blogs, we conclude that journalists follow the same conventions and routines as regular (online) articles. Despite the possibilities for polyvocality (more and different voices in live blogs) due to the accessibility by social media, journalists choose predominantly formal sources and report their speech predominantly in a direct way.

Towards an ecologically valid naturalistic cognitive neuroscience of memory and event cognition

The landscape of human memory and event cognition research has witnessed a transformative journey toward the use of naturalistic contexts and tasks. In this review, we track this progression from abrupt, artificial stimuli used in extensively controlled laboratory experiments to more naturalistic tasks and stimuli that present a more faithful representation of the real world. We argue that in order to improve ecological validity, naturalistic study designs must consider the complexity of the cognitive phenomenon being studied. Then, we review the current state of “naturalistic” event segmentation studies and critically assess frequently employed movie stimuli. We evaluate recently developed tools like lifelogging and other extended reality technologies to help address the challenges we identified with existing naturalistic approaches. We conclude by offering some guidelines that can be used to design ecologically valid cognitive neuroscience studies of memory and event cognition.

Toward trustworthy medical device in silico clinical trials: a hierarchical framework for establishing credibility and strategies for overcoming key challenges.

Computational models of patients and medical devices can be combined to perform an in silico clinical trial (ISCT) to investigate questions related to device safety and/or effectiveness across the total product life cycle. ISCTs can potentially accelerate product development by more quickly informing device design and testing or they could be used to refine, reduce, or in some cases to completely replace human subjects in a clinical trial. There are numerous potential benefits of ISCTs. An important caveat, however, is that an ISCT is a virtual representation of the real world that has to be shown to be credible before being relied upon to make decisions that have the potential to cause patient harm. There are many challenges to establishing ISCT credibility. ISCTs can integrate many different submodels that potentially use different modeling types (e.g., physics-based, data-driven, rule-based) that necessitate different strategies and approaches for generating credibility evidence. ISCT submodels can include those for the medical device, the patient, the interaction of the device and patient, generating virtual patients, clinical decision making and simulating an intervention (e.g., device implantation), and translating acute physics-based simulation outputs to health-related clinical outcomes (e.g., device safety and/or effectiveness endpoints). Establishing the credibility of each ISCT submodel is challenging, but is nonetheless important because inaccurate output from a single submodel could potentially compromise the credibility of the entire ISCT. The objective of this study is to begin addressing some of these challenges and to identify general strategies for establishing ISCT credibility. Most notably, we propose a hierarchical approach for assessing the credibility of an ISCT that involves systematically gathering credibility evidence for each ISCT submodel in isolation before demonstrating credibility of the full ISCT. Also, following FDA Guidance for assessing computational model credibility, we provide suggestions for ways to clearly describe each of the ISCT submodels and the full ISCT, discuss considerations for performing an ISCT model risk assessment, identify common challenges to demonstrating ISCT credibility, and present strategies for addressing these challenges using our proposed hierarchical approach. Finally, in the Appendix we illustrate the many concepts described here using a hypothetical ISCT example.

Stimulus invariant aspects of the retinal code drive discriminability of natural scenes.

Everything that the brain sees must first be encoded by the retina, which maintains a reliable representation of the visual world in many different, complex natural scenes while also adapting to stimulus changes. This study quantifies whether and how the brain selectively encodes stimulus features about scene identity in complex naturalistic environments. While a wealth of previous work has dug into the static and dynamic features of the population code in retinal ganglion cells, less is known about how populations form both flexible and reliable encoding in natural moving scenes. We record from the larval salamander retina responding to five different natural movies, over many repeats, and use these data to characterize the population code in terms of single-cell fluctuations in rate and pairwise couplings between cells. Decomposing the population code into independent and cell-cell interactions reveals how broad scene structure is encoded in the retinal output. while the single-cell activity adapts to different stimuli, the population structure captured in the sparse, strong couplings is consistent across natural movies as well as synthetic stimuli. We show that these interactions contribute to encoding scene identity. We also demonstrate that this structure likely arises in part from shared bipolar cell input as well as from gap junctions between retinal ganglion cells and amacrine cells.

Practical and empirical cognition of the cognitive self

This paper explores the different ways in which knowledge of ourselves as cognizers depends on the transcendental unity of apperception. First, since all cognition requires the transcendental unity of apperception, so does empirical knowledge of ourselves as cognizers. Second, since empirical cognizers are cognizers, they must possess the unity of self-consciousness required for cognition. Third, empirical psychology needs an object and the transcendental unity of apperception makes it possible to attach ‘I-think’ to representations of the empirical world, thereby supplying psychological states, such as ‘I think that bodies are heavy,’ to be studied. Finally, the Psychological Idea through which psychology is made systematic gets it first principle from the necessary unity of apperception.

Towards National Connected Digital Twins - A Geospatial Perspective

Abstract. Digital Twins are realistic digital representations of the physical world, frequently characterised by a two way link between digital and physical. Originating in manufacturing, they are now expanding to city and national scales. In this paper we explore connections between Geographic Information Science and National Digital Twins. Six different viewpoints and perspectives are presented on the topic, highlighting the importance of: geospatial data engineering; metadata engineering; standards; challenges facing mapping agencies; governance and public values; and a ”reality check” that explores the gaps between what is required and what can currently be achieved. We present 22 recommendations and summarise the findings by presenting a high level research agenda to enable better understanding and articulation of the link between the two.

Perceptual Resolution of Ambiguity: Can Tuned, Divisive Normalization Account for both Interocular Similarity Grouping and Difference Enhancement.

Our visual system usually provides a unique and functional representation of the external world. At times, however, the visual system has more than one compelling interpretation of the same retinal stimulus; in this case, neural populations compete for perceptual dominance to resolve ambiguity. Spatial and temporal context can guide perceptual experience. Recent evidence shows that ambiguous retinal stimuli are sometimes resolved by enhancing either similarity or differences among multiple percepts. Divisive normalization is a canonical neural computation that enables context-dependent sensory processing by attenuating a neuron's response by other neurons. Experiments here show that divisive normalization can account for perceptual representations of either similarity enhancement (so-called grouping) or difference enhancement, offering a unified framework for opposite perceptual outcomes.