Emergent Features Research Articles

Sex, sexes, sex roles, and gender in land plants.

"When we view gender as an accomplishment, an achieved property of situated conduct, our attention shifts from matters internal to the individual and focuses on interactional and, ultimately, institutional arenas. In one sense, of course, it is individuals who 'do' gender. But it is a situated doing, carried out in the virtual or real presence of others who are presumed to be oriented to its production. Rather than as a property of individuals, we conceive of gender as of an emergent feature of social situations: both as an outcome of and a rationale for various social arrangements and as a means of legitimating one of the most fundamental divisions of society." This article is protected by copyright. All rights reserved.

Perceptual grouping strategies and texture segmentation: Strategic connections and selection

In a series of articles, Jacob Beck proposed that a variety of texture segmentation phenomena occurs due to emergent features that arise from “links” between elements with appropriate local properties, such as alignment, orientation, and proximity. His findings and ideas guided theoretical and computational models, and some of his demonstrations became textbook knowledge about visual perception. We build on this work in two ways. First, we provide a modern replication of a classic texture segmentation study using a much larger sample size. Overall, the replication agrees with Beck’s original findings, although there are some quantitative differences. Second, we show how to apply a quantitative model of visual cortex to Beck’s experiment and demonstrate that the model can explain many aspects of Beck’s findings. Key to the model’s success is cognitive control of connections between individual elements (akin to Beck’s “links” between elements) and a selection mechanism that makes it easy to identify how well elements within a region connect and how well different regions are disconnected. Overall, the model supports Beck’s claim that local properties can facilitate patterns of connections between stimulus elements and that some connection patterns allow an observer to easily distinguish textures.

Single-cell subcellular protein localisation using novel ensembles of diverse deep architectures

Unravelling protein distributions within individual cells is vital to understanding their function and state and indispensable to developing new treatments. Here we present the Hybrid subCellular Protein Localiser (HCPL), which learns from weakly labelled data to robustly localise single-cell subcellular protein patterns. It comprises innovative DNN architectures exploiting wavelet filters and learnt parametric activations that successfully tackle drastic cell variability. HCPL features correlation-based ensembling of novel architectures that boosts performance and aids generalisation. Large-scale data annotation is made feasible by our AI-trains-AI approach, which determines the visual integrity of cells and emphasises reliable labels for efficient training. In the Human Protein Atlas context, we demonstrate that HCPL is best performing in the single-cell classification of protein localisation patterns. To better understand the inner workings of HCPL and assess its biological relevance, we analyse the contributions of each system component and dissect the emergent features from which the localisation predictions are derived.

Robust rhythm reporting will advance ecological and evolutionary research

Abstract Rhythmicity in the millisecond to second range is a fundamental building block of communication and coordinated movement. But how widespread are rhythmic capacities across species, and how did they evolve under different environmental pressures? Comparative research is necessary to answer these questions but has been hindered by limited crosstalk and comparability among results from different study species. Most acoustics studies do not explicitly focus on characterising or quantifying rhythm, but many are just a few scrapes away from contributing to and advancing the field of comparative rhythm research. Here, we present an eight‐level rhythm reporting framework which details actionable steps researchers can take to report rhythm‐relevant metrics. Levels fall into two categories: metric reporting and data sharing. Metric reporting levels include defining rhythm‐relevant metrics, providing point estimates of temporal interval variability, reporting interval distributions, and conducting rhythm analyses. Data sharing levels are: sharing audio recordings, sharing interval durations, sharing sound element start and end times, and sharing audio recordings with sound element start/end times. Using sounds recorded from a sperm whale as a case study, we demonstrate how each reporting framework level can be implemented on real data. We also highlight existing best practice examples from recent research spanning multiple species. We clearly detail how engagement with our framework can be tailored case‐by‐case based on how much time and effort researchers are willing to contribute. Finally, we illustrate how reporting at any of the suggested levels will help advance comparative rhythm research. This framework will actively facilitate a comparative approach to acoustic rhythms while also promoting cooperation and data sustainability. By quantifying and reporting rhythm metrics more consistently and broadly, new avenues of inquiry and several long‐standing, big picture research questions become more tractable. These lines of research can inform not only about the behavioural ecology of animals but also about the evolution of rhythm‐relevant phenomena and the behavioural neuroscience of rhythm production and perception. Rhythm is clearly an emergent feature of life; adopting our framework, researchers from different fields and with different study species can help understand why.

Conspiracy as ARG: media and game essence of QAnon

The results of a comparative analysis of the functional features of the QAnon theory and the conceptual signs of ARG (games in alternative reality) are displayed. The signs of ARG are designated and given as elements of the reference game model, the basis for comparison. The authors found that the QAnon conspiracy theory, the history of its emergence and development features is of a synthetic nature: ARG elements are present in modified form. They transform the roles of developers and participants. The QAnon quest structure was visualized, the gameplay based on experiencing the state of apophenia - a painful search for a connection between random phenomena or events - was described. The similarities of QAnon with religion and at the same time political ideology based on the mechanics of the game were identified, which explains its popularity. The relevance of the topic is due to the steady growth in the number of conspiracy theories and their followers since the beginning of the Covid-19 pandemic against the backdrop of audience distrust in the media. The authors demonstrate how QAnon, not being essentially a game in an alternative reality, but using game technologies and eschatological narratives about the Great Tribulation and Judgment Day, achieves high efficiency in shaping public opinion.

Attractor-Like Dynamics Extracted from Human Electrocorticographic Recordings Underlie Computational Principles of Auditory Bistable Perception.

In bistable perception, observers experience alternations between two interpretations of an unchanging stimulus. Neurophysiological studies of bistable perception typically partition neural measurements into stimulus-based epochs and assess neuronal differences between epochs based on subjects' perceptual reports. Computational studies replicate statistical properties of percept durations with modeling principles like competitive attractors or Bayesian inference. However, bridging neuro-behavioral findings with modeling theory requires the analysis of single-trial dynamic data. Here, we propose an algorithm for extracting nonstationary timeseries features from single-trial electrocorticography (ECoG) data. We applied the proposed algorithm to 5-min ECoG recordings from human primary auditory cortex obtained during perceptual alternations in an auditory triplet streaming task (six subjects: four male, two female). We report two ensembles of emergent neuronal features in all trial blocks. One ensemble consists of periodic functions that encode a stereotypical response to the stimulus. The other comprises more transient features and encodes dynamics associated with bistable perception at multiple time scales: minutes (within-trial alternations), seconds (duration of individual percepts), and milliseconds (switches between percepts). Within the second ensemble, we identified a slowly drifting rhythm that correlates with the perceptual states and several oscillators with phase shifts near perceptual switches. Projections of single-trial ECoG data onto these features establish low-dimensional attractor-like geometric structures invariant across subjects and stimulus types. These findings provide supporting neural evidence for computational models with oscillatory-driven attractor-based principles. The feature extraction techniques described here generalize across recording modality and are appropriate when hypothesized low-dimensional dynamics characterize an underlying neural system.SIGNIFICANCE STATEMENT Irrespective of the sensory modality, neurophysiological studies of multistable perception have typically investigated events time-locked to the perceptual switching rather than the time course of the perceptual states per se. Here, we propose an algorithm that extracts neuronal features of bistable auditory perception from largescale single-trial data while remaining agnostic to the subject's perceptual reports. The algorithm captures the dynamics of perception at multiple timescales, minutes (within-trial alternations), seconds (durations of individual percepts), and milliseconds (timing of switches), and distinguishes attributes of neural encoding of the stimulus from those encoding the perceptual states. Finally, our analysis identifies a set of latent variables that exhibit alternating dynamics along a low-dimensional manifold, similar to trajectories in attractor-based models for perceptual bistability.

Collective Motion and Pattern Formation in Phase-Synchronizing Active Fluids

Many active particles, such as swimming micro-organisms or motor proteins, do work on their environment by going though a periodic sequence of shapes. Interactions between particles can lead to synchronization of their duty cycles. Here, we study the collective dynamics of a suspension of active particles coupled through hydrodynamics. We find that at high enough density the system transitions to a state of collective motion by a mechanism that is distinct from other instabilities in active matter systems. Second, we demonstrate that the emergent nonequilibrium states feature stationary chimera patterns in which synchronized and phase-isotropic regions coexist. Third, we show that in confinement, oscillatory flows and robust unidirectional pumping states exist, and can be selected by choice of alignment boundary conditions. These results point toward a new route to collective motion and pattern formation and could guide the design of new active materials.

Colour and melanopsin mediated responses in the murine retina.

Introduction: Intrinsically photosensitive retinal ganglion cells (ipRGCs) integrate melanopsin and rod/cone-mediated inputs to signal to the brain. Whilst originally identified as a cell type specialised for encoding ambient illumination, several lines of evidence indicate a strong association between colour discrimination and ipRGC-driven responses. Thus, cone-mediated colour opponent responses have been widely found across ipRGC target regions in the mouse brain and influence a key ipRGC-dependent function, circadian photoentrainment. Although ipRGCs exhibiting spectrally opponent responses have also been identified, the prevalence of such properties have not been systematically evaluated across the mouse retina or yet been found in ipRGC subtypes known to influence the circadian system. Indeed, there is still uncertainty around the overall prevalence of cone-dependent colour opponency across the mouse retina, given the strong retinal gradient in S and M-cone opsin (co)-expression and overlapping spectral sensitivities of most mouse opsins. Methods: To address this, we use photoreceptor isolating stimuli in multielectrode recordings from human red cone opsin knock-in mouse (Opn1mwR) retinas to systematically survey cone mediated responses and the occurrence of colour opponency across ganglion cell layer (GCL) neurons and identify ipRGCs based on spectral comparisons and/or the persistence of light responses under synaptic blockade. Results: Despite detecting robust cone-mediated responses across the retina, we find cone opponency is rare, especially outside of the central retina (overall ~3% of GCL neurons). In keeping with previous suggestions we also see some evidence of rod-cone opponency (albeit even more rare under our experimental conditions), but find no evidence for any enrichment of cone (or rod) opponent responses among functionally identified ipRGCs. Conclusion: In summary, these data suggest the widespread appearance of cone-opponency across the mouse early visual system and ipRGC-related responses may be an emergent feature of central visual processing mechanisms.

Interaction-driven spontaneous ferromagnetic insulating states with odd Chern numbers

Motivated by recent experimental work on moiré systems in a strong magnetic field, we compute the compressibility as well as the spin correlations and Hofstadter spectrum of spinful electrons on a honeycomb lattice with Hubbard interactions using the determinantal quantum Monte Carlo method. While the interactions in general preserve quantum and anomalous Hall states, emergent features arise corresponding to an antiferromagnetic insulator at half-filling and other incompressible states following the Chern sequence ± (2N + 1). These odd integer Chern states exhibit strong ferromagnetic correlations and arise spontaneously without any external mechanism for breaking the spin-rotation symmetry. Analogs of these magnetic states should be observable in general interacting quantum Hall systems. In addition, the interacting Hofstadter spectrum is qualitatively similar to the experimental data at intermediate values of the on-site interaction.

From edge to bulk: Cavity-induced displacement of topological nonlocal qubits

We investigate the ability of selective cavity coupling to a topological chain for tailoring the connectivity of Majorana fermions. We show how topological qubits (TQs), associated with nonlocal Majorana fermion pairing, can be displaced from the edges to the bulk of a topological chain through selective access to light-matter interaction with specific physical sites. In particular, we present a comprehensive density matrix renormalization group study of ground-state features in different chain-cavity coupling geometries, and we validate analytical insights in the strong-coupling regime. This type of Majorana fermion correlation generation process comes with emergent cavity photon features. Moreover, by considering the time evolution after a sudden quench of the cavity-matter coupling strength, we show that the development of high nontrivial matter (Majorana) correlations leaves behind measurable nonclassical photon imprints in the cavity. Innovative ways to dynamically generate TQ nonlocal correlations in topological chains of arbitrary length are thus provided, opening alternative routes to controllable long-range entanglement in hybrid photonic solid-state systems.

Better Medicine: Shared Suffering and Chronic Vulnerability in Brian Teare's The Empty Form Goes All the Way to Heaven.

A posthumanist understanding of the body does not view "illness" and "health" as properties of the individual body, but as emergent features of the relationships between bodies. As such, a relational view of health opens up avenues for the betterment of both human bodies and their social and physical environments. Drawing on posthumanism and the ethics of vulnerability, this article demonstrates how Brian Teare's The Empty Form Goes All the Way to Heaven (2015) provides a different way of thinking (and doing) illness, death, and vulnerability. With his acceptance and promotion of the body's dynamic materiality and chronic vulnerability, Teare advances a posthuman ethics based on our shared embodied condition.

Amplified radio-over-fiber system linearization using recurrent neural networks

Ubiquitous communication is an emergent feature of the future sixth generation of mobile communication (6G) networks. One of the main challenges of this upcoming mobile network is providing broadband communication wherever connectivity is necessary, including rural areas. Up to now, all previous generations of mobile networks have not satisfactorily accomplished this task, and the high cost of deploying and maintaining complex communication infrastructure in remote areas is one of the main reasons. The centralized radio access network might play an important role in overcoming it, since it enables all baseband centralization in a central office (CO), simplifying network deployment and reducing operating/maintenance costs. Additionally, in this scenario, the radio over fiber (RoF) system might be used for transporting analog signals from the CO to a simplified remote base station, composed only of an optical detector and radio-frequency front-end. However, the Mach–Zehnder modulator and power amplifier, commonly employed in RoF systems, introduce undesired nonlinear effects that can severely degrade overall system performance and prohibitively increase the out-of-band emission. We investigate the use of machine learning (ML) algorithms applied to the linearization of an electrical-amplified RoF system. Particularly, a memory recurrent neural network (RNN) linearization is proposed and compared with a memoryless multilayer perceptron linearization. The root mean square error vector magnitude, normalized mean square error, and adjacent channel leakage ratio metrics have been calculated to evaluate the performance of our ML-based approach. Numerical results demonstrate promising linearization performance when the RNN memory depth is equal to or higher than the amplified-RoF system memory depth.

Structure and dynamics of RNA in biomolecular condensate.

Although it is known that RNA undergoes phase separation, the interplay between the molecular driving forces and the emergent features of the condensates, such as their morphologies and dynamic properties, is not well understood. We introduce a coarse-grained model to simulate phase separation of RNAs. Simulations for the trinucleotide repeat RNAs, implicated in neurological disorders, reveal the structures and dynamics of RNA in condensates, which are drastically different from the dilute phase. Interestingly, the interaction network and dynamics in the condensate depend on the RNA sequence, and the droplet is most compact in the case of repeat RNAs. These findings shed light on the mechanisms of condensate formation of RNA repeat sequences, which can be helpful for the understanding of neurological disease onset.

Moral Disjunction and Role Coadunation in Business and the Professions

We consider the problem of moral disjunction in professional and business activities from a virtue-ethical perspective. Moral disjunction arises when the behavioral demands of a role conflict with personal morality; it is an important problem because most people in modern societies occupy several complex roles that can cause this clash to occur. We argue that moral disjunction, and the psychological mechanisms that people use to cope with it, are problematic because they make it hard to pursue virtue and to live with integrity. We present role coadunation as a process with epistemic and behavioral aspects that people can use to resolve moral disjunction with integrity. When role coadunation is successful, it enables people to live virtuous lives of appropriate narrative disunity and to honor their identity-conferring commitments. We show how role coadunation can be facilitated by interpretive communities and discuss the emergence and ideal features of those communities.

Emergence of Hadron Mass and Structure

Visible matter is characterised by a single mass scale; namely, the proton mass. The proton’s existence and structure are supposed to be described by quantum chromodynamics (QCD); yet, absent Higgs boson couplings, chromodynamics is scale-invariant. Thus, if the Standard Model is truly a part of the theory of Nature, then the proton mass is an emergent feature of QCD; and emergent hadron mass (EHM) must provide the basic link between theory and observation. Nonperturbative tools are necessary if such connections are to be made; and in this context, we sketch recent progress in the application of continuum Schwinger function methods to an array of related problems in hadron and particle physics. Special emphasis is given to the three pillars of EHM—namely, the running gluon mass, process-independent effective charge, and running quark mass; their role in stabilising QCD; and their measurable expressions in a diverse array of observables.

Development of Pag-asa Reefs, West Philippine Sea: Role of Relative Sea Level Change and Wave Exposure

Atoll reefs are associated with subsiding regions. In the West Philippine Sea, the Kalayaan Island Group is an emergent feature of the region’s atoll reefs. In this study, we established the long-term rate of subsidence in the Pag-asa Atoll Reefs by indicators of sea level positions on the seafloor and in Pag-asa Island. For submerged indicators of paleo-sea levels, a multibeam bathymetry with a 5-m resolution was used as the primary data source. Four pairs of submerged terraces and scarps, interpreted as former coral reef flats and reef fronts, respectively, were mapped. The terraces, PARa-d, from shallowest to deepest, occur at depth ranges of 7–10, 36–45, 82–90, and 115–120 m. The step-like morphology of the slopes off Pag-asa is likely due to the backstepping of reefs during the overall rise of sea level from the Last Glacial Maximum (LGM). Terraces PARa-d are interpreted as records of reef re-establishments during the stillstand periods following meltwater pulse event (MWP)-1C, MWP-1B, MWP-1A, and MWP-2B/2A. There is no clear morphological indicator of coral terraces that can be attributed to the LGM period. Variation in the widths and depths of the terraces between the leeward and windward sides of the island is also observed. Greater wave exposure appears favorable for coral reef terrace growth in Pag-asa, except for deeper terraces. The possible absence of the deepest terrace on the north side and an LGM terrace is attributed to possible thinner coral reef accretion due to the combination of cooler waters and possible swifter winds prior to 14 kyr. Correlation of the terrace depths and beach rock elevations as Pag-asa with the paleo-sea level of correlative stillstand events indicate long-term subsidence of 1.2 mm/yr between 15–12 kyr that declined to 0.3 mm/yr between 12 kyr to present. With sea level rise due to global warming and continuing subsidence, Pag-asa Island is threatened by coastal erosion, more frequent inundation, and groundwater salinization that needs to be addressed through proper adaptation practices.

Taking the Person Seriously: Ethically Aware IS Research in the Era of Reinforcement Learning-Based Personalization

Advances in reinforcement learning and implicit data collection on large-scale commercial platforms mark the beginning of a new era of personalization aimed at the adaptive control of human user environments. We present five emergent features of this new paradigm of personalization that endanger persons and societies at scale and analyze their potential to reduce personal autonomy, destabilize social and political systems, and facilitate mass surveillance and social control, among other concerns. We argue that current data protection laws, most notably the European Union’s General Data Protection Regulation, are limited in their ability to adequately address many of these issues. Nevertheless, we believe that IS researchers are well-situated to engage with and investigate this new era of personalization. We propose three distinct directions for ethically aware reinforcement learning-based personalization research uniquely suited to the strengths of IS researchers across the sociotechnical spectrum.

Leveraging Data Analytics to Improve User Satisfaction for Key Personas: The Impact of Feedback Loops

A well-known method in human-computer interaction is the use of personas. Nevertheless, robust empirical study comparing persons to alternative approaches is lacking. Agile techniques' theoretical underpinnings are based on a number of important frameworks of theory. According to complexity theory, emergent features are present in complex systems, such as digital financial ecosystems. These are difficult for conventional linear algorithms to forecast. Agile recognises this complexity and supports continuous improvement cycles and flexibility to changing requirements. Lean thinking, which is drawn from manufacturing, places a higher priority on maximising customer value and removing waste. A promising market for IT-driven products, or Smart, Connected Products (SCPs), is made possible in this day and age by the rapid growth of Information and Communication Technology (ICT) (such as wireless sensor networks and cyber-physical systems). This also modifies the way that manufacturers and users interact during the product's process of development. Big data analysis allows businesses to base judgements on facts instead of gut feeling or internal knowledge that may be disguised. Business organisations gain from better informed choices and consistent results than ever before when knowledge workers and those making decisions have access to reliable sources of information that are constantly updated and accurate, as well as the analytical tools needed to make sense of it. The manner in which knowledge workers carry out their duties and the company's overall operations may be impacted by this method of decision support. Large data sets provided insights for analytical tools. They contribute to the expansion of the context and backgrounds that are available for rational, precise, and coherent decision-making. This study illustrates how Adaptive Case Management (ACM) systems' DSS component can be expanded through Big Data analysis. The article's authors explore the idea that businesses might use big data to enhance their operations by combining analytical tools, adaptable process management, and easy access to all the necessary data into a single application.

Higher-order interactions shape microbial interactions as microbial community complexity increases

Non-pairwise interactions, or higher-order interactions (HOIs), in microbial communities have been described as significant drivers of emergent features in microbiomes. Yet, the re-organization of microbial interactions between pairwise cultures and larger communities remains largely unexplored from a molecular perspective but is central to our understanding and further manipulation of microbial communities. Here, we used a bottom-up approach to investigate microbial interaction mechanisms from pairwise cultures up to 4-species communities from a simple microbiome (Hafnia alvei, Geotrichum candidum, Pencillium camemberti and Escherichia coli). Specifically, we characterized the interaction landscape for each species combination involving E. coli by identifying E. coli’s interaction-associated mutants using an RB-TnSeq-based interaction assay. We observed a deep reorganization of the interaction-associated mutants, with very few 2-species interactions conserved all the way up to a 4-species community and the emergence of multiple HOIs. We further used a quantitative genetics strategy to decipher how 2-species interactions were quantitatively conserved in higher community compositions. Epistasis-based analysis revealed that, of the interactions that are conserved at all levels of complexity, 82% follow an additive pattern. Altogether, we demonstrate the complex architecture of microbial interactions even within a simple microbiome, and provide a mechanistic and molecular explanation of HOIs.

Protein as evolvable functionally constrained amorphous matter

We explore current ideas around the representation of a protein as an amorphous material, in turn represented by an abstract graph G with edges weighted by elastic stiffnesses. By embedding this graph in physical space, we can map every graph to a spectrum of conformational fluctuations and responses (as a result of, say, ligandbinding). This sets up a 'genotype-phenotype' map, which we use to evolve the amorphous material to select for fitness. Using this, we study the emergence of allosteric interaction, hinge joint, crack formation and a slide bolt in functional proteins such as adenylate kinase, HSP90, calmodulin and GPCR proteins. We find that these emergent features are associated with specific geometries and mode spectra of floppy or liquid-like regions. Our analysis provides insight into understanding the architectural demands on a protein that enable a prescribed function and its stability to mutations.